partition
stringclasses 3
values | func_name
stringlengths 1
134
| docstring
stringlengths 1
46.9k
| path
stringlengths 4
223
| original_string
stringlengths 75
104k
| code
stringlengths 75
104k
| docstring_tokens
listlengths 1
1.97k
| repo
stringlengths 7
55
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stringclasses 1
value | url
stringlengths 87
315
| code_tokens
listlengths 19
28.4k
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stringlengths 40
40
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|---|---|---|---|---|---|---|---|---|---|---|---|
valid
|
Chart.scanner
|
For each edge expecting a word of this category here, extend the edge.
|
aima/nlp.py
|
def scanner(self, j, word):
"For each edge expecting a word of this category here, extend the edge."
for (i, j, A, alpha, Bb) in self.chart[j]:
if Bb and self.grammar.isa(word, Bb[0]):
self.add_edge([i, j+1, A, alpha + [(Bb[0], word)], Bb[1:]])
|
def scanner(self, j, word):
"For each edge expecting a word of this category here, extend the edge."
for (i, j, A, alpha, Bb) in self.chart[j]:
if Bb and self.grammar.isa(word, Bb[0]):
self.add_edge([i, j+1, A, alpha + [(Bb[0], word)], Bb[1:]])
|
[
"For",
"each",
"edge",
"expecting",
"a",
"word",
"of",
"this",
"category",
"here",
"extend",
"the",
"edge",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/nlp.py#L160-L164
|
[
"def",
"scanner",
"(",
"self",
",",
"j",
",",
"word",
")",
":",
"for",
"(",
"i",
",",
"j",
",",
"A",
",",
"alpha",
",",
"Bb",
")",
"in",
"self",
".",
"chart",
"[",
"j",
"]",
":",
"if",
"Bb",
"and",
"self",
".",
"grammar",
".",
"isa",
"(",
"word",
",",
"Bb",
"[",
"0",
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")",
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"self",
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"add_edge",
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",",
"j",
"+",
"1",
",",
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",",
"alpha",
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"[",
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"0",
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",",
"word",
")",
"]",
",",
"Bb",
"[",
"1",
":",
"]",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
Chart.predictor
|
Add to chart any rules for B that could help extend this edge.
|
aima/nlp.py
|
def predictor(self, (i, j, A, alpha, Bb)):
"Add to chart any rules for B that could help extend this edge."
B = Bb[0]
if B in self.grammar.rules:
for rhs in self.grammar.rewrites_for(B):
self.add_edge([j, j, B, [], rhs])
|
def predictor(self, (i, j, A, alpha, Bb)):
"Add to chart any rules for B that could help extend this edge."
B = Bb[0]
if B in self.grammar.rules:
for rhs in self.grammar.rewrites_for(B):
self.add_edge([j, j, B, [], rhs])
|
[
"Add",
"to",
"chart",
"any",
"rules",
"for",
"B",
"that",
"could",
"help",
"extend",
"this",
"edge",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/nlp.py#L166-L171
|
[
"def",
"predictor",
"(",
"self",
",",
"(",
"i",
",",
"j",
",",
"A",
",",
"alpha",
",",
"Bb",
")",
")",
":",
"B",
"=",
"Bb",
"[",
"0",
"]",
"if",
"B",
"in",
"self",
".",
"grammar",
".",
"rules",
":",
"for",
"rhs",
"in",
"self",
".",
"grammar",
".",
"rewrites_for",
"(",
"B",
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"add_edge",
"(",
"[",
"j",
",",
"j",
",",
"B",
",",
"[",
"]",
",",
"rhs",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
Chart.extender
|
See what edges can be extended by this edge.
|
aima/nlp.py
|
def extender(self, edge):
"See what edges can be extended by this edge."
(j, k, B, _, _) = edge
for (i, j, A, alpha, B1b) in self.chart[j]:
if B1b and B == B1b[0]:
self.add_edge([i, k, A, alpha + [edge], B1b[1:]])
|
def extender(self, edge):
"See what edges can be extended by this edge."
(j, k, B, _, _) = edge
for (i, j, A, alpha, B1b) in self.chart[j]:
if B1b and B == B1b[0]:
self.add_edge([i, k, A, alpha + [edge], B1b[1:]])
|
[
"See",
"what",
"edges",
"can",
"be",
"extended",
"by",
"this",
"edge",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/nlp.py#L173-L178
|
[
"def",
"extender",
"(",
"self",
",",
"edge",
")",
":",
"(",
"j",
",",
"k",
",",
"B",
",",
"_",
",",
"_",
")",
"=",
"edge",
"for",
"(",
"i",
",",
"j",
",",
"A",
",",
"alpha",
",",
"B1b",
")",
"in",
"self",
".",
"chart",
"[",
"j",
"]",
":",
"if",
"B1b",
"and",
"B",
"==",
"B1b",
"[",
"0",
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":",
"self",
".",
"add_edge",
"(",
"[",
"i",
",",
"k",
",",
"A",
",",
"alpha",
"+",
"[",
"edge",
"]",
",",
"B1b",
"[",
"1",
":",
"]",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
settings
|
Adds a ``SettingDict`` object for the ``Setting`` model to the context as
``SETTINGS``. Automatically creates non-existent settings with an empty
string as the default value.
|
model_settings/context_processors.py
|
def settings(request):
"""
Adds a ``SettingDict`` object for the ``Setting`` model to the context as
``SETTINGS``. Automatically creates non-existent settings with an empty
string as the default value.
"""
settings = Setting.objects.all().as_dict(default='')
context = {
'SETTINGS': settings,
}
return context
|
def settings(request):
"""
Adds a ``SettingDict`` object for the ``Setting`` model to the context as
``SETTINGS``. Automatically creates non-existent settings with an empty
string as the default value.
"""
settings = Setting.objects.all().as_dict(default='')
context = {
'SETTINGS': settings,
}
return context
|
[
"Adds",
"a",
"SettingDict",
"object",
"for",
"the",
"Setting",
"model",
"to",
"the",
"context",
"as",
"SETTINGS",
".",
"Automatically",
"creates",
"non",
"-",
"existent",
"settings",
"with",
"an",
"empty",
"string",
"as",
"the",
"default",
"value",
"."
] |
ixc/django-model-settings
|
python
|
https://github.com/ixc/django-model-settings/blob/654233bf7f13619e4531741f9158e7034eac031b/model_settings/context_processors.py#L3-L13
|
[
"def",
"settings",
"(",
"request",
")",
":",
"settings",
"=",
"Setting",
".",
"objects",
".",
"all",
"(",
")",
".",
"as_dict",
"(",
"default",
"=",
"''",
")",
"context",
"=",
"{",
"'SETTINGS'",
":",
"settings",
",",
"}",
"return",
"context"
] |
654233bf7f13619e4531741f9158e7034eac031b
|
valid
|
SettingModelAdmin.get_child_models
|
Returns a list of ``(Model, ModelAdmin)`` tuples for ``base_model``
subclasses.
|
model_settings/admin.py
|
def get_child_models(self):
"""
Returns a list of ``(Model, ModelAdmin)`` tuples for ``base_model``
subclasses.
"""
child_models = []
# Loop through all models with FKs back to `base_model`.
for related_object in get_all_related_objects(self.base_model._meta):
# Django 1.8 deprecated `get_all_related_objects()`. We're still
# using it for now with the documented work-around for
# compatibility with Django <=1.7.
model = getattr(
related_object, 'related_model', related_object.model)
# Only consider `base_model` subclasses.
if issubclass(model, self.base_model):
class SettingValueAdmin(self.base_admin_class):
pass
child_models.append((model, SettingValueAdmin))
return child_models
|
def get_child_models(self):
"""
Returns a list of ``(Model, ModelAdmin)`` tuples for ``base_model``
subclasses.
"""
child_models = []
# Loop through all models with FKs back to `base_model`.
for related_object in get_all_related_objects(self.base_model._meta):
# Django 1.8 deprecated `get_all_related_objects()`. We're still
# using it for now with the documented work-around for
# compatibility with Django <=1.7.
model = getattr(
related_object, 'related_model', related_object.model)
# Only consider `base_model` subclasses.
if issubclass(model, self.base_model):
class SettingValueAdmin(self.base_admin_class):
pass
child_models.append((model, SettingValueAdmin))
return child_models
|
[
"Returns",
"a",
"list",
"of",
"(",
"Model",
"ModelAdmin",
")",
"tuples",
"for",
"base_model",
"subclasses",
"."
] |
ixc/django-model-settings
|
python
|
https://github.com/ixc/django-model-settings/blob/654233bf7f13619e4531741f9158e7034eac031b/model_settings/admin.py#L17-L35
|
[
"def",
"get_child_models",
"(",
"self",
")",
":",
"child_models",
"=",
"[",
"]",
"# Loop through all models with FKs back to `base_model`.",
"for",
"related_object",
"in",
"get_all_related_objects",
"(",
"self",
".",
"base_model",
".",
"_meta",
")",
":",
"# Django 1.8 deprecated `get_all_related_objects()`. We're still",
"# using it for now with the documented work-around for",
"# compatibility with Django <=1.7.",
"model",
"=",
"getattr",
"(",
"related_object",
",",
"'related_model'",
",",
"related_object",
".",
"model",
")",
"# Only consider `base_model` subclasses.",
"if",
"issubclass",
"(",
"model",
",",
"self",
".",
"base_model",
")",
":",
"class",
"SettingValueAdmin",
"(",
"self",
".",
"base_admin_class",
")",
":",
"pass",
"child_models",
".",
"append",
"(",
"(",
"model",
",",
"SettingValueAdmin",
")",
")",
"return",
"child_models"
] |
654233bf7f13619e4531741f9158e7034eac031b
|
valid
|
DTAgentProgram
|
A decision-theoretic agent. [Fig. 13.1]
|
aima/probability.py
|
def DTAgentProgram(belief_state):
"A decision-theoretic agent. [Fig. 13.1]"
def program(percept):
belief_state.observe(program.action, percept)
program.action = argmax(belief_state.actions(),
belief_state.expected_outcome_utility)
return program.action
program.action = None
return program
|
def DTAgentProgram(belief_state):
"A decision-theoretic agent. [Fig. 13.1]"
def program(percept):
belief_state.observe(program.action, percept)
program.action = argmax(belief_state.actions(),
belief_state.expected_outcome_utility)
return program.action
program.action = None
return program
|
[
"A",
"decision",
"-",
"theoretic",
"agent",
".",
"[",
"Fig",
".",
"13",
".",
"1",
"]"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L10-L18
|
[
"def",
"DTAgentProgram",
"(",
"belief_state",
")",
":",
"def",
"program",
"(",
"percept",
")",
":",
"belief_state",
".",
"observe",
"(",
"program",
".",
"action",
",",
"percept",
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"program",
".",
"action",
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"argmax",
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"belief_state",
".",
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"(",
")",
",",
"belief_state",
".",
"expected_outcome_utility",
")",
"return",
"program",
".",
"action",
"program",
".",
"action",
"=",
"None",
"return",
"program"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
event_values
|
Return a tuple of the values of variables vars in event.
>>> event_values ({'A': 10, 'B': 9, 'C': 8}, ['C', 'A'])
(8, 10)
>>> event_values ((1, 2), ['C', 'A'])
(1, 2)
|
aima/probability.py
|
def event_values(event, vars):
"""Return a tuple of the values of variables vars in event.
>>> event_values ({'A': 10, 'B': 9, 'C': 8}, ['C', 'A'])
(8, 10)
>>> event_values ((1, 2), ['C', 'A'])
(1, 2)
"""
if isinstance(event, tuple) and len(event) == len(vars):
return event
else:
return tuple([event[var] for var in vars])
|
def event_values(event, vars):
"""Return a tuple of the values of variables vars in event.
>>> event_values ({'A': 10, 'B': 9, 'C': 8}, ['C', 'A'])
(8, 10)
>>> event_values ((1, 2), ['C', 'A'])
(1, 2)
"""
if isinstance(event, tuple) and len(event) == len(vars):
return event
else:
return tuple([event[var] for var in vars])
|
[
"Return",
"a",
"tuple",
"of",
"the",
"values",
"of",
"variables",
"vars",
"in",
"event",
".",
">>>",
"event_values",
"(",
"{",
"A",
":",
"10",
"B",
":",
"9",
"C",
":",
"8",
"}",
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"A",
"]",
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"((",
"1",
"2",
")",
"[",
"C",
"A",
"]",
")",
"(",
"1",
"2",
")"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L107-L117
|
[
"def",
"event_values",
"(",
"event",
",",
"vars",
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":",
"if",
"isinstance",
"(",
"event",
",",
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"return",
"event",
"else",
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"return",
"tuple",
"(",
"[",
"event",
"[",
"var",
"]",
"for",
"var",
"in",
"vars",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
enumerate_joint_ask
|
Return a probability distribution over the values of the variable X,
given the {var:val} observations e, in the JointProbDist P. [Section 13.3]
>>> P = JointProbDist(['X', 'Y'])
>>> P[0,0] = 0.25; P[0,1] = 0.5; P[1,1] = P[2,1] = 0.125
>>> enumerate_joint_ask('X', dict(Y=1), P).show_approx()
'0: 0.667, 1: 0.167, 2: 0.167'
|
aima/probability.py
|
def enumerate_joint_ask(X, e, P):
"""Return a probability distribution over the values of the variable X,
given the {var:val} observations e, in the JointProbDist P. [Section 13.3]
>>> P = JointProbDist(['X', 'Y'])
>>> P[0,0] = 0.25; P[0,1] = 0.5; P[1,1] = P[2,1] = 0.125
>>> enumerate_joint_ask('X', dict(Y=1), P).show_approx()
'0: 0.667, 1: 0.167, 2: 0.167'
"""
assert X not in e, "Query variable must be distinct from evidence"
Q = ProbDist(X) # probability distribution for X, initially empty
Y = [v for v in P.variables if v != X and v not in e] # hidden vars.
for xi in P.values(X):
Q[xi] = enumerate_joint(Y, extend(e, X, xi), P)
return Q.normalize()
|
def enumerate_joint_ask(X, e, P):
"""Return a probability distribution over the values of the variable X,
given the {var:val} observations e, in the JointProbDist P. [Section 13.3]
>>> P = JointProbDist(['X', 'Y'])
>>> P[0,0] = 0.25; P[0,1] = 0.5; P[1,1] = P[2,1] = 0.125
>>> enumerate_joint_ask('X', dict(Y=1), P).show_approx()
'0: 0.667, 1: 0.167, 2: 0.167'
"""
assert X not in e, "Query variable must be distinct from evidence"
Q = ProbDist(X) # probability distribution for X, initially empty
Y = [v for v in P.variables if v != X and v not in e] # hidden vars.
for xi in P.values(X):
Q[xi] = enumerate_joint(Y, extend(e, X, xi), P)
return Q.normalize()
|
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"0",
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"167",
"2",
":",
"0",
".",
"167"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L121-L134
|
[
"def",
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"# probability distribution for X, initially empty",
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"(",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
enumerate_joint
|
Return the sum of those entries in P consistent with e,
provided vars is P's remaining variables (the ones not in e).
|
aima/probability.py
|
def enumerate_joint(vars, e, P):
"""Return the sum of those entries in P consistent with e,
provided vars is P's remaining variables (the ones not in e)."""
if not vars:
return P[e]
Y, rest = vars[0], vars[1:]
return sum([enumerate_joint(rest, extend(e, Y, y), P)
for y in P.values(Y)])
|
def enumerate_joint(vars, e, P):
"""Return the sum of those entries in P consistent with e,
provided vars is P's remaining variables (the ones not in e)."""
if not vars:
return P[e]
Y, rest = vars[0], vars[1:]
return sum([enumerate_joint(rest, extend(e, Y, y), P)
for y in P.values(Y)])
|
[
"Return",
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"of",
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"entries",
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"P",
"consistent",
"with",
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"provided",
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"P",
"s",
"remaining",
"variables",
"(",
"the",
"ones",
"not",
"in",
"e",
")",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L136-L143
|
[
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",",
"rest",
"=",
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"[",
"0",
"]",
",",
"vars",
"[",
"1",
":",
"]",
"return",
"sum",
"(",
"[",
"enumerate_joint",
"(",
"rest",
",",
"extend",
"(",
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",",
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",",
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")",
",",
"P",
")",
"for",
"y",
"in",
"P",
".",
"values",
"(",
"Y",
")",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
enumeration_ask
|
Return the conditional probability distribution of variable X
given evidence e, from BayesNet bn. [Fig. 14.9]
>>> enumeration_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284
|
aima/probability.py
|
def enumeration_ask(X, e, bn):
"""Return the conditional probability distribution of variable X
given evidence e, from BayesNet bn. [Fig. 14.9]
>>> enumeration_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284'"""
assert X not in e, "Query variable must be distinct from evidence"
Q = ProbDist(X)
for xi in bn.variable_values(X):
Q[xi] = enumerate_all(bn.vars, extend(e, X, xi), bn)
return Q.normalize()
|
def enumeration_ask(X, e, bn):
"""Return the conditional probability distribution of variable X
given evidence e, from BayesNet bn. [Fig. 14.9]
>>> enumeration_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284'"""
assert X not in e, "Query variable must be distinct from evidence"
Q = ProbDist(X)
for xi in bn.variable_values(X):
Q[xi] = enumerate_all(bn.vars, extend(e, X, xi), bn)
return Q.normalize()
|
[
"Return",
"the",
"conditional",
"probability",
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"of",
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"X",
"given",
"evidence",
"e",
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"()",
"False",
":",
"0",
".",
"716",
"True",
":",
"0",
".",
"284"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L265-L275
|
[
"def",
"enumeration_ask",
"(",
"X",
",",
"e",
",",
"bn",
")",
":",
"assert",
"X",
"not",
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",",
"\"Query variable must be distinct from evidence\"",
"Q",
"=",
"ProbDist",
"(",
"X",
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"for",
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"bn",
".",
"variable_values",
"(",
"X",
")",
":",
"Q",
"[",
"xi",
"]",
"=",
"enumerate_all",
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"bn",
".",
"vars",
",",
"extend",
"(",
"e",
",",
"X",
",",
"xi",
")",
",",
"bn",
")",
"return",
"Q",
".",
"normalize",
"(",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
enumerate_all
|
Return the sum of those entries in P(vars | e{others})
consistent with e, where P is the joint distribution represented
by bn, and e{others} means e restricted to bn's other variables
(the ones other than vars). Parents must precede children in vars.
|
aima/probability.py
|
def enumerate_all(vars, e, bn):
"""Return the sum of those entries in P(vars | e{others})
consistent with e, where P is the joint distribution represented
by bn, and e{others} means e restricted to bn's other variables
(the ones other than vars). Parents must precede children in vars."""
if not vars:
return 1.0
Y, rest = vars[0], vars[1:]
Ynode = bn.variable_node(Y)
if Y in e:
return Ynode.p(e[Y], e) * enumerate_all(rest, e, bn)
else:
return sum(Ynode.p(y, e) * enumerate_all(rest, extend(e, Y, y), bn)
for y in bn.variable_values(Y))
|
def enumerate_all(vars, e, bn):
"""Return the sum of those entries in P(vars | e{others})
consistent with e, where P is the joint distribution represented
by bn, and e{others} means e restricted to bn's other variables
(the ones other than vars). Parents must precede children in vars."""
if not vars:
return 1.0
Y, rest = vars[0], vars[1:]
Ynode = bn.variable_node(Y)
if Y in e:
return Ynode.p(e[Y], e) * enumerate_all(rest, e, bn)
else:
return sum(Ynode.p(y, e) * enumerate_all(rest, extend(e, Y, y), bn)
for y in bn.variable_values(Y))
|
[
"Return",
"the",
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"those",
"entries",
"in",
"P",
"(",
"vars",
"|",
"e",
"{",
"others",
"}",
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"consistent",
"with",
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"where",
"P",
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"the",
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"other",
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"other",
"than",
"vars",
")",
".",
"Parents",
"must",
"precede",
"children",
"in",
"vars",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L277-L290
|
[
"def",
"enumerate_all",
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",",
"e",
",",
"bn",
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":",
"if",
"not",
"vars",
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"return",
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"Y",
",",
"rest",
"=",
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"0",
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",",
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",",
"bn",
")",
"for",
"y",
"in",
"bn",
".",
"variable_values",
"(",
"Y",
")",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
elimination_ask
|
Compute bn's P(X|e) by variable elimination. [Fig. 14.11]
>>> elimination_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284
|
aima/probability.py
|
def elimination_ask(X, e, bn):
"""Compute bn's P(X|e) by variable elimination. [Fig. 14.11]
>>> elimination_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284'"""
assert X not in e, "Query variable must be distinct from evidence"
factors = []
for var in reversed(bn.vars):
factors.append(make_factor(var, e, bn))
if is_hidden(var, X, e):
factors = sum_out(var, factors, bn)
return pointwise_product(factors, bn).normalize()
|
def elimination_ask(X, e, bn):
"""Compute bn's P(X|e) by variable elimination. [Fig. 14.11]
>>> elimination_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary
... ).show_approx()
'False: 0.716, True: 0.284'"""
assert X not in e, "Query variable must be distinct from evidence"
factors = []
for var in reversed(bn.vars):
factors.append(make_factor(var, e, bn))
if is_hidden(var, X, e):
factors = sum_out(var, factors, bn)
return pointwise_product(factors, bn).normalize()
|
[
"Compute",
"bn",
"s",
"P",
"(",
"X|e",
")",
"by",
"variable",
"elimination",
".",
"[",
"Fig",
".",
"14",
".",
"11",
"]",
">>>",
"elimination_ask",
"(",
"Burglary",
"dict",
"(",
"JohnCalls",
"=",
"T",
"MaryCalls",
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"T",
")",
"burglary",
"...",
")",
".",
"show_approx",
"()",
"False",
":",
"0",
".",
"716",
"True",
":",
"0",
".",
"284"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L294-L305
|
[
"def",
"elimination_ask",
"(",
"X",
",",
"e",
",",
"bn",
")",
":",
"assert",
"X",
"not",
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",",
"\"Query variable must be distinct from evidence\"",
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":",
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"var",
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")",
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",",
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"bn",
")",
"return",
"pointwise_product",
"(",
"factors",
",",
"bn",
")",
".",
"normalize",
"(",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
make_factor
|
Return the factor for var in bn's joint distribution given e.
That is, bn's full joint distribution, projected to accord with e,
is the pointwise product of these factors for bn's variables.
|
aima/probability.py
|
def make_factor(var, e, bn):
"""Return the factor for var in bn's joint distribution given e.
That is, bn's full joint distribution, projected to accord with e,
is the pointwise product of these factors for bn's variables."""
node = bn.variable_node(var)
vars = [X for X in [var] + node.parents if X not in e]
cpt = dict((event_values(e1, vars), node.p(e1[var], e1))
for e1 in all_events(vars, bn, e))
return Factor(vars, cpt)
|
def make_factor(var, e, bn):
"""Return the factor for var in bn's joint distribution given e.
That is, bn's full joint distribution, projected to accord with e,
is the pointwise product of these factors for bn's variables."""
node = bn.variable_node(var)
vars = [X for X in [var] + node.parents if X not in e]
cpt = dict((event_values(e1, vars), node.p(e1[var], e1))
for e1 in all_events(vars, bn, e))
return Factor(vars, cpt)
|
[
"Return",
"the",
"factor",
"for",
"var",
"in",
"bn",
"s",
"joint",
"distribution",
"given",
"e",
".",
"That",
"is",
"bn",
"s",
"full",
"joint",
"distribution",
"projected",
"to",
"accord",
"with",
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"is",
"the",
"pointwise",
"product",
"of",
"these",
"factors",
"for",
"bn",
"s",
"variables",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L311-L319
|
[
"def",
"make_factor",
"(",
"var",
",",
"e",
",",
"bn",
")",
":",
"node",
"=",
"bn",
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"variable_node",
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"var",
")",
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"X",
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"+",
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",",
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",",
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"(",
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",",
"bn",
",",
"e",
")",
")",
"return",
"Factor",
"(",
"vars",
",",
"cpt",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
sum_out
|
Eliminate var from all factors by summing over its values.
|
aima/probability.py
|
def sum_out(var, factors, bn):
"Eliminate var from all factors by summing over its values."
result, var_factors = [], []
for f in factors:
(var_factors if var in f.vars else result).append(f)
result.append(pointwise_product(var_factors, bn).sum_out(var, bn))
return result
|
def sum_out(var, factors, bn):
"Eliminate var from all factors by summing over its values."
result, var_factors = [], []
for f in factors:
(var_factors if var in f.vars else result).append(f)
result.append(pointwise_product(var_factors, bn).sum_out(var, bn))
return result
|
[
"Eliminate",
"var",
"from",
"all",
"factors",
"by",
"summing",
"over",
"its",
"values",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L324-L330
|
[
"def",
"sum_out",
"(",
"var",
",",
"factors",
",",
"bn",
")",
":",
"result",
",",
"var_factors",
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"[",
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",",
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"(",
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",",
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")",
".",
"sum_out",
"(",
"var",
",",
"bn",
")",
")",
"return",
"result"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
all_events
|
Yield every way of extending e with values for all vars.
|
aima/probability.py
|
def all_events(vars, bn, e):
"Yield every way of extending e with values for all vars."
if not vars:
yield e
else:
X, rest = vars[0], vars[1:]
for e1 in all_events(rest, bn, e):
for x in bn.variable_values(X):
yield extend(e1, X, x)
|
def all_events(vars, bn, e):
"Yield every way of extending e with values for all vars."
if not vars:
yield e
else:
X, rest = vars[0], vars[1:]
for e1 in all_events(rest, bn, e):
for x in bn.variable_values(X):
yield extend(e1, X, x)
|
[
"Yield",
"every",
"way",
"of",
"extending",
"e",
"with",
"values",
"for",
"all",
"vars",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L364-L372
|
[
"def",
"all_events",
"(",
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",",
"bn",
",",
"e",
")",
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"if",
"not",
"vars",
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",",
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":",
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"(",
"X",
")",
":",
"yield",
"extend",
"(",
"e1",
",",
"X",
",",
"x",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
prior_sample
|
Randomly sample from bn's full joint distribution. The result
is a {variable: value} dict. [Fig. 14.13]
|
aima/probability.py
|
def prior_sample(bn):
"""Randomly sample from bn's full joint distribution. The result
is a {variable: value} dict. [Fig. 14.13]"""
event = {}
for node in bn.nodes:
event[node.variable] = node.sample(event)
return event
|
def prior_sample(bn):
"""Randomly sample from bn's full joint distribution. The result
is a {variable: value} dict. [Fig. 14.13]"""
event = {}
for node in bn.nodes:
event[node.variable] = node.sample(event)
return event
|
[
"Randomly",
"sample",
"from",
"bn",
"s",
"full",
"joint",
"distribution",
".",
"The",
"result",
"is",
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"{",
"variable",
":",
"value",
"}",
"dict",
".",
"[",
"Fig",
".",
"14",
".",
"13",
"]"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L387-L393
|
[
"def",
"prior_sample",
"(",
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")",
":",
"event",
"=",
"{",
"}",
"for",
"node",
"in",
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":",
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"[",
"node",
".",
"variable",
"]",
"=",
"node",
".",
"sample",
"(",
"event",
")",
"return",
"event"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
rejection_sampling
|
Estimate the probability distribution of variable X given
evidence e in BayesNet bn, using N samples. [Fig. 14.14]
Raises a ZeroDivisionError if all the N samples are rejected,
i.e., inconsistent with e.
>>> seed(47)
>>> rejection_sampling('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.7, True: 0.3'
|
aima/probability.py
|
def rejection_sampling(X, e, bn, N):
"""Estimate the probability distribution of variable X given
evidence e in BayesNet bn, using N samples. [Fig. 14.14]
Raises a ZeroDivisionError if all the N samples are rejected,
i.e., inconsistent with e.
>>> seed(47)
>>> rejection_sampling('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.7, True: 0.3'
"""
counts = dict((x, 0) for x in bn.variable_values(X)) # bold N in Fig. 14.14
for j in xrange(N):
sample = prior_sample(bn) # boldface x in Fig. 14.14
if consistent_with(sample, e):
counts[sample[X]] += 1
return ProbDist(X, counts)
|
def rejection_sampling(X, e, bn, N):
"""Estimate the probability distribution of variable X given
evidence e in BayesNet bn, using N samples. [Fig. 14.14]
Raises a ZeroDivisionError if all the N samples are rejected,
i.e., inconsistent with e.
>>> seed(47)
>>> rejection_sampling('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.7, True: 0.3'
"""
counts = dict((x, 0) for x in bn.variable_values(X)) # bold N in Fig. 14.14
for j in xrange(N):
sample = prior_sample(bn) # boldface x in Fig. 14.14
if consistent_with(sample, e):
counts[sample[X]] += 1
return ProbDist(X, counts)
|
[
"Estimate",
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"X",
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"Burglary",
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"...",
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"show_approx",
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"False",
":",
"0",
".",
"7",
"True",
":",
"0",
".",
"3"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L397-L412
|
[
"def",
"rejection_sampling",
"(",
"X",
",",
"e",
",",
"bn",
",",
"N",
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":",
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"(",
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",",
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"variable_values",
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"X",
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"# bold N in Fig. 14.14",
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"N",
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"sample",
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"prior_sample",
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"bn",
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"# boldface x in Fig. 14.14",
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"sample",
",",
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"[",
"X",
"]",
"]",
"+=",
"1",
"return",
"ProbDist",
"(",
"X",
",",
"counts",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
consistent_with
|
Is event consistent with the given evidence?
|
aima/probability.py
|
def consistent_with(event, evidence):
"Is event consistent with the given evidence?"
return every(lambda (k, v): evidence.get(k, v) == v,
event.items())
|
def consistent_with(event, evidence):
"Is event consistent with the given evidence?"
return every(lambda (k, v): evidence.get(k, v) == v,
event.items())
|
[
"Is",
"event",
"consistent",
"with",
"the",
"given",
"evidence?"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L414-L417
|
[
"def",
"consistent_with",
"(",
"event",
",",
"evidence",
")",
":",
"return",
"every",
"(",
"lambda",
"(",
"k",
",",
"v",
")",
":",
"evidence",
".",
"get",
"(",
"k",
",",
"v",
")",
"==",
"v",
",",
"event",
".",
"items",
"(",
")",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
likelihood_weighting
|
Estimate the probability distribution of variable X given
evidence e in BayesNet bn. [Fig. 14.15]
>>> seed(1017)
>>> likelihood_weighting('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.702, True: 0.298'
|
aima/probability.py
|
def likelihood_weighting(X, e, bn, N):
"""Estimate the probability distribution of variable X given
evidence e in BayesNet bn. [Fig. 14.15]
>>> seed(1017)
>>> likelihood_weighting('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.702, True: 0.298'
"""
W = dict((x, 0) for x in bn.variable_values(X))
for j in xrange(N):
sample, weight = weighted_sample(bn, e) # boldface x, w in Fig. 14.15
W[sample[X]] += weight
return ProbDist(X, W)
|
def likelihood_weighting(X, e, bn, N):
"""Estimate the probability distribution of variable X given
evidence e in BayesNet bn. [Fig. 14.15]
>>> seed(1017)
>>> likelihood_weighting('Burglary', dict(JohnCalls=T, MaryCalls=T),
... burglary, 10000).show_approx()
'False: 0.702, True: 0.298'
"""
W = dict((x, 0) for x in bn.variable_values(X))
for j in xrange(N):
sample, weight = weighted_sample(bn, e) # boldface x, w in Fig. 14.15
W[sample[X]] += weight
return ProbDist(X, W)
|
[
"Estimate",
"the",
"probability",
"distribution",
"of",
"variable",
"X",
"given",
"evidence",
"e",
"in",
"BayesNet",
"bn",
".",
"[",
"Fig",
".",
"14",
".",
"15",
"]",
">>>",
"seed",
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"1017",
")",
">>>",
"likelihood_weighting",
"(",
"Burglary",
"dict",
"(",
"JohnCalls",
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"MaryCalls",
"=",
"T",
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"...",
"burglary",
"10000",
")",
".",
"show_approx",
"()",
"False",
":",
"0",
".",
"702",
"True",
":",
"0",
".",
"298"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L421-L433
|
[
"def",
"likelihood_weighting",
"(",
"X",
",",
"e",
",",
"bn",
",",
"N",
")",
":",
"W",
"=",
"dict",
"(",
"(",
"x",
",",
"0",
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"for",
"x",
"in",
"bn",
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"variable_values",
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"X",
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")",
"for",
"j",
"in",
"xrange",
"(",
"N",
")",
":",
"sample",
",",
"weight",
"=",
"weighted_sample",
"(",
"bn",
",",
"e",
")",
"# boldface x, w in Fig. 14.15",
"W",
"[",
"sample",
"[",
"X",
"]",
"]",
"+=",
"weight",
"return",
"ProbDist",
"(",
"X",
",",
"W",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
weighted_sample
|
Sample an event from bn that's consistent with the evidence e;
return the event and its weight, the likelihood that the event
accords to the evidence.
|
aima/probability.py
|
def weighted_sample(bn, e):
"""Sample an event from bn that's consistent with the evidence e;
return the event and its weight, the likelihood that the event
accords to the evidence."""
w = 1
event = dict(e) # boldface x in Fig. 14.15
for node in bn.nodes:
Xi = node.variable
if Xi in e:
w *= node.p(e[Xi], event)
else:
event[Xi] = node.sample(event)
return event, w
|
def weighted_sample(bn, e):
"""Sample an event from bn that's consistent with the evidence e;
return the event and its weight, the likelihood that the event
accords to the evidence."""
w = 1
event = dict(e) # boldface x in Fig. 14.15
for node in bn.nodes:
Xi = node.variable
if Xi in e:
w *= node.p(e[Xi], event)
else:
event[Xi] = node.sample(event)
return event, w
|
[
"Sample",
"an",
"event",
"from",
"bn",
"that",
"s",
"consistent",
"with",
"the",
"evidence",
"e",
";",
"return",
"the",
"event",
"and",
"its",
"weight",
"the",
"likelihood",
"that",
"the",
"event",
"accords",
"to",
"the",
"evidence",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L435-L447
|
[
"def",
"weighted_sample",
"(",
"bn",
",",
"e",
")",
":",
"w",
"=",
"1",
"event",
"=",
"dict",
"(",
"e",
")",
"# boldface x in Fig. 14.15",
"for",
"node",
"in",
"bn",
".",
"nodes",
":",
"Xi",
"=",
"node",
".",
"variable",
"if",
"Xi",
"in",
"e",
":",
"w",
"*=",
"node",
".",
"p",
"(",
"e",
"[",
"Xi",
"]",
",",
"event",
")",
"else",
":",
"event",
"[",
"Xi",
"]",
"=",
"node",
".",
"sample",
"(",
"event",
")",
"return",
"event",
",",
"w"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
gibbs_ask
|
[Fig. 14.16]
>>> seed(1017)
>>> gibbs_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary, 1000
... ).show_approx()
'False: 0.738, True: 0.262'
|
aima/probability.py
|
def gibbs_ask(X, e, bn, N):
"""[Fig. 14.16]
>>> seed(1017)
>>> gibbs_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary, 1000
... ).show_approx()
'False: 0.738, True: 0.262'
"""
assert X not in e, "Query variable must be distinct from evidence"
counts = dict((x, 0) for x in bn.variable_values(X)) # bold N in Fig. 14.16
Z = [var for var in bn.vars if var not in e]
state = dict(e) # boldface x in Fig. 14.16
for Zi in Z:
state[Zi] = choice(bn.variable_values(Zi))
for j in xrange(N):
for Zi in Z:
state[Zi] = markov_blanket_sample(Zi, state, bn)
counts[state[X]] += 1
return ProbDist(X, counts)
|
def gibbs_ask(X, e, bn, N):
"""[Fig. 14.16]
>>> seed(1017)
>>> gibbs_ask('Burglary', dict(JohnCalls=T, MaryCalls=T), burglary, 1000
... ).show_approx()
'False: 0.738, True: 0.262'
"""
assert X not in e, "Query variable must be distinct from evidence"
counts = dict((x, 0) for x in bn.variable_values(X)) # bold N in Fig. 14.16
Z = [var for var in bn.vars if var not in e]
state = dict(e) # boldface x in Fig. 14.16
for Zi in Z:
state[Zi] = choice(bn.variable_values(Zi))
for j in xrange(N):
for Zi in Z:
state[Zi] = markov_blanket_sample(Zi, state, bn)
counts[state[X]] += 1
return ProbDist(X, counts)
|
[
"[",
"Fig",
".",
"14",
".",
"16",
"]",
">>>",
"seed",
"(",
"1017",
")",
">>>",
"gibbs_ask",
"(",
"Burglary",
"dict",
"(",
"JohnCalls",
"=",
"T",
"MaryCalls",
"=",
"T",
")",
"burglary",
"1000",
"...",
")",
".",
"show_approx",
"()",
"False",
":",
"0",
".",
"738",
"True",
":",
"0",
".",
"262"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L451-L468
|
[
"def",
"gibbs_ask",
"(",
"X",
",",
"e",
",",
"bn",
",",
"N",
")",
":",
"assert",
"X",
"not",
"in",
"e",
",",
"\"Query variable must be distinct from evidence\"",
"counts",
"=",
"dict",
"(",
"(",
"x",
",",
"0",
")",
"for",
"x",
"in",
"bn",
".",
"variable_values",
"(",
"X",
")",
")",
"# bold N in Fig. 14.16",
"Z",
"=",
"[",
"var",
"for",
"var",
"in",
"bn",
".",
"vars",
"if",
"var",
"not",
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"e",
"]",
"state",
"=",
"dict",
"(",
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")",
"# boldface x in Fig. 14.16",
"for",
"Zi",
"in",
"Z",
":",
"state",
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")",
"for",
"j",
"in",
"xrange",
"(",
"N",
")",
":",
"for",
"Zi",
"in",
"Z",
":",
"state",
"[",
"Zi",
"]",
"=",
"markov_blanket_sample",
"(",
"Zi",
",",
"state",
",",
"bn",
")",
"counts",
"[",
"state",
"[",
"X",
"]",
"]",
"+=",
"1",
"return",
"ProbDist",
"(",
"X",
",",
"counts",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
markov_blanket_sample
|
Return a sample from P(X | mb) where mb denotes that the
variables in the Markov blanket of X take their values from event
e (which must assign a value to each). The Markov blanket of X is
X's parents, children, and children's parents.
|
aima/probability.py
|
def markov_blanket_sample(X, e, bn):
"""Return a sample from P(X | mb) where mb denotes that the
variables in the Markov blanket of X take their values from event
e (which must assign a value to each). The Markov blanket of X is
X's parents, children, and children's parents."""
Xnode = bn.variable_node(X)
Q = ProbDist(X)
for xi in bn.variable_values(X):
ei = extend(e, X, xi)
# [Equation 14.12:]
Q[xi] = Xnode.p(xi, e) * product(Yj.p(ei[Yj.variable], ei)
for Yj in Xnode.children)
return probability(Q.normalize()[True])
|
def markov_blanket_sample(X, e, bn):
"""Return a sample from P(X | mb) where mb denotes that the
variables in the Markov blanket of X take their values from event
e (which must assign a value to each). The Markov blanket of X is
X's parents, children, and children's parents."""
Xnode = bn.variable_node(X)
Q = ProbDist(X)
for xi in bn.variable_values(X):
ei = extend(e, X, xi)
# [Equation 14.12:]
Q[xi] = Xnode.p(xi, e) * product(Yj.p(ei[Yj.variable], ei)
for Yj in Xnode.children)
return probability(Q.normalize()[True])
|
[
"Return",
"a",
"sample",
"from",
"P",
"(",
"X",
"|",
"mb",
")",
"where",
"mb",
"denotes",
"that",
"the",
"variables",
"in",
"the",
"Markov",
"blanket",
"of",
"X",
"take",
"their",
"values",
"from",
"event",
"e",
"(",
"which",
"must",
"assign",
"a",
"value",
"to",
"each",
")",
".",
"The",
"Markov",
"blanket",
"of",
"X",
"is",
"X",
"s",
"parents",
"children",
"and",
"children",
"s",
"parents",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L470-L482
|
[
"def",
"markov_blanket_sample",
"(",
"X",
",",
"e",
",",
"bn",
")",
":",
"Xnode",
"=",
"bn",
".",
"variable_node",
"(",
"X",
")",
"Q",
"=",
"ProbDist",
"(",
"X",
")",
"for",
"xi",
"in",
"bn",
".",
"variable_values",
"(",
"X",
")",
":",
"ei",
"=",
"extend",
"(",
"e",
",",
"X",
",",
"xi",
")",
"# [Equation 14.12:]",
"Q",
"[",
"xi",
"]",
"=",
"Xnode",
".",
"p",
"(",
"xi",
",",
"e",
")",
"*",
"product",
"(",
"Yj",
".",
"p",
"(",
"ei",
"[",
"Yj",
".",
"variable",
"]",
",",
"ei",
")",
"for",
"Yj",
"in",
"Xnode",
".",
"children",
")",
"return",
"probability",
"(",
"Q",
".",
"normalize",
"(",
")",
"[",
"True",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
ProbDist.normalize
|
Make sure the probabilities of all values sum to 1.
Returns the normalized distribution.
Raises a ZeroDivisionError if the sum of the values is 0.
>>> P = ProbDist('Flip'); P['H'], P['T'] = 35, 65
>>> P = P.normalize()
>>> print '%5.3f %5.3f' % (P.prob['H'], P.prob['T'])
0.350 0.650
|
aima/probability.py
|
def normalize(self):
"""Make sure the probabilities of all values sum to 1.
Returns the normalized distribution.
Raises a ZeroDivisionError if the sum of the values is 0.
>>> P = ProbDist('Flip'); P['H'], P['T'] = 35, 65
>>> P = P.normalize()
>>> print '%5.3f %5.3f' % (P.prob['H'], P.prob['T'])
0.350 0.650
"""
total = float(sum(self.prob.values()))
if not (1.0-epsilon < total < 1.0+epsilon):
for val in self.prob:
self.prob[val] /= total
return self
|
def normalize(self):
"""Make sure the probabilities of all values sum to 1.
Returns the normalized distribution.
Raises a ZeroDivisionError if the sum of the values is 0.
>>> P = ProbDist('Flip'); P['H'], P['T'] = 35, 65
>>> P = P.normalize()
>>> print '%5.3f %5.3f' % (P.prob['H'], P.prob['T'])
0.350 0.650
"""
total = float(sum(self.prob.values()))
if not (1.0-epsilon < total < 1.0+epsilon):
for val in self.prob:
self.prob[val] /= total
return self
|
[
"Make",
"sure",
"the",
"probabilities",
"of",
"all",
"values",
"sum",
"to",
"1",
".",
"Returns",
"the",
"normalized",
"distribution",
".",
"Raises",
"a",
"ZeroDivisionError",
"if",
"the",
"sum",
"of",
"the",
"values",
"is",
"0",
".",
">>>",
"P",
"=",
"ProbDist",
"(",
"Flip",
")",
";",
"P",
"[",
"H",
"]",
"P",
"[",
"T",
"]",
"=",
"35",
"65",
">>>",
"P",
"=",
"P",
".",
"normalize",
"()",
">>>",
"print",
"%5",
".",
"3f",
"%5",
".",
"3f",
"%",
"(",
"P",
".",
"prob",
"[",
"H",
"]",
"P",
".",
"prob",
"[",
"T",
"]",
")",
"0",
".",
"350",
"0",
".",
"650"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L51-L64
|
[
"def",
"normalize",
"(",
"self",
")",
":",
"total",
"=",
"float",
"(",
"sum",
"(",
"self",
".",
"prob",
".",
"values",
"(",
")",
")",
")",
"if",
"not",
"(",
"1.0",
"-",
"epsilon",
"<",
"total",
"<",
"1.0",
"+",
"epsilon",
")",
":",
"for",
"val",
"in",
"self",
".",
"prob",
":",
"self",
".",
"prob",
"[",
"val",
"]",
"/=",
"total",
"return",
"self"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
ProbDist.show_approx
|
Show the probabilities rounded and sorted by key, for the
sake of portable doctests.
|
aima/probability.py
|
def show_approx(self, numfmt='%.3g'):
"""Show the probabilities rounded and sorted by key, for the
sake of portable doctests."""
return ', '.join([('%s: ' + numfmt) % (v, p)
for (v, p) in sorted(self.prob.items())])
|
def show_approx(self, numfmt='%.3g'):
"""Show the probabilities rounded and sorted by key, for the
sake of portable doctests."""
return ', '.join([('%s: ' + numfmt) % (v, p)
for (v, p) in sorted(self.prob.items())])
|
[
"Show",
"the",
"probabilities",
"rounded",
"and",
"sorted",
"by",
"key",
"for",
"the",
"sake",
"of",
"portable",
"doctests",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L66-L70
|
[
"def",
"show_approx",
"(",
"self",
",",
"numfmt",
"=",
"'%.3g'",
")",
":",
"return",
"', '",
".",
"join",
"(",
"[",
"(",
"'%s: '",
"+",
"numfmt",
")",
"%",
"(",
"v",
",",
"p",
")",
"for",
"(",
"v",
",",
"p",
")",
"in",
"sorted",
"(",
"self",
".",
"prob",
".",
"items",
"(",
")",
")",
"]",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
BayesNet.add
|
Add a node to the net. Its parents must already be in the
net, and its variable must not.
|
aima/probability.py
|
def add(self, node_spec):
"""Add a node to the net. Its parents must already be in the
net, and its variable must not."""
node = BayesNode(*node_spec)
assert node.variable not in self.vars
assert every(lambda parent: parent in self.vars, node.parents)
self.nodes.append(node)
self.vars.append(node.variable)
for parent in node.parents:
self.variable_node(parent).children.append(node)
|
def add(self, node_spec):
"""Add a node to the net. Its parents must already be in the
net, and its variable must not."""
node = BayesNode(*node_spec)
assert node.variable not in self.vars
assert every(lambda parent: parent in self.vars, node.parents)
self.nodes.append(node)
self.vars.append(node.variable)
for parent in node.parents:
self.variable_node(parent).children.append(node)
|
[
"Add",
"a",
"node",
"to",
"the",
"net",
".",
"Its",
"parents",
"must",
"already",
"be",
"in",
"the",
"net",
"and",
"its",
"variable",
"must",
"not",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L156-L165
|
[
"def",
"add",
"(",
"self",
",",
"node_spec",
")",
":",
"node",
"=",
"BayesNode",
"(",
"*",
"node_spec",
")",
"assert",
"node",
".",
"variable",
"not",
"in",
"self",
".",
"vars",
"assert",
"every",
"(",
"lambda",
"parent",
":",
"parent",
"in",
"self",
".",
"vars",
",",
"node",
".",
"parents",
")",
"self",
".",
"nodes",
".",
"append",
"(",
"node",
")",
"self",
".",
"vars",
".",
"append",
"(",
"node",
".",
"variable",
")",
"for",
"parent",
"in",
"node",
".",
"parents",
":",
"self",
".",
"variable_node",
"(",
"parent",
")",
".",
"children",
".",
"append",
"(",
"node",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
BayesNet.variable_node
|
Return the node for the variable named var.
>>> burglary.variable_node('Burglary').variable
'Burglary
|
aima/probability.py
|
def variable_node(self, var):
"""Return the node for the variable named var.
>>> burglary.variable_node('Burglary').variable
'Burglary'"""
for n in self.nodes:
if n.variable == var:
return n
raise Exception("No such variable: %s" % var)
|
def variable_node(self, var):
"""Return the node for the variable named var.
>>> burglary.variable_node('Burglary').variable
'Burglary'"""
for n in self.nodes:
if n.variable == var:
return n
raise Exception("No such variable: %s" % var)
|
[
"Return",
"the",
"node",
"for",
"the",
"variable",
"named",
"var",
".",
">>>",
"burglary",
".",
"variable_node",
"(",
"Burglary",
")",
".",
"variable",
"Burglary"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L167-L174
|
[
"def",
"variable_node",
"(",
"self",
",",
"var",
")",
":",
"for",
"n",
"in",
"self",
".",
"nodes",
":",
"if",
"n",
".",
"variable",
"==",
"var",
":",
"return",
"n",
"raise",
"Exception",
"(",
"\"No such variable: %s\"",
"%",
"var",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
BayesNode.p
|
Return the conditional probability
P(X=value | parents=parent_values), where parent_values
are the values of parents in event. (event must assign each
parent a value.)
>>> bn = BayesNode('X', 'Burglary', {T: 0.2, F: 0.625})
>>> bn.p(False, {'Burglary': False, 'Earthquake': True})
0.375
|
aima/probability.py
|
def p(self, value, event):
"""Return the conditional probability
P(X=value | parents=parent_values), where parent_values
are the values of parents in event. (event must assign each
parent a value.)
>>> bn = BayesNode('X', 'Burglary', {T: 0.2, F: 0.625})
>>> bn.p(False, {'Burglary': False, 'Earthquake': True})
0.375"""
assert isinstance(value, bool)
ptrue = self.cpt[event_values(event, self.parents)]
return if_(value, ptrue, 1 - ptrue)
|
def p(self, value, event):
"""Return the conditional probability
P(X=value | parents=parent_values), where parent_values
are the values of parents in event. (event must assign each
parent a value.)
>>> bn = BayesNode('X', 'Burglary', {T: 0.2, F: 0.625})
>>> bn.p(False, {'Burglary': False, 'Earthquake': True})
0.375"""
assert isinstance(value, bool)
ptrue = self.cpt[event_values(event, self.parents)]
return if_(value, ptrue, 1 - ptrue)
|
[
"Return",
"the",
"conditional",
"probability",
"P",
"(",
"X",
"=",
"value",
"|",
"parents",
"=",
"parent_values",
")",
"where",
"parent_values",
"are",
"the",
"values",
"of",
"parents",
"in",
"event",
".",
"(",
"event",
"must",
"assign",
"each",
"parent",
"a",
"value",
".",
")",
">>>",
"bn",
"=",
"BayesNode",
"(",
"X",
"Burglary",
"{",
"T",
":",
"0",
".",
"2",
"F",
":",
"0",
".",
"625",
"}",
")",
">>>",
"bn",
".",
"p",
"(",
"False",
"{",
"Burglary",
":",
"False",
"Earthquake",
":",
"True",
"}",
")",
"0",
".",
"375"
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L228-L238
|
[
"def",
"p",
"(",
"self",
",",
"value",
",",
"event",
")",
":",
"assert",
"isinstance",
"(",
"value",
",",
"bool",
")",
"ptrue",
"=",
"self",
".",
"cpt",
"[",
"event_values",
"(",
"event",
",",
"self",
".",
"parents",
")",
"]",
"return",
"if_",
"(",
"value",
",",
"ptrue",
",",
"1",
"-",
"ptrue",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
Factor.pointwise_product
|
Multiply two factors, combining their variables.
|
aima/probability.py
|
def pointwise_product(self, other, bn):
"Multiply two factors, combining their variables."
vars = list(set(self.vars) | set(other.vars))
cpt = dict((event_values(e, vars), self.p(e) * other.p(e))
for e in all_events(vars, bn, {}))
return Factor(vars, cpt)
|
def pointwise_product(self, other, bn):
"Multiply two factors, combining their variables."
vars = list(set(self.vars) | set(other.vars))
cpt = dict((event_values(e, vars), self.p(e) * other.p(e))
for e in all_events(vars, bn, {}))
return Factor(vars, cpt)
|
[
"Multiply",
"two",
"factors",
"combining",
"their",
"variables",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L338-L343
|
[
"def",
"pointwise_product",
"(",
"self",
",",
"other",
",",
"bn",
")",
":",
"vars",
"=",
"list",
"(",
"set",
"(",
"self",
".",
"vars",
")",
"|",
"set",
"(",
"other",
".",
"vars",
")",
")",
"cpt",
"=",
"dict",
"(",
"(",
"event_values",
"(",
"e",
",",
"vars",
")",
",",
"self",
".",
"p",
"(",
"e",
")",
"*",
"other",
".",
"p",
"(",
"e",
")",
")",
"for",
"e",
"in",
"all_events",
"(",
"vars",
",",
"bn",
",",
"{",
"}",
")",
")",
"return",
"Factor",
"(",
"vars",
",",
"cpt",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
Factor.sum_out
|
Make a factor eliminating var by summing over its values.
|
aima/probability.py
|
def sum_out(self, var, bn):
"Make a factor eliminating var by summing over its values."
vars = [X for X in self.vars if X != var]
cpt = dict((event_values(e, vars),
sum(self.p(extend(e, var, val))
for val in bn.variable_values(var)))
for e in all_events(vars, bn, {}))
return Factor(vars, cpt)
|
def sum_out(self, var, bn):
"Make a factor eliminating var by summing over its values."
vars = [X for X in self.vars if X != var]
cpt = dict((event_values(e, vars),
sum(self.p(extend(e, var, val))
for val in bn.variable_values(var)))
for e in all_events(vars, bn, {}))
return Factor(vars, cpt)
|
[
"Make",
"a",
"factor",
"eliminating",
"var",
"by",
"summing",
"over",
"its",
"values",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L345-L352
|
[
"def",
"sum_out",
"(",
"self",
",",
"var",
",",
"bn",
")",
":",
"vars",
"=",
"[",
"X",
"for",
"X",
"in",
"self",
".",
"vars",
"if",
"X",
"!=",
"var",
"]",
"cpt",
"=",
"dict",
"(",
"(",
"event_values",
"(",
"e",
",",
"vars",
")",
",",
"sum",
"(",
"self",
".",
"p",
"(",
"extend",
"(",
"e",
",",
"var",
",",
"val",
")",
")",
"for",
"val",
"in",
"bn",
".",
"variable_values",
"(",
"var",
")",
")",
")",
"for",
"e",
"in",
"all_events",
"(",
"vars",
",",
"bn",
",",
"{",
"}",
")",
")",
"return",
"Factor",
"(",
"vars",
",",
"cpt",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
Factor.normalize
|
Return my probabilities; must be down to one variable.
|
aima/probability.py
|
def normalize(self):
"Return my probabilities; must be down to one variable."
assert len(self.vars) == 1
return ProbDist(self.vars[0],
dict((k, v) for ((k,), v) in self.cpt.items()))
|
def normalize(self):
"Return my probabilities; must be down to one variable."
assert len(self.vars) == 1
return ProbDist(self.vars[0],
dict((k, v) for ((k,), v) in self.cpt.items()))
|
[
"Return",
"my",
"probabilities",
";",
"must",
"be",
"down",
"to",
"one",
"variable",
"."
] |
hobson/aima
|
python
|
https://github.com/hobson/aima/blob/3572b2fb92039b4a1abe384be8545560fbd3d470/aima/probability.py#L354-L358
|
[
"def",
"normalize",
"(",
"self",
")",
":",
"assert",
"len",
"(",
"self",
".",
"vars",
")",
"==",
"1",
"return",
"ProbDist",
"(",
"self",
".",
"vars",
"[",
"0",
"]",
",",
"dict",
"(",
"(",
"k",
",",
"v",
")",
"for",
"(",
"(",
"k",
",",
")",
",",
"v",
")",
"in",
"self",
".",
"cpt",
".",
"items",
"(",
")",
")",
")"
] |
3572b2fb92039b4a1abe384be8545560fbd3d470
|
valid
|
BaseMultiLevelChunker.next_chunk_boundaries
|
Computes the next chunk boundaries within `buf`.
See :meth:`.BaseChunker.next_chunk_boundaries`.
|
fastchunking/__init__.py
|
def next_chunk_boundaries(self, buf, prepend_bytes=0):
"""Computes the next chunk boundaries within `buf`.
See :meth:`.BaseChunker.next_chunk_boundaries`.
"""
return (boundary for boundary, _ in self.next_chunk_boundaries_levels(buf, prepend_bytes))
|
def next_chunk_boundaries(self, buf, prepend_bytes=0):
"""Computes the next chunk boundaries within `buf`.
See :meth:`.BaseChunker.next_chunk_boundaries`.
"""
return (boundary for boundary, _ in self.next_chunk_boundaries_levels(buf, prepend_bytes))
|
[
"Computes",
"the",
"next",
"chunk",
"boundaries",
"within",
"buf",
"."
] |
netleibi/fastchunking
|
python
|
https://github.com/netleibi/fastchunking/blob/069b7689d26bc067120907f01d9453ab3d2efa74/fastchunking/__init__.py#L73-L78
|
[
"def",
"next_chunk_boundaries",
"(",
"self",
",",
"buf",
",",
"prepend_bytes",
"=",
"0",
")",
":",
"return",
"(",
"boundary",
"for",
"boundary",
",",
"_",
"in",
"self",
".",
"next_chunk_boundaries_levels",
"(",
"buf",
",",
"prepend_bytes",
")",
")"
] |
069b7689d26bc067120907f01d9453ab3d2efa74
|
valid
|
DefaultMultiLevelChunker.next_chunk_boundaries_levels
|
Computes the next chunk boundaries within `buf`.
Similar to :meth:`.next_chunk_boundaries`, but information about which chunker led to a respective boundary is
included in the returned value.
Args:
buf (bytes): The message that is to be chunked.
prepend_bytes (Optional[int]): Optional number of zero bytes that should be input to the chunking algorithm
before `buf`.
Returns:
list: List of tuples (boundary, level), where boundary is a boundary position relative to `buf` and level is
the index of the chunker (i.e., the index of its chunk size specified during instantiation) that yielded
the boundary.
If multiple chunkers yield the same boundary, it is returned only once, along with the highest matching
chunker index.
|
fastchunking/__init__.py
|
def next_chunk_boundaries_levels(self, buf, prepend_bytes=0):
"""Computes the next chunk boundaries within `buf`.
Similar to :meth:`.next_chunk_boundaries`, but information about which chunker led to a respective boundary is
included in the returned value.
Args:
buf (bytes): The message that is to be chunked.
prepend_bytes (Optional[int]): Optional number of zero bytes that should be input to the chunking algorithm
before `buf`.
Returns:
list: List of tuples (boundary, level), where boundary is a boundary position relative to `buf` and level is
the index of the chunker (i.e., the index of its chunk size specified during instantiation) that yielded
the boundary.
If multiple chunkers yield the same boundary, it is returned only once, along with the highest matching
chunker index.
"""
boundaries = {}
for level_index, chunker in enumerate(self._chunkers):
boundaries.update(
dict([(boundary, level_index) for boundary in chunker.next_chunk_boundaries(buf, prepend_bytes)]))
return sorted(boundaries.items())
|
def next_chunk_boundaries_levels(self, buf, prepend_bytes=0):
"""Computes the next chunk boundaries within `buf`.
Similar to :meth:`.next_chunk_boundaries`, but information about which chunker led to a respective boundary is
included in the returned value.
Args:
buf (bytes): The message that is to be chunked.
prepend_bytes (Optional[int]): Optional number of zero bytes that should be input to the chunking algorithm
before `buf`.
Returns:
list: List of tuples (boundary, level), where boundary is a boundary position relative to `buf` and level is
the index of the chunker (i.e., the index of its chunk size specified during instantiation) that yielded
the boundary.
If multiple chunkers yield the same boundary, it is returned only once, along with the highest matching
chunker index.
"""
boundaries = {}
for level_index, chunker in enumerate(self._chunkers):
boundaries.update(
dict([(boundary, level_index) for boundary in chunker.next_chunk_boundaries(buf, prepend_bytes)]))
return sorted(boundaries.items())
|
[
"Computes",
"the",
"next",
"chunk",
"boundaries",
"within",
"buf",
"."
] |
netleibi/fastchunking
|
python
|
https://github.com/netleibi/fastchunking/blob/069b7689d26bc067120907f01d9453ab3d2efa74/fastchunking/__init__.py#L115-L138
|
[
"def",
"next_chunk_boundaries_levels",
"(",
"self",
",",
"buf",
",",
"prepend_bytes",
"=",
"0",
")",
":",
"boundaries",
"=",
"{",
"}",
"for",
"level_index",
",",
"chunker",
"in",
"enumerate",
"(",
"self",
".",
"_chunkers",
")",
":",
"boundaries",
".",
"update",
"(",
"dict",
"(",
"[",
"(",
"boundary",
",",
"level_index",
")",
"for",
"boundary",
"in",
"chunker",
".",
"next_chunk_boundaries",
"(",
"buf",
",",
"prepend_bytes",
")",
"]",
")",
")",
"return",
"sorted",
"(",
"boundaries",
".",
"items",
"(",
")",
")"
] |
069b7689d26bc067120907f01d9453ab3d2efa74
|
valid
|
RabinKarpCDC.create_chunker
|
Create a chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme with a
specific, expected chunk size.
Args:
chunk_size (int): (Expected) target chunk size.
Returns:
BaseChunker: A chunker object.
|
fastchunking/__init__.py
|
def create_chunker(self, chunk_size):
"""Create a chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme with a
specific, expected chunk size.
Args:
chunk_size (int): (Expected) target chunk size.
Returns:
BaseChunker: A chunker object.
"""
rolling_hash = _rabinkarprh.RabinKarpHash(self.window_size, self._seed)
rolling_hash.set_threshold(1.0 / chunk_size)
return RabinKarpCDC._Chunker(rolling_hash)
|
def create_chunker(self, chunk_size):
"""Create a chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme with a
specific, expected chunk size.
Args:
chunk_size (int): (Expected) target chunk size.
Returns:
BaseChunker: A chunker object.
"""
rolling_hash = _rabinkarprh.RabinKarpHash(self.window_size, self._seed)
rolling_hash.set_threshold(1.0 / chunk_size)
return RabinKarpCDC._Chunker(rolling_hash)
|
[
"Create",
"a",
"chunker",
"performing",
"content",
"-",
"defined",
"chunking",
"(",
"CDC",
")",
"using",
"Rabin",
"Karp",
"s",
"rolling",
"hash",
"scheme",
"with",
"a",
"specific",
"expected",
"chunk",
"size",
"."
] |
netleibi/fastchunking
|
python
|
https://github.com/netleibi/fastchunking/blob/069b7689d26bc067120907f01d9453ab3d2efa74/fastchunking/__init__.py#L200-L212
|
[
"def",
"create_chunker",
"(",
"self",
",",
"chunk_size",
")",
":",
"rolling_hash",
"=",
"_rabinkarprh",
".",
"RabinKarpHash",
"(",
"self",
".",
"window_size",
",",
"self",
".",
"_seed",
")",
"rolling_hash",
".",
"set_threshold",
"(",
"1.0",
"/",
"chunk_size",
")",
"return",
"RabinKarpCDC",
".",
"_Chunker",
"(",
"rolling_hash",
")"
] |
069b7689d26bc067120907f01d9453ab3d2efa74
|
valid
|
RabinKarpCDC.create_multilevel_chunker
|
Create a multi-level chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme
with different specific, expected chunk sizes.
Args:
chunk_sizes (list): List of (expected) target chunk sizes.
Warning:
For performance reasons, behavior is only defined if chunk sizes are passed in order, i.e., from
lowest to highest value.
Returns:
BaseMultiLevelChunker: A multi-level chunker object.
|
fastchunking/__init__.py
|
def create_multilevel_chunker(self, chunk_sizes):
"""Create a multi-level chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme
with different specific, expected chunk sizes.
Args:
chunk_sizes (list): List of (expected) target chunk sizes.
Warning:
For performance reasons, behavior is only defined if chunk sizes are passed in order, i.e., from
lowest to highest value.
Returns:
BaseMultiLevelChunker: A multi-level chunker object.
"""
rolling_hash = _rabinkarprh.RabinKarpMultiThresholdHash(self.window_size, self._seed,
[1.0 / chunk_size for chunk_size in chunk_sizes])
return RabinKarpCDC._MultiLevelChunker(rolling_hash)
|
def create_multilevel_chunker(self, chunk_sizes):
"""Create a multi-level chunker performing content-defined chunking (CDC) using Rabin Karp's rolling hash scheme
with different specific, expected chunk sizes.
Args:
chunk_sizes (list): List of (expected) target chunk sizes.
Warning:
For performance reasons, behavior is only defined if chunk sizes are passed in order, i.e., from
lowest to highest value.
Returns:
BaseMultiLevelChunker: A multi-level chunker object.
"""
rolling_hash = _rabinkarprh.RabinKarpMultiThresholdHash(self.window_size, self._seed,
[1.0 / chunk_size for chunk_size in chunk_sizes])
return RabinKarpCDC._MultiLevelChunker(rolling_hash)
|
[
"Create",
"a",
"multi",
"-",
"level",
"chunker",
"performing",
"content",
"-",
"defined",
"chunking",
"(",
"CDC",
")",
"using",
"Rabin",
"Karp",
"s",
"rolling",
"hash",
"scheme",
"with",
"different",
"specific",
"expected",
"chunk",
"sizes",
"."
] |
netleibi/fastchunking
|
python
|
https://github.com/netleibi/fastchunking/blob/069b7689d26bc067120907f01d9453ab3d2efa74/fastchunking/__init__.py#L214-L230
|
[
"def",
"create_multilevel_chunker",
"(",
"self",
",",
"chunk_sizes",
")",
":",
"rolling_hash",
"=",
"_rabinkarprh",
".",
"RabinKarpMultiThresholdHash",
"(",
"self",
".",
"window_size",
",",
"self",
".",
"_seed",
",",
"[",
"1.0",
"/",
"chunk_size",
"for",
"chunk_size",
"in",
"chunk_sizes",
"]",
")",
"return",
"RabinKarpCDC",
".",
"_MultiLevelChunker",
"(",
"rolling_hash",
")"
] |
069b7689d26bc067120907f01d9453ab3d2efa74
|
valid
|
brightness
|
Assumes level is out of 100
|
milight/rgbw.py
|
def brightness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Brightness must be value between 0 and 100")
b = int(floor(level / 4.0) + 2) #lights want values 2-27
return (COMMANDS['ON'][group], Command(0x4E, b))
|
def brightness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Brightness must be value between 0 and 100")
b = int(floor(level / 4.0) + 2) #lights want values 2-27
return (COMMANDS['ON'][group], Command(0x4E, b))
|
[
"Assumes",
"level",
"is",
"out",
"of",
"100"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/rgbw.py#L57-L62
|
[
"def",
"brightness",
"(",
"level",
"=",
"100",
",",
"group",
"=",
"0",
")",
":",
"if",
"level",
"not",
"in",
"range",
"(",
"0",
",",
"101",
")",
":",
"raise",
"Exception",
"(",
"\"Brightness must be value between 0 and 100\"",
")",
"b",
"=",
"int",
"(",
"floor",
"(",
"level",
"/",
"4.0",
")",
"+",
"2",
")",
"#lights want values 2-27",
"return",
"(",
"COMMANDS",
"[",
"'ON'",
"]",
"[",
"group",
"]",
",",
"Command",
"(",
"0x4E",
",",
"b",
")",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
strip_minidom_whitespace
|
Strips all whitespace from a minidom XML node and its children
This operation is made in-place.
|
structlog_pretty/utils.py
|
def strip_minidom_whitespace(node):
"""Strips all whitespace from a minidom XML node and its children
This operation is made in-place."""
for child in node.childNodes:
if child.nodeType == Node.TEXT_NODE:
if child.nodeValue:
child.nodeValue = child.nodeValue.strip()
elif child.nodeType == Node.ELEMENT_NODE:
strip_minidom_whitespace(child)
|
def strip_minidom_whitespace(node):
"""Strips all whitespace from a minidom XML node and its children
This operation is made in-place."""
for child in node.childNodes:
if child.nodeType == Node.TEXT_NODE:
if child.nodeValue:
child.nodeValue = child.nodeValue.strip()
elif child.nodeType == Node.ELEMENT_NODE:
strip_minidom_whitespace(child)
|
[
"Strips",
"all",
"whitespace",
"from",
"a",
"minidom",
"XML",
"node",
"and",
"its",
"children"
] |
underyx/structlog-pretty
|
python
|
https://github.com/underyx/structlog-pretty/blob/e87e1ce582b94b21e1b65b1c326d4edf87f8bef3/structlog_pretty/utils.py#L4-L13
|
[
"def",
"strip_minidom_whitespace",
"(",
"node",
")",
":",
"for",
"child",
"in",
"node",
".",
"childNodes",
":",
"if",
"child",
".",
"nodeType",
"==",
"Node",
".",
"TEXT_NODE",
":",
"if",
"child",
".",
"nodeValue",
":",
"child",
".",
"nodeValue",
"=",
"child",
".",
"nodeValue",
".",
"strip",
"(",
")",
"elif",
"child",
".",
"nodeType",
"==",
"Node",
".",
"ELEMENT_NODE",
":",
"strip_minidom_whitespace",
"(",
"child",
")"
] |
e87e1ce582b94b21e1b65b1c326d4edf87f8bef3
|
valid
|
brightness
|
Assumes level is out of 100
|
milight/rgb.py
|
def brightness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Brightness must be value between 0 and 100")
b = int(floor(level / 10.0)) #lights have 10 levels of brightness
commands = list(darkest(group))
for i in range(0, b):
commands.append(COMMANDS['BRIGHTER'])
return tuple(commands)
|
def brightness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Brightness must be value between 0 and 100")
b = int(floor(level / 10.0)) #lights have 10 levels of brightness
commands = list(darkest(group))
for i in range(0, b):
commands.append(COMMANDS['BRIGHTER'])
return tuple(commands)
|
[
"Assumes",
"level",
"is",
"out",
"of",
"100"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/rgb.py#L63-L71
|
[
"def",
"brightness",
"(",
"level",
"=",
"100",
",",
"group",
"=",
"0",
")",
":",
"if",
"level",
"not",
"in",
"range",
"(",
"0",
",",
"101",
")",
":",
"raise",
"Exception",
"(",
"\"Brightness must be value between 0 and 100\"",
")",
"b",
"=",
"int",
"(",
"floor",
"(",
"level",
"/",
"10.0",
")",
")",
"#lights have 10 levels of brightness",
"commands",
"=",
"list",
"(",
"darkest",
"(",
"group",
")",
")",
"for",
"i",
"in",
"range",
"(",
"0",
",",
"b",
")",
":",
"commands",
".",
"append",
"(",
"COMMANDS",
"[",
"'BRIGHTER'",
"]",
")",
"return",
"tuple",
"(",
"commands",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
warmness
|
Assumes level is out of 100
|
milight/white.py
|
def warmness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Warmness must be value between 0 and 100")
b = int(floor(level / 10.0)) #lights have 10 levels of warmness
commands = list(coolest(group))
for i in range(0, b):
commands.append(COMMANDS['WARMER'])
return tuple(commands)
|
def warmness(level=100, group=0):
""" Assumes level is out of 100 """
if level not in range(0,101):
raise Exception("Warmness must be value between 0 and 100")
b = int(floor(level / 10.0)) #lights have 10 levels of warmness
commands = list(coolest(group))
for i in range(0, b):
commands.append(COMMANDS['WARMER'])
return tuple(commands)
|
[
"Assumes",
"level",
"is",
"out",
"of",
"100"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/white.py#L87-L95
|
[
"def",
"warmness",
"(",
"level",
"=",
"100",
",",
"group",
"=",
"0",
")",
":",
"if",
"level",
"not",
"in",
"range",
"(",
"0",
",",
"101",
")",
":",
"raise",
"Exception",
"(",
"\"Warmness must be value between 0 and 100\"",
")",
"b",
"=",
"int",
"(",
"floor",
"(",
"level",
"/",
"10.0",
")",
")",
"#lights have 10 levels of warmness",
"commands",
"=",
"list",
"(",
"coolest",
"(",
"group",
")",
")",
"for",
"i",
"in",
"range",
"(",
"0",
",",
"b",
")",
":",
"commands",
".",
"append",
"(",
"COMMANDS",
"[",
"'WARMER'",
"]",
")",
"return",
"tuple",
"(",
"commands",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
color_from_hls
|
Takes a hls color and converts to proper hue
Bulbs use a BGR order instead of RGB
|
milight/__init__.py
|
def color_from_hls(hue, light, sat):
""" Takes a hls color and converts to proper hue
Bulbs use a BGR order instead of RGB """
if light > 0.95: #too bright, let's just switch to white
return 256
elif light < 0.05: #too dark, let's shut it off
return -1
else:
hue = (-hue + 1 + 2.0/3.0) % 1 # invert and translate by 2/3
return int(floor(hue * 256))
|
def color_from_hls(hue, light, sat):
""" Takes a hls color and converts to proper hue
Bulbs use a BGR order instead of RGB """
if light > 0.95: #too bright, let's just switch to white
return 256
elif light < 0.05: #too dark, let's shut it off
return -1
else:
hue = (-hue + 1 + 2.0/3.0) % 1 # invert and translate by 2/3
return int(floor(hue * 256))
|
[
"Takes",
"a",
"hls",
"color",
"and",
"converts",
"to",
"proper",
"hue",
"Bulbs",
"use",
"a",
"BGR",
"order",
"instead",
"of",
"RGB"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/__init__.py#L7-L16
|
[
"def",
"color_from_hls",
"(",
"hue",
",",
"light",
",",
"sat",
")",
":",
"if",
"light",
">",
"0.95",
":",
"#too bright, let's just switch to white",
"return",
"256",
"elif",
"light",
"<",
"0.05",
":",
"#too dark, let's shut it off",
"return",
"-",
"1",
"else",
":",
"hue",
"=",
"(",
"-",
"hue",
"+",
"1",
"+",
"2.0",
"/",
"3.0",
")",
"%",
"1",
"# invert and translate by 2/3",
"return",
"int",
"(",
"floor",
"(",
"hue",
"*",
"256",
")",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
color_from_rgb
|
Takes your standard rgb color
and converts it to a proper hue value
|
milight/__init__.py
|
def color_from_rgb(red, green, blue):
""" Takes your standard rgb color
and converts it to a proper hue value """
r = min(red, 255)
g = min(green, 255)
b = min(blue, 255)
if r > 1 or g > 1 or b > 1:
r = r / 255.0
g = g / 255.0
b = b / 255.0
return color_from_hls(*rgb_to_hls(r,g,b))
|
def color_from_rgb(red, green, blue):
""" Takes your standard rgb color
and converts it to a proper hue value """
r = min(red, 255)
g = min(green, 255)
b = min(blue, 255)
if r > 1 or g > 1 or b > 1:
r = r / 255.0
g = g / 255.0
b = b / 255.0
return color_from_hls(*rgb_to_hls(r,g,b))
|
[
"Takes",
"your",
"standard",
"rgb",
"color",
"and",
"converts",
"it",
"to",
"a",
"proper",
"hue",
"value"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/__init__.py#L18-L30
|
[
"def",
"color_from_rgb",
"(",
"red",
",",
"green",
",",
"blue",
")",
":",
"r",
"=",
"min",
"(",
"red",
",",
"255",
")",
"g",
"=",
"min",
"(",
"green",
",",
"255",
")",
"b",
"=",
"min",
"(",
"blue",
",",
"255",
")",
"if",
"r",
">",
"1",
"or",
"g",
">",
"1",
"or",
"b",
">",
"1",
":",
"r",
"=",
"r",
"/",
"255.0",
"g",
"=",
"g",
"/",
"255.0",
"b",
"=",
"b",
"/",
"255.0",
"return",
"color_from_hls",
"(",
"*",
"rgb_to_hls",
"(",
"r",
",",
"g",
",",
"b",
")",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
color_from_hex
|
Takes an HTML hex code
and converts it to a proper hue value
|
milight/__init__.py
|
def color_from_hex(value):
""" Takes an HTML hex code
and converts it to a proper hue value """
if "#" in value:
value = value[1:]
try:
unhexed = bytes.fromhex(value)
except:
unhexed = binascii.unhexlify(value) # Fallback for 2.7 compatibility
return color_from_rgb(*struct.unpack('BBB',unhexed))
|
def color_from_hex(value):
""" Takes an HTML hex code
and converts it to a proper hue value """
if "#" in value:
value = value[1:]
try:
unhexed = bytes.fromhex(value)
except:
unhexed = binascii.unhexlify(value) # Fallback for 2.7 compatibility
return color_from_rgb(*struct.unpack('BBB',unhexed))
|
[
"Takes",
"an",
"HTML",
"hex",
"code",
"and",
"converts",
"it",
"to",
"a",
"proper",
"hue",
"value"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/__init__.py#L32-L42
|
[
"def",
"color_from_hex",
"(",
"value",
")",
":",
"if",
"\"#\"",
"in",
"value",
":",
"value",
"=",
"value",
"[",
"1",
":",
"]",
"try",
":",
"unhexed",
"=",
"bytes",
".",
"fromhex",
"(",
"value",
")",
"except",
":",
"unhexed",
"=",
"binascii",
".",
"unhexlify",
"(",
"value",
")",
"# Fallback for 2.7 compatibility",
"return",
"color_from_rgb",
"(",
"*",
"struct",
".",
"unpack",
"(",
"'BBB'",
",",
"unhexed",
")",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
LightBulb.wait
|
Wait for x seconds
each wait command is 100ms
|
milight/__init__.py
|
def wait(self, sec=0.1):
""" Wait for x seconds
each wait command is 100ms """
sec = max(sec, 0)
reps = int(floor(sec / 0.1))
commands = []
for i in range(0, reps):
commands.append(Command(0x00, wait=True))
return tuple(commands)
|
def wait(self, sec=0.1):
""" Wait for x seconds
each wait command is 100ms """
sec = max(sec, 0)
reps = int(floor(sec / 0.1))
commands = []
for i in range(0, reps):
commands.append(Command(0x00, wait=True))
return tuple(commands)
|
[
"Wait",
"for",
"x",
"seconds",
"each",
"wait",
"command",
"is",
"100ms"
] |
McSwindler/python-milight
|
python
|
https://github.com/McSwindler/python-milight/blob/4891b1d7d6a720901a27a64f7b0d0c208f0c291f/milight/__init__.py#L181-L189
|
[
"def",
"wait",
"(",
"self",
",",
"sec",
"=",
"0.1",
")",
":",
"sec",
"=",
"max",
"(",
"sec",
",",
"0",
")",
"reps",
"=",
"int",
"(",
"floor",
"(",
"sec",
"/",
"0.1",
")",
")",
"commands",
"=",
"[",
"]",
"for",
"i",
"in",
"range",
"(",
"0",
",",
"reps",
")",
":",
"commands",
".",
"append",
"(",
"Command",
"(",
"0x00",
",",
"wait",
"=",
"True",
")",
")",
"return",
"tuple",
"(",
"commands",
")"
] |
4891b1d7d6a720901a27a64f7b0d0c208f0c291f
|
valid
|
toc
|
ex1)
tic() # save start time - time1
toc() # print elapsed time from last calling tic()
toc() # print elapsed time from last calling tic()
ex2)
t0 = tic() # simple
t1 = tic()
toc(t1) # print time from t1
toc(t0) # print time from t0
:param t: time: 시작 시간 (tic()의 리턴 값)
:param name: str: 출력시 포함할 문자 ['tictoc']
|
snipy/tictoc.py
|
def toc(t=None, name='tictoc'):
"""
ex1)
tic() # save start time - time1
toc() # print elapsed time from last calling tic()
toc() # print elapsed time from last calling tic()
ex2)
t0 = tic() # simple
t1 = tic()
toc(t1) # print time from t1
toc(t0) # print time from t0
:param t: time: 시작 시간 (tic()의 리턴 값)
:param name: str: 출력시 포함할 문자 ['tictoc']
"""
try:
t = t or tic.last_tic_time
except AttributeError:
# tic()부터 콜하세요
logg.warn('calling tic() need to use toc()')
return
elapsed = time.time() - t
logg.info('%s Elapsed: %s secs' % (name, elapsed))
return elapsed
|
def toc(t=None, name='tictoc'):
"""
ex1)
tic() # save start time - time1
toc() # print elapsed time from last calling tic()
toc() # print elapsed time from last calling tic()
ex2)
t0 = tic() # simple
t1 = tic()
toc(t1) # print time from t1
toc(t0) # print time from t0
:param t: time: 시작 시간 (tic()의 리턴 값)
:param name: str: 출력시 포함할 문자 ['tictoc']
"""
try:
t = t or tic.last_tic_time
except AttributeError:
# tic()부터 콜하세요
logg.warn('calling tic() need to use toc()')
return
elapsed = time.time() - t
logg.info('%s Elapsed: %s secs' % (name, elapsed))
return elapsed
|
[
"ex1",
")",
"tic",
"()",
"#",
"save",
"start",
"time",
"-",
"time1",
"toc",
"()",
"#",
"print",
"elapsed",
"time",
"from",
"last",
"calling",
"tic",
"()",
"toc",
"()",
"#",
"print",
"elapsed",
"time",
"from",
"last",
"calling",
"tic",
"()"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/tictoc.py#L29-L53
|
[
"def",
"toc",
"(",
"t",
"=",
"None",
",",
"name",
"=",
"'tictoc'",
")",
":",
"try",
":",
"t",
"=",
"t",
"or",
"tic",
".",
"last_tic_time",
"except",
"AttributeError",
":",
"# tic()부터 콜하세요",
"logg",
".",
"warn",
"(",
"'calling tic() need to use toc()'",
")",
"return",
"elapsed",
"=",
"time",
".",
"time",
"(",
")",
"-",
"t",
"logg",
".",
"info",
"(",
"'%s Elapsed: %s secs'",
"%",
"(",
"name",
",",
"elapsed",
")",
")",
"return",
"elapsed"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
tictoc
|
with tictoc('any string or not'):
print 'cool~~~'
cool~~~
2015-12-30 14:39:28,458 [INFO] tictoc Elapsed: 7.10487365723e-05 secs
:param name: str
|
snipy/tictoc.py
|
def tictoc(name='tictoc'):
"""
with tictoc('any string or not'):
print 'cool~~~'
cool~~~
2015-12-30 14:39:28,458 [INFO] tictoc Elapsed: 7.10487365723e-05 secs
:param name: str
"""
t = time.time()
yield
logg.info('%s Elapsed: %s secs' % (name, time.time() - t))
|
def tictoc(name='tictoc'):
"""
with tictoc('any string or not'):
print 'cool~~~'
cool~~~
2015-12-30 14:39:28,458 [INFO] tictoc Elapsed: 7.10487365723e-05 secs
:param name: str
"""
t = time.time()
yield
logg.info('%s Elapsed: %s secs' % (name, time.time() - t))
|
[
"with",
"tictoc",
"(",
"any",
"string",
"or",
"not",
")",
":",
"print",
"cool~~~",
"cool~~~",
"2015",
"-",
"12",
"-",
"30",
"14",
":",
"39",
":",
"28",
"458",
"[",
"INFO",
"]",
"tictoc",
"Elapsed",
":",
"7",
".",
"10487365723e",
"-",
"05",
"secs",
":",
"param",
"name",
":",
"str"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/tictoc.py#L57-L67
|
[
"def",
"tictoc",
"(",
"name",
"=",
"'tictoc'",
")",
":",
"t",
"=",
"time",
".",
"time",
"(",
")",
"yield",
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"info",
"(",
"'%s Elapsed: %s secs'",
"%",
"(",
"name",
",",
"time",
".",
"time",
"(",
")",
"-",
"t",
")",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
split_rand
|
data(1-ratio), data(with ratio) = split_rand(data_or_size, ratio, seed)
:param data_or_size: data or count
:param ratio:
:param seed:
:return:
|
snipy/train/crossvalidation_set.py
|
def split_rand(data_or_size, ratio, seed):
"""
data(1-ratio), data(with ratio) = split_rand(data_or_size, ratio, seed)
:param data_or_size: data or count
:param ratio:
:param seed:
:return:
"""
if not isinstance(data_or_size, int):
sz = len(data_or_size)
data = np.asarray(data_or_size)
else:
sz = data_or_size
data = np.arange(sz)
if not ratio:
return data, []
i = np.zeros(sz, dtype='bool')
lattersz = int(sz * ratio)
i[:lattersz] = True
with np_seed(seed):
np.random.shuffle(i)
return data[~i], data[i]
|
def split_rand(data_or_size, ratio, seed):
"""
data(1-ratio), data(with ratio) = split_rand(data_or_size, ratio, seed)
:param data_or_size: data or count
:param ratio:
:param seed:
:return:
"""
if not isinstance(data_or_size, int):
sz = len(data_or_size)
data = np.asarray(data_or_size)
else:
sz = data_or_size
data = np.arange(sz)
if not ratio:
return data, []
i = np.zeros(sz, dtype='bool')
lattersz = int(sz * ratio)
i[:lattersz] = True
with np_seed(seed):
np.random.shuffle(i)
return data[~i], data[i]
|
[
"data",
"(",
"1",
"-",
"ratio",
")",
"data",
"(",
"with",
"ratio",
")",
"=",
"split_rand",
"(",
"data_or_size",
"ratio",
"seed",
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":",
"param",
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"or",
"count",
":",
"param",
"ratio",
":",
":",
"param",
"seed",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/train/crossvalidation_set.py#L6-L30
|
[
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":",
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"i",
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",",
"data",
"[",
"i",
"]"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
kfolds
|
return train, valid [,test]
testset if p_testset
:param n:
:param k:
:param sz:
:param p_testset:
:param seed:
:return:
|
snipy/train/crossvalidation_set.py
|
def kfolds(n, k, sz, p_testset=None, seed=7238):
"""
return train, valid [,test]
testset if p_testset
:param n:
:param k:
:param sz:
:param p_testset:
:param seed:
:return:
"""
trains, tests = split_rand(sz, p_testset, seed)
ntrain = len(trains)
# np.random.seed(seed)
with np_seed(seed):
np.random.shuffle(trains)
if n == k:
# no split
train, valid = trains, trains
else:
foldsz = ntrain // k
itrain = np.arange(ntrain) // foldsz != n
train = trains[itrain]
valid = trains[~itrain]
if not p_testset:
return train, valid
else:
return train, valid, tests
|
def kfolds(n, k, sz, p_testset=None, seed=7238):
"""
return train, valid [,test]
testset if p_testset
:param n:
:param k:
:param sz:
:param p_testset:
:param seed:
:return:
"""
trains, tests = split_rand(sz, p_testset, seed)
ntrain = len(trains)
# np.random.seed(seed)
with np_seed(seed):
np.random.shuffle(trains)
if n == k:
# no split
train, valid = trains, trains
else:
foldsz = ntrain // k
itrain = np.arange(ntrain) // foldsz != n
train = trains[itrain]
valid = trains[~itrain]
if not p_testset:
return train, valid
else:
return train, valid, tests
|
[
"return",
"train",
"valid",
"[",
"test",
"]",
"testset",
"if",
"p_testset",
":",
"param",
"n",
":",
":",
"param",
"k",
":",
":",
"param",
"sz",
":",
":",
"param",
"p_testset",
":",
":",
"param",
"seed",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/train/crossvalidation_set.py#L45-L76
|
[
"def",
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",",
"k",
",",
"sz",
",",
"p_testset",
"=",
"None",
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":",
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"split_rand",
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"trains",
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"# no split",
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"valid",
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"//",
"foldsz",
"!=",
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"train",
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"trains",
"[",
"itrain",
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"valid",
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"itrain",
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"if",
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":",
"return",
"train",
",",
"valid",
"else",
":",
"return",
"train",
",",
"valid",
",",
"tests"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
date_proc
|
An decorator checking whether date parameter is passing in or not. If not, default date value is all PTT data.
Else, return PTT data with right date.
Args:
func: function you want to decorate.
request: WSGI request parameter getten from django.
Returns:
date:
a datetime variable, you can only give year, year + month or year + month + day, three type.
The missing part would be assigned default value 1 (for month is Jan, for day is 1).
|
djangoApiDec/djangoApiDec.py
|
def date_proc(func):
""" An decorator checking whether date parameter is passing in or not. If not, default date value is all PTT data.
Else, return PTT data with right date.
Args:
func: function you want to decorate.
request: WSGI request parameter getten from django.
Returns:
date:
a datetime variable, you can only give year, year + month or year + month + day, three type.
The missing part would be assigned default value 1 (for month is Jan, for day is 1).
"""
@wraps(func)
def wrapped(request, *args, **kwargs):
if 'date' in request.GET and request.GET['date'] == '':
raise Http404("api does not exist")
elif 'date' not in request.GET:
date = datetime.today()
return func(request, date)
else:
date = tuple(int(intValue) for intValue in request.GET['date'].split('-'))
if len(date) == 3:
date = datetime(*date)
elif len(date) == 2:
date = datetime(*date, day = 1)
else:
date = datetime(*date, month = 1, day = 1)
return func(request, date)
return wrapped
|
def date_proc(func):
""" An decorator checking whether date parameter is passing in or not. If not, default date value is all PTT data.
Else, return PTT data with right date.
Args:
func: function you want to decorate.
request: WSGI request parameter getten from django.
Returns:
date:
a datetime variable, you can only give year, year + month or year + month + day, three type.
The missing part would be assigned default value 1 (for month is Jan, for day is 1).
"""
@wraps(func)
def wrapped(request, *args, **kwargs):
if 'date' in request.GET and request.GET['date'] == '':
raise Http404("api does not exist")
elif 'date' not in request.GET:
date = datetime.today()
return func(request, date)
else:
date = tuple(int(intValue) for intValue in request.GET['date'].split('-'))
if len(date) == 3:
date = datetime(*date)
elif len(date) == 2:
date = datetime(*date, day = 1)
else:
date = datetime(*date, month = 1, day = 1)
return func(request, date)
return wrapped
|
[
"An",
"decorator",
"checking",
"whether",
"date",
"parameter",
"is",
"passing",
"in",
"or",
"not",
".",
"If",
"not",
"default",
"date",
"value",
"is",
"all",
"PTT",
"data",
".",
"Else",
"return",
"PTT",
"data",
"with",
"right",
"date",
".",
"Args",
":",
"func",
":",
"function",
"you",
"want",
"to",
"decorate",
".",
"request",
":",
"WSGI",
"request",
"parameter",
"getten",
"from",
"django",
"."
] |
Stufinite/djangoApiDec
|
python
|
https://github.com/Stufinite/djangoApiDec/blob/8b2d5776b3413b1b850df12a92f30526c05c0a46/djangoApiDec/djangoApiDec.py#L8-L36
|
[
"def",
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":",
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"func",
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"GET",
"[",
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"=",
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"(",
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"1",
")",
"return",
"func",
"(",
"request",
",",
"date",
")",
"return",
"wrapped"
] |
8b2d5776b3413b1b850df12a92f30526c05c0a46
|
valid
|
queryString_required
|
An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
|
djangoApiDec/djangoApiDec.py
|
def queryString_required(strList):
""" An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
"""
def _dec(function):
@wraps(function)
def _wrap(request, *args, **kwargs):
for i in strList:
if i not in request.GET:
raise Http404("api does not exist")
return function(request, *args, **kwargs)
return _wrap
return _dec
|
def queryString_required(strList):
""" An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
"""
def _dec(function):
@wraps(function)
def _wrap(request, *args, **kwargs):
for i in strList:
if i not in request.GET:
raise Http404("api does not exist")
return function(request, *args, **kwargs)
return _wrap
return _dec
|
[
"An",
"decorator",
"checking",
"whether",
"queryString",
"key",
"is",
"valid",
"or",
"not",
"Args",
":",
"str",
":",
"allowed",
"queryString",
"key"
] |
Stufinite/djangoApiDec
|
python
|
https://github.com/Stufinite/djangoApiDec/blob/8b2d5776b3413b1b850df12a92f30526c05c0a46/djangoApiDec/djangoApiDec.py#L38-L54
|
[
"def",
"queryString_required",
"(",
"strList",
")",
":",
"def",
"_dec",
"(",
"function",
")",
":",
"@",
"wraps",
"(",
"function",
")",
"def",
"_wrap",
"(",
"request",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
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"i",
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":",
"if",
"i",
"not",
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"request",
".",
"GET",
":",
"raise",
"Http404",
"(",
"\"api does not exist\"",
")",
"return",
"function",
"(",
"request",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"return",
"_wrap",
"return",
"_dec"
] |
8b2d5776b3413b1b850df12a92f30526c05c0a46
|
valid
|
queryString_required_ClassVersion
|
An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
|
djangoApiDec/djangoApiDec.py
|
def queryString_required_ClassVersion(strList):
""" An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
"""
def _dec(function):
@wraps(function)
def _wrap(classInstance, request, *args, **kwargs):
for i in strList:
if i not in request.GET:
raise Http404("api does not exist")
return function(classInstance, request, *args, **kwargs)
return _wrap
return _dec
|
def queryString_required_ClassVersion(strList):
""" An decorator checking whether queryString key is valid or not
Args:
str: allowed queryString key
Returns:
if contains invalid queryString key, it will raise exception.
"""
def _dec(function):
@wraps(function)
def _wrap(classInstance, request, *args, **kwargs):
for i in strList:
if i not in request.GET:
raise Http404("api does not exist")
return function(classInstance, request, *args, **kwargs)
return _wrap
return _dec
|
[
"An",
"decorator",
"checking",
"whether",
"queryString",
"key",
"is",
"valid",
"or",
"not",
"Args",
":",
"str",
":",
"allowed",
"queryString",
"key"
] |
Stufinite/djangoApiDec
|
python
|
https://github.com/Stufinite/djangoApiDec/blob/8b2d5776b3413b1b850df12a92f30526c05c0a46/djangoApiDec/djangoApiDec.py#L56-L72
|
[
"def",
"queryString_required_ClassVersion",
"(",
"strList",
")",
":",
"def",
"_dec",
"(",
"function",
")",
":",
"@",
"wraps",
"(",
"function",
")",
"def",
"_wrap",
"(",
"classInstance",
",",
"request",
",",
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",",
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")",
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"GET",
":",
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"Http404",
"(",
"\"api does not exist\"",
")",
"return",
"function",
"(",
"classInstance",
",",
"request",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"return",
"_wrap",
"return",
"_dec"
] |
8b2d5776b3413b1b850df12a92f30526c05c0a46
|
valid
|
getJsonFromApi
|
Return json from querying Web Api
Args:
view: django view function.
request: http request object got from django.
Returns: json format dictionary
|
djangoApiDec/djangoApiDec.py
|
def getJsonFromApi(view, request):
"""Return json from querying Web Api
Args:
view: django view function.
request: http request object got from django.
Returns: json format dictionary
"""
jsonText = view(request)
jsonText = json.loads(jsonText.content.decode('utf-8'))
return jsonText
|
def getJsonFromApi(view, request):
"""Return json from querying Web Api
Args:
view: django view function.
request: http request object got from django.
Returns: json format dictionary
"""
jsonText = view(request)
jsonText = json.loads(jsonText.content.decode('utf-8'))
return jsonText
|
[
"Return",
"json",
"from",
"querying",
"Web",
"Api"
] |
Stufinite/djangoApiDec
|
python
|
https://github.com/Stufinite/djangoApiDec/blob/8b2d5776b3413b1b850df12a92f30526c05c0a46/djangoApiDec/djangoApiDec.py#L101-L112
|
[
"def",
"getJsonFromApi",
"(",
"view",
",",
"request",
")",
":",
"jsonText",
"=",
"view",
"(",
"request",
")",
"jsonText",
"=",
"json",
".",
"loads",
"(",
"jsonText",
".",
"content",
".",
"decode",
"(",
"'utf-8'",
")",
")",
"return",
"jsonText"
] |
8b2d5776b3413b1b850df12a92f30526c05c0a46
|
valid
|
progress
|
프로그래스 bar
for i in progress(10):
print i
for i in progress(iter):
print i
|
snipy/progress.py
|
def progress(iter, **kwargs):
"""
프로그래스 bar
for i in progress(10):
print i
for i in progress(iter):
print i
"""
if isinstance(iter, int):
iter = xrange(iter)
if hasattr(iter, '__len__') or 'target' in kwargs:
cls = Progress
else:
cls = ProgressBase
return cls(iter, **kwargs)
|
def progress(iter, **kwargs):
"""
프로그래스 bar
for i in progress(10):
print i
for i in progress(iter):
print i
"""
if isinstance(iter, int):
iter = xrange(iter)
if hasattr(iter, '__len__') or 'target' in kwargs:
cls = Progress
else:
cls = ProgressBase
return cls(iter, **kwargs)
|
[
"프로그래스",
"bar",
"for",
"i",
"in",
"progress",
"(",
"10",
")",
":",
"print",
"i"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/progress.py#L180-L196
|
[
"def",
"progress",
"(",
"iter",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"isinstance",
"(",
"iter",
",",
"int",
")",
":",
"iter",
"=",
"xrange",
"(",
"iter",
")",
"if",
"hasattr",
"(",
"iter",
",",
"'__len__'",
")",
"or",
"'target'",
"in",
"kwargs",
":",
"cls",
"=",
"Progress",
"else",
":",
"cls",
"=",
"ProgressBase",
"return",
"cls",
"(",
"iter",
",",
"*",
"*",
"kwargs",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
threaded
|
function decorator
|
snipy/concurrent.py
|
def threaded(f, *args, **kwargs):
"""function decorator
"""
if args or kwargs:
return Threaded(f, *args, **kwargs)
@wraps(f)
def wrapped(*wargs, **wkwargs):
return Threaded(f, *wargs, **wkwargs)
return wrapped
|
def threaded(f, *args, **kwargs):
"""function decorator
"""
if args or kwargs:
return Threaded(f, *args, **kwargs)
@wraps(f)
def wrapped(*wargs, **wkwargs):
return Threaded(f, *wargs, **wkwargs)
return wrapped
|
[
"function",
"decorator"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/concurrent.py#L84-L94
|
[
"def",
"threaded",
"(",
"f",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"args",
"or",
"kwargs",
":",
"return",
"Threaded",
"(",
"f",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"@",
"wraps",
"(",
"f",
")",
"def",
"wrapped",
"(",
"*",
"wargs",
",",
"*",
"*",
"wkwargs",
")",
":",
"return",
"Threaded",
"(",
"f",
",",
"*",
"wargs",
",",
"*",
"*",
"wkwargs",
")",
"return",
"wrapped"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
spawn
|
decorator
|
snipy/concurrent.py
|
def spawn(f, *args, **kwargs):
"""decorator
"""
if args or kwargs:
return Spawn(f, *args, **kwargs)
@wraps(f)
def wrapped(*args, **kwargs):
return Spawn(f, *args, **kwargs)
return wrapped
|
def spawn(f, *args, **kwargs):
"""decorator
"""
if args or kwargs:
return Spawn(f, *args, **kwargs)
@wraps(f)
def wrapped(*args, **kwargs):
return Spawn(f, *args, **kwargs)
return wrapped
|
[
"decorator"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/concurrent.py#L97-L107
|
[
"def",
"spawn",
"(",
"f",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"if",
"args",
"or",
"kwargs",
":",
"return",
"Spawn",
"(",
"f",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"@",
"wraps",
"(",
"f",
")",
"def",
"wrapped",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"return",
"Spawn",
"(",
"f",
",",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
"return",
"wrapped"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
ODict.intersect
|
self와 other 키가 동일한 아이템의 dictobj
:type other: dict
:rtype: dictobj:
|
snipy/odict.py
|
def intersect(self, other):
"""
self와 other 키가 동일한 아이템의 dictobj
:type other: dict
:rtype: dictobj:
"""
return ODict((k, self[k]) for k in self if k in other)
|
def intersect(self, other):
"""
self와 other 키가 동일한 아이템의 dictobj
:type other: dict
:rtype: dictobj:
"""
return ODict((k, self[k]) for k in self if k in other)
|
[
"self와",
"other",
"키가",
"동일한",
"아이템의",
"dictobj",
":",
"type",
"other",
":",
"dict",
":",
"rtype",
":",
"dictobj",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/odict.py#L80-L86
|
[
"def",
"intersect",
"(",
"self",
",",
"other",
")",
":",
"return",
"ODict",
"(",
"(",
"k",
",",
"self",
"[",
"k",
"]",
")",
"for",
"k",
"in",
"self",
"if",
"k",
"in",
"other",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
ODict.from_dict
|
recursive dict to dictobj 컨버트
:param dic:
:return:
|
snipy/odict.py
|
def from_dict(dic):
"""
recursive dict to dictobj 컨버트
:param dic:
:return:
"""
return ODict((k, ODict.convert_ifdic(v)) for k, v in dic.items())
|
def from_dict(dic):
"""
recursive dict to dictobj 컨버트
:param dic:
:return:
"""
return ODict((k, ODict.convert_ifdic(v)) for k, v in dic.items())
|
[
"recursive",
"dict",
"to",
"dictobj",
"컨버트",
":",
"param",
"dic",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/odict.py#L89-L95
|
[
"def",
"from_dict",
"(",
"dic",
")",
":",
"return",
"ODict",
"(",
"(",
"k",
",",
"ODict",
".",
"convert_ifdic",
"(",
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")",
")",
"for",
"k",
",",
"v",
"in",
"dic",
".",
"items",
"(",
")",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
plots
|
simple wrapper plot with labels and skip x
:param yonly_or_xy:
:param kwargs:
:return:
|
snipy/plt/ploting.py
|
def plots(data, **kwargs):
"""
simple wrapper plot with labels and skip x
:param yonly_or_xy:
:param kwargs:
:return:
"""
labels = kwargs.pop('labels', '')
loc = kwargs.pop('loc', 1)
# if len(yonly_or_xy) == 1:
# x = range(len(yonly_or_xy))
# y = yonly_or_xy
# else:
# x = yonly_or_xy[0]
# y = yonly_or_xy[1:]
lines = plt.plot(np.asarray(data).T, **kwargs)
if labels:
plt.legend(lines, labels, loc=loc)
return lines
|
def plots(data, **kwargs):
"""
simple wrapper plot with labels and skip x
:param yonly_or_xy:
:param kwargs:
:return:
"""
labels = kwargs.pop('labels', '')
loc = kwargs.pop('loc', 1)
# if len(yonly_or_xy) == 1:
# x = range(len(yonly_or_xy))
# y = yonly_or_xy
# else:
# x = yonly_or_xy[0]
# y = yonly_or_xy[1:]
lines = plt.plot(np.asarray(data).T, **kwargs)
if labels:
plt.legend(lines, labels, loc=loc)
return lines
|
[
"simple",
"wrapper",
"plot",
"with",
"labels",
"and",
"skip",
"x",
":",
"param",
"yonly_or_xy",
":",
":",
"param",
"kwargs",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L17-L37
|
[
"def",
"plots",
"(",
"data",
",",
"*",
"*",
"kwargs",
")",
":",
"labels",
"=",
"kwargs",
".",
"pop",
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",",
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"kwargs",
".",
"pop",
"(",
"'loc'",
",",
"1",
")",
"# if len(yonly_or_xy) == 1:",
"# x = range(len(yonly_or_xy))",
"# y = yonly_or_xy",
"# else:",
"# x = yonly_or_xy[0]",
"# y = yonly_or_xy[1:]",
"lines",
"=",
"plt",
".",
"plot",
"(",
"np",
".",
"asarray",
"(",
"data",
")",
".",
"T",
",",
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":",
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".",
"legend",
"(",
"lines",
",",
"labels",
",",
"loc",
"=",
"loc",
")",
"return",
"lines"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imshow_grid
|
:param images: nhwc
:return:
|
snipy/plt/ploting.py
|
def imshow_grid(images, grid=None, showfun=None, **opt):
"""
:param images: nhwc
:return:
"""
# assert images.ndim == 4 or list
showfun = showfun or plt.imshow
count = len(images)
grid = grid or grid_recommend(count, sorted(images[0].shape[:2]))
res = []
for i, img in enumerate(images):
# grid row first index
plt.subplot2grid(grid, (i % grid[0], i // grid[0]))
res.append(showfun(img.squeeze(), **opt))
return res
|
def imshow_grid(images, grid=None, showfun=None, **opt):
"""
:param images: nhwc
:return:
"""
# assert images.ndim == 4 or list
showfun = showfun or plt.imshow
count = len(images)
grid = grid or grid_recommend(count, sorted(images[0].shape[:2]))
res = []
for i, img in enumerate(images):
# grid row first index
plt.subplot2grid(grid, (i % grid[0], i // grid[0]))
res.append(showfun(img.squeeze(), **opt))
return res
|
[
":",
"param",
"images",
":",
"nhwc",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L48-L64
|
[
"def",
"imshow_grid",
"(",
"images",
",",
"grid",
"=",
"None",
",",
"showfun",
"=",
"None",
",",
"*",
"*",
"opt",
")",
":",
"# assert images.ndim == 4 or list",
"showfun",
"=",
"showfun",
"or",
"plt",
".",
"imshow",
"count",
"=",
"len",
"(",
"images",
")",
"grid",
"=",
"grid",
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"grid_recommend",
"(",
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",",
"sorted",
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"images",
"[",
"0",
"]",
".",
"shape",
"[",
":",
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")",
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"[",
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",",
"img",
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"images",
")",
":",
"# grid row first index",
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"subplot2grid",
"(",
"grid",
",",
"(",
"i",
"%",
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"[",
"0",
"]",
",",
"i",
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")",
")",
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"(",
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"(",
"img",
".",
"squeeze",
"(",
")",
",",
"*",
"*",
"opt",
")",
")",
"return",
"res"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
plt_range
|
for i in plot_range(n):
plt.imshow(imgs[i])
left arrow yield prev value
other key yield next value
:param args:
:return:
|
snipy/plt/ploting.py
|
def plt_range(*args, **kwargs):
"""
for i in plot_range(n):
plt.imshow(imgs[i])
left arrow yield prev value
other key yield next value
:param args:
:return:
"""
wait = kwargs.pop('wait', True)
if not wait:
# no interactive just pass range
for i in progress(range(*args)):
yield i
return
class _holder(object):
pass
hold = _holder()
hold.i = 0
hold.done = False
def press(event):
# import sys
# sys.stdout.flush()
hold.i += -1 if event.key == 'left' else 1
hold.i = 0 if hold.i < 0 else hold.i
def onclose(event):
hold.done = True
fig = kwargs.pop('fig', None)
figsize = kwargs.pop('figsize', None)
if fig is None:
fig = plt.gcf()
if figsize:
fig.set_size_inches(figsize)
elif isinstance(fig, (int, str)):
if figsize:
fig = plt.figure(fig, figsize=figsize)
else:
fig = plt.figure(fig)
elif isinstance(fig, plt.Figure):
if figsize:
fig.set_size_inches(figsize)
else:
raise ValueError
onkey_fig(press, fig)
onclose_fig(onclose, fig)
ranges = range(*args)
l = len(ranges)
while hold.i < l:
print('hold.i', ranges[hold.i])
yield ranges[hold.i] # yield first without keypress
before = hold.i
while before == hold.i:
while not fig.waitforbuttonpress(0.01):
if hold.done:
return
while fig.waitforbuttonpress(0.1):
if hold.done:
return
|
def plt_range(*args, **kwargs):
"""
for i in plot_range(n):
plt.imshow(imgs[i])
left arrow yield prev value
other key yield next value
:param args:
:return:
"""
wait = kwargs.pop('wait', True)
if not wait:
# no interactive just pass range
for i in progress(range(*args)):
yield i
return
class _holder(object):
pass
hold = _holder()
hold.i = 0
hold.done = False
def press(event):
# import sys
# sys.stdout.flush()
hold.i += -1 if event.key == 'left' else 1
hold.i = 0 if hold.i < 0 else hold.i
def onclose(event):
hold.done = True
fig = kwargs.pop('fig', None)
figsize = kwargs.pop('figsize', None)
if fig is None:
fig = plt.gcf()
if figsize:
fig.set_size_inches(figsize)
elif isinstance(fig, (int, str)):
if figsize:
fig = plt.figure(fig, figsize=figsize)
else:
fig = plt.figure(fig)
elif isinstance(fig, plt.Figure):
if figsize:
fig.set_size_inches(figsize)
else:
raise ValueError
onkey_fig(press, fig)
onclose_fig(onclose, fig)
ranges = range(*args)
l = len(ranges)
while hold.i < l:
print('hold.i', ranges[hold.i])
yield ranges[hold.i] # yield first without keypress
before = hold.i
while before == hold.i:
while not fig.waitforbuttonpress(0.01):
if hold.done:
return
while fig.waitforbuttonpress(0.1):
if hold.done:
return
|
[
"for",
"i",
"in",
"plot_range",
"(",
"n",
")",
":",
"plt",
".",
"imshow",
"(",
"imgs",
"[",
"i",
"]",
")"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L69-L134
|
[
"def",
"plt_range",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"wait",
"=",
"kwargs",
".",
"pop",
"(",
"'wait'",
",",
"True",
")",
"if",
"not",
"wait",
":",
"# no interactive just pass range",
"for",
"i",
"in",
"progress",
"(",
"range",
"(",
"*",
"args",
")",
")",
":",
"yield",
"i",
"return",
"class",
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"(",
"object",
")",
":",
"pass",
"hold",
"=",
"_holder",
"(",
")",
"hold",
".",
"i",
"=",
"0",
"hold",
".",
"done",
"=",
"False",
"def",
"press",
"(",
"event",
")",
":",
"# import sys",
"# sys.stdout.flush()",
"hold",
".",
"i",
"+=",
"-",
"1",
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"event",
".",
"key",
"==",
"'left'",
"else",
"1",
"hold",
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"i",
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"0",
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"else",
"hold",
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"i",
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"(",
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":",
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"done",
"=",
"True",
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"kwargs",
".",
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"(",
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",",
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"figsize",
"=",
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".",
"pop",
"(",
"'figsize'",
",",
"None",
")",
"if",
"fig",
"is",
"None",
":",
"fig",
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"plt",
".",
"gcf",
"(",
")",
"if",
"figsize",
":",
"fig",
".",
"set_size_inches",
"(",
"figsize",
")",
"elif",
"isinstance",
"(",
"fig",
",",
"(",
"int",
",",
"str",
")",
")",
":",
"if",
"figsize",
":",
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"figure",
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",",
"figsize",
"=",
"figsize",
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"figure",
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")",
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"(",
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",",
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"if",
"figsize",
":",
"fig",
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"set_size_inches",
"(",
"figsize",
")",
"else",
":",
"raise",
"ValueError",
"onkey_fig",
"(",
"press",
",",
"fig",
")",
"onclose_fig",
"(",
"onclose",
",",
"fig",
")",
"ranges",
"=",
"range",
"(",
"*",
"args",
")",
"l",
"=",
"len",
"(",
"ranges",
")",
"while",
"hold",
".",
"i",
"<",
"l",
":",
"print",
"(",
"'hold.i'",
",",
"ranges",
"[",
"hold",
".",
"i",
"]",
")",
"yield",
"ranges",
"[",
"hold",
".",
"i",
"]",
"# yield first without keypress",
"before",
"=",
"hold",
".",
"i",
"while",
"before",
"==",
"hold",
".",
"i",
":",
"while",
"not",
"fig",
".",
"waitforbuttonpress",
"(",
"0.01",
")",
":",
"if",
"hold",
".",
"done",
":",
"return",
"while",
"fig",
".",
"waitforbuttonpress",
"(",
"0.1",
")",
":",
"if",
"hold",
".",
"done",
":",
"return"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
plot_pause
|
todo : add some example
:param timeout: wait time. if None, blocking
:param msg:
:return:
|
snipy/plt/ploting.py
|
def plot_pause(timeout=None, msg=''):
"""
todo : add some example
:param timeout: wait time. if None, blocking
:param msg:
:return:
"""
if timeout is not None:
print(msg or 'Press key for continue in time {}'.format(timeout))
plt.waitforbuttonpress(timeout=timeout)
return True
print(msg or 'Press key for continue')
while not plt.waitforbuttonpress(timeout=0.01):
if not plt.get_fignums():
return False
return len(plt.get_fignums()) != 0
|
def plot_pause(timeout=None, msg=''):
"""
todo : add some example
:param timeout: wait time. if None, blocking
:param msg:
:return:
"""
if timeout is not None:
print(msg or 'Press key for continue in time {}'.format(timeout))
plt.waitforbuttonpress(timeout=timeout)
return True
print(msg or 'Press key for continue')
while not plt.waitforbuttonpress(timeout=0.01):
if not plt.get_fignums():
return False
return len(plt.get_fignums()) != 0
|
[
"todo",
":",
"add",
"some",
"example",
":",
"param",
"timeout",
":",
"wait",
"time",
".",
"if",
"None",
"blocking",
":",
"param",
"msg",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L141-L158
|
[
"def",
"plot_pause",
"(",
"timeout",
"=",
"None",
",",
"msg",
"=",
"''",
")",
":",
"if",
"timeout",
"is",
"not",
"None",
":",
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"(",
"msg",
"or",
"'Press key for continue in time {}'",
".",
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"(",
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")",
")",
"plt",
".",
"waitforbuttonpress",
"(",
"timeout",
"=",
"timeout",
")",
"return",
"True",
"print",
"(",
"msg",
"or",
"'Press key for continue'",
")",
"while",
"not",
"plt",
".",
"waitforbuttonpress",
"(",
"timeout",
"=",
"0.01",
")",
":",
"if",
"not",
"plt",
".",
"get_fignums",
"(",
")",
":",
"return",
"False",
"return",
"len",
"(",
"plt",
".",
"get_fignums",
"(",
")",
")",
"!=",
"0"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
flat_images
|
convert batch image to flat image with margin inserted
[B,h,w,c] => [H,W,c]
:param images:
:param grid: patch grid cell size of (Row, Col)
:param bfill: board filling value
:param bsz: int or (int, int) board size
:return: flatted image
|
snipy/plt/ploting.py
|
def flat_images(images, grid=None, bfill=1.0, bsz=(1, 1)):
"""
convert batch image to flat image with margin inserted
[B,h,w,c] => [H,W,c]
:param images:
:param grid: patch grid cell size of (Row, Col)
:param bfill: board filling value
:param bsz: int or (int, int) board size
:return: flatted image
"""
if images.ndim == 4 and images.shape[-1] == 1:
images = images.squeeze(axis=-1)
grid = grid or grid_recommend(len(images), sorted(images[0].shape[:2]))
if not isinstance(bsz, (tuple, list)):
bsz = (bsz, bsz)
# np.empty()
imshape = list(images.shape)
imshape[0] = grid[0] * grid[1]
imshape[1] += bsz[0]
imshape[2] += bsz[1]
# data = np.empty((grid[0] * grid[1], imshape[1], imshape[2]), dtype=images.dtype)
data = np.empty(imshape, dtype=images.dtype)
data.fill(bfill)
bslice0 = slice(0, -bsz[0]) if bsz[0] else slice(None, None)
bslice1 = slice(0, -bsz[1]) if bsz[1] else slice(None, None)
data[:len(images), bslice0, bslice1] = images
imshape = list(grid) + imshape[1:] # [grid[0], grid[1], H, W, [Channel]]
data = data.reshape(imshape)
if len(imshape) == 5:
data = data.transpose(0, 2, 1, 3, 4)
imshape = [imshape[0]*imshape[2], imshape[1]*imshape[3], imshape[4]]
else: # len == 4
data = data.transpose(0, 2, 1, 3)
imshape = [imshape[0]*imshape[2], imshape[1]*imshape[3]]
data = data.reshape(imshape)
# remove last margin
data = data[bslice0, bslice1]
return data
|
def flat_images(images, grid=None, bfill=1.0, bsz=(1, 1)):
"""
convert batch image to flat image with margin inserted
[B,h,w,c] => [H,W,c]
:param images:
:param grid: patch grid cell size of (Row, Col)
:param bfill: board filling value
:param bsz: int or (int, int) board size
:return: flatted image
"""
if images.ndim == 4 and images.shape[-1] == 1:
images = images.squeeze(axis=-1)
grid = grid or grid_recommend(len(images), sorted(images[0].shape[:2]))
if not isinstance(bsz, (tuple, list)):
bsz = (bsz, bsz)
# np.empty()
imshape = list(images.shape)
imshape[0] = grid[0] * grid[1]
imshape[1] += bsz[0]
imshape[2] += bsz[1]
# data = np.empty((grid[0] * grid[1], imshape[1], imshape[2]), dtype=images.dtype)
data = np.empty(imshape, dtype=images.dtype)
data.fill(bfill)
bslice0 = slice(0, -bsz[0]) if bsz[0] else slice(None, None)
bslice1 = slice(0, -bsz[1]) if bsz[1] else slice(None, None)
data[:len(images), bslice0, bslice1] = images
imshape = list(grid) + imshape[1:] # [grid[0], grid[1], H, W, [Channel]]
data = data.reshape(imshape)
if len(imshape) == 5:
data = data.transpose(0, 2, 1, 3, 4)
imshape = [imshape[0]*imshape[2], imshape[1]*imshape[3], imshape[4]]
else: # len == 4
data = data.transpose(0, 2, 1, 3)
imshape = [imshape[0]*imshape[2], imshape[1]*imshape[3]]
data = data.reshape(imshape)
# remove last margin
data = data[bslice0, bslice1]
return data
|
[
"convert",
"batch",
"image",
"to",
"flat",
"image",
"with",
"margin",
"inserted",
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"B",
"h",
"w",
"c",
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"=",
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"[",
"H",
"W",
"c",
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":",
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"(",
"int",
"int",
")",
"board",
"size",
":",
"return",
":",
"flatted",
"image"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L169-L214
|
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"# remove last margin",
"data",
"=",
"data",
"[",
"bslice0",
",",
"bslice1",
"]",
"return",
"data"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imshow_flat
|
imshow after applying flat_images
:param images: [bhwc]
:param grid: None for auto grid
:param showfun: plt.imshow
:param bfill: color for board fill
:param bsz: size of board
:param opt: option for showfun
:return:
|
snipy/plt/ploting.py
|
def imshow_flat(images, grid=None, showfun=None, bfill=1.0, bsz=(1,1), **opt):
"""
imshow after applying flat_images
:param images: [bhwc]
:param grid: None for auto grid
:param showfun: plt.imshow
:param bfill: color for board fill
:param bsz: size of board
:param opt: option for showfun
:return:
"""
showfun = showfun or plt.imshow
count = len(images)
# decide grid shape if need pick one
grid = grid or grid_recommend(count, ratio=sorted(images[0].shape[:2]))
flatted = flat_images(images, grid, bfill=bfill, bsz=bsz)
res = showfun(flatted, **opt)
plt.draw()
|
def imshow_flat(images, grid=None, showfun=None, bfill=1.0, bsz=(1,1), **opt):
"""
imshow after applying flat_images
:param images: [bhwc]
:param grid: None for auto grid
:param showfun: plt.imshow
:param bfill: color for board fill
:param bsz: size of board
:param opt: option for showfun
:return:
"""
showfun = showfun or plt.imshow
count = len(images)
# decide grid shape if need pick one
grid = grid or grid_recommend(count, ratio=sorted(images[0].shape[:2]))
flatted = flat_images(images, grid, bfill=bfill, bsz=bsz)
res = showfun(flatted, **opt)
plt.draw()
|
[
"imshow",
"after",
"applying",
"flat_images",
":",
"param",
"images",
":",
"[",
"bhwc",
"]",
":",
"param",
"grid",
":",
"None",
"for",
"auto",
"grid",
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"param",
"showfun",
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"plt",
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"param",
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"param",
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"size",
"of",
"board",
":",
"param",
"opt",
":",
"option",
"for",
"showfun",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L217-L236
|
[
"def",
"imshow_flat",
"(",
"images",
",",
"grid",
"=",
"None",
",",
"showfun",
"=",
"None",
",",
"bfill",
"=",
"1.0",
",",
"bsz",
"=",
"(",
"1",
",",
"1",
")",
",",
"*",
"*",
"opt",
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"showfun",
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"showfun",
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"len",
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"images",
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"# decide grid shape if need pick one",
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"grid_recommend",
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"count",
",",
"ratio",
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"images",
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",",
"*",
"*",
"opt",
")",
"plt",
".",
"draw",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
matshow
|
imshow without interpolation like as matshow
:param args:
:param kwargs:
:return:
|
snipy/plt/ploting.py
|
def matshow(*args, **kwargs):
"""
imshow without interpolation like as matshow
:param args:
:param kwargs:
:return:
"""
kwargs['interpolation'] = kwargs.pop('interpolation', 'none')
return plt.imshow(*args, **kwargs)
|
def matshow(*args, **kwargs):
"""
imshow without interpolation like as matshow
:param args:
:param kwargs:
:return:
"""
kwargs['interpolation'] = kwargs.pop('interpolation', 'none')
return plt.imshow(*args, **kwargs)
|
[
"imshow",
"without",
"interpolation",
"like",
"as",
"matshow",
":",
"param",
"args",
":",
":",
"param",
"kwargs",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L279-L287
|
[
"def",
"matshow",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")",
":",
"kwargs",
"[",
"'interpolation'",
"]",
"=",
"kwargs",
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"(",
"'interpolation'",
",",
"'none'",
")",
"return",
"plt",
".",
"imshow",
"(",
"*",
"args",
",",
"*",
"*",
"kwargs",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imbox
|
draw boundary box
:param xy: start index xy (ji)
:param w: width
:param h: height
:param angle:
:param kwargs:
:return:
|
snipy/plt/ploting.py
|
def imbox(xy, w, h, angle=0.0, **kwargs):
"""
draw boundary box
:param xy: start index xy (ji)
:param w: width
:param h: height
:param angle:
:param kwargs:
:return:
"""
from matplotlib.patches import Rectangle
return imbound(Rectangle, xy, w, h, angle, **kwargs)
|
def imbox(xy, w, h, angle=0.0, **kwargs):
"""
draw boundary box
:param xy: start index xy (ji)
:param w: width
:param h: height
:param angle:
:param kwargs:
:return:
"""
from matplotlib.patches import Rectangle
return imbound(Rectangle, xy, w, h, angle, **kwargs)
|
[
"draw",
"boundary",
"box",
":",
"param",
"xy",
":",
"start",
"index",
"xy",
"(",
"ji",
")",
":",
"param",
"w",
":",
"width",
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"param",
"h",
":",
"height",
":",
"param",
"angle",
":",
":",
"param",
"kwargs",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L413-L424
|
[
"def",
"imbox",
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"xy",
",",
"w",
",",
"h",
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"=",
"0.0",
",",
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",",
"xy",
",",
"w",
",",
"h",
",",
"angle",
",",
"*",
"*",
"kwargs",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imbound
|
:param clspatch:
:param args:
:param kwargs:
:return:
|
snipy/plt/ploting.py
|
def imbound(clspatch, *args, **kwargs):
"""
:param clspatch:
:param args:
:param kwargs:
:return:
"""
# todo : add example
c = kwargs.pop('color', kwargs.get('edgecolor', None))
kwargs.update(facecolor='none', edgecolor=c)
return impatch(clspatch, *args, **kwargs)
|
def imbound(clspatch, *args, **kwargs):
"""
:param clspatch:
:param args:
:param kwargs:
:return:
"""
# todo : add example
c = kwargs.pop('color', kwargs.get('edgecolor', None))
kwargs.update(facecolor='none', edgecolor=c)
return impatch(clspatch, *args, **kwargs)
|
[
":",
"param",
"clspatch",
":",
":",
"param",
"args",
":",
":",
"param",
"kwargs",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L433-L444
|
[
"def",
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"kwargs",
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",",
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"args",
",",
"*",
"*",
"kwargs",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imslic
|
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
|
snipy/plt/ploting.py
|
def imslic(img, n_segments=100, aspect=None):
"""
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
"""
from skimage.segmentation import (slic, mark_boundaries)
from skimage.morphology import (dilation)
if img.ndim == 2 or img.ndim == 3 and img.shape[-1] == 1:
imz = np.stack([img, img, img], 2)
else:
imz = img
slics = slic(imz, n_segments=n_segments)
boundaries = mark_boundaries(imz, slics)
return plt.imshow(boundaries, aspect=aspect)
|
def imslic(img, n_segments=100, aspect=None):
"""
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
"""
from skimage.segmentation import (slic, mark_boundaries)
from skimage.morphology import (dilation)
if img.ndim == 2 or img.ndim == 3 and img.shape[-1] == 1:
imz = np.stack([img, img, img], 2)
else:
imz = img
slics = slic(imz, n_segments=n_segments)
boundaries = mark_boundaries(imz, slics)
return plt.imshow(boundaries, aspect=aspect)
|
[
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"None",
"multichannel",
"=",
"True",
"convert2lab",
"=",
"None",
"enforce_connectivity",
"=",
"True",
"min_size_factor",
"=",
"0",
".",
"5",
"max_size_factor",
"=",
"3",
"slic_zero",
"=",
"False"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L476-L509
|
[
"def",
"imslic",
"(",
"img",
",",
"n_segments",
"=",
"100",
",",
"aspect",
"=",
"None",
")",
":",
"from",
"skimage",
".",
"segmentation",
"import",
"(",
"slic",
",",
"mark_boundaries",
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"from",
"skimage",
".",
"morphology",
"import",
"(",
"dilation",
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"if",
"img",
".",
"ndim",
"==",
"2",
"or",
"img",
".",
"ndim",
"==",
"3",
"and",
"img",
".",
"shape",
"[",
"-",
"1",
"]",
"==",
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"imz",
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"(",
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",",
"img",
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"img",
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",",
"2",
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"imz",
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"slics",
"=",
"slic",
"(",
"imz",
",",
"n_segments",
"=",
"n_segments",
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"=",
"mark_boundaries",
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"imz",
",",
"slics",
")",
"return",
"plt",
".",
"imshow",
"(",
"boundaries",
",",
"aspect",
"=",
"aspect",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
imslic2
|
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
|
snipy/plt/ploting.py
|
def imslic2(img, n_segments=100, color=None, outline_color=None, mode='thick', **kwargs):
"""
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
"""
from skimage.segmentation import (slic, find_boundaries) # mark_boundaries
from skimage.morphology import (dilation)
kwslic = {'compactness', 'max_iter', 'sigma', 'spacing', 'multichannel', 'convert2lab',
'enforce_connectivity', 'min_size_factor', 'max_size_factor', 'slic_zero=False'}
imshowkw = {'cmap', 'norm', 'aspect', 'interpolation', 'alpha', 'vmin', 'vmax', 'origin',
'extent', 'shape', 'filternorm', 'filterrad', 'imlim', 'resample', 'url', 'hold', 'data'}
slicarg = {k: v for k, v in kwargs.iteritems() if k in kwslic}
imshowarg = {k: v for k, v in kwargs.iteritems() if k in imshowkw}
if img.ndim == 2 or img.ndim == 3 and img.shape[-1] == 1:
imz = np.stack([img, img, img], 2)
color = color or 1.
else:
imgz = img
color = color or (1,1,0)
slics = slic(imz, n_segments=n_segments, **slicarg)
boundaries = find_boundaries(slics, mode=mode)
if outline_color is not None:
outlines = dilation(boundaries, np.ones((3, 3), np.uint8))
img[outlines] = outline_color
img[boundaries] = color
return plt.imshow(img, **imshowarg)
|
def imslic2(img, n_segments=100, color=None, outline_color=None, mode='thick', **kwargs):
"""
slic args :
n_segments=100, compactness=10., max_iter=10,
sigma=0, spacing=None,
multichannel=True, convert2lab=None, enforce_connectivity=True,
min_size_factor=0.5, max_size_factor=3, slic_zero=False
mark_boundaries args:
label_img, color=(1, 1, 0), outline_color=None, mode='outer', background_label=0
imshow args:
cmap=None, norm=None, aspect=None, interpolation=None,
alpha=None, vmin=None, vmax=None, origin=None,
extent=None, shape=None, filternorm=1, filterrad=4.0,
imlim=None, resample=None, url=None, hold=None, data=None,
:param img:
:param slicarg:
:param slickw:
:return:
"""
from skimage.segmentation import (slic, find_boundaries) # mark_boundaries
from skimage.morphology import (dilation)
kwslic = {'compactness', 'max_iter', 'sigma', 'spacing', 'multichannel', 'convert2lab',
'enforce_connectivity', 'min_size_factor', 'max_size_factor', 'slic_zero=False'}
imshowkw = {'cmap', 'norm', 'aspect', 'interpolation', 'alpha', 'vmin', 'vmax', 'origin',
'extent', 'shape', 'filternorm', 'filterrad', 'imlim', 'resample', 'url', 'hold', 'data'}
slicarg = {k: v for k, v in kwargs.iteritems() if k in kwslic}
imshowarg = {k: v for k, v in kwargs.iteritems() if k in imshowkw}
if img.ndim == 2 or img.ndim == 3 and img.shape[-1] == 1:
imz = np.stack([img, img, img], 2)
color = color or 1.
else:
imgz = img
color = color or (1,1,0)
slics = slic(imz, n_segments=n_segments, **slicarg)
boundaries = find_boundaries(slics, mode=mode)
if outline_color is not None:
outlines = dilation(boundaries, np.ones((3, 3), np.uint8))
img[outlines] = outline_color
img[boundaries] = color
return plt.imshow(img, **imshowarg)
|
[
"slic",
"args",
":",
"n_segments",
"=",
"100",
"compactness",
"=",
"10",
".",
"max_iter",
"=",
"10",
"sigma",
"=",
"0",
"spacing",
"=",
"None",
"multichannel",
"=",
"True",
"convert2lab",
"=",
"None",
"enforce_connectivity",
"=",
"True",
"min_size_factor",
"=",
"0",
".",
"5",
"max_size_factor",
"=",
"3",
"slic_zero",
"=",
"False"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L512-L559
|
[
"def",
"imslic2",
"(",
"img",
",",
"n_segments",
"=",
"100",
",",
"color",
"=",
"None",
",",
"outline_color",
"=",
"None",
",",
"mode",
"=",
"'thick'",
",",
"*",
"*",
"kwargs",
")",
":",
"from",
"skimage",
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"segmentation",
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"(",
"slic",
",",
"find_boundaries",
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"# mark_boundaries",
"from",
"skimage",
".",
"morphology",
"import",
"(",
"dilation",
")",
"kwslic",
"=",
"{",
"'compactness'",
",",
"'max_iter'",
",",
"'sigma'",
",",
"'spacing'",
",",
"'multichannel'",
",",
"'convert2lab'",
",",
"'enforce_connectivity'",
",",
"'min_size_factor'",
",",
"'max_size_factor'",
",",
"'slic_zero=False'",
"}",
"imshowkw",
"=",
"{",
"'cmap'",
",",
"'norm'",
",",
"'aspect'",
",",
"'interpolation'",
",",
"'alpha'",
",",
"'vmin'",
",",
"'vmax'",
",",
"'origin'",
",",
"'extent'",
",",
"'shape'",
",",
"'filternorm'",
",",
"'filterrad'",
",",
"'imlim'",
",",
"'resample'",
",",
"'url'",
",",
"'hold'",
",",
"'data'",
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"slicarg",
"=",
"{",
"k",
":",
"v",
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",",
"v",
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"(",
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"k",
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"imshowkw",
"}",
"if",
"img",
".",
"ndim",
"==",
"2",
"or",
"img",
".",
"ndim",
"==",
"3",
"and",
"img",
".",
"shape",
"[",
"-",
"1",
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"np",
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",",
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",",
"img",
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",",
"2",
")",
"color",
"=",
"color",
"or",
"1.",
"else",
":",
"imgz",
"=",
"img",
"color",
"=",
"color",
"or",
"(",
"1",
",",
"1",
",",
"0",
")",
"slics",
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"imz",
",",
"n_segments",
"=",
"n_segments",
",",
"*",
"*",
"slicarg",
")",
"boundaries",
"=",
"find_boundaries",
"(",
"slics",
",",
"mode",
"=",
"mode",
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"if",
"outline_color",
"is",
"not",
"None",
":",
"outlines",
"=",
"dilation",
"(",
"boundaries",
",",
"np",
".",
"ones",
"(",
"(",
"3",
",",
"3",
")",
",",
"np",
".",
"uint8",
")",
")",
"img",
"[",
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"]",
"=",
"outline_color",
"img",
"[",
"boundaries",
"]",
"=",
"color",
"return",
"plt",
".",
"imshow",
"(",
"img",
",",
"*",
"*",
"imshowarg",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
movie_saving
|
contextmanager for PlotMovieWriter
Example:
with movie_saving('output.mp4', dpi=100) as plot:
for i in range(10):
plot(data[i])
:param outfile:
:param showfun:
:param fig:
:param tight:
:param drawopt:
:param dpi:
:param movieopt: fps=5, codec=None, bitrate=None, extra_args=None, metadata=None
:return:
|
snipy/plt/ploting.py
|
def movie_saving(outfile, showfun=imshow, fig=None, tight=True, drawopt=None, dpi=100, **movieopt):
"""
contextmanager for PlotMovieWriter
Example:
with movie_saving('output.mp4', dpi=100) as plot:
for i in range(10):
plot(data[i])
:param outfile:
:param showfun:
:param fig:
:param tight:
:param drawopt:
:param dpi:
:param movieopt: fps=5, codec=None, bitrate=None, extra_args=None, metadata=None
:return:
"""
if tight:
plot_writer = ImageMovieWriter(outfile, showfun=showfun, fig=fig, drawopt=drawopt, dpi=dpi, **movieopt)
else:
plot_writer = PlotMovieWriter(outfile, showfun=showfun, fig=fig, drawopt=drawopt, dpi=dpi, **movieopt)
try:
yield plot_writer
finally:
plot_writer.finish()
|
def movie_saving(outfile, showfun=imshow, fig=None, tight=True, drawopt=None, dpi=100, **movieopt):
"""
contextmanager for PlotMovieWriter
Example:
with movie_saving('output.mp4', dpi=100) as plot:
for i in range(10):
plot(data[i])
:param outfile:
:param showfun:
:param fig:
:param tight:
:param drawopt:
:param dpi:
:param movieopt: fps=5, codec=None, bitrate=None, extra_args=None, metadata=None
:return:
"""
if tight:
plot_writer = ImageMovieWriter(outfile, showfun=showfun, fig=fig, drawopt=drawopt, dpi=dpi, **movieopt)
else:
plot_writer = PlotMovieWriter(outfile, showfun=showfun, fig=fig, drawopt=drawopt, dpi=dpi, **movieopt)
try:
yield plot_writer
finally:
plot_writer.finish()
|
[
"contextmanager",
"for",
"PlotMovieWriter",
"Example",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/plt/ploting.py#L700-L726
|
[
"def",
"movie_saving",
"(",
"outfile",
",",
"showfun",
"=",
"imshow",
",",
"fig",
"=",
"None",
",",
"tight",
"=",
"True",
",",
"drawopt",
"=",
"None",
",",
"dpi",
"=",
"100",
",",
"*",
"*",
"movieopt",
")",
":",
"if",
"tight",
":",
"plot_writer",
"=",
"ImageMovieWriter",
"(",
"outfile",
",",
"showfun",
"=",
"showfun",
",",
"fig",
"=",
"fig",
",",
"drawopt",
"=",
"drawopt",
",",
"dpi",
"=",
"dpi",
",",
"*",
"*",
"movieopt",
")",
"else",
":",
"plot_writer",
"=",
"PlotMovieWriter",
"(",
"outfile",
",",
"showfun",
"=",
"showfun",
",",
"fig",
"=",
"fig",
",",
"drawopt",
"=",
"drawopt",
",",
"dpi",
"=",
"dpi",
",",
"*",
"*",
"movieopt",
")",
"try",
":",
"yield",
"plot_writer",
"finally",
":",
"plot_writer",
".",
"finish",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
put
|
put text on on screen
a tuple as first argument tells absolute position for the text
does not change TermCursor position
args = list of optional position, formatting tokens and strings
|
snipy/term.py
|
def put(xy, *args):
"""
put text on on screen
a tuple as first argument tells absolute position for the text
does not change TermCursor position
args = list of optional position, formatting tokens and strings
"""
cmd = [TermCursor.save, TermCursor.move(*xy), ''.join(args), TermCursor.restore]
write(''.join(cmd))
|
def put(xy, *args):
"""
put text on on screen
a tuple as first argument tells absolute position for the text
does not change TermCursor position
args = list of optional position, formatting tokens and strings
"""
cmd = [TermCursor.save, TermCursor.move(*xy), ''.join(args), TermCursor.restore]
write(''.join(cmd))
|
[
"put",
"text",
"on",
"on",
"screen",
"a",
"tuple",
"as",
"first",
"argument",
"tells",
"absolute",
"position",
"for",
"the",
"text",
"does",
"not",
"change",
"TermCursor",
"position",
"args",
"=",
"list",
"of",
"optional",
"position",
"formatting",
"tokens",
"and",
"strings"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/term.py#L135-L143
|
[
"def",
"put",
"(",
"xy",
",",
"*",
"args",
")",
":",
"cmd",
"=",
"[",
"TermCursor",
".",
"save",
",",
"TermCursor",
".",
"move",
"(",
"*",
"xy",
")",
",",
"''",
".",
"join",
"(",
"args",
")",
",",
"TermCursor",
".",
"restore",
"]",
"write",
"(",
"''",
".",
"join",
"(",
"cmd",
")",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
getpassword
|
get user input without echo
|
snipy/term.py
|
def getpassword(prompt="Password: "):
"""
get user input without echo
"""
fd = sys.stdin.fileno()
old = termios.tcgetattr(fd)
new = termios.tcgetattr(fd)
new[3] &= ~termios.ECHO # lflags
try:
termios.tcsetattr(fd, termios.TCSADRAIN, new)
passwd = raw_input(prompt)
finally:
termios.tcsetattr(fd, termios.TCSADRAIN, old)
return passwd
|
def getpassword(prompt="Password: "):
"""
get user input without echo
"""
fd = sys.stdin.fileno()
old = termios.tcgetattr(fd)
new = termios.tcgetattr(fd)
new[3] &= ~termios.ECHO # lflags
try:
termios.tcsetattr(fd, termios.TCSADRAIN, new)
passwd = raw_input(prompt)
finally:
termios.tcsetattr(fd, termios.TCSADRAIN, old)
return passwd
|
[
"get",
"user",
"input",
"without",
"echo"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/term.py#L146-L160
|
[
"def",
"getpassword",
"(",
"prompt",
"=",
"\"Password: \"",
")",
":",
"fd",
"=",
"sys",
".",
"stdin",
".",
"fileno",
"(",
")",
"old",
"=",
"termios",
".",
"tcgetattr",
"(",
"fd",
")",
"new",
"=",
"termios",
".",
"tcgetattr",
"(",
"fd",
")",
"new",
"[",
"3",
"]",
"&=",
"~",
"termios",
".",
"ECHO",
"# lflags",
"try",
":",
"termios",
".",
"tcsetattr",
"(",
"fd",
",",
"termios",
".",
"TCSADRAIN",
",",
"new",
")",
"passwd",
"=",
"raw_input",
"(",
"prompt",
")",
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"termios",
".",
"tcsetattr",
"(",
"fd",
",",
"termios",
".",
"TCSADRAIN",
",",
"old",
")",
"return",
"passwd"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
getch
|
get character. waiting for key
|
snipy/term.py
|
def getch():
"""
get character. waiting for key
"""
try:
termios.tcsetattr(_fd, termios.TCSANOW, _new_settings)
ch = sys.stdin.read(1)
finally:
termios.tcsetattr(_fd, termios.TCSADRAIN, _old_settings)
return ch
|
def getch():
"""
get character. waiting for key
"""
try:
termios.tcsetattr(_fd, termios.TCSANOW, _new_settings)
ch = sys.stdin.read(1)
finally:
termios.tcsetattr(_fd, termios.TCSADRAIN, _old_settings)
return ch
|
[
"get",
"character",
".",
"waiting",
"for",
"key"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/term.py#L163-L172
|
[
"def",
"getch",
"(",
")",
":",
"try",
":",
"termios",
".",
"tcsetattr",
"(",
"_fd",
",",
"termios",
".",
"TCSANOW",
",",
"_new_settings",
")",
"ch",
"=",
"sys",
".",
"stdin",
".",
"read",
"(",
"1",
")",
"finally",
":",
"termios",
".",
"tcsetattr",
"(",
"_fd",
",",
"termios",
".",
"TCSADRAIN",
",",
"_old_settings",
")",
"return",
"ch"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
getlogger
|
패키지 혹은 채널 로거
logging.getLogger(package_name) or logg.getLogger()
:param pkg: str
|
snipy/ilogging.py
|
def getlogger(pkg='', handler=None):
"""
패키지 혹은 채널 로거
logging.getLogger(package_name) or logg.getLogger()
:param pkg: str
"""
from .caller import caller
if not pkg:
m = caller.modulename()
s = m.split('.', 1)
if len(s) > 1:
pkg = s[0]
if haslogger(pkg):
return logging.getLogger(pkg)
else:
# local
logger = logging.getLogger(pkg)
logger.addHandler(handler or default_handler)
logger.setLevel(logging.DEBUG)
return logger
|
def getlogger(pkg='', handler=None):
"""
패키지 혹은 채널 로거
logging.getLogger(package_name) or logg.getLogger()
:param pkg: str
"""
from .caller import caller
if not pkg:
m = caller.modulename()
s = m.split('.', 1)
if len(s) > 1:
pkg = s[0]
if haslogger(pkg):
return logging.getLogger(pkg)
else:
# local
logger = logging.getLogger(pkg)
logger.addHandler(handler or default_handler)
logger.setLevel(logging.DEBUG)
return logger
|
[
"패키지",
"혹은",
"채널",
"로거",
"logging",
".",
"getLogger",
"(",
"package_name",
")",
"or",
"logg",
".",
"getLogger",
"()",
":",
"param",
"pkg",
":",
"str"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/ilogging.py#L90-L111
|
[
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"getlogger",
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"''",
",",
"handler",
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"None",
")",
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"caller",
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"modulename",
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")",
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"(",
"'.'",
",",
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"[",
"0",
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"# local",
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"getLogger",
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"pkg",
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"logger",
".",
"addHandler",
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"handler",
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"default_handler",
")",
"logger",
".",
"setLevel",
"(",
"logging",
".",
"DEBUG",
")",
"return",
"logger"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
basicConfig
|
logging의 로그를 한번 호출하면 basicConfig가 안먹으므로. 기존 핸들러 삭제후 재설정.
http://stackoverflow.com/questions/1943747/python-logging-before-you-run-logging-basicconfig
ex)
basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG)
:param filename: Specifies that a FileHandler be created, using the specified filename, rather than a StreamHandler.
:param filemode: Specifies the mode to open the file, if filename is specified (if filemode is unspecified, it defaults to ‘a’).
:param format: Use the specified format string for the handler. (https://docs.python.org/2.7/library/logging.html#logging.basicConfig
:param datefmt: Use the specified date/time format.
:param level: Set the root logger level to the specified level.
:param stream: Use the specified stream to initialize the StreamHandler. Note that this argument is incompatible with ‘filename’ - if both are present, ‘stream’ is ignored.
|
snipy/ilogging.py
|
def basicConfig(**kw):
"""logging의 로그를 한번 호출하면 basicConfig가 안먹으므로. 기존 핸들러 삭제후 재설정.
http://stackoverflow.com/questions/1943747/python-logging-before-you-run-logging-basicconfig
ex)
basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG)
:param filename: Specifies that a FileHandler be created, using the specified filename, rather than a StreamHandler.
:param filemode: Specifies the mode to open the file, if filename is specified (if filemode is unspecified, it defaults to ‘a’).
:param format: Use the specified format string for the handler. (https://docs.python.org/2.7/library/logging.html#logging.basicConfig
:param datefmt: Use the specified date/time format.
:param level: Set the root logger level to the specified level.
:param stream: Use the specified stream to initialize the StreamHandler. Note that this argument is incompatible with ‘filename’ - if both are present, ‘stream’ is ignored.
"""
while len(logging.root.handlers) > 0:
logging.root.removeHandler(logging.root.handlers[-1])
logging.basicConfig(**kw)
|
def basicConfig(**kw):
"""logging의 로그를 한번 호출하면 basicConfig가 안먹으므로. 기존 핸들러 삭제후 재설정.
http://stackoverflow.com/questions/1943747/python-logging-before-you-run-logging-basicconfig
ex)
basicConfig(format='%(asctime)s %(message)s', level=logging.DEBUG)
:param filename: Specifies that a FileHandler be created, using the specified filename, rather than a StreamHandler.
:param filemode: Specifies the mode to open the file, if filename is specified (if filemode is unspecified, it defaults to ‘a’).
:param format: Use the specified format string for the handler. (https://docs.python.org/2.7/library/logging.html#logging.basicConfig
:param datefmt: Use the specified date/time format.
:param level: Set the root logger level to the specified level.
:param stream: Use the specified stream to initialize the StreamHandler. Note that this argument is incompatible with ‘filename’ - if both are present, ‘stream’ is ignored.
"""
while len(logging.root.handlers) > 0:
logging.root.removeHandler(logging.root.handlers[-1])
logging.basicConfig(**kw)
|
[
"logging의",
"로그를",
"한번",
"호출하면",
"basicConfig가",
"안먹으므로",
".",
"기존",
"핸들러",
"삭제후",
"재설정",
".",
"http",
":",
"//",
"stackoverflow",
".",
"com",
"/",
"questions",
"/",
"1943747",
"/",
"python",
"-",
"logging",
"-",
"before",
"-",
"you",
"-",
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"logging",
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"format",
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"%",
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"asctime",
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"s",
"%",
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"message",
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"s",
"level",
"=",
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":",
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"a",
"FileHandler",
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"StreamHandler",
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"mode",
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"file",
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"if",
"filemode",
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"unspecified",
"it",
"defaults",
"to",
"‘a’",
")",
".",
":",
"param",
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"Use",
"the",
"specified",
"format",
"string",
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"(",
"https",
":",
"//",
"docs",
".",
"python",
".",
"org",
"/",
"2",
".",
"7",
"/",
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"html#logging",
".",
"basicConfig",
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"date",
"/",
"time",
"format",
".",
":",
"param",
"level",
":",
"Set",
"the",
"root",
"logger",
"level",
"to",
"the",
"specified",
"level",
".",
":",
"param",
"stream",
":",
"Use",
"the",
"specified",
"stream",
"to",
"initialize",
"the",
"StreamHandler",
".",
"Note",
"that",
"this",
"argument",
"is",
"incompatible",
"with",
"‘filename’",
"-",
"if",
"both",
"are",
"present",
"‘stream’",
"is",
"ignored",
"."
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/ilogging.py#L176-L192
|
[
"def",
"basicConfig",
"(",
"*",
"*",
"kw",
")",
":",
"while",
"len",
"(",
"logging",
".",
"root",
".",
"handlers",
")",
">",
"0",
":",
"logging",
".",
"root",
".",
"removeHandler",
"(",
"logging",
".",
"root",
".",
"handlers",
"[",
"-",
"1",
"]",
")",
"logging",
".",
"basicConfig",
"(",
"*",
"*",
"kw",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
FormatterX.format
|
tweaked from source of base
|
snipy/ilogging.py
|
def format(self, record):
"""tweaked from source of base"""
try:
record.message = record.getMessage()
except TypeError:
# if error during msg = msg % self.args
if record.args:
if isinstance(record.args, collections.Mapping):
record.message = record.msg.format(**record.args)
else:
record.message = record.msg.format(record.args)
self._fmt = self.getfmt(record.levelname)
if self.usesTime():
record.asctime = self.formatTime(record, self.datefmt)
s = self._fmt.format(**record.__dict__)
if record.exc_info:
# Cache the traceback text to avoid converting it multiple times
# (it's constant anyway)
if not record.exc_text:
record.exc_text = self.formatException(record.exc_info)
if record.exc_text:
if s[-1:] != '\n':
s += '\n'
try:
s = s + record.exc_text
except UnicodeError:
s = s + record.exc_text.decode(sys.getfilesystemencoding(), 'replace')
return s
|
def format(self, record):
"""tweaked from source of base"""
try:
record.message = record.getMessage()
except TypeError:
# if error during msg = msg % self.args
if record.args:
if isinstance(record.args, collections.Mapping):
record.message = record.msg.format(**record.args)
else:
record.message = record.msg.format(record.args)
self._fmt = self.getfmt(record.levelname)
if self.usesTime():
record.asctime = self.formatTime(record, self.datefmt)
s = self._fmt.format(**record.__dict__)
if record.exc_info:
# Cache the traceback text to avoid converting it multiple times
# (it's constant anyway)
if not record.exc_text:
record.exc_text = self.formatException(record.exc_info)
if record.exc_text:
if s[-1:] != '\n':
s += '\n'
try:
s = s + record.exc_text
except UnicodeError:
s = s + record.exc_text.decode(sys.getfilesystemencoding(), 'replace')
return s
|
[
"tweaked",
"from",
"source",
"of",
"base"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/ilogging.py#L32-L61
|
[
"def",
"format",
"(",
"self",
",",
"record",
")",
":",
"try",
":",
"record",
".",
"message",
"=",
"record",
".",
"getMessage",
"(",
")",
"except",
"TypeError",
":",
"# if error during msg = msg % self.args",
"if",
"record",
".",
"args",
":",
"if",
"isinstance",
"(",
"record",
".",
"args",
",",
"collections",
".",
"Mapping",
")",
":",
"record",
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"message",
"=",
"record",
".",
"msg",
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"format",
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"*",
"*",
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"args",
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"usesTime",
"(",
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"asctime",
"=",
"self",
".",
"formatTime",
"(",
"record",
",",
"self",
".",
"datefmt",
")",
"s",
"=",
"self",
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"_fmt",
".",
"format",
"(",
"*",
"*",
"record",
".",
"__dict__",
")",
"if",
"record",
".",
"exc_info",
":",
"# Cache the traceback text to avoid converting it multiple times",
"# (it's constant anyway)",
"if",
"not",
"record",
".",
"exc_text",
":",
"record",
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"exc_text",
"=",
"self",
".",
"formatException",
"(",
"record",
".",
"exc_info",
")",
"if",
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".",
"exc_text",
":",
"if",
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"[",
"-",
"1",
":",
"]",
"!=",
"'\\n'",
":",
"s",
"+=",
"'\\n'",
"try",
":",
"s",
"=",
"s",
"+",
"record",
".",
"exc_text",
"except",
"UnicodeError",
":",
"s",
"=",
"s",
"+",
"record",
".",
"exc_text",
".",
"decode",
"(",
"sys",
".",
"getfilesystemencoding",
"(",
")",
",",
"'replace'",
")",
"return",
"s"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
getProcessOwner
|
getProcessOwner - Get the process owner of a pid
@param pid <int> - process id
@return - None if process not found or can't be determined. Otherwise, a dict:
{
uid - Owner UID
name - Owner name, or None if one cannot be determined
}
|
ProcessMappingScanner/__init__.py
|
def getProcessOwner(pid):
'''
getProcessOwner - Get the process owner of a pid
@param pid <int> - process id
@return - None if process not found or can't be determined. Otherwise, a dict:
{
uid - Owner UID
name - Owner name, or None if one cannot be determined
}
'''
try:
ownerUid = os.stat('/proc/' + str(pid)).st_uid
except:
return None
try:
ownerName = pwd.getpwuid(ownerUid).pw_name
except:
ownerName = None
return {
'uid' : ownerUid,
'name' : ownerName
}
|
def getProcessOwner(pid):
'''
getProcessOwner - Get the process owner of a pid
@param pid <int> - process id
@return - None if process not found or can't be determined. Otherwise, a dict:
{
uid - Owner UID
name - Owner name, or None if one cannot be determined
}
'''
try:
ownerUid = os.stat('/proc/' + str(pid)).st_uid
except:
return None
try:
ownerName = pwd.getpwuid(ownerUid).pw_name
except:
ownerName = None
return {
'uid' : ownerUid,
'name' : ownerName
}
|
[
"getProcessOwner",
"-",
"Get",
"the",
"process",
"owner",
"of",
"a",
"pid"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L25-L50
|
[
"def",
"getProcessOwner",
"(",
"pid",
")",
":",
"try",
":",
"ownerUid",
"=",
"os",
".",
"stat",
"(",
"'/proc/'",
"+",
"str",
"(",
"pid",
")",
")",
".",
"st_uid",
"except",
":",
"return",
"None",
"try",
":",
"ownerName",
"=",
"pwd",
".",
"getpwuid",
"(",
"ownerUid",
")",
".",
"pw_name",
"except",
":",
"ownerName",
"=",
"None",
"return",
"{",
"'uid'",
":",
"ownerUid",
",",
"'name'",
":",
"ownerName",
"}"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
getProcessOwnerStr
|
getProcessOwner - Get Process owner of a pid as a string instead of components (#getProcessOwner)
@return - Returns username if it can be determined, otherwise uid, otherwise "unknown"
|
ProcessMappingScanner/__init__.py
|
def getProcessOwnerStr(pid):
'''
getProcessOwner - Get Process owner of a pid as a string instead of components (#getProcessOwner)
@return - Returns username if it can be determined, otherwise uid, otherwise "unknown"
'''
ownerInfo = getProcessOwner(pid)
if ownerInfo:
if ownerInfo['name']:
owner = ownerInfo['name']
else:
owner = str(ownerInfo['uid'])
else:
owner = 'unknown'
return owner
|
def getProcessOwnerStr(pid):
'''
getProcessOwner - Get Process owner of a pid as a string instead of components (#getProcessOwner)
@return - Returns username if it can be determined, otherwise uid, otherwise "unknown"
'''
ownerInfo = getProcessOwner(pid)
if ownerInfo:
if ownerInfo['name']:
owner = ownerInfo['name']
else:
owner = str(ownerInfo['uid'])
else:
owner = 'unknown'
return owner
|
[
"getProcessOwner",
"-",
"Get",
"Process",
"owner",
"of",
"a",
"pid",
"as",
"a",
"string",
"instead",
"of",
"components",
"(",
"#getProcessOwner",
")"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L52-L67
|
[
"def",
"getProcessOwnerStr",
"(",
"pid",
")",
":",
"ownerInfo",
"=",
"getProcessOwner",
"(",
"pid",
")",
"if",
"ownerInfo",
":",
"if",
"ownerInfo",
"[",
"'name'",
"]",
":",
"owner",
"=",
"ownerInfo",
"[",
"'name'",
"]",
"else",
":",
"owner",
"=",
"str",
"(",
"ownerInfo",
"[",
"'uid'",
"]",
")",
"else",
":",
"owner",
"=",
"'unknown'",
"return",
"owner"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
getProcessCommandLineStr
|
getProcessCommandLineStr - Gets a the commandline (program + arguments) of a given pid
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a string of commandline.
@note Caution, args may have spaces in them, and you cannot surmise from this method. If you care (like trying to replay a command), use getProcessCommandLineList instead
|
ProcessMappingScanner/__init__.py
|
def getProcessCommandLineStr(pid):
'''
getProcessCommandLineStr - Gets a the commandline (program + arguments) of a given pid
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a string of commandline.
@note Caution, args may have spaces in them, and you cannot surmise from this method. If you care (like trying to replay a command), use getProcessCommandLineList instead
'''
try:
with open('/proc/%d/cmdline' %(int(pid),), 'r') as f:
cmdline = f.read()
return cmdline.replace('\x00', ' ')
except:
return None
|
def getProcessCommandLineStr(pid):
'''
getProcessCommandLineStr - Gets a the commandline (program + arguments) of a given pid
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a string of commandline.
@note Caution, args may have spaces in them, and you cannot surmise from this method. If you care (like trying to replay a command), use getProcessCommandLineList instead
'''
try:
with open('/proc/%d/cmdline' %(int(pid),), 'r') as f:
cmdline = f.read()
return cmdline.replace('\x00', ' ')
except:
return None
|
[
"getProcessCommandLineStr",
"-",
"Gets",
"a",
"the",
"commandline",
"(",
"program",
"+",
"arguments",
")",
"of",
"a",
"given",
"pid"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L69-L84
|
[
"def",
"getProcessCommandLineStr",
"(",
"pid",
")",
":",
"try",
":",
"with",
"open",
"(",
"'/proc/%d/cmdline'",
"%",
"(",
"int",
"(",
"pid",
")",
",",
")",
",",
"'r'",
")",
"as",
"f",
":",
"cmdline",
"=",
"f",
".",
"read",
"(",
")",
"return",
"cmdline",
".",
"replace",
"(",
"'\\x00'",
",",
"' '",
")",
"except",
":",
"return",
"None"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
getProcessCommandLineList
|
getProcessCommandLineList - Gets the commandline (program + argumentS) of a given pid as a list.
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a list representing argv. First argument is process name, remainder are arguments.
@note - Use this if you care about whether a process had a space in the commands
|
ProcessMappingScanner/__init__.py
|
def getProcessCommandLineList(pid):
'''
getProcessCommandLineList - Gets the commandline (program + argumentS) of a given pid as a list.
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a list representing argv. First argument is process name, remainder are arguments.
@note - Use this if you care about whether a process had a space in the commands
'''
try:
with open('/proc/%d/cmdline' %(int(pid),), 'r') as f:
cmdline = f.read()
return cmdline.split('\x00')
except:
return None
|
def getProcessCommandLineList(pid):
'''
getProcessCommandLineList - Gets the commandline (program + argumentS) of a given pid as a list.
@param pid <int> - Process ID
@return - None if process not found or can't be determined. Otherwise a list representing argv. First argument is process name, remainder are arguments.
@note - Use this if you care about whether a process had a space in the commands
'''
try:
with open('/proc/%d/cmdline' %(int(pid),), 'r') as f:
cmdline = f.read()
return cmdline.split('\x00')
except:
return None
|
[
"getProcessCommandLineList",
"-",
"Gets",
"the",
"commandline",
"(",
"program",
"+",
"argumentS",
")",
"of",
"a",
"given",
"pid",
"as",
"a",
"list",
"."
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L87-L103
|
[
"def",
"getProcessCommandLineList",
"(",
"pid",
")",
":",
"try",
":",
"with",
"open",
"(",
"'/proc/%d/cmdline'",
"%",
"(",
"int",
"(",
"pid",
")",
",",
")",
",",
"'r'",
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"as",
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"cmdline",
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".",
"read",
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")",
"return",
"cmdline",
".",
"split",
"(",
"'\\x00'",
")",
"except",
":",
"return",
"None"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanProcessForCwd
|
scanProcessForCwd - Searches a given pid's cwd for a given pattern
@param pid <int> - A running process ID on this system
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'cwd' : The exact cwd of matched process
}
|
ProcessMappingScanner/__init__.py
|
def scanProcessForCwd(pid, searchPortion, isExactMatch=False):
'''
scanProcessForCwd - Searches a given pid's cwd for a given pattern
@param pid <int> - A running process ID on this system
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'cwd' : The exact cwd of matched process
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
cwd = getProcessCwd(pid)
if not cwd:
return None
isMatch = False
if isExactMatch is True:
if searchPortion == cwd:
isMatch = True
else:
if searchPortion.endswith('/') and searchPortion[:-1] == cwd:
isMatch = True
else:
if searchPortion in cwd:
isMatch = True
else:
if searchPortion.endswith('/') and searchPortion[:-1] in cwd:
isMatch = True
if not isMatch:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'cwd' : cwd,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
def scanProcessForCwd(pid, searchPortion, isExactMatch=False):
'''
scanProcessForCwd - Searches a given pid's cwd for a given pattern
@param pid <int> - A running process ID on this system
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'cwd' : The exact cwd of matched process
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
cwd = getProcessCwd(pid)
if not cwd:
return None
isMatch = False
if isExactMatch is True:
if searchPortion == cwd:
isMatch = True
else:
if searchPortion.endswith('/') and searchPortion[:-1] == cwd:
isMatch = True
else:
if searchPortion in cwd:
isMatch = True
else:
if searchPortion.endswith('/') and searchPortion[:-1] in cwd:
isMatch = True
if not isMatch:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'cwd' : cwd,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
[
"scanProcessForCwd",
"-",
"Searches",
"a",
"given",
"pid",
"s",
"cwd",
"for",
"a",
"given",
"pattern"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L131-L194
|
[
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"searchPortion",
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"isExactMatch",
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"False",
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"'Expected an integer, got %s for pid.\\n'",
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"str",
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",",
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":",
"return",
"None",
"except",
"PermissionError",
":",
"return",
"None"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanAllProcessesForCwd
|
scanAllProcessesForCwd - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return - <dict> - A dictionary of pid -> cwdResults for each pid that matched the search pattern. For format of "cwdResults", @see scanProcessForCwd
|
ProcessMappingScanner/__init__.py
|
def scanAllProcessesForCwd(searchPortion, isExactMatch=False):
'''
scanAllProcessesForCwd - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return - <dict> - A dictionary of pid -> cwdResults for each pid that matched the search pattern. For format of "cwdResults", @see scanProcessForCwd
'''
pids = getAllRunningPids()
cwdResults = [scanProcessForCwd(pid, searchPortion, isExactMatch) for pid in pids]
ret = {}
for i in range(len(pids)):
if cwdResults[i] is not None:
ret[pids[i]] = cwdResults[i]
return ret
|
def scanAllProcessesForCwd(searchPortion, isExactMatch=False):
'''
scanAllProcessesForCwd - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - Any portion of directory to search
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@return - <dict> - A dictionary of pid -> cwdResults for each pid that matched the search pattern. For format of "cwdResults", @see scanProcessForCwd
'''
pids = getAllRunningPids()
cwdResults = [scanProcessForCwd(pid, searchPortion, isExactMatch) for pid in pids]
ret = {}
for i in range(len(pids)):
if cwdResults[i] is not None:
ret[pids[i]] = cwdResults[i]
return ret
|
[
"scanAllProcessesForCwd",
"-",
"Scans",
"all",
"processes",
"on",
"the",
"system",
"for",
"a",
"given",
"search",
"pattern",
"."
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L196-L214
|
[
"def",
"scanAllProcessesForCwd",
"(",
"searchPortion",
",",
"isExactMatch",
"=",
"False",
")",
":",
"pids",
"=",
"getAllRunningPids",
"(",
")",
"cwdResults",
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"[",
"scanProcessForCwd",
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":",
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"[",
"pids",
"[",
"i",
"]",
"]",
"=",
"cwdResults",
"[",
"i",
"]",
"return",
"ret"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanProcessForMapping
|
scanProcessForMapping - Searches a given pid's mappings for a certain pattern.
@param pid <int> - A running process ID on this system
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'matchedMappings' : All mappings likes that matched the given search pattern
}
|
ProcessMappingScanner/__init__.py
|
def scanProcessForMapping(pid, searchPortion, isExactMatch=False, ignoreCase=False):
'''
scanProcessForMapping - Searches a given pid's mappings for a certain pattern.
@param pid <int> - A running process ID on this system
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'matchedMappings' : All mappings likes that matched the given search pattern
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
with open('/proc/%d/maps' %(pid,), 'r') as f:
contents = f.read()
lines = contents.split('\n')
matchedMappings = []
if isExactMatch is True:
if ignoreCase is False:
isMatch = lambda searchFor, searchIn : bool(searchFor == searchIn)
else:
isMatch = lambda searchFor, searchIn : bool(searchFor.lower() == searchIn.lower())
else:
if ignoreCase is False:
isMatch = lambda searchFor, searchIn : bool(searchFor in searchIn)
else:
isMatch = lambda searchFor, searchIn : bool(searchFor.lower() in searchIn.lower())
for line in lines:
portion = ' '.join(line.split(' ')[5:]).lstrip()
if isMatch(searchPortion, portion):
matchedMappings.append('\t' + line)
if len(matchedMappings) == 0:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'matchedMappings' : matchedMappings,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
def scanProcessForMapping(pid, searchPortion, isExactMatch=False, ignoreCase=False):
'''
scanProcessForMapping - Searches a given pid's mappings for a certain pattern.
@param pid <int> - A running process ID on this system
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return <dict> - If result is found, the following dict is returned. If no match found on the given pid, or pid is not found running, None is returned.
{
'searchPortion' : The passed search pattern
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or uid if no mapping can be found, or "unknown" if neither could be determined.
'cmdline' : Commandline string
'matchedMappings' : All mappings likes that matched the given search pattern
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
with open('/proc/%d/maps' %(pid,), 'r') as f:
contents = f.read()
lines = contents.split('\n')
matchedMappings = []
if isExactMatch is True:
if ignoreCase is False:
isMatch = lambda searchFor, searchIn : bool(searchFor == searchIn)
else:
isMatch = lambda searchFor, searchIn : bool(searchFor.lower() == searchIn.lower())
else:
if ignoreCase is False:
isMatch = lambda searchFor, searchIn : bool(searchFor in searchIn)
else:
isMatch = lambda searchFor, searchIn : bool(searchFor.lower() in searchIn.lower())
for line in lines:
portion = ' '.join(line.split(' ')[5:]).lstrip()
if isMatch(searchPortion, portion):
matchedMappings.append('\t' + line)
if len(matchedMappings) == 0:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'matchedMappings' : matchedMappings,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
[
"scanProcessForMapping",
"-",
"Searches",
"a",
"given",
"pid",
"s",
"mappings",
"for",
"a",
"certain",
"pattern",
"."
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L216-L287
|
[
"def",
"scanProcessForMapping",
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"pid",
",",
"searchPortion",
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"isExactMatch",
"=",
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"except",
"FileNotFoundError",
":",
"return",
"None",
"except",
"PermissionError",
":",
"return",
"None"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanAllProcessesForMapping
|
scanAllProcessesForMapping - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForMapping
|
ProcessMappingScanner/__init__.py
|
def scanAllProcessesForMapping(searchPortion, isExactMatch=False, ignoreCase=False):
'''
scanAllProcessesForMapping - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForMapping
'''
pids = getAllRunningPids()
# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.
mappingResults = [scanProcessForMapping(pid, searchPortion, isExactMatch, ignoreCase) for pid in pids]
ret = {}
for i in range(len(pids)):
if mappingResults[i] is not None:
ret[pids[i]] = mappingResults[i]
return ret
|
def scanAllProcessesForMapping(searchPortion, isExactMatch=False, ignoreCase=False):
'''
scanAllProcessesForMapping - Scans all processes on the system for a given search pattern.
@param searchPortion <str> - A mapping for which to search, example: libc or python or libz.so.1. Give empty string to return all mappings.
@param isExactMatch <bool> Default False - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForMapping
'''
pids = getAllRunningPids()
# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.
mappingResults = [scanProcessForMapping(pid, searchPortion, isExactMatch, ignoreCase) for pid in pids]
ret = {}
for i in range(len(pids)):
if mappingResults[i] is not None:
ret[pids[i]] = mappingResults[i]
return ret
|
[
"scanAllProcessesForMapping",
"-",
"Scans",
"all",
"processes",
"on",
"the",
"system",
"for",
"a",
"given",
"search",
"pattern",
"."
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L290-L309
|
[
"def",
"scanAllProcessesForMapping",
"(",
"searchPortion",
",",
"isExactMatch",
"=",
"False",
",",
"ignoreCase",
"=",
"False",
")",
":",
"pids",
"=",
"getAllRunningPids",
"(",
")",
"# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.",
"mappingResults",
"=",
"[",
"scanProcessForMapping",
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"[",
"i",
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"return",
"ret"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanProcessForOpenFile
|
scanProcessForOpenFile - Scans open FDs for a given pid to see if any are the provided searchPortion
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - If result is found, the following dict is returned. If no match found on the given pid, or the pid is not found running, None is returned.
{
'searchPortion' : The search portion provided
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or "unknown" if one could not be determined
'cmdline' : Commandline string
'fds' : List of file descriptors assigned to this file (could be mapped several times)
'filenames' : List of the filenames matched
}
|
ProcessMappingScanner/__init__.py
|
def scanProcessForOpenFile(pid, searchPortion, isExactMatch=True, ignoreCase=False):
'''
scanProcessForOpenFile - Scans open FDs for a given pid to see if any are the provided searchPortion
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - If result is found, the following dict is returned. If no match found on the given pid, or the pid is not found running, None is returned.
{
'searchPortion' : The search portion provided
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or "unknown" if one could not be determined
'cmdline' : Commandline string
'fds' : List of file descriptors assigned to this file (could be mapped several times)
'filenames' : List of the filenames matched
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
prefixDir = "/proc/%d/fd" % (pid,)
processFDs = os.listdir(prefixDir)
matchedFDs = []
matchedFilenames = []
if isExactMatch is True:
if ignoreCase is False:
isMatch = lambda searchFor, totalPath : bool(searchFor == totalPath)
else:
isMatch = lambda searchFor, totalPath : bool(searchFor.lower() == totalPath.lower())
else:
if ignoreCase is False:
isMatch = lambda searchFor, totalPath : bool(searchFor in totalPath)
else:
isMatch = lambda searchFor, totalPath : bool(searchFor.lower() in totalPath.lower())
for fd in processFDs:
fdPath = os.readlink(prefixDir + '/' + fd)
if isMatch(searchPortion, fdPath):
matchedFDs.append(fd)
matchedFilenames.append(fdPath)
if len(matchedFDs) == 0:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'fds' : matchedFDs,
'filenames' : matchedFilenames,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
def scanProcessForOpenFile(pid, searchPortion, isExactMatch=True, ignoreCase=False):
'''
scanProcessForOpenFile - Scans open FDs for a given pid to see if any are the provided searchPortion
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - If result is found, the following dict is returned. If no match found on the given pid, or the pid is not found running, None is returned.
{
'searchPortion' : The search portion provided
'pid' : The passed pid (as an integer)
'owner' : String of process owner, or "unknown" if one could not be determined
'cmdline' : Commandline string
'fds' : List of file descriptors assigned to this file (could be mapped several times)
'filenames' : List of the filenames matched
}
'''
try:
try:
pid = int(pid)
except ValueError as e:
sys.stderr.write('Expected an integer, got %s for pid.\n' %(str(type(pid)),))
raise e
prefixDir = "/proc/%d/fd" % (pid,)
processFDs = os.listdir(prefixDir)
matchedFDs = []
matchedFilenames = []
if isExactMatch is True:
if ignoreCase is False:
isMatch = lambda searchFor, totalPath : bool(searchFor == totalPath)
else:
isMatch = lambda searchFor, totalPath : bool(searchFor.lower() == totalPath.lower())
else:
if ignoreCase is False:
isMatch = lambda searchFor, totalPath : bool(searchFor in totalPath)
else:
isMatch = lambda searchFor, totalPath : bool(searchFor.lower() in totalPath.lower())
for fd in processFDs:
fdPath = os.readlink(prefixDir + '/' + fd)
if isMatch(searchPortion, fdPath):
matchedFDs.append(fd)
matchedFilenames.append(fdPath)
if len(matchedFDs) == 0:
return None
cmdline = getProcessCommandLineStr(pid)
owner = getProcessOwnerStr(pid)
return {
'searchPortion' : searchPortion,
'pid' : pid,
'owner' : owner,
'cmdline' : cmdline,
'fds' : matchedFDs,
'filenames' : matchedFilenames,
}
except OSError:
return None
except IOError:
return None
except FileNotFoundError:
return None
except PermissionError:
return None
|
[
"scanProcessForOpenFile",
"-",
"Scans",
"open",
"FDs",
"for",
"a",
"given",
"pid",
"to",
"see",
"if",
"any",
"are",
"the",
"provided",
"searchPortion"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L315-L392
|
[
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"None",
"except",
"PermissionError",
":",
"return",
"None"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
scanAllProcessesForOpenFile
|
scanAllProcessessForOpenFile - Scans all processes on the system for a given filename
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForOpenFile
|
ProcessMappingScanner/__init__.py
|
def scanAllProcessesForOpenFile(searchPortion, isExactMatch=True, ignoreCase=False):
'''
scanAllProcessessForOpenFile - Scans all processes on the system for a given filename
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForOpenFile
'''
pids = getAllRunningPids()
# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.
mappingResults = [scanProcessForOpenFile(pid, searchPortion, isExactMatch, ignoreCase) for pid in pids]
ret = {}
for i in range(len(pids)):
if mappingResults[i] is not None:
ret[pids[i]] = mappingResults[i]
return ret
|
def scanAllProcessesForOpenFile(searchPortion, isExactMatch=True, ignoreCase=False):
'''
scanAllProcessessForOpenFile - Scans all processes on the system for a given filename
@param searchPortion <str> - Filename to check
@param isExactMatch <bool> Default True - If match should be exact, otherwise a partial match is performed.
@param ignoreCase <bool> Default False - If True, search will be performed case-insensitively
@return - <dict> - A dictionary of pid -> mappingResults for each pid that matched the search pattern. For format of "mappingResults", @see scanProcessForOpenFile
'''
pids = getAllRunningPids()
# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.
mappingResults = [scanProcessForOpenFile(pid, searchPortion, isExactMatch, ignoreCase) for pid in pids]
ret = {}
for i in range(len(pids)):
if mappingResults[i] is not None:
ret[pids[i]] = mappingResults[i]
return ret
|
[
"scanAllProcessessForOpenFile",
"-",
"Scans",
"all",
"processes",
"on",
"the",
"system",
"for",
"a",
"given",
"filename"
] |
kata198/ProcessMappingScanner
|
python
|
https://github.com/kata198/ProcessMappingScanner/blob/d1735fe6746493c51aaae213b982fa96f5c5b621/ProcessMappingScanner/__init__.py#L395-L414
|
[
"def",
"scanAllProcessesForOpenFile",
"(",
"searchPortion",
",",
"isExactMatch",
"=",
"True",
",",
"ignoreCase",
"=",
"False",
")",
":",
"pids",
"=",
"getAllRunningPids",
"(",
")",
"# Since processes could disappear, we run the scan as fast as possible here with a list comprehension, then assemble the return dictionary later.",
"mappingResults",
"=",
"[",
"scanProcessForOpenFile",
"(",
"pid",
",",
"searchPortion",
",",
"isExactMatch",
",",
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"]",
"ret",
"=",
"{",
"}",
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"(",
"pids",
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")",
":",
"if",
"mappingResults",
"[",
"i",
"]",
"is",
"not",
"None",
":",
"ret",
"[",
"pids",
"[",
"i",
"]",
"]",
"=",
"mappingResults",
"[",
"i",
"]",
"return",
"ret"
] |
d1735fe6746493c51aaae213b982fa96f5c5b621
|
valid
|
enum
|
class buider
|
snipy/enum.py
|
def enum(name, *members, **withvalue):
"""class buider"""
if len(members) == 1:
if isinstance(members[0], str):
members = members[0].split()
elif isinstance(members[0], (list, tuple)):
members = members[0]
dic = {v: v for v in members}
dic.update(withvalue)
return type(name, (Enum,), dic)
|
def enum(name, *members, **withvalue):
"""class buider"""
if len(members) == 1:
if isinstance(members[0], str):
members = members[0].split()
elif isinstance(members[0], (list, tuple)):
members = members[0]
dic = {v: v for v in members}
dic.update(withvalue)
return type(name, (Enum,), dic)
|
[
"class",
"buider"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/enum.py#L26-L37
|
[
"def",
"enum",
"(",
"name",
",",
"*",
"members",
",",
"*",
"*",
"withvalue",
")",
":",
"if",
"len",
"(",
"members",
")",
"==",
"1",
":",
"if",
"isinstance",
"(",
"members",
"[",
"0",
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",",
"str",
")",
":",
"members",
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"isinstance",
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"members",
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",",
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",",
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")",
":",
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")",
"return",
"type",
"(",
"name",
",",
"(",
"Enum",
",",
")",
",",
"dic",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
database
|
usage:
with database('my_db') as conn:
c = conn.cursor()
....
database 커넥션 with 문과 같이 사용하고, 알아서 close하기
:param db: str: db스키마
:param kwargs:
:return:
|
snipy/database.py
|
def database(db='', **kwargs):
"""
usage:
with database('my_db') as conn:
c = conn.cursor()
....
database 커넥션 with 문과 같이 사용하고, 알아서 close하기
:param db: str: db스키마
:param kwargs:
:return:
"""
db = kwargs.pop('db', db)
arg = db_config(db)
arg.update(kwargs)
return closing(MySQLdb.connect(**arg))
|
def database(db='', **kwargs):
"""
usage:
with database('my_db') as conn:
c = conn.cursor()
....
database 커넥션 with 문과 같이 사용하고, 알아서 close하기
:param db: str: db스키마
:param kwargs:
:return:
"""
db = kwargs.pop('db', db)
arg = db_config(db)
arg.update(kwargs)
return closing(MySQLdb.connect(**arg))
|
[
"usage",
":",
"with",
"database",
"(",
"my_db",
")",
"as",
"conn",
":",
"c",
"=",
"conn",
".",
"cursor",
"()",
"....",
"database",
"커넥션",
"with",
"문과",
"같이",
"사용하고",
"알아서",
"close하기",
":",
"param",
"db",
":",
"str",
":",
"db스키마",
":",
"param",
"kwargs",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L23-L38
|
[
"def",
"database",
"(",
"db",
"=",
"''",
",",
"*",
"*",
"kwargs",
")",
":",
"db",
"=",
"kwargs",
".",
"pop",
"(",
"'db'",
",",
"db",
")",
"arg",
"=",
"db_config",
"(",
"db",
")",
"arg",
".",
"update",
"(",
"kwargs",
")",
"return",
"closing",
"(",
"MySQLdb",
".",
"connect",
"(",
"*",
"*",
"arg",
")",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
connect
|
db 접속 공통 인자들 채워서 접속, schema만 넣으면 됩니다.
db connection 객체 반환이지만
with 문과 같이 쓰이면 cursor임에 주의 (MySQLdb의 구현이 그렇습니다.)
ex1)
import snipy.database as db
conn = db.connect('my_db')
cursor = conn.cursor()
ex2)
import snipy.database as db
with db.connect('my_db') as cursor:
cursor.execute(query)
:param db: str: db schema
:param kwargs: 추가 접속 정보
:return: connection or cursor
|
snipy/database.py
|
def connect(db='', **kwargs):
"""
db 접속 공통 인자들 채워서 접속, schema만 넣으면 됩니다.
db connection 객체 반환이지만
with 문과 같이 쓰이면 cursor임에 주의 (MySQLdb의 구현이 그렇습니다.)
ex1)
import snipy.database as db
conn = db.connect('my_db')
cursor = conn.cursor()
ex2)
import snipy.database as db
with db.connect('my_db') as cursor:
cursor.execute(query)
:param db: str: db schema
:param kwargs: 추가 접속 정보
:return: connection or cursor
"""
arg = db_config(db)
arg.update(kwargs)
return MySQLdb.connect(**arg)
|
def connect(db='', **kwargs):
"""
db 접속 공통 인자들 채워서 접속, schema만 넣으면 됩니다.
db connection 객체 반환이지만
with 문과 같이 쓰이면 cursor임에 주의 (MySQLdb의 구현이 그렇습니다.)
ex1)
import snipy.database as db
conn = db.connect('my_db')
cursor = conn.cursor()
ex2)
import snipy.database as db
with db.connect('my_db') as cursor:
cursor.execute(query)
:param db: str: db schema
:param kwargs: 추가 접속 정보
:return: connection or cursor
"""
arg = db_config(db)
arg.update(kwargs)
return MySQLdb.connect(**arg)
|
[
"db",
"접속",
"공통",
"인자들",
"채워서",
"접속",
"schema만",
"넣으면",
"됩니다",
".",
"db",
"connection",
"객체",
"반환이지만",
"with",
"문과",
"같이",
"쓰이면",
"cursor임에",
"주의",
"(",
"MySQLdb의",
"구현이",
"그렇습니다",
".",
")",
"ex1",
")",
"import",
"snipy",
".",
"database",
"as",
"db",
"conn",
"=",
"db",
".",
"connect",
"(",
"my_db",
")",
"cursor",
"=",
"conn",
".",
"cursor",
"()"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L41-L62
|
[
"def",
"connect",
"(",
"db",
"=",
"''",
",",
"*",
"*",
"kwargs",
")",
":",
"arg",
"=",
"db_config",
"(",
"db",
")",
"arg",
".",
"update",
"(",
"kwargs",
")",
"return",
"MySQLdb",
".",
"connect",
"(",
"*",
"*",
"arg",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
_cursor_exit
|
cursor with문과 쓸수 있게 __exit__에 바인딩
:param cursor:
:param exc_type:
:param exc_value:
:param traceback:
:return:
|
snipy/database.py
|
def _cursor_exit(cursor, exc_type, exc_value, traceback):
"""
cursor with문과 쓸수 있게 __exit__에 바인딩
:param cursor:
:param exc_type:
:param exc_value:
:param traceback:
:return:
"""
if exc_type is not None:
print(exc_value, traceback)
cursor.connection.close()
|
def _cursor_exit(cursor, exc_type, exc_value, traceback):
"""
cursor with문과 쓸수 있게 __exit__에 바인딩
:param cursor:
:param exc_type:
:param exc_value:
:param traceback:
:return:
"""
if exc_type is not None:
print(exc_value, traceback)
cursor.connection.close()
|
[
"cursor",
"with문과",
"쓸수",
"있게",
"__exit__에",
"바인딩",
":",
"param",
"cursor",
":",
":",
"param",
"exc_type",
":",
":",
"param",
"exc_value",
":",
":",
"param",
"traceback",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L65-L76
|
[
"def",
"_cursor_exit",
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"cursor",
",",
"exc_type",
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"exc_value",
",",
"traceback",
")",
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"exc_value",
",",
"traceback",
")",
"cursor",
".",
"connection",
".",
"close",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
fetch
|
for record in fetch(query, args, **configs):
print record
:param args:
:param db: str: db 스키마
:param query: 쿼리 스트링
:param kwargs: db connection 추가 인자. 보통 생략
:return: iterator
|
snipy/database.py
|
def fetch(query, args=None, **kwargs):
"""
for record in fetch(query, args, **configs):
print record
:param args:
:param db: str: db 스키마
:param query: 쿼리 스트링
:param kwargs: db connection 추가 인자. 보통 생략
:return: iterator
"""
cur = execute(kwargs.pop('db', ''), query, args, **kwargs)
for r in cur:
yield r
cur.connection.close()
|
def fetch(query, args=None, **kwargs):
"""
for record in fetch(query, args, **configs):
print record
:param args:
:param db: str: db 스키마
:param query: 쿼리 스트링
:param kwargs: db connection 추가 인자. 보통 생략
:return: iterator
"""
cur = execute(kwargs.pop('db', ''), query, args, **kwargs)
for r in cur:
yield r
cur.connection.close()
|
[
"for",
"record",
"in",
"fetch",
"(",
"query",
"args",
"**",
"configs",
")",
":",
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"record",
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"db",
"connection",
"추가",
"인자",
".",
"보통",
"생략",
":",
"return",
":",
"iterator"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L105-L120
|
[
"def",
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",",
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"None",
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"*",
"kwargs",
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",",
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",",
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"kwargs",
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"r",
"in",
"cur",
":",
"yield",
"r",
"cur",
".",
"connection",
".",
"close",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
get_insert_query
|
format insert query
:param table: str
:param fields: list[str]
:param field_count: int
:return: str
|
snipy/database.py
|
def get_insert_query(table, fields=None, field_count=None):
"""
format insert query
:param table: str
:param fields: list[str]
:param field_count: int
:return: str
"""
if fields:
q = 'insert into %s ({0}) values ({1});' % table
l = len(fields)
q = q.format(','.join(fields), ','.join(['%s'] * l))
elif field_count:
q = 'insert into %s values ({0});' % table
q = q.format(','.join(['%s'] * field_count))
else:
raise ValueError('fields or field_count need')
return q
|
def get_insert_query(table, fields=None, field_count=None):
"""
format insert query
:param table: str
:param fields: list[str]
:param field_count: int
:return: str
"""
if fields:
q = 'insert into %s ({0}) values ({1});' % table
l = len(fields)
q = q.format(','.join(fields), ','.join(['%s'] * l))
elif field_count:
q = 'insert into %s values ({0});' % table
q = q.format(','.join(['%s'] * field_count))
else:
raise ValueError('fields or field_count need')
return q
|
[
"format",
"insert",
"query",
":",
"param",
"table",
":",
"str",
":",
"param",
"fields",
":",
"list",
"[",
"str",
"]",
":",
"param",
"field_count",
":",
"int",
":",
"return",
":",
"str"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L145-L163
|
[
"def",
"get_insert_query",
"(",
"table",
",",
"fields",
"=",
"None",
",",
"field_count",
"=",
"None",
")",
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"if",
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":",
"q",
"=",
"'insert into %s ({0}) values ({1});'",
"%",
"table",
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"=",
"len",
"(",
"fields",
")",
"q",
"=",
"q",
".",
"format",
"(",
"','",
".",
"join",
"(",
"fields",
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",",
"','",
".",
"join",
"(",
"[",
"'%s'",
"]",
"*",
"l",
")",
")",
"elif",
"field_count",
":",
"q",
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"%",
"table",
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"=",
"q",
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"join",
"(",
"[",
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"]",
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"field_count",
")",
")",
"else",
":",
"raise",
"ValueError",
"(",
"'fields or field_count need'",
")",
"return",
"q"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
insert
|
db에 레코드 집어넣기
ex)
cursor.insert(table, v1, v2,...)
ex)
cursor.insert(table, id=v1, word=v2, commit=True)
:param commit:
:param cursor:
:param table:
:param args:
:param field_values:
:return:
|
snipy/database.py
|
def insert(cursor, table, *args, **field_values):
"""
db에 레코드 집어넣기
ex)
cursor.insert(table, v1, v2,...)
ex)
cursor.insert(table, id=v1, word=v2, commit=True)
:param commit:
:param cursor:
:param table:
:param args:
:param field_values:
:return:
"""
commit = field_values.pop('commit', True)
q, a = None, None
if args is not None and len(args) > 0:
q = get_insert_query(table, field_count=len(args))
a = args
elif len(field_values) > 0:
q = get_insert_query(table, fields=field_values.keys())
a = field_values.values()
else:
raise ValueError('need table, record...')
cursor.execute(q, args=a)
if commit:
cursor.connection.commit()
|
def insert(cursor, table, *args, **field_values):
"""
db에 레코드 집어넣기
ex)
cursor.insert(table, v1, v2,...)
ex)
cursor.insert(table, id=v1, word=v2, commit=True)
:param commit:
:param cursor:
:param table:
:param args:
:param field_values:
:return:
"""
commit = field_values.pop('commit', True)
q, a = None, None
if args is not None and len(args) > 0:
q = get_insert_query(table, field_count=len(args))
a = args
elif len(field_values) > 0:
q = get_insert_query(table, fields=field_values.keys())
a = field_values.values()
else:
raise ValueError('need table, record...')
cursor.execute(q, args=a)
if commit:
cursor.connection.commit()
|
[
"db에",
"레코드",
"집어넣기",
"ex",
")",
"cursor",
".",
"insert",
"(",
"table",
"v1",
"v2",
"...",
")",
"ex",
")",
"cursor",
".",
"insert",
"(",
"table",
"id",
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"v1",
"word",
"=",
"v2",
"commit",
"=",
"True",
")",
":",
"param",
"commit",
":",
":",
"param",
"cursor",
":",
":",
"param",
"table",
":",
":",
"param",
"args",
":",
":",
"param",
"field_values",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L167-L195
|
[
"def",
"insert",
"(",
"cursor",
",",
"table",
",",
"*",
"args",
",",
"*",
"*",
"field_values",
")",
":",
"commit",
"=",
"field_values",
".",
"pop",
"(",
"'commit'",
",",
"True",
")",
"q",
",",
"a",
"=",
"None",
",",
"None",
"if",
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"len",
"(",
"args",
")",
">",
"0",
":",
"q",
"=",
"get_insert_query",
"(",
"table",
",",
"field_count",
"=",
"len",
"(",
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")",
")",
"a",
"=",
"args",
"elif",
"len",
"(",
"field_values",
")",
">",
"0",
":",
"q",
"=",
"get_insert_query",
"(",
"table",
",",
"fields",
"=",
"field_values",
".",
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"(",
")",
")",
"a",
"=",
"field_values",
".",
"values",
"(",
")",
"else",
":",
"raise",
"ValueError",
"(",
"'need table, record...'",
")",
"cursor",
".",
"execute",
"(",
"q",
",",
"args",
"=",
"a",
")",
"if",
"commit",
":",
"cursor",
".",
"connection",
".",
"commit",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
update
|
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블 이름
:type table: str
:param where_kv: 업데이트 where 조건 dictionary, key:field, value:equal condition only
:type where_kv: dict
:param field_values: kwarg 업데이트용
:type field_values: dict
:param commit: 커밋 여부
:type commit: bool
:return:
|
snipy/database.py
|
def update(cursor, table, where_kv, commit=True, **field_values):
"""
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블 이름
:type table: str
:param where_kv: 업데이트 where 조건 dictionary, key:field, value:equal condition only
:type where_kv: dict
:param field_values: kwarg 업데이트용
:type field_values: dict
:param commit: 커밋 여부
:type commit: bool
:return:
"""
q = """update %s \nset {0} \nwhere {1} """ % table
fields = field_values.keys()
kv = ','.join(['{}=%s'.format(f) for f in fields])
where = ' and '.join(['{}=%s'.format(f) for f in where_kv.keys()])
q = q.format(kv, where)
args = field_values.values() + where_kv.values()
cursor.execute(q, args=args)
if commit:
cursor.connection.commit()
|
def update(cursor, table, where_kv, commit=True, **field_values):
"""
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블 이름
:type table: str
:param where_kv: 업데이트 where 조건 dictionary, key:field, value:equal condition only
:type where_kv: dict
:param field_values: kwarg 업데이트용
:type field_values: dict
:param commit: 커밋 여부
:type commit: bool
:return:
"""
q = """update %s \nset {0} \nwhere {1} """ % table
fields = field_values.keys()
kv = ','.join(['{}=%s'.format(f) for f in fields])
where = ' and '.join(['{}=%s'.format(f) for f in where_kv.keys()])
q = q.format(kv, where)
args = field_values.values() + where_kv.values()
cursor.execute(q, args=args)
if commit:
cursor.connection.commit()
|
[
"db",
"update",
"쿼리",
"빌딩",
"및",
"실행",
"단",
"commit은",
":",
"param",
"cursor",
":",
"커서",
":",
"type",
"cursor",
":",
"Cursor",
":",
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"table",
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"테이블",
"이름",
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":",
"kwarg",
"업데이트용",
":",
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"field_values",
":",
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":",
"param",
"commit",
":",
"커밋",
"여부",
":",
"type",
"commit",
":",
"bool",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L199-L227
|
[
"def",
"update",
"(",
"cursor",
",",
"table",
",",
"where_kv",
",",
"commit",
"=",
"True",
",",
"*",
"*",
"field_values",
")",
":",
"q",
"=",
"\"\"\"update %s \\nset {0} \\nwhere {1} \"\"\"",
"%",
"table",
"fields",
"=",
"field_values",
".",
"keys",
"(",
")",
"kv",
"=",
"','",
".",
"join",
"(",
"[",
"'{}=%s'",
".",
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"(",
"f",
")",
"for",
"f",
"in",
"fields",
"]",
")",
"where",
"=",
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"[",
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")",
"q",
"=",
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"(",
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",",
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"(",
")",
"+",
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".",
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"(",
")",
"cursor",
".",
"execute",
"(",
"q",
",",
"args",
"=",
"args",
")",
"if",
"commit",
":",
"cursor",
".",
"connection",
".",
"commit",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
insert_or_update
|
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블이름
:type table: str
:param commit: 커밋 여부
:type commit: bool
:param field_values: insert 또는 업데이트 할 필드 및 값 dict pairs
:type field_values:dict
:return:
|
snipy/database.py
|
def insert_or_update(cursor, table, commit=True, **field_values):
"""
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블이름
:type table: str
:param commit: 커밋 여부
:type commit: bool
:param field_values: insert 또는 업데이트 할 필드 및 값 dict pairs
:type field_values:dict
:return:
"""
q = """INSERT INTO %s ({0}) \nVALUES ({1}) \nON DUPLICATE KEY UPDATE {2} """ % table
l = len(field_values)
fields = field_values.keys()
field = ','.join(fields)
value = ','.join(['%s'] * l)
kv = ','.join(['{}=%s'.format(f) for f in fields])
q = q.format(field, value, kv)
args = field_values.values() * 2
cursor.execute(q, args=args)
if commit:
cursor.connection.commit()
|
def insert_or_update(cursor, table, commit=True, **field_values):
"""
db update 쿼리 빌딩 및 실행, 단, commit은
:param cursor: 커서
:type cursor: Cursor
:param table: 테이블이름
:type table: str
:param commit: 커밋 여부
:type commit: bool
:param field_values: insert 또는 업데이트 할 필드 및 값 dict pairs
:type field_values:dict
:return:
"""
q = """INSERT INTO %s ({0}) \nVALUES ({1}) \nON DUPLICATE KEY UPDATE {2} """ % table
l = len(field_values)
fields = field_values.keys()
field = ','.join(fields)
value = ','.join(['%s'] * l)
kv = ','.join(['{}=%s'.format(f) for f in fields])
q = q.format(field, value, kv)
args = field_values.values() * 2
cursor.execute(q, args=args)
if commit:
cursor.connection.commit()
|
[
"db",
"update",
"쿼리",
"빌딩",
"및",
"실행",
"단",
"commit은",
":",
"param",
"cursor",
":",
"커서",
":",
"type",
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":",
"Cursor",
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":",
"테이블이름",
":",
"type",
"table",
":",
"str",
":",
"param",
"commit",
":",
"커밋",
"여부",
":",
"type",
"commit",
":",
"bool",
":",
"param",
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":",
"insert",
"또는",
"업데이트",
"할",
"필드",
"및",
"값",
"dict",
"pairs",
":",
"type",
"field_values",
":",
"dict",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/database.py#L231-L258
|
[
"def",
"insert_or_update",
"(",
"cursor",
",",
"table",
",",
"commit",
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"True",
",",
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")",
":",
"q",
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"%",
"table",
"l",
"=",
"len",
"(",
"field_values",
")",
"fields",
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"field_values",
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"(",
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"(",
"[",
"'%s'",
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")",
"*",
"2",
"cursor",
".",
"execute",
"(",
"q",
",",
"args",
"=",
"args",
")",
"if",
"commit",
":",
"cursor",
".",
"connection",
".",
"commit",
"(",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
tojson
|
recursive implementation
|
snipy/jsonutil.py
|
def tojson(o):
"""
recursive implementation
"""
try:
return json.encode(o)
except json.EncodeError:
pass
try:
return o.tojson()
except AttributeError as e:
pass
t = type(o)
if isinstance(o, list):
return '[%s]' % ', '.join([tojson(e) for e in o])
elif isinstance(o, dict):
d = ['%s:%s' % (k, tojson(v)) for k, v in o.iteritems()]
return '{%s}' % ', '.join(d)
elif isinstance(o, set):
d = ['%s:%s' % (tojson(e)) for e in o]
return '{%s}' % ', '.join(d)
elif isinstance(o, np.ndarray):
return numpy_to_json(o)
else:
raise ValueError('error, failed encoding type(%s) to json' % t)
|
def tojson(o):
"""
recursive implementation
"""
try:
return json.encode(o)
except json.EncodeError:
pass
try:
return o.tojson()
except AttributeError as e:
pass
t = type(o)
if isinstance(o, list):
return '[%s]' % ', '.join([tojson(e) for e in o])
elif isinstance(o, dict):
d = ['%s:%s' % (k, tojson(v)) for k, v in o.iteritems()]
return '{%s}' % ', '.join(d)
elif isinstance(o, set):
d = ['%s:%s' % (tojson(e)) for e in o]
return '{%s}' % ', '.join(d)
elif isinstance(o, np.ndarray):
return numpy_to_json(o)
else:
raise ValueError('error, failed encoding type(%s) to json' % t)
|
[
"recursive",
"implementation"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/jsonutil.py#L15-L40
|
[
"def",
"tojson",
"(",
"o",
")",
":",
"try",
":",
"return",
"json",
".",
"encode",
"(",
"o",
")",
"except",
"json",
".",
"EncodeError",
":",
"pass",
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"(",
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"'%s:%s'",
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"e",
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"in",
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"return",
"'{%s}'",
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"', '",
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")",
"elif",
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",",
"np",
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":",
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"numpy_to_json",
"(",
"o",
")",
"else",
":",
"raise",
"ValueError",
"(",
"'error, failed encoding type(%s) to json'",
"%",
"t",
")"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
named
|
namedtuple with default values
named('typename', fields | *fields, default=x, [**defaults])
:param typename:
:param fieldnames:
:param defaults:
:return:
|
snipy/named.py
|
def named(typename, *fieldnames, **defaults):
"""
namedtuple with default values
named('typename', fields | *fields, default=x, [**defaults])
:param typename:
:param fieldnames:
:param defaults:
:return:
"""
if len(fieldnames) == 1:
if isinstance(fieldnames[0], str):
fieldnames = tuple(fieldnames[0].replace(',', ' ').split())
elif isinstance(fieldnames[0], (list, tuple)):
fieldnames = fieldnames[0]
# set default of defaults
default_of_defaults = defaults.pop('default', None)
dfields = tuple(f for f in defaults if f not in fieldnames)
T = collections.namedtuple(typename, fieldnames + dfields)
T.__new__.__defaults__ = (default_of_defaults,) * len(T._fields)
prototype = T(**defaults)
T.__new__.__defaults__ = tuple(prototype)
# make picklable
globals()[typename] = T
return T
|
def named(typename, *fieldnames, **defaults):
"""
namedtuple with default values
named('typename', fields | *fields, default=x, [**defaults])
:param typename:
:param fieldnames:
:param defaults:
:return:
"""
if len(fieldnames) == 1:
if isinstance(fieldnames[0], str):
fieldnames = tuple(fieldnames[0].replace(',', ' ').split())
elif isinstance(fieldnames[0], (list, tuple)):
fieldnames = fieldnames[0]
# set default of defaults
default_of_defaults = defaults.pop('default', None)
dfields = tuple(f for f in defaults if f not in fieldnames)
T = collections.namedtuple(typename, fieldnames + dfields)
T.__new__.__defaults__ = (default_of_defaults,) * len(T._fields)
prototype = T(**defaults)
T.__new__.__defaults__ = tuple(prototype)
# make picklable
globals()[typename] = T
return T
|
[
"namedtuple",
"with",
"default",
"values",
"named",
"(",
"typename",
"fields",
"|",
"*",
"fields",
"default",
"=",
"x",
"[",
"**",
"defaults",
"]",
")",
":",
"param",
"typename",
":",
":",
"param",
"fieldnames",
":",
":",
"param",
"defaults",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/named.py#L5-L33
|
[
"def",
"named",
"(",
"typename",
",",
"*",
"fieldnames",
",",
"*",
"*",
"defaults",
")",
":",
"if",
"len",
"(",
"fieldnames",
")",
"==",
"1",
":",
"if",
"isinstance",
"(",
"fieldnames",
"[",
"0",
"]",
",",
"str",
")",
":",
"fieldnames",
"=",
"tuple",
"(",
"fieldnames",
"[",
"0",
"]",
".",
"replace",
"(",
"','",
",",
"' '",
")",
".",
"split",
"(",
")",
")",
"elif",
"isinstance",
"(",
"fieldnames",
"[",
"0",
"]",
",",
"(",
"list",
",",
"tuple",
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")",
":",
"fieldnames",
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"fieldnames",
"[",
"0",
"]",
"# set default of defaults",
"default_of_defaults",
"=",
"defaults",
".",
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"(",
"'default'",
",",
"None",
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"dfields",
"=",
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"(",
"f",
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"if",
"f",
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"in",
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")",
"T",
"=",
"collections",
".",
"namedtuple",
"(",
"typename",
",",
"fieldnames",
"+",
"dfields",
")",
"T",
".",
"__new__",
".",
"__defaults__",
"=",
"(",
"default_of_defaults",
",",
")",
"*",
"len",
"(",
"T",
".",
"_fields",
")",
"prototype",
"=",
"T",
"(",
"*",
"*",
"defaults",
")",
"T",
".",
"__new__",
".",
"__defaults__",
"=",
"tuple",
"(",
"prototype",
")",
"# make picklable",
"globals",
"(",
")",
"[",
"typename",
"]",
"=",
"T",
"return",
"T"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
np_seed
|
numpy random seed context
:param seed:
:return:
|
snipy/irandom.py
|
def np_seed(seed):
"""
numpy random seed context
:param seed:
:return:
"""
if seed is not None:
state = np.random.get_state()
np.random.seed(seed)
yield
np.random.set_state(state)
else:
yield
|
def np_seed(seed):
"""
numpy random seed context
:param seed:
:return:
"""
if seed is not None:
state = np.random.get_state()
np.random.seed(seed)
yield
np.random.set_state(state)
else:
yield
|
[
"numpy",
"random",
"seed",
"context",
":",
"param",
"seed",
":",
":",
"return",
":"
] |
dade-ai/snipy
|
python
|
https://github.com/dade-ai/snipy/blob/408520867179f99b3158b57520e2619f3fecd69b/snipy/irandom.py#L7-L20
|
[
"def",
"np_seed",
"(",
"seed",
")",
":",
"if",
"seed",
"is",
"not",
"None",
":",
"state",
"=",
"np",
".",
"random",
".",
"get_state",
"(",
")",
"np",
".",
"random",
".",
"seed",
"(",
"seed",
")",
"yield",
"np",
".",
"random",
".",
"set_state",
"(",
"state",
")",
"else",
":",
"yield"
] |
408520867179f99b3158b57520e2619f3fecd69b
|
valid
|
Hub.connect
|
Create and connect to socket for TCP communication with hub.
|
yeelightsunflower/main.py
|
def connect(self):
"""Create and connect to socket for TCP communication with hub."""
try:
self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self._socket.settimeout(TIMEOUT_SECONDS)
self._socket.connect((self._ip, self._port))
_LOGGER.debug("Successfully created Hub at %s:%s :)", self._ip,
self._port)
except socket.error as error:
_LOGGER.error("Error creating Hub: %s :(", error)
self._socket.close()
|
def connect(self):
"""Create and connect to socket for TCP communication with hub."""
try:
self._socket = socket.socket(socket.AF_INET, socket.SOCK_STREAM)
self._socket.settimeout(TIMEOUT_SECONDS)
self._socket.connect((self._ip, self._port))
_LOGGER.debug("Successfully created Hub at %s:%s :)", self._ip,
self._port)
except socket.error as error:
_LOGGER.error("Error creating Hub: %s :(", error)
self._socket.close()
|
[
"Create",
"and",
"connect",
"to",
"socket",
"for",
"TCP",
"communication",
"with",
"hub",
"."
] |
lindsaymarkward/python-yeelight-sunflower
|
python
|
https://github.com/lindsaymarkward/python-yeelight-sunflower/blob/4ec72d005ce307f832429620ba0bcbf6b236eead/yeelightsunflower/main.py#L40-L50
|
[
"def",
"connect",
"(",
"self",
")",
":",
"try",
":",
"self",
".",
"_socket",
"=",
"socket",
".",
"socket",
"(",
"socket",
".",
"AF_INET",
",",
"socket",
".",
"SOCK_STREAM",
")",
"self",
".",
"_socket",
".",
"settimeout",
"(",
"TIMEOUT_SECONDS",
")",
"self",
".",
"_socket",
".",
"connect",
"(",
"(",
"self",
".",
"_ip",
",",
"self",
".",
"_port",
")",
")",
"_LOGGER",
".",
"debug",
"(",
"\"Successfully created Hub at %s:%s :)\"",
",",
"self",
".",
"_ip",
",",
"self",
".",
"_port",
")",
"except",
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".",
"error",
"as",
"error",
":",
"_LOGGER",
".",
"error",
"(",
"\"Error creating Hub: %s :(\"",
",",
"error",
")",
"self",
".",
"_socket",
".",
"close",
"(",
")"
] |
4ec72d005ce307f832429620ba0bcbf6b236eead
|
valid
|
Hub.send_command
|
Send TCP command to hub and return response.
|
yeelightsunflower/main.py
|
def send_command(self, command):
"""Send TCP command to hub and return response."""
# use lock to make TCP send/receive thread safe
with self._lock:
try:
self._socket.send(command.encode("utf8"))
result = self.receive()
# hub may send "status"/"new" messages that should be ignored
while result.startswith("S") or result.startswith("NEW"):
_LOGGER.debug("!Got response: %s", result)
result = self.receive()
_LOGGER.debug("Received: %s", result)
return result
except socket.error as error:
_LOGGER.error("Error sending command: %s", error)
# try re-connecting socket
self.connect()
return ""
|
def send_command(self, command):
"""Send TCP command to hub and return response."""
# use lock to make TCP send/receive thread safe
with self._lock:
try:
self._socket.send(command.encode("utf8"))
result = self.receive()
# hub may send "status"/"new" messages that should be ignored
while result.startswith("S") or result.startswith("NEW"):
_LOGGER.debug("!Got response: %s", result)
result = self.receive()
_LOGGER.debug("Received: %s", result)
return result
except socket.error as error:
_LOGGER.error("Error sending command: %s", error)
# try re-connecting socket
self.connect()
return ""
|
[
"Send",
"TCP",
"command",
"to",
"hub",
"and",
"return",
"response",
"."
] |
lindsaymarkward/python-yeelight-sunflower
|
python
|
https://github.com/lindsaymarkward/python-yeelight-sunflower/blob/4ec72d005ce307f832429620ba0bcbf6b236eead/yeelightsunflower/main.py#L58-L75
|
[
"def",
"send_command",
"(",
"self",
",",
"command",
")",
":",
"# use lock to make TCP send/receive thread safe",
"with",
"self",
".",
"_lock",
":",
"try",
":",
"self",
".",
"_socket",
".",
"send",
"(",
"command",
".",
"encode",
"(",
"\"utf8\"",
")",
")",
"result",
"=",
"self",
".",
"receive",
"(",
")",
"# hub may send \"status\"/\"new\" messages that should be ignored",
"while",
"result",
".",
"startswith",
"(",
"\"S\"",
")",
"or",
"result",
".",
"startswith",
"(",
"\"NEW\"",
")",
":",
"_LOGGER",
".",
"debug",
"(",
"\"!Got response: %s\"",
",",
"result",
")",
"result",
"=",
"self",
".",
"receive",
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")",
"_LOGGER",
".",
"debug",
"(",
"\"Received: %s\"",
",",
"result",
")",
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"result",
"except",
"socket",
".",
"error",
"as",
"error",
":",
"_LOGGER",
".",
"error",
"(",
"\"Error sending command: %s\"",
",",
"error",
")",
"# try re-connecting socket",
"self",
".",
"connect",
"(",
")",
"return",
"\"\""
] |
4ec72d005ce307f832429620ba0bcbf6b236eead
|
valid
|
Hub.receive
|
Receive TCP response, looping to get whole thing or timeout.
|
yeelightsunflower/main.py
|
def receive(self):
"""Receive TCP response, looping to get whole thing or timeout."""
try:
buffer = self._socket.recv(BUFFER_SIZE)
except socket.timeout as error:
# Something is wrong, assume it's offline temporarily
_LOGGER.error("Error receiving: %s", error)
# self._socket.close()
return ""
# Read until a newline or timeout
buffering = True
response = ''
while buffering:
if '\n' in buffer.decode("utf8"):
response = buffer.decode("utf8").split('\n')[0]
buffering = False
else:
try:
more = self._socket.recv(BUFFER_SIZE)
except socket.timeout:
more = None
if not more:
buffering = False
response = buffer.decode("utf8")
else:
buffer += more
return response
|
def receive(self):
"""Receive TCP response, looping to get whole thing or timeout."""
try:
buffer = self._socket.recv(BUFFER_SIZE)
except socket.timeout as error:
# Something is wrong, assume it's offline temporarily
_LOGGER.error("Error receiving: %s", error)
# self._socket.close()
return ""
# Read until a newline or timeout
buffering = True
response = ''
while buffering:
if '\n' in buffer.decode("utf8"):
response = buffer.decode("utf8").split('\n')[0]
buffering = False
else:
try:
more = self._socket.recv(BUFFER_SIZE)
except socket.timeout:
more = None
if not more:
buffering = False
response = buffer.decode("utf8")
else:
buffer += more
return response
|
[
"Receive",
"TCP",
"response",
"looping",
"to",
"get",
"whole",
"thing",
"or",
"timeout",
"."
] |
lindsaymarkward/python-yeelight-sunflower
|
python
|
https://github.com/lindsaymarkward/python-yeelight-sunflower/blob/4ec72d005ce307f832429620ba0bcbf6b236eead/yeelightsunflower/main.py#L77-L104
|
[
"def",
"receive",
"(",
"self",
")",
":",
"try",
":",
"buffer",
"=",
"self",
".",
"_socket",
".",
"recv",
"(",
"BUFFER_SIZE",
")",
"except",
"socket",
".",
"timeout",
"as",
"error",
":",
"# Something is wrong, assume it's offline temporarily",
"_LOGGER",
".",
"error",
"(",
"\"Error receiving: %s\"",
",",
"error",
")",
"# self._socket.close()",
"return",
"\"\"",
"# Read until a newline or timeout",
"buffering",
"=",
"True",
"response",
"=",
"''",
"while",
"buffering",
":",
"if",
"'\\n'",
"in",
"buffer",
".",
"decode",
"(",
"\"utf8\"",
")",
":",
"response",
"=",
"buffer",
".",
"decode",
"(",
"\"utf8\"",
")",
".",
"split",
"(",
"'\\n'",
")",
"[",
"0",
"]",
"buffering",
"=",
"False",
"else",
":",
"try",
":",
"more",
"=",
"self",
".",
"_socket",
".",
"recv",
"(",
"BUFFER_SIZE",
")",
"except",
"socket",
".",
"timeout",
":",
"more",
"=",
"None",
"if",
"not",
"more",
":",
"buffering",
"=",
"False",
"response",
"=",
"buffer",
".",
"decode",
"(",
"\"utf8\"",
")",
"else",
":",
"buffer",
"+=",
"more",
"return",
"response"
] |
4ec72d005ce307f832429620ba0bcbf6b236eead
|
valid
|
Hub.get_data
|
Get current light data as dictionary with light zids as keys.
|
yeelightsunflower/main.py
|
def get_data(self):
"""Get current light data as dictionary with light zids as keys."""
response = self.send_command(GET_LIGHTS_COMMAND)
_LOGGER.debug("get_data response: %s", repr(response))
if not response:
_LOGGER.debug("Empty response: %s", response)
return {}
response = response.strip()
# Check string before splitting (avoid IndexError if malformed)
if not (response.startswith("GLB") and response.endswith(";")):
_LOGGER.debug("Invalid response: %s", repr(response))
return {}
# deconstruct response string into light data. Example data:
# GLB 143E,1,1,25,255,255,255,0,0;287B,1,1,22,255,255,255,0,0;\r\n
response = response[4:-3] # strip start (GLB) and end (;\r\n)
light_strings = response.split(';')
light_data_by_id = {}
for light_string in light_strings:
values = light_string.split(',')
try:
light_data_by_id[values[0]] = [int(values[2]), int(values[4]),
int(values[5]), int(values[6]),
int(values[7])]
except ValueError as error:
_LOGGER.error("Error %s: %s (%s)", error, values, response)
except IndexError as error:
_LOGGER.error("Error %s: %s (%s)", error, values, response)
return light_data_by_id
|
def get_data(self):
"""Get current light data as dictionary with light zids as keys."""
response = self.send_command(GET_LIGHTS_COMMAND)
_LOGGER.debug("get_data response: %s", repr(response))
if not response:
_LOGGER.debug("Empty response: %s", response)
return {}
response = response.strip()
# Check string before splitting (avoid IndexError if malformed)
if not (response.startswith("GLB") and response.endswith(";")):
_LOGGER.debug("Invalid response: %s", repr(response))
return {}
# deconstruct response string into light data. Example data:
# GLB 143E,1,1,25,255,255,255,0,0;287B,1,1,22,255,255,255,0,0;\r\n
response = response[4:-3] # strip start (GLB) and end (;\r\n)
light_strings = response.split(';')
light_data_by_id = {}
for light_string in light_strings:
values = light_string.split(',')
try:
light_data_by_id[values[0]] = [int(values[2]), int(values[4]),
int(values[5]), int(values[6]),
int(values[7])]
except ValueError as error:
_LOGGER.error("Error %s: %s (%s)", error, values, response)
except IndexError as error:
_LOGGER.error("Error %s: %s (%s)", error, values, response)
return light_data_by_id
|
[
"Get",
"current",
"light",
"data",
"as",
"dictionary",
"with",
"light",
"zids",
"as",
"keys",
"."
] |
lindsaymarkward/python-yeelight-sunflower
|
python
|
https://github.com/lindsaymarkward/python-yeelight-sunflower/blob/4ec72d005ce307f832429620ba0bcbf6b236eead/yeelightsunflower/main.py#L106-L134
|
[
"def",
"get_data",
"(",
"self",
")",
":",
"response",
"=",
"self",
".",
"send_command",
"(",
"GET_LIGHTS_COMMAND",
")",
"_LOGGER",
".",
"debug",
"(",
"\"get_data response: %s\"",
",",
"repr",
"(",
"response",
")",
")",
"if",
"not",
"response",
":",
"_LOGGER",
".",
"debug",
"(",
"\"Empty response: %s\"",
",",
"response",
")",
"return",
"{",
"}",
"response",
"=",
"response",
".",
"strip",
"(",
")",
"# Check string before splitting (avoid IndexError if malformed)",
"if",
"not",
"(",
"response",
".",
"startswith",
"(",
"\"GLB\"",
")",
"and",
"response",
".",
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"\";\"",
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")",
":",
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"debug",
"(",
"\"Invalid response: %s\"",
",",
"repr",
"(",
"response",
")",
")",
"return",
"{",
"}",
"# deconstruct response string into light data. Example data:",
"# GLB 143E,1,1,25,255,255,255,0,0;287B,1,1,22,255,255,255,0,0;\\r\\n",
"response",
"=",
"response",
"[",
"4",
":",
"-",
"3",
"]",
"# strip start (GLB) and end (;\\r\\n)",
"light_strings",
"=",
"response",
".",
"split",
"(",
"';'",
")",
"light_data_by_id",
"=",
"{",
"}",
"for",
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":",
"values",
"=",
"light_string",
".",
"split",
"(",
"','",
")",
"try",
":",
"light_data_by_id",
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"values",
"[",
"0",
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")",
",",
"int",
"(",
"values",
"[",
"6",
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",",
"int",
"(",
"values",
"[",
"7",
"]",
")",
"]",
"except",
"ValueError",
"as",
"error",
":",
"_LOGGER",
".",
"error",
"(",
"\"Error %s: %s (%s)\"",
",",
"error",
",",
"values",
",",
"response",
")",
"except",
"IndexError",
"as",
"error",
":",
"_LOGGER",
".",
"error",
"(",
"\"Error %s: %s (%s)\"",
",",
"error",
",",
"values",
",",
"response",
")",
"return",
"light_data_by_id"
] |
4ec72d005ce307f832429620ba0bcbf6b236eead
|
valid
|
Hub.get_lights
|
Get current light data, set and return as list of Bulb objects.
|
yeelightsunflower/main.py
|
def get_lights(self):
"""Get current light data, set and return as list of Bulb objects."""
# Throttle updates. Use cached data if within UPDATE_INTERVAL_SECONDS
now = datetime.datetime.now()
if (now - self._last_updated) < datetime.timedelta(
seconds=UPDATE_INTERVAL_SECONDS):
# _LOGGER.debug("Using cached light data")
return self._bulbs
else:
self._last_updated = now
light_data = self.get_data()
_LOGGER.debug("got: %s", light_data)
if not light_data:
return []
if self._bulbs:
# Bulbs already created, just update values
for bulb in self._bulbs:
# use the values for the bulb with the correct ID
try:
values = light_data[bulb.zid]
bulb._online, bulb._red, bulb._green, bulb._blue, \
bulb._level = values
except KeyError:
pass
else:
for light_id in light_data:
self._bulbs.append(Bulb(self, light_id, *light_data[light_id]))
# return a list of Bulb objects
return self._bulbs
|
def get_lights(self):
"""Get current light data, set and return as list of Bulb objects."""
# Throttle updates. Use cached data if within UPDATE_INTERVAL_SECONDS
now = datetime.datetime.now()
if (now - self._last_updated) < datetime.timedelta(
seconds=UPDATE_INTERVAL_SECONDS):
# _LOGGER.debug("Using cached light data")
return self._bulbs
else:
self._last_updated = now
light_data = self.get_data()
_LOGGER.debug("got: %s", light_data)
if not light_data:
return []
if self._bulbs:
# Bulbs already created, just update values
for bulb in self._bulbs:
# use the values for the bulb with the correct ID
try:
values = light_data[bulb.zid]
bulb._online, bulb._red, bulb._green, bulb._blue, \
bulb._level = values
except KeyError:
pass
else:
for light_id in light_data:
self._bulbs.append(Bulb(self, light_id, *light_data[light_id]))
# return a list of Bulb objects
return self._bulbs
|
[
"Get",
"current",
"light",
"data",
"set",
"and",
"return",
"as",
"list",
"of",
"Bulb",
"objects",
"."
] |
lindsaymarkward/python-yeelight-sunflower
|
python
|
https://github.com/lindsaymarkward/python-yeelight-sunflower/blob/4ec72d005ce307f832429620ba0bcbf6b236eead/yeelightsunflower/main.py#L136-L166
|
[
"def",
"get_lights",
"(",
"self",
")",
":",
"# Throttle updates. Use cached data if within UPDATE_INTERVAL_SECONDS",
"now",
"=",
"datetime",
".",
"datetime",
".",
"now",
"(",
")",
"if",
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"now",
"-",
"self",
".",
"_last_updated",
")",
"<",
"datetime",
".",
"timedelta",
"(",
"seconds",
"=",
"UPDATE_INTERVAL_SECONDS",
")",
":",
"# _LOGGER.debug(\"Using cached light data\")",
"return",
"self",
".",
"_bulbs",
"else",
":",
"self",
".",
"_last_updated",
"=",
"now",
"light_data",
"=",
"self",
".",
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")",
"_LOGGER",
".",
"debug",
"(",
"\"got: %s\"",
",",
"light_data",
")",
"if",
"not",
"light_data",
":",
"return",
"[",
"]",
"if",
"self",
".",
"_bulbs",
":",
"# Bulbs already created, just update values",
"for",
"bulb",
"in",
"self",
".",
"_bulbs",
":",
"# use the values for the bulb with the correct ID",
"try",
":",
"values",
"=",
"light_data",
"[",
"bulb",
".",
"zid",
"]",
"bulb",
".",
"_online",
",",
"bulb",
".",
"_red",
",",
"bulb",
".",
"_green",
",",
"bulb",
".",
"_blue",
",",
"bulb",
".",
"_level",
"=",
"values",
"except",
"KeyError",
":",
"pass",
"else",
":",
"for",
"light_id",
"in",
"light_data",
":",
"self",
".",
"_bulbs",
".",
"append",
"(",
"Bulb",
"(",
"self",
",",
"light_id",
",",
"*",
"light_data",
"[",
"light_id",
"]",
")",
")",
"# return a list of Bulb objects",
"return",
"self",
".",
"_bulbs"
] |
4ec72d005ce307f832429620ba0bcbf6b236eead
|
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