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 | language stringclasses 1
value | url stringlengths 87 315 | code_tokens listlengths 19 28.4k | sha stringlengths 40 40 |
|---|---|---|---|---|---|---|---|---|---|---|---|
valid | Armv7Cpu.CBZ | Compare and Branch on Zero compares the value in a register with zero, and conditionally branches forward
a constant value. It does not affect the condition flags.
:param ARMv7Operand op: Specifies the register that contains the first operand.
:param ARMv7Operand dest:
Specifies the... | manticore/native/cpu/arm.py | def CBZ(cpu, op, dest):
"""
Compare and Branch on Zero compares the value in a register with zero, and conditionally branches forward
a constant value. It does not affect the condition flags.
:param ARMv7Operand op: Specifies the register that contains the first operand.
:param ... | def CBZ(cpu, op, dest):
"""
Compare and Branch on Zero compares the value in a register with zero, and conditionally branches forward
a constant value. It does not affect the condition flags.
:param ARMv7Operand op: Specifies the register that contains the first operand.
:param ... | [
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valid | Armv7Cpu.TBH | Table Branch Halfword causes a PC-relative forward branch using a table of single halfword offsets. A base
register provides a pointer to the table, and a second register supplies an index into the table. The branch
length is twice the value of the halfword returned from the table.
:param ARMv7... | manticore/native/cpu/arm.py | def TBH(cpu, dest):
"""
Table Branch Halfword causes a PC-relative forward branch using a table of single halfword offsets. A base
register provides a pointer to the table, and a second register supplies an index into the table. The branch
length is twice the value of the halfword return... | def TBH(cpu, dest):
"""
Table Branch Halfword causes a PC-relative forward branch using a table of single halfword offsets. A base
register provides a pointer to the table, and a second register supplies an index into the table. The branch
length is twice the value of the halfword return... | [
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"# register is allowed to be the PC. If it is, the tab... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | Armv7Cpu._LDM | LDM (Load Multiple) loads a non-empty subset, or possibly all, of the general-purpose registers from
sequential memory locations. It is useful for block loads, stack operations and procedure exit sequences.
:param int insn_id: should be one of ARM_INS_LDM, ARM_INS_LDMIB, ARM_INS_LDMDA, ARM_INS_LDMDB
... | manticore/native/cpu/arm.py | def _LDM(cpu, insn_id, base, regs):
"""
LDM (Load Multiple) loads a non-empty subset, or possibly all, of the general-purpose registers from
sequential memory locations. It is useful for block loads, stack operations and procedure exit sequences.
:param int insn_id: should be one of ARM... | def _LDM(cpu, insn_id, base, regs):
"""
LDM (Load Multiple) loads a non-empty subset, or possibly all, of the general-purpose registers from
sequential memory locations. It is useful for block loads, stack operations and procedure exit sequences.
:param int insn_id: should be one of ARM... | [
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valid | Armv7Cpu._STM | STM (Store Multiple) stores a non-empty subset (or possibly all) of the general-purpose registers to
sequential memory locations.
:param int insn_id: should be one of ARM_INS_STM, ARM_INS_STMIB, ARM_INS_STMDA, ARM_INS_STMDB
:param Armv7Operand base: Specifies the base register.
:param l... | manticore/native/cpu/arm.py | def _STM(cpu, insn_id, base, regs):
"""
STM (Store Multiple) stores a non-empty subset (or possibly all) of the general-purpose registers to
sequential memory locations.
:param int insn_id: should be one of ARM_INS_STM, ARM_INS_STMIB, ARM_INS_STMDA, ARM_INS_STMDB
:param Armv7Ope... | def _STM(cpu, insn_id, base, regs):
"""
STM (Store Multiple) stores a non-empty subset (or possibly all) of the general-purpose registers to
sequential memory locations.
:param int insn_id: should be one of ARM_INS_STM, ARM_INS_STMIB, ARM_INS_STMDA, ARM_INS_STMDB
:param Armv7Ope... | [
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valid | Armv7Cpu._SR | Notes on Capstone behavior:
- In ARM mode, _SR reg has `rest`, but _SR imm does not, its baked into `op`.
- In ARM mode, `lsr r1, r2` will have a `rest[0]`
- In Thumb mode, `lsr r1, r2` will have an empty `rest`
- In ARM mode, something like `lsr r1, 3` will not have `rest` and op will b... | manticore/native/cpu/arm.py | def _SR(cpu, insn_id, dest, op, *rest):
"""
Notes on Capstone behavior:
- In ARM mode, _SR reg has `rest`, but _SR imm does not, its baked into `op`.
- In ARM mode, `lsr r1, r2` will have a `rest[0]`
- In Thumb mode, `lsr r1, r2` will have an empty `rest`
- In ARM mode, s... | def _SR(cpu, insn_id, dest, op, *rest):
"""
Notes on Capstone behavior:
- In ARM mode, _SR reg has `rest`, but _SR imm does not, its baked into `op`.
- In ARM mode, `lsr r1, r2` will have a `rest[0]`
- In Thumb mode, `lsr r1, r2` will have an empty `rest`
- In ARM mode, s... | [
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"ARM_INS_LS... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | Array._fix_index | :param slice index: | manticore/core/smtlib/expression.py | def _fix_index(self, index):
"""
:param slice index:
"""
stop, start = index.stop, index.start
if start is None:
start = 0
if stop is None:
stop = len(self)
return start, stop | def _fix_index(self, index):
"""
:param slice index:
"""
stop, start = index.stop, index.start
if start is None:
start = 0
if stop is None:
stop = len(self)
return start, stop | [
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... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | _dict_diff | Produce a dict that includes all the keys in d2 that represent different values in d1, as well as values that
aren't in d1.
:param dict d1: First dict
:param dict d2: Dict to compare with
:rtype: dict | manticore/core/plugin.py | def _dict_diff(d1, d2):
"""
Produce a dict that includes all the keys in d2 that represent different values in d1, as well as values that
aren't in d1.
:param dict d1: First dict
:param dict d2: Dict to compare with
:rtype: dict
"""
d = {}
for key in set(d1).intersection(set(d2)):
... | def _dict_diff(d1, d2):
"""
Produce a dict that includes all the keys in d2 that represent different values in d1, as well as values that
aren't in d1.
:param dict d1: First dict
:param dict d2: Dict to compare with
:rtype: dict
"""
d = {}
for key in set(d1).intersection(set(d2)):
... | [
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... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | Plugin.locked_context | A context manager that provides safe parallel access to the global Manticore context.
This should be used to access the global Manticore context
when parallel analysis is activated. Code within the `with` block is executed
atomically, so access of shared variables should occur within. | manticore/core/plugin.py | def locked_context(self, key=None, value_type=list):
"""
A context manager that provides safe parallel access to the global Manticore context.
This should be used to access the global Manticore context
when parallel analysis is activated. Code within the `with` block is executed
... | def locked_context(self, key=None, value_type=list):
"""
A context manager that provides safe parallel access to the global Manticore context.
This should be used to access the global Manticore context
when parallel analysis is activated. Code within the `with` block is executed
... | [
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valid | Plugin.context | Convenient access to shared context | manticore/core/plugin.py | def context(self):
""" Convenient access to shared context """
plugin_context_name = str(type(self))
if plugin_context_name not in self.manticore.context:
self.manticore.context[plugin_context_name] = {}
return self.manticore.context[plugin_context_name] | def context(self):
""" Convenient access to shared context """
plugin_context_name = str(type(self))
if plugin_context_name not in self.manticore.context:
self.manticore.context[plugin_context_name] = {}
return self.manticore.context[plugin_context_name] | [
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] | trailofbits/manticore | python | https://github.com/trailofbits/manticore/blob/54c5a15b1119c523ae54c09972413e8b97f11629/manticore/core/plugin.py#L29-L34 | [
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valid | Detector.add_finding | Logs a finding at specified contract and assembler line.
:param state: current state
:param address: contract address of the finding
:param pc: program counter of the finding
:param at_init: true if executing the constructor
:param finding: textual description of the finding
... | manticore/ethereum/detectors.py | def add_finding(self, state, address, pc, finding, at_init, constraint=True):
"""
Logs a finding at specified contract and assembler line.
:param state: current state
:param address: contract address of the finding
:param pc: program counter of the finding
:param at_init:... | def add_finding(self, state, address, pc, finding, at_init, constraint=True):
"""
Logs a finding at specified contract and assembler line.
:param state: current state
:param address: contract address of the finding
:param pc: program counter of the finding
:param at_init:... | [
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valid | Detector.add_finding_here | Logs a finding in current contract and assembler line.
:param state: current state
:param finding: textual description of the finding
:param constraint: finding is considered reproducible only when constraint is True | manticore/ethereum/detectors.py | def add_finding_here(self, state, finding, constraint=True):
"""
Logs a finding in current contract and assembler line.
:param state: current state
:param finding: textual description of the finding
:param constraint: finding is considered reproducible only when constraint is Tru... | def add_finding_here(self, state, finding, constraint=True):
"""
Logs a finding in current contract and assembler line.
:param state: current state
:param finding: textual description of the finding
:param constraint: finding is considered reproducible only when constraint is Tru... | [
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valid | Detector._save_current_location | Save current location in the internal locations list and returns a textual id for it.
This is used to save locations that could later be promoted to a finding if other conditions hold
See _get_location()
:param state: current state
:param finding: textual description of the finding
... | manticore/ethereum/detectors.py | def _save_current_location(self, state, finding, condition=True):
"""
Save current location in the internal locations list and returns a textual id for it.
This is used to save locations that could later be promoted to a finding if other conditions hold
See _get_location()
:param... | def _save_current_location(self, state, finding, condition=True):
"""
Save current location in the internal locations list and returns a textual id for it.
This is used to save locations that could later be promoted to a finding if other conditions hold
See _get_location()
:param... | [
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... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | Detector._get_location | Get previously saved location
A location is composed of: address, pc, finding, at_init, condition | manticore/ethereum/detectors.py | def _get_location(self, state, hash_id):
"""
Get previously saved location
A location is composed of: address, pc, finding, at_init, condition
"""
return state.context.setdefault('{:s}.locations'.format(self.name), {})[hash_id] | def _get_location(self, state, hash_id):
"""
Get previously saved location
A location is composed of: address, pc, finding, at_init, condition
"""
return state.context.setdefault('{:s}.locations'.format(self.name), {})[hash_id] | [
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] | trailofbits/manticore | python | https://github.com/trailofbits/manticore/blob/54c5a15b1119c523ae54c09972413e8b97f11629/manticore/ethereum/detectors.py#L103-L108 | [
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] | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | DetectIntegerOverflow._signed_sub_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 False False False False True True True
... | manticore/ethereum/detectors.py | def _signed_sub_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 False ... | def _signed_sub_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 False ... | [
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valid | DetectIntegerOverflow._signed_add_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 True True True False False False False
... | manticore/ethereum/detectors.py | def _signed_add_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 True... | def _signed_add_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b -80000000 -3fffffff -00000001 +00000000 +00000001 +3fffffff +7fffffff
+80000000 True... | [
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valid | DetectIntegerOverflow._unsigned_sub_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True True True False True True True
bff... | manticore/ethereum/detectors.py | def _unsigned_sub_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True ... | def _unsigned_sub_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a - b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True ... | [
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] | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | DetectIntegerOverflow._unsigned_add_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True True True False True True True
bff... | manticore/ethereum/detectors.py | def _unsigned_add_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True ... | def _unsigned_add_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a + b ffffffff bfffffff 80000001 00000000 00000001 3ffffffff 7fffffff
ffffffff True ... | [
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valid | DetectIntegerOverflow._signed_mul_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +00000000080000001 +000000000bfffffff +000000000ffffffff
+00000... | manticore/ethereum/detectors.py | def _signed_mul_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +00000000080... | def _signed_mul_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +00000000080... | [
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valid | DetectIntegerOverflow._unsigned_mul_overflow | Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +00000000080000001 +000000000bfffffff +000000000ffffffff
+00000... | manticore/ethereum/detectors.py | def _unsigned_mul_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +000000000... | def _unsigned_mul_overflow(state, a, b):
"""
Sign extend the value to 512 bits and check the result can be represented
in 256. Following there is a 32 bit excerpt of this condition:
a * b +00000000000000000 +00000000000000001 +0000000003fffffff +0000000007fffffff +000000000... | [
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"Op... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | DetectRaceCondition._in_user_func | :param state: current state
:return: whether the current execution is in a user-defined function or not.
NOTE / TODO / FIXME: As this may produce false postives, this is not in the base `Detector` class.
It should be fixed at some point and moved there. See below.
The first 4 bytes of ... | manticore/ethereum/detectors.py | def _in_user_func(state):
"""
:param state: current state
:return: whether the current execution is in a user-defined function or not.
NOTE / TODO / FIXME: As this may produce false postives, this is not in the base `Detector` class.
It should be fixed at some point and moved th... | def _in_user_func(state):
"""
:param state: current state
:return: whether the current execution is in a user-defined function or not.
NOTE / TODO / FIXME: As this may produce false postives, this is not in the base `Detector` class.
It should be fixed at some point and moved th... | [
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] | trailofbits/manticore | python | https://github.com/trailofbits/manticore/blob/54c5a15b1119c523ae54c09972413e8b97f11629/manticore/ethereum/detectors.py#L675-L712 | [
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valid | CapstoneDisasm.disassemble_instruction | Get next instruction using the Capstone disassembler
:param str code: binary blob to be disassembled
:param long pc: program counter | manticore/native/cpu/disasm.py | def disassemble_instruction(self, code, pc):
"""Get next instruction using the Capstone disassembler
:param str code: binary blob to be disassembled
:param long pc: program counter
"""
return next(self.disasm.disasm(code, pc)) | def disassemble_instruction(self, code, pc):
"""Get next instruction using the Capstone disassembler
:param str code: binary blob to be disassembled
:param long pc: program counter
"""
return next(self.disasm.disasm(code, pc)) | [
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] | trailofbits/manticore | python | https://github.com/trailofbits/manticore/blob/54c5a15b1119c523ae54c09972413e8b97f11629/manticore/native/cpu/disasm.py#L71-L77 | [
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valid | istainted | Helper to determine whether an object if tainted.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value. | manticore/utils/helpers.py | def istainted(arg, taint=None):
"""
Helper to determine whether an object if tainted.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
if not issymbolic(arg):
return Fa... | def istainted(arg, taint=None):
"""
Helper to determine whether an object if tainted.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
if not issymbolic(arg):
return Fa... | [
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valid | get_taints | Helper to list an object taints.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value. | manticore/utils/helpers.py | def get_taints(arg, taint=None):
"""
Helper to list an object taints.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
if not issymbolic(arg):
return
for arg_taint ... | def get_taints(arg, taint=None):
"""
Helper to list an object taints.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
if not issymbolic(arg):
return
for arg_taint ... | [
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valid | taint_with | Helper to taint a value.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value. | manticore/utils/helpers.py | def taint_with(arg, taint, value_bits=256, index_bits=256):
"""
Helper to taint a value.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
from ..core.smtlib import BitVecConstan... | def taint_with(arg, taint, value_bits=256, index_bits=256):
"""
Helper to taint a value.
:param arg: a value or Expression
:param taint: a regular expression matching a taint value (eg. 'IMPORTANT.*'). If None, this function checks for any taint value.
"""
from ..core.smtlib import BitVecConstan... | [
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valid | interval_intersection | Given two intervals, (min1, max1) and (min2, max2) return their intersecting interval,
or None if they do not overlap. | manticore/utils/helpers.py | def interval_intersection(min1, max1, min2, max2):
"""
Given two intervals, (min1, max1) and (min2, max2) return their intersecting interval,
or None if they do not overlap.
"""
left, right = max(min1, min2), min(max1, max2)
if left < right:
return left, right
return None | def interval_intersection(min1, max1, min2, max2):
"""
Given two intervals, (min1, max1) and (min2, max2) return their intersecting interval,
or None if they do not overlap.
"""
left, right = max(min1, min2), min(max1, max2)
if left < right:
return left, right
return None | [
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valid | ConstraintSet.add | Add a constraint to the set
:param constraint: The constraint to add to the set.
:param check: Currently unused.
:return: | manticore/core/smtlib/constraints.py | def add(self, constraint, check=False):
"""
Add a constraint to the set
:param constraint: The constraint to add to the set.
:param check: Currently unused.
:return:
"""
if isinstance(constraint, bool):
constraint = BoolConstant(constraint)
as... | def add(self, constraint, check=False):
"""
Add a constraint to the set
:param constraint: The constraint to add to the set.
:param check: Currently unused.
:return:
"""
if isinstance(constraint, bool):
constraint = BoolConstant(constraint)
as... | [
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valid | ConstraintSet._declare | Declare the variable `var` | manticore/core/smtlib/constraints.py | def _declare(self, var):
""" Declare the variable `var` """
if var.name in self._declarations:
raise ValueError('Variable already declared')
self._declarations[var.name] = var
return var | def _declare(self, var):
""" Declare the variable `var` """
if var.name in self._declarations:
raise ValueError('Variable already declared')
self._declarations[var.name] = var
return var | [
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valid | ConstraintSet.declarations | Returns the variable expressions of this constraint set | manticore/core/smtlib/constraints.py | def declarations(self):
""" Returns the variable expressions of this constraint set """
declarations = GetDeclarations()
for a in self.constraints:
try:
declarations.visit(a)
except RuntimeError:
# TODO: (defunct) move recursion management ... | def declarations(self):
""" Returns the variable expressions of this constraint set """
declarations = GetDeclarations()
for a in self.constraints:
try:
declarations.visit(a)
except RuntimeError:
# TODO: (defunct) move recursion management ... | [
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valid | ConstraintSet.constraints | :rtype tuple
:return: All constraints represented by this and parent sets. | manticore/core/smtlib/constraints.py | def constraints(self):
"""
:rtype tuple
:return: All constraints represented by this and parent sets.
"""
if self._parent is not None:
return tuple(self._constraints) + self._parent.constraints
return tuple(self._constraints) | def constraints(self):
"""
:rtype tuple
:return: All constraints represented by this and parent sets.
"""
if self._parent is not None:
return tuple(self._constraints) + self._parent.constraints
return tuple(self._constraints) | [
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valid | ConstraintSet.is_declared | True if expression_var is declared in this constraint set | manticore/core/smtlib/constraints.py | def is_declared(self, expression_var):
""" True if expression_var is declared in this constraint set """
if not isinstance(expression_var, Variable):
raise ValueError(f'Expression must be a Variable (not a {type(expression_var)})')
return any(expression_var is x for x in self.get_dec... | def is_declared(self, expression_var):
""" True if expression_var is declared in this constraint set """
if not isinstance(expression_var, Variable):
raise ValueError(f'Expression must be a Variable (not a {type(expression_var)})')
return any(expression_var is x for x in self.get_dec... | [
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valid | ConstraintSet.migrate | Migrate an expression created for a different constraint set to self.
Returns an expression that can be used with this constraintSet
All the foreign variables used in the expression are replaced by
variables of this constraint set. If the variable was replaced before
the... | manticore/core/smtlib/constraints.py | def migrate(self, expression, name_migration_map=None):
""" Migrate an expression created for a different constraint set to self.
Returns an expression that can be used with this constraintSet
All the foreign variables used in the expression are replaced by
variables of this... | def migrate(self, expression, name_migration_map=None):
""" Migrate an expression created for a different constraint set to self.
Returns an expression that can be used with this constraintSet
All the foreign variables used in the expression are replaced by
variables of this... | [
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valid | ConstraintSet.new_bool | Declares a free symbolic boolean in the constraint store
:param name: try to assign name to internal variable representation,
if not unique, a numeric nonce will be appended
:param avoid_collisions: potentially avoid_collisions the variable to avoid name collisions if Tr... | manticore/core/smtlib/constraints.py | def new_bool(self, name=None, taint=frozenset(), avoid_collisions=False):
""" Declares a free symbolic boolean in the constraint store
:param name: try to assign name to internal variable representation,
if not unique, a numeric nonce will be appended
:param avoi... | def new_bool(self, name=None, taint=frozenset(), avoid_collisions=False):
""" Declares a free symbolic boolean in the constraint store
:param name: try to assign name to internal variable representation,
if not unique, a numeric nonce will be appended
:param avoi... | [
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"avoid_coll... | 54c5a15b1119c523ae54c09972413e8b97f11629 |
valid | ConstraintSet.new_bitvec | Declares a free symbolic bitvector in the constraint store
:param size: size in bits for the bitvector
:param name: try to assign name to internal variable representation,
if not unique, a numeric nonce will be appended
:param avoid_collisions: potentially av... | manticore/core/smtlib/constraints.py | def new_bitvec(self, size, name=None, taint=frozenset(), avoid_collisions=False):
""" Declares a free symbolic bitvector in the constraint store
:param size: size in bits for the bitvector
:param name: try to assign name to internal variable representation,
if no... | def new_bitvec(self, size, name=None, taint=frozenset(), avoid_collisions=False):
""" Declares a free symbolic bitvector in the constraint store
:param size: size in bits for the bitvector
:param name: try to assign name to internal variable representation,
if no... | [
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valid | ConstraintSet.new_array | Declares a free symbolic array of value_bits long bitvectors in the constraint store.
:param index_bits: size in bits for the array indexes one of [32, 64]
:param value_bits: size in bits for the array values
:param name: try to assign name to internal variable representation,
... | manticore/core/smtlib/constraints.py | def new_array(self, index_bits=32, name=None, index_max=None, value_bits=8, taint=frozenset(), avoid_collisions=False, default=None):
""" Declares a free symbolic array of value_bits long bitvectors in the constraint store.
:param index_bits: size in bits for the array indexes one of [32, 64]
... | def new_array(self, index_bits=32, name=None, index_max=None, value_bits=8, taint=frozenset(), avoid_collisions=False, default=None):
""" Declares a free symbolic array of value_bits long bitvectors in the constraint store.
:param index_bits: size in bits for the array indexes one of [32, 64]
... | [
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valid | train_encoder | Defines folds and performs the data preprocessing (categorical encoding, NaN imputation, normalization)
Returns a list with {X_train, y_train, X_test, y_test}, average fit_encoder_time and average score_encoder_time
Note: We normalize all features (not only numerical features) because otherwise SVM would
... | examples/benchmarking_large/util.py | def train_encoder(X, y, fold_count, encoder):
"""
Defines folds and performs the data preprocessing (categorical encoding, NaN imputation, normalization)
Returns a list with {X_train, y_train, X_test, y_test}, average fit_encoder_time and average score_encoder_time
Note: We normalize all features (not ... | def train_encoder(X, y, fold_count, encoder):
"""
Defines folds and performs the data preprocessing (categorical encoding, NaN imputation, normalization)
Returns a list with {X_train, y_train, X_test, y_test}, average fit_encoder_time and average score_encoder_time
Note: We normalize all features (not ... | [
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valid | train_model | Evaluation with:
Matthews correlation coefficient: represents thresholding measures
AUC: represents ranking measures
Brier score: represents calibration measures | examples/benchmarking_large/util.py | def train_model(folds, model):
"""
Evaluation with:
Matthews correlation coefficient: represents thresholding measures
AUC: represents ranking measures
Brier score: represents calibration measures
"""
scores = []
fit_model_time = 0 # Sum of all the time spend on fitting the tr... | def train_model(folds, model):
"""
Evaluation with:
Matthews correlation coefficient: represents thresholding measures
AUC: represents ranking measures
Brier score: represents calibration measures
"""
scores = []
fit_model_time = 0 # Sum of all the time spend on fitting the tr... | [
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valid | BinaryEncoder.fit | Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, shape = [n_samples]
Target va... | category_encoders/binary.py | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | [
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valid | SumEncoder.fit | Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, shape = [n_samples]
Target va... | category_encoders/sum_coding.py | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | [
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valid | OrdinalEncoder.inverse_transform | Perform the inverse transformation to encoded data. Will attempt best case reconstruction, which means
it will return nan for handle_missing and handle_unknown settings that break the bijection. We issue
warnings when some of those cases occur.
Parameters
----------
X_in : array... | category_encoders/ordinal.py | def inverse_transform(self, X_in):
"""
Perform the inverse transformation to encoded data. Will attempt best case reconstruction, which means
it will return nan for handle_missing and handle_unknown settings that break the bijection. We issue
warnings when some of those cases occur.
... | def inverse_transform(self, X_in):
"""
Perform the inverse transformation to encoded data. Will attempt best case reconstruction, which means
it will return nan for handle_missing and handle_unknown settings that break the bijection. We issue
warnings when some of those cases occur.
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valid | OrdinalEncoder.ordinal_encoding | Ordinal encoding uses a single column of integers to represent the classes. An optional mapping dict can be passed
in, in this case we use the knowledge that there is some true order to the classes themselves. Otherwise, the classes
are assumed to have no true order and integers are selected at random. | category_encoders/ordinal.py | def ordinal_encoding(X_in, mapping=None, cols=None, handle_unknown='value', handle_missing='value'):
"""
Ordinal encoding uses a single column of integers to represent the classes. An optional mapping dict can be passed
in, in this case we use the knowledge that there is some true order to the c... | def ordinal_encoding(X_in, mapping=None, cols=None, handle_unknown='value', handle_missing='value'):
"""
Ordinal encoding uses a single column of integers to represent the classes. An optional mapping dict can be passed
in, in this case we use the knowledge that there is some true order to the c... | [
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valid | OneHotEncoder.transform | Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
Transformed values with encoding applied. | category_encoders/one_hot.py | def transform(self, X, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
Transformed... | def transform(self, X, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
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valid | OneHotEncoder.reverse_dummies | Convert dummy variable into numerical variables
Parameters
----------
X : DataFrame
mapping: list-like
Contains mappings of column to be transformed to it's new columns and value represented
Returns
-------
numerical: DataFrame | category_encoders/one_hot.py | def reverse_dummies(self, X, mapping):
"""
Convert dummy variable into numerical variables
Parameters
----------
X : DataFrame
mapping: list-like
Contains mappings of column to be transformed to it's new columns and value represented
Returns
... | def reverse_dummies(self, X, mapping):
"""
Convert dummy variable into numerical variables
Parameters
----------
X : DataFrame
mapping: list-like
Contains mappings of column to be transformed to it's new columns and value represented
Returns
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valid | get_cars_data | Load the cars dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return: | examples/source_data/loaders.py | def get_cars_data():
"""
Load the cars dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return:
"""
df = pd.read_csv('source_data/cars/car.data.txt')
X = df.reindex(columns=[x for x in df.columns.values if x != 'class'])
y = df.reindex(columns=['... | def get_cars_data():
"""
Load the cars dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return:
"""
df = pd.read_csv('source_data/cars/car.data.txt')
X = df.reindex(columns=[x for x in df.columns.values if x != 'class'])
y = df.reindex(columns=['... | [
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valid | get_splice_data | Load the mushroom dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return: | examples/source_data/loaders.py | def get_splice_data():
"""
Load the mushroom dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return:
"""
df = pd.read_csv('source_data/splice/splice.csv')
X = df.reindex(columns=[x for x in df.columns.values if x != 'class'])
X['dna'] = X['dna']... | def get_splice_data():
"""
Load the mushroom dataset, split it into X and y, and then call the label encoder to get an integer y column.
:return:
"""
df = pd.read_csv('source_data/splice/splice.csv')
X = df.reindex(columns=[x for x in df.columns.values if x != 'class'])
X['dna'] = X['dna']... | [
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valid | BaseNEncoder.basen_to_integer | Convert basen code as integers.
Parameters
----------
X : DataFrame
encoded data
cols : list-like
Column names in the DataFrame that be encoded
base : int
The base of transform
Returns
-------
numerical: DataFrame | category_encoders/basen.py | def basen_to_integer(self, X, cols, base):
"""
Convert basen code as integers.
Parameters
----------
X : DataFrame
encoded data
cols : list-like
Column names in the DataFrame that be encoded
base : int
The base of transform
... | def basen_to_integer(self, X, cols, base):
"""
Convert basen code as integers.
Parameters
----------
X : DataFrame
encoded data
cols : list-like
Column names in the DataFrame that be encoded
base : int
The base of transform
... | [
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valid | BaseNEncoder.col_transform | The lambda body to transform the column values | category_encoders/basen.py | def col_transform(self, col, digits):
"""
The lambda body to transform the column values
"""
if col is None or float(col) < 0.0:
return None
else:
col = self.number_to_base(int(col), self.base, digits)
if len(col) == digits:
re... | def col_transform(self, col, digits):
"""
The lambda body to transform the column values
"""
if col is None or float(col) < 0.0:
return None
else:
col = self.number_to_base(int(col), self.base, digits)
if len(col) == digits:
re... | [
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] | scikit-learn-contrib/categorical-encoding | python | https://github.com/scikit-learn-contrib/categorical-encoding/blob/5e9e803c9131b377af305d5302723ba2415001da/category_encoders/basen.py#L372-L384 | [
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... | 5e9e803c9131b377af305d5302723ba2415001da |
valid | HashingEncoder.fit | Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, shape = [n_samples]
Target va... | category_encoders/hashing.py | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | def fit(self, X, y=None, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-... | [
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valid | HashingEncoder.transform | Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
Transformed values with encoding applied. | category_encoders/hashing.py | def transform(self, X, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
Transformed... | def transform(self, X, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Returns
-------
p : array, shape = [n_samples, n_numeric + N]
Transformed... | [
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valid | HashingEncoder.hashing_trick | A basic hashing implementation with configurable dimensionality/precision
Performs the hashing trick on a pandas dataframe, `X`, using the hashing method from hashlib
identified by `hashing_method`. The number of output dimensions (`N`), and columns to hash (`cols`) are
also configurable.
... | category_encoders/hashing.py | def hashing_trick(X_in, hashing_method='md5', N=2, cols=None, make_copy=False):
"""A basic hashing implementation with configurable dimensionality/precision
Performs the hashing trick on a pandas dataframe, `X`, using the hashing method from hashlib
identified by `hashing_method`. The number o... | def hashing_trick(X_in, hashing_method='md5', N=2, cols=None, make_copy=False):
"""A basic hashing implementation with configurable dimensionality/precision
Performs the hashing trick on a pandas dataframe, `X`, using the hashing method from hashlib
identified by `hashing_method`. The number o... | [
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valid | CatBoostEncoder.transform | Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
y : array-like, shape = [n_samples] when transform by leave one out
None, when transform without target information (such as transform test set)
... | category_encoders/cat_boost.py | def transform(self, X, y=None, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
y : array-like, shape = [n_samples] when transform by leave one out
None, when tran... | def transform(self, X, y=None, override_return_df=False):
"""Perform the transformation to new categorical data.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
y : array-like, shape = [n_samples] when transform by leave one out
None, when tran... | [
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valid | CatBoostEncoder.transform_leave_one_out | Leave one out encoding uses a single column of floats to represent the means of the target variables. | category_encoders/cat_boost.py | def transform_leave_one_out(self, X_in, y, mapping=None):
"""
Leave one out encoding uses a single column of floats to represent the means of the target variables.
"""
X = X_in.copy(deep=True)
random_state_ = check_random_state(self.random_state)
# Prepare the data
... | def transform_leave_one_out(self, X_in, y, mapping=None):
"""
Leave one out encoding uses a single column of floats to represent the means of the target variables.
"""
X = X_in.copy(deep=True)
random_state_ = check_random_state(self.random_state)
# Prepare the data
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valid | get_obj_cols | Returns names of 'object' columns in the DataFrame. | category_encoders/utils.py | def get_obj_cols(df):
"""
Returns names of 'object' columns in the DataFrame.
"""
obj_cols = []
for idx, dt in enumerate(df.dtypes):
if dt == 'object' or is_category(dt):
obj_cols.append(df.columns.values[idx])
return obj_cols | def get_obj_cols(df):
"""
Returns names of 'object' columns in the DataFrame.
"""
obj_cols = []
for idx, dt in enumerate(df.dtypes):
if dt == 'object' or is_category(dt):
obj_cols.append(df.columns.values[idx])
return obj_cols | [
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valid | convert_input | Unite data into a DataFrame. | category_encoders/utils.py | def convert_input(X):
"""
Unite data into a DataFrame.
"""
if not isinstance(X, pd.DataFrame):
if isinstance(X, list):
X = pd.DataFrame(X)
elif isinstance(X, (np.generic, np.ndarray)):
X = pd.DataFrame(X)
elif isinstance(X, csr_matrix):
X = pd.... | def convert_input(X):
"""
Unite data into a DataFrame.
"""
if not isinstance(X, pd.DataFrame):
if isinstance(X, list):
X = pd.DataFrame(X)
elif isinstance(X, (np.generic, np.ndarray)):
X = pd.DataFrame(X)
elif isinstance(X, csr_matrix):
X = pd.... | [
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valid | convert_input_vector | Unite target data type into a Series.
If the target is a Series or a DataFrame, we preserve its index.
But if the target does not contain index attribute, we use the index from the argument. | category_encoders/utils.py | def convert_input_vector(y, index):
"""
Unite target data type into a Series.
If the target is a Series or a DataFrame, we preserve its index.
But if the target does not contain index attribute, we use the index from the argument.
"""
if y is None:
return None
if isinstance(y, pd.Ser... | def convert_input_vector(y, index):
"""
Unite target data type into a Series.
If the target is a Series or a DataFrame, we preserve its index.
But if the target does not contain index attribute, we use the index from the argument.
"""
if y is None:
return None
if isinstance(y, pd.Ser... | [
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valid | get_generated_cols | Returns a list of the generated/transformed columns.
Arguments:
X_original: df
the original (input) DataFrame.
X_transformed: df
the transformed (current) DataFrame.
to_transform: [str]
a list of columns that were transformed (as in the original DataFrame... | category_encoders/utils.py | def get_generated_cols(X_original, X_transformed, to_transform):
"""
Returns a list of the generated/transformed columns.
Arguments:
X_original: df
the original (input) DataFrame.
X_transformed: df
the transformed (current) DataFrame.
to_transform: [str]
... | def get_generated_cols(X_original, X_transformed, to_transform):
"""
Returns a list of the generated/transformed columns.
Arguments:
X_original: df
the original (input) DataFrame.
X_transformed: df
the transformed (current) DataFrame.
to_transform: [str]
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valid | TargetEncoder.fit | Fit encoder according to X and y.
Parameters
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X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, shape = [n_samples]
Target val... | category_encoders/target_encoder.py | def fit(self, X, y, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
and n_features is the number of features.
y : array-like, ... | def fit(self, X, y, **kwargs):
"""Fit encoder according to X and y.
Parameters
----------
X : array-like, shape = [n_samples, n_features]
Training vectors, where n_samples is the number of samples
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y : array-like, ... | [
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valid | LeaveOneOutEncoder.transform_leave_one_out | Leave one out encoding uses a single column of floats to represent the means of the target variables. | category_encoders/leave_one_out.py | def transform_leave_one_out(self, X_in, y, mapping=None):
"""
Leave one out encoding uses a single column of floats to represent the means of the target variables.
"""
X = X_in.copy(deep=True)
random_state_ = check_random_state(self.random_state)
for col, colmap in mapp... | def transform_leave_one_out(self, X_in, y, mapping=None):
"""
Leave one out encoding uses a single column of floats to represent the means of the target variables.
"""
X = X_in.copy(deep=True)
random_state_ = check_random_state(self.random_state)
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valid | score_models | Takes in a classifier that supports multiclass classification, and X and a y, and returns a cross validation score. | examples/encoding_examples.py | def score_models(clf, X, y, encoder, runs=1):
"""
Takes in a classifier that supports multiclass classification, and X and a y, and returns a cross validation score.
"""
scores = []
X_test = None
for _ in range(runs):
X_test = encoder().fit_transform(X, y)
# Some models, like... | def score_models(clf, X, y, encoder, runs=1):
"""
Takes in a classifier that supports multiclass classification, and X and a y, and returns a cross validation score.
"""
scores = []
X_test = None
for _ in range(runs):
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valid | main | Here we iterate through the datasets and score them with a classifier using different encodings. | examples/encoding_examples.py | def main(loader, name):
"""
Here we iterate through the datasets and score them with a classifier using different encodings.
"""
scores = []
raw_scores_ds = {}
# first get the dataset
X, y, mapping = loader()
clf = linear_model.LogisticRegression(solver='lbfgs', multi_class='auto', m... | def main(loader, name):
"""
Here we iterate through the datasets and score them with a classifier using different encodings.
"""
scores = []
raw_scores_ds = {}
# first get the dataset
X, y, mapping = loader()
clf = linear_model.LogisticRegression(solver='lbfgs', multi_class='auto', m... | [
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valid | secho | A wrapper around click.secho that disables any coloring being used
if colors have been disabled. | tower_cli/utils/__init__.py | def secho(message, **kwargs):
"""A wrapper around click.secho that disables any coloring being used
if colors have been disabled.
"""
# If colors are disabled, remove any color or other style data
# from keyword arguments.
if not settings.color:
for key in ('fg', 'bg', 'bold', 'blink'):
... | def secho(message, **kwargs):
"""A wrapper around click.secho that disables any coloring being used
if colors have been disabled.
"""
# If colors are disabled, remove any color or other style data
# from keyword arguments.
if not settings.color:
for key in ('fg', 'bg', 'bold', 'blink'):
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valid | Resource.associate_notification_template | Associate a notification template from this job template.
=====API DOCS=====
Associate a notification template from this job template.
:param job_template: The job template to associate to.
:type job_template: str
:param notification_template: The notification template to be as... | tower_cli/resources/job_template.py | def associate_notification_template(self, job_template,
notification_template, status):
"""Associate a notification template from this job template.
=====API DOCS=====
Associate a notification template from this job template.
:param job_template:... | def associate_notification_template(self, job_template,
notification_template, status):
"""Associate a notification template from this job template.
=====API DOCS=====
Associate a notification template from this job template.
:param job_template:... | [
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valid | Resource.disassociate_notification_template | Disassociate a notification template from this job template.
=====API DOCS=====
Disassociate a notification template from this job template.
:param job_template: The job template to disassociate from.
:type job_template: str
:param notification_template: The notification templa... | tower_cli/resources/job_template.py | def disassociate_notification_template(self, job_template,
notification_template, status):
"""Disassociate a notification template from this job template.
=====API DOCS=====
Disassociate a notification template from this job template.
:param j... | def disassociate_notification_template(self, job_template,
notification_template, status):
"""Disassociate a notification template from this job template.
=====API DOCS=====
Disassociate a notification template from this job template.
:param j... | [
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valid | Resource.callback | Contact Tower and request a configuration update using this job template.
=====API DOCS=====
Contact Tower and request a provisioning callback using this job template.
:param pk: Primary key of the job template to run provisioning callback against.
:type pk: int
:param host_con... | tower_cli/resources/job_template.py | def callback(self, pk=None, host_config_key='', extra_vars=None):
"""Contact Tower and request a configuration update using this job template.
=====API DOCS=====
Contact Tower and request a provisioning callback using this job template.
:param pk: Primary key of the job template to run... | def callback(self, pk=None, host_config_key='', extra_vars=None):
"""Contact Tower and request a configuration update using this job template.
=====API DOCS=====
Contact Tower and request a provisioning callback using this job template.
:param pk: Primary key of the job template to run... | [
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valid | jt_aggregate | Decorator to aggregate unified_jt-related fields.
Args:
func: The CURD method to be decorated.
is_create: Boolean flag showing whether this method is create.
has_pk: Boolean flag showing whether this method uses pk as argument.
Returns:
A function with necessary click-related a... | tower_cli/resources/schedule.py | def jt_aggregate(func, is_create=False, has_pk=False):
"""Decorator to aggregate unified_jt-related fields.
Args:
func: The CURD method to be decorated.
is_create: Boolean flag showing whether this method is create.
has_pk: Boolean flag showing whether this method uses pk as argument.
... | def jt_aggregate(func, is_create=False, has_pk=False):
"""Decorator to aggregate unified_jt-related fields.
Args:
func: The CURD method to be decorated.
is_create: Boolean flag showing whether this method is create.
has_pk: Boolean flag showing whether this method uses pk as argument.
... | [
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valid | Resource.lookup_stdout | Internal method that lies to our `monitor` method by returning
a scorecard for the workflow job where the standard out
would have been expected. | tower_cli/resources/workflow_job.py | def lookup_stdout(self, pk=None, start_line=None, end_line=None,
full=True):
"""
Internal method that lies to our `monitor` method by returning
a scorecard for the workflow job where the standard out
would have been expected.
"""
uj_res = get_resourc... | def lookup_stdout(self, pk=None, start_line=None, end_line=None,
full=True):
"""
Internal method that lies to our `monitor` method by returning
a scorecard for the workflow job where the standard out
would have been expected.
"""
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valid | Resource.launch | Launch a new workflow job based on a workflow job template.
Creates a new workflow job in Ansible Tower, starts it, and
returns back an ID in order for its status to be monitored.
=====API DOCS=====
Launch a new workflow job based on a workflow job template.
:param workflow_jo... | tower_cli/resources/workflow_job.py | def launch(self, workflow_job_template=None, monitor=False, wait=False,
timeout=None, extra_vars=None, **kwargs):
"""Launch a new workflow job based on a workflow job template.
Creates a new workflow job in Ansible Tower, starts it, and
returns back an ID in order for its status ... | def launch(self, workflow_job_template=None, monitor=False, wait=False,
timeout=None, extra_vars=None, **kwargs):
"""Launch a new workflow job based on a workflow job template.
Creates a new workflow job in Ansible Tower, starts it, and
returns back an ID in order for its status ... | [
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valid | ActionSubcommand.parse_args | Parse arguments sent to this command.
The code for this method is taken from MultiCommand:
https://github.com/mitsuhiko/click/blob/master/click/core.py
It is Copyright (c) 2014 by Armin Ronacher.
See the license:
https://github.com/mitsuhiko/click/blob/master/LICENSE | tower_cli/cli/action.py | def parse_args(self, ctx, args):
"""Parse arguments sent to this command.
The code for this method is taken from MultiCommand:
https://github.com/mitsuhiko/click/blob/master/click/core.py
It is Copyright (c) 2014 by Armin Ronacher.
See the license:
https://github.com/mi... | def parse_args(self, ctx, args):
"""Parse arguments sent to this command.
The code for this method is taken from MultiCommand:
https://github.com/mitsuhiko/click/blob/master/click/core.py
It is Copyright (c) 2014 by Armin Ronacher.
See the license:
https://github.com/mi... | [
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] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/cli/action.py#L33-L46 | [
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valid | ActionSubcommand.format_options | Monkey-patch click's format_options method to support option categorization. | tower_cli/cli/action.py | def format_options(self, ctx, formatter):
"""Monkey-patch click's format_options method to support option categorization.
"""
field_opts = []
global_opts = []
local_opts = []
other_opts = []
for param in self.params:
if param.name in SETTINGS_PARMS:
... | def format_options(self, ctx, formatter):
"""Monkey-patch click's format_options method to support option categorization.
"""
field_opts = []
global_opts = []
local_opts = []
other_opts = []
for param in self.params:
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valid | Resource.list | Return a list of objects.
=====API DOCS=====
Retrieve a list of Tower settings.
:param category: The category slug in which to look up indevidual settings.
:type category: str
:param `**kwargs`: Keyword arguments list of available fields used for searching resource objects.
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"""Return a list of objects.
=====API DOCS=====
Retrieve a list of Tower settings.
:param category: The category slug in which to look up indevidual settings.
:type category: str
:param `**kwargs`: Keyword arguments list of available fields use... | def list(self, **kwargs):
"""Return a list of objects.
=====API DOCS=====
Retrieve a list of Tower settings.
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:type category: str
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valid | Resource.get | Return one and exactly one object
=====API DOCS=====
Return one and exactly one Tower setting.
:param pk: Primary key of the Tower setting to retrieve
:type pk: int
:returns: loaded JSON of the retrieved Tower setting object.
:rtype: dict
:raises tower_cli.excep... | tower_cli/resources/setting.py | def get(self, pk):
"""Return one and exactly one object
=====API DOCS=====
Return one and exactly one Tower setting.
:param pk: Primary key of the Tower setting to retrieve
:type pk: int
:returns: loaded JSON of the retrieved Tower setting object.
:rtype: dict
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"""Return one and exactly one object
=====API DOCS=====
Return one and exactly one Tower setting.
:param pk: Primary key of the Tower setting to retrieve
:type pk: int
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:rtype: dict
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valid | Resource.modify | Modify an already existing object.
Positional argument SETTING is the setting name and VALUE is its value,
which can be provided directly or obtained from a file name if prefixed with '@'.
=====API DOCS=====
Modify an already existing Tower setting.
:param setting: The name of... | tower_cli/resources/setting.py | def modify(self, setting, value):
"""Modify an already existing object.
Positional argument SETTING is the setting name and VALUE is its value,
which can be provided directly or obtained from a file name if prefixed with '@'.
=====API DOCS=====
Modify an already existing Tower ... | def modify(self, setting, value):
"""Modify an already existing object.
Positional argument SETTING is the setting name and VALUE is its value,
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=====API DOCS=====
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valid | BaseResource._pop_none | Remove default values (anything where the value is None). click is unfortunately bad at the way it
sends through unspecified defaults. | tower_cli/models/base.py | def _pop_none(self, kwargs):
"""Remove default values (anything where the value is None). click is unfortunately bad at the way it
sends through unspecified defaults."""
for key, value in copy(kwargs).items():
# options with multiple=True return a tuple
if value is None o... | def _pop_none(self, kwargs):
"""Remove default values (anything where the value is None). click is unfortunately bad at the way it
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# options with multiple=True return a tuple
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valid | BaseResource._lookup | =====API DOCS=====
Attempt to perform a lookup that is expected to return a single result, and return the record.
This method is a wrapper around `get` that strips out non-unique keys, and is used internally by
`write` and `delete`.
:param fail_on_missing: Flag that raise exception if ... | tower_cli/models/base.py | def _lookup(self, fail_on_missing=False, fail_on_found=False, include_debug_header=True, **kwargs):
"""
=====API DOCS=====
Attempt to perform a lookup that is expected to return a single result, and return the record.
This method is a wrapper around `get` that strips out non-unique keys... | def _lookup(self, fail_on_missing=False, fail_on_found=False, include_debug_header=True, **kwargs):
"""
=====API DOCS=====
Attempt to perform a lookup that is expected to return a single result, and return the record.
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valid | BaseResource._convert_pagenum | Convert next and previous from URLs to integers | tower_cli/models/base.py | def _convert_pagenum(self, kwargs):
"""
Convert next and previous from URLs to integers
"""
for key in ('next', 'previous'):
if not kwargs.get(key):
continue
match = re.search(r'page=(?P<num>[\d]+)', kwargs[key])
if match is None and ke... | def _convert_pagenum(self, kwargs):
"""
Convert next and previous from URLs to integers
"""
for key in ('next', 'previous'):
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continue
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valid | BaseResource.read | =====API DOCS=====
Retrieve and return objects from the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
if ``pk`` is provided (not ``None``).
:type pk: int
:param fail_on_no_results: Flag that if se... | tower_cli/models/base.py | def read(self, pk=None, fail_on_no_results=False, fail_on_multiple_results=False, **kwargs):
"""
=====API DOCS=====
Retrieve and return objects from the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
... | def read(self, pk=None, fail_on_no_results=False, fail_on_multiple_results=False, **kwargs):
"""
=====API DOCS=====
Retrieve and return objects from the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
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valid | BaseResource.write | =====API DOCS=====
Modify the given object using the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
if ``pk`` is provided (not ``None``).
:type pk: int
:param create_on_missing: Flag that if set, a... | tower_cli/models/base.py | def write(self, pk=None, create_on_missing=False, fail_on_found=False, force_on_exists=True, **kwargs):
"""
=====API DOCS=====
Modify the given object using the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
... | def write(self, pk=None, create_on_missing=False, fail_on_found=False, force_on_exists=True, **kwargs):
"""
=====API DOCS=====
Modify the given object using the Ansible Tower API.
:param pk: Primary key of the resource to be read. Tower CLI will only attempt to read that object
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valid | BaseResource.delete | Remove the given object.
If `fail_on_missing` is True, then the object's not being found is considered a failure; otherwise,
a success with no change is reported.
=====API DOCS=====
Remove the given object.
:param pk: Primary key of the resource to be deleted.
:type pk... | tower_cli/models/base.py | def delete(self, pk=None, fail_on_missing=False, **kwargs):
"""Remove the given object.
If `fail_on_missing` is True, then the object's not being found is considered a failure; otherwise,
a success with no change is reported.
=====API DOCS=====
Remove the given object.
... | def delete(self, pk=None, fail_on_missing=False, **kwargs):
"""Remove the given object.
If `fail_on_missing` is True, then the object's not being found is considered a failure; otherwise,
a success with no change is reported.
=====API DOCS=====
Remove the given object.
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valid | BaseResource.get | Return one and exactly one object.
Lookups may be through a primary key, specified as a positional argument, and/or through filters specified
through keyword arguments.
If the number of results does not equal one, raise an exception.
=====API DOCS=====
Retrieve one and exactly... | tower_cli/models/base.py | def get(self, pk=None, **kwargs):
"""Return one and exactly one object.
Lookups may be through a primary key, specified as a positional argument, and/or through filters specified
through keyword arguments.
If the number of results does not equal one, raise an exception.
=====A... | def get(self, pk=None, **kwargs):
"""Return one and exactly one object.
Lookups may be through a primary key, specified as a positional argument, and/or through filters specified
through keyword arguments.
If the number of results does not equal one, raise an exception.
=====A... | [
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valid | BaseResource.list | Return a list of objects.
If one or more filters are provided through keyword arguments, filter the results accordingly.
If no filters are provided, return all results.
=====API DOCS=====
Retrieve a list of objects.
:param all_pages: Flag that if set, collect all pages of con... | tower_cli/models/base.py | def list(self, all_pages=False, **kwargs):
"""Return a list of objects.
If one or more filters are provided through keyword arguments, filter the results accordingly.
If no filters are provided, return all results.
=====API DOCS=====
Retrieve a list of objects.
:param... | def list(self, all_pages=False, **kwargs):
"""Return a list of objects.
If one or more filters are provided through keyword arguments, filter the results accordingly.
If no filters are provided, return all results.
=====API DOCS=====
Retrieve a list of objects.
:param... | [
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valid | BaseResource._disassoc | Disassociate the `other` record from the `me` record. | tower_cli/models/base.py | def _disassoc(self, url_fragment, me, other):
"""Disassociate the `other` record from the `me` record."""
# Get the endpoint for foreign records within this object.
url = self.endpoint + '%d/%s/' % (me, url_fragment)
# Attempt to determine whether the other record already is absent, fo... | def _disassoc(self, url_fragment, me, other):
"""Disassociate the `other` record from the `me` record."""
# Get the endpoint for foreign records within this object.
url = self.endpoint + '%d/%s/' % (me, url_fragment)
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valid | Resource.copy | Copy an object.
Only the ID is used for the lookup. All provided fields are used to override the old data from the
copied resource.
=====API DOCS=====
Copy an object.
:param pk: Primary key of the resource object to be copied
:param new_name: The new name to give the r... | tower_cli/models/base.py | def copy(self, pk=None, new_name=None, **kwargs):
"""Copy an object.
Only the ID is used for the lookup. All provided fields are used to override the old data from the
copied resource.
=====API DOCS=====
Copy an object.
:param pk: Primary key of the resource object to ... | def copy(self, pk=None, new_name=None, **kwargs):
"""Copy an object.
Only the ID is used for the lookup. All provided fields are used to override the old data from the
copied resource.
=====API DOCS=====
Copy an object.
:param pk: Primary key of the resource object to ... | [
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valid | Resource.modify | Modify an already existing object.
Fields in the resource's `identity` tuple can be used in lieu of a primary key for a lookup; in such a case,
only other fields are written.
To modify unique fields, you must use the primary key for the lookup.
=====API DOCS=====
Modify an alr... | tower_cli/models/base.py | def modify(self, pk=None, create_on_missing=False, **kwargs):
"""Modify an already existing object.
Fields in the resource's `identity` tuple can be used in lieu of a primary key for a lookup; in such a case,
only other fields are written.
To modify unique fields, you must use the prim... | def modify(self, pk=None, create_on_missing=False, **kwargs):
"""Modify an already existing object.
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valid | MonitorableResource.last_job_data | Internal utility function for Unified Job Templates. Returns data about the last job run off of that UJT | tower_cli/models/base.py | def last_job_data(self, pk=None, **kwargs):
"""
Internal utility function for Unified Job Templates. Returns data about the last job run off of that UJT
"""
ujt = self.get(pk, include_debug_header=True, **kwargs)
# Determine the appropriate inventory source update.
if 'c... | def last_job_data(self, pk=None, **kwargs):
"""
Internal utility function for Unified Job Templates. Returns data about the last job run off of that UJT
"""
ujt = self.get(pk, include_debug_header=True, **kwargs)
# Determine the appropriate inventory source update.
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valid | MonitorableResource.lookup_stdout | Internal utility function to return standard out. Requires the pk of a unified job. | tower_cli/models/base.py | def lookup_stdout(self, pk=None, start_line=None, end_line=None, full=True):
"""
Internal utility function to return standard out. Requires the pk of a unified job.
"""
stdout_url = '%s%s/stdout/' % (self.unified_job_type, pk)
payload = {'format': 'json', 'content_encoding': 'bas... | def lookup_stdout(self, pk=None, start_line=None, end_line=None, full=True):
"""
Internal utility function to return standard out. Requires the pk of a unified job.
"""
stdout_url = '%s%s/stdout/' % (self.unified_job_type, pk)
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valid | MonitorableResource.stdout | Print out the standard out of a unified job to the command line or output file.
For Projects, print the standard out of most recent update.
For Inventory Sources, print standard out of most recent sync.
For Jobs, print the job's standard out.
For Workflow Jobs, print a status table of it... | tower_cli/models/base.py | def stdout(self, pk, start_line=None, end_line=None, outfile=sys.stdout, **kwargs):
"""
Print out the standard out of a unified job to the command line or output file.
For Projects, print the standard out of most recent update.
For Inventory Sources, print standard out of most recent syn... | def stdout(self, pk, start_line=None, end_line=None, outfile=sys.stdout, **kwargs):
"""
Print out the standard out of a unified job to the command line or output file.
For Projects, print the standard out of most recent update.
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valid | MonitorableResource.monitor | Stream the standard output from a job, project update, or inventory udpate.
=====API DOCS=====
Stream the standard output from a job run to stdout.
:param pk: Primary key of the job resource object to be monitored.
:type pk: int
:param parent_pk: Primary key of the unified job ... | tower_cli/models/base.py | def monitor(self, pk, parent_pk=None, timeout=None, interval=0.5, outfile=sys.stdout, **kwargs):
"""
Stream the standard output from a job, project update, or inventory udpate.
=====API DOCS=====
Stream the standard output from a job run to stdout.
:param pk: Primary key of the... | def monitor(self, pk, parent_pk=None, timeout=None, interval=0.5, outfile=sys.stdout, **kwargs):
"""
Stream the standard output from a job, project update, or inventory udpate.
=====API DOCS=====
Stream the standard output from a job run to stdout.
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valid | MonitorableResource.wait | Wait for a running job to finish. Blocks further input until the job completes (whether successfully
or unsuccessfully) and a final status can be given.
=====API DOCS=====
Wait for a job resource object to enter certain status.
:param pk: Primary key of the job resource object to wait.... | tower_cli/models/base.py | def wait(self, pk, parent_pk=None, min_interval=1, max_interval=30, timeout=None, outfile=sys.stdout,
exit_on=['successful'], **kwargs):
"""
Wait for a running job to finish. Blocks further input until the job completes (whether successfully
or unsuccessfully) and a final status can... | def wait(self, pk, parent_pk=None, min_interval=1, max_interval=30, timeout=None, outfile=sys.stdout,
exit_on=['successful'], **kwargs):
"""
Wait for a running job to finish. Blocks further input until the job completes (whether successfully
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valid | ExeResource.status | Print the current job status. This is used to check a running job. You can look up the job with
the same parameters used for a get request.
=====API DOCS=====
Retrieve the current job status.
:param pk: Primary key of the resource to retrieve status from.
:type pk: int
... | tower_cli/models/base.py | def status(self, pk=None, detail=False, **kwargs):
"""Print the current job status. This is used to check a running job. You can look up the job with
the same parameters used for a get request.
=====API DOCS=====
Retrieve the current job status.
:param pk: Primary key of the re... | def status(self, pk=None, detail=False, **kwargs):
"""Print the current job status. This is used to check a running job. You can look up the job with
the same parameters used for a get request.
=====API DOCS=====
Retrieve the current job status.
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valid | ExeResource.cancel | Cancel a currently running job.
Fails with a non-zero exit status if the job cannot be canceled.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Cancel a currently running job.
:param pk: Primary key of the job resource to restart.
... | tower_cli/models/base.py | def cancel(self, pk=None, fail_if_not_running=False, **kwargs):
"""Cancel a currently running job.
Fails with a non-zero exit status if the job cannot be canceled.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Cancel a currently running jo... | def cancel(self, pk=None, fail_if_not_running=False, **kwargs):
"""Cancel a currently running job.
Fails with a non-zero exit status if the job cannot be canceled.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Cancel a currently running jo... | [
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] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/models/base.py#L1094-L1132 | [
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valid | ExeResource.relaunch | Relaunch a stopped job.
Fails with a non-zero exit status if the job cannot be relaunched.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Relaunch a stopped job resource.
:param pk: Primary key of the job resource to relaunch.
:typ... | tower_cli/models/base.py | def relaunch(self, pk=None, **kwargs):
"""Relaunch a stopped job.
Fails with a non-zero exit status if the job cannot be relaunched.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Relaunch a stopped job resource.
:param pk: Primary... | def relaunch(self, pk=None, **kwargs):
"""Relaunch a stopped job.
Fails with a non-zero exit status if the job cannot be relaunched.
You must provide either a pk or parameters in the job's identity.
=====API DOCS=====
Relaunch a stopped job resource.
:param pk: Primary... | [
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valid | SurveyResource.survey | Get the survey_spec for the job template.
To write a survey, use the modify command with the --survey-spec parameter.
=====API DOCS=====
Get the survey specification of a resource object.
:param pk: Primary key of the resource to retrieve survey from. Tower CLI will only attempt to
... | tower_cli/models/base.py | def survey(self, pk=None, **kwargs):
"""Get the survey_spec for the job template.
To write a survey, use the modify command with the --survey-spec parameter.
=====API DOCS=====
Get the survey specification of a resource object.
:param pk: Primary key of the resource to retrieve... | def survey(self, pk=None, **kwargs):
"""Get the survey_spec for the job template.
To write a survey, use the modify command with the --survey-spec parameter.
=====API DOCS=====
Get the survey specification of a resource object.
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valid | Resource.batch_update | Update all related inventory sources of the given inventory.
Note global option --format is not available here, as the output would always be JSON-formatted.
=====API DOCS=====
Update all related inventory sources of the given inventory.
:param pk: Primary key of the given inventory.
... | tower_cli/resources/inventory.py | def batch_update(self, pk=None, **kwargs):
"""Update all related inventory sources of the given inventory.
Note global option --format is not available here, as the output would always be JSON-formatted.
=====API DOCS=====
Update all related inventory sources of the given inventory.
... | def batch_update(self, pk=None, **kwargs):
"""Update all related inventory sources of the given inventory.
Note global option --format is not available here, as the output would always be JSON-formatted.
=====API DOCS=====
Update all related inventory sources of the given inventory.
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valid | Resource.read | Do extra processing so we can display the actor field as
a top-level field | tower_cli/resources/activity_stream.py | def read(self, *args, **kwargs):
'''
Do extra processing so we can display the actor field as
a top-level field
'''
if 'actor' in kwargs:
kwargs['actor'] = kwargs.pop('actor')
r = super(Resource, self).read(*args, **kwargs)
if 'results' in r:
... | def read(self, *args, **kwargs):
'''
Do extra processing so we can display the actor field as
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kwargs['actor'] = kwargs.pop('actor')
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valid | log | Log the given output to stderr if and only if we are in
verbose mode.
If we are not in verbose mode, this is a no-op. | tower_cli/utils/debug.py | def log(s, header='', file=sys.stderr, nl=1, **kwargs):
"""Log the given output to stderr if and only if we are in
verbose mode.
If we are not in verbose mode, this is a no-op.
"""
# Sanity check: If we are not in verbose mode, this is a no-op.
if not settings.verbose:
return
# Con... | def log(s, header='', file=sys.stderr, nl=1, **kwargs):
"""Log the given output to stderr if and only if we are in
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If we are not in verbose mode, this is a no-op.
"""
# Sanity check: If we are not in verbose mode, this is a no-op.
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valid | ManyToManyField.configure_model | Hook for ResourceMeta class to call when initializing model class.
Saves fields obtained from resource class backlinks | tower_cli/models/fields.py | def configure_model(self, attrs, field_name):
'''
Hook for ResourceMeta class to call when initializing model class.
Saves fields obtained from resource class backlinks
'''
self.relationship = field_name
self._set_method_names(relationship=field_name)
if self.res_... | def configure_model(self, attrs, field_name):
'''
Hook for ResourceMeta class to call when initializing model class.
Saves fields obtained from resource class backlinks
'''
self.relationship = field_name
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valid | ManyToManyField._produce_raw_method | Returns a callable which becomes the associate or disassociate
method for the related field.
Method can be overridden to add additional functionality, but
`_produce_method` may also need to be subclassed to decorate
it appropriately. | tower_cli/models/fields.py | def _produce_raw_method(self):
'''
Returns a callable which becomes the associate or disassociate
method for the related field.
Method can be overridden to add additional functionality, but
`_produce_method` may also need to be subclassed to decorate
it appropriately.
... | def _produce_raw_method(self):
'''
Returns a callable which becomes the associate or disassociate
method for the related field.
Method can be overridden to add additional functionality, but
`_produce_method` may also need to be subclassed to decorate
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"get",
"(",
"method... | a2b151fed93c47725018d3034848cb3a1814bed7 |
valid | Resource.create | Create a new label.
There are two types of label creation: isolatedly creating a new label and creating a new label under
a job template. Here the two types are discriminated by whether to provide --job-template option.
Fields in the resource's `identity` tuple are used for a lookup; if a matc... | tower_cli/resources/label.py | def create(self, fail_on_found=False, force_on_exists=False, **kwargs):
"""Create a new label.
There are two types of label creation: isolatedly creating a new label and creating a new label under
a job template. Here the two types are discriminated by whether to provide --job-template option.
... | def create(self, fail_on_found=False, force_on_exists=False, **kwargs):
"""Create a new label.
There are two types of label creation: isolatedly creating a new label and creating a new label under
a job template. Here the two types are discriminated by whether to provide --job-template option.
... | [
"Create",
"a",
"new",
"label",
"."
] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/resources/label.py#L43-L93 | [
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"e... | a2b151fed93c47725018d3034848cb3a1814bed7 |
valid | version | Display full version information. | tower_cli/cli/misc.py | def version():
"""Display full version information."""
# Print out the current version of Tower CLI.
click.echo('Tower CLI %s' % __version__)
# Print out the current API version of the current code base.
click.echo('API %s' % CUR_API_VERSION)
# Attempt to connect to the Ansible Tower server.
... | def version():
"""Display full version information."""
# Print out the current version of Tower CLI.
click.echo('Tower CLI %s' % __version__)
# Print out the current API version of the current code base.
click.echo('API %s' % CUR_API_VERSION)
# Attempt to connect to the Ansible Tower server.
... | [
"Display",
"full",
"version",
"information",
"."
] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/cli/misc.py#L39-L64 | [
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"CUR_API_VERS... | a2b151fed93c47725018d3034848cb3a1814bed7 |
valid | _echo_setting | Echo a setting to the CLI. | tower_cli/cli/misc.py | def _echo_setting(key):
"""Echo a setting to the CLI."""
value = getattr(settings, key)
secho('%s: ' % key, fg='magenta', bold=True, nl=False)
secho(
six.text_type(value),
bold=True,
fg='white' if isinstance(value, six.text_type) else 'cyan',
) | def _echo_setting(key):
"""Echo a setting to the CLI."""
value = getattr(settings, key)
secho('%s: ' % key, fg='magenta', bold=True, nl=False)
secho(
six.text_type(value),
bold=True,
fg='white' if isinstance(value, six.text_type) else 'cyan',
) | [
"Echo",
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"the",
"CLI",
"."
] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/cli/misc.py#L67-L75 | [
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... | a2b151fed93c47725018d3034848cb3a1814bed7 |
valid | config | Read or write tower-cli configuration.
`tower config` saves the given setting to the appropriate Tower CLI;
either the user's ~/.tower_cli.cfg file, or the /etc/tower/tower_cli.cfg
file if --global is used.
Writing to /etc/tower/tower_cli.cfg is likely to require heightened
permissions (in other w... | tower_cli/cli/misc.py | def config(key=None, value=None, scope='user', global_=False, unset=False):
"""Read or write tower-cli configuration.
`tower config` saves the given setting to the appropriate Tower CLI;
either the user's ~/.tower_cli.cfg file, or the /etc/tower/tower_cli.cfg
file if --global is used.
Writing to /... | def config(key=None, value=None, scope='user', global_=False, unset=False):
"""Read or write tower-cli configuration.
`tower config` saves the given setting to the appropriate Tower CLI;
either the user's ~/.tower_cli.cfg file, or the /etc/tower/tower_cli.cfg
file if --global is used.
Writing to /... | [
"Read",
"or",
"write",
"tower",
"-",
"cli",
"configuration",
"."
] | ansible/tower-cli | python | https://github.com/ansible/tower-cli/blob/a2b151fed93c47725018d3034848cb3a1814bed7/tower_cli/cli/misc.py#L97-L210 | [
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"# If the old-style `global_` option is set, issue a deprecation notice.",
"if",
"global_",
":",... | a2b151fed93c47725018d3034848cb3a1814bed7 |
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