id int32 0 252k | repo stringlengths 7 55 | path stringlengths 4 127 | func_name stringlengths 1 88 | original_string stringlengths 75 19.8k | language stringclasses 1
value | code stringlengths 75 19.8k | code_tokens list | docstring stringlengths 3 17.3k | docstring_tokens list | sha stringlengths 40 40 | url stringlengths 87 242 |
|---|---|---|---|---|---|---|---|---|---|---|---|
12,300 | thunder-project/thunder | thunder/images/images.py | Images.subtract | def subtract(self, val):
"""
Subtract a constant value or an image from all images.
Parameters
----------
val : int, float, or ndarray
Value to subtract.
"""
if isinstance(val, ndarray):
if val.shape != self.value_shape:
ra... | python | def subtract(self, val):
"""
Subtract a constant value or an image from all images.
Parameters
----------
val : int, float, or ndarray
Value to subtract.
"""
if isinstance(val, ndarray):
if val.shape != self.value_shape:
ra... | [
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Parameters
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12,301 | thunder-project/thunder | thunder/images/images.py | Images.topng | def topng(self, path, prefix='image', overwrite=False):
"""
Write 2d images as PNG files.
Files will be written into a newly-created directory.
Three-dimensional data will be treated as RGB channels.
Parameters
----------
path : string
Path to output... | python | def topng(self, path, prefix='image', overwrite=False):
"""
Write 2d images as PNG files.
Files will be written into a newly-created directory.
Three-dimensional data will be treated as RGB channels.
Parameters
----------
path : string
Path to output... | [
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Files will be written into a newly-created directory.
Three-dimensional data will be treated as RGB channels.
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path : string
Path to output directory, must be one level below an existing directory.
prefix :... | [
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12,302 | thunder-project/thunder | thunder/images/images.py | Images.map_as_series | def map_as_series(self, func, value_size=None, dtype=None, chunk_size='auto'):
"""
Efficiently apply a function to images as series data.
For images data that represent image sequences, this method
applies a function to each pixel's series, and then returns to
the images format,... | python | def map_as_series(self, func, value_size=None, dtype=None, chunk_size='auto'):
"""
Efficiently apply a function to images as series data.
For images data that represent image sequences, this method
applies a function to each pixel's series, and then returns to
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For images data that represent image sequences, this method
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Parameters
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12,303 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.count | def count(self):
"""
Explicit count of the number of items.
For lazy or distributed data, will force a computation.
"""
if self.mode == 'spark':
return self.tordd().count()
if self.mode == 'local':
return prod(self.values.values.shape) | python | def count(self):
"""
Explicit count of the number of items.
For lazy or distributed data, will force a computation.
"""
if self.mode == 'spark':
return self.tordd().count()
if self.mode == 'local':
return prod(self.values.values.shape) | [
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12,304 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.collect_blocks | def collect_blocks(self):
"""
Collect the blocks in a list
"""
if self.mode == 'spark':
return self.values.tordd().sortByKey().values().collect()
if self.mode == 'local':
return self.values.values.flatten().tolist() | python | def collect_blocks(self):
"""
Collect the blocks in a list
"""
if self.mode == 'spark':
return self.values.tordd().sortByKey().values().collect()
if self.mode == 'local':
return self.values.values.flatten().tolist() | [
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12,305 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.map | def map(self, func, value_shape=None, dtype=None):
"""
Apply an array -> array function to each block
"""
mapped = self.values.map(func, value_shape=value_shape, dtype=dtype)
return self._constructor(mapped).__finalize__(self, noprop=('dtype',)) | python | def map(self, func, value_shape=None, dtype=None):
"""
Apply an array -> array function to each block
"""
mapped = self.values.map(func, value_shape=value_shape, dtype=dtype)
return self._constructor(mapped).__finalize__(self, noprop=('dtype',)) | [
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12,306 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.toimages | def toimages(self):
"""
Convert blocks to images.
"""
from thunder.images.images import Images
if self.mode == 'spark':
values = self.values.values_to_keys((0,)).unchunk()
if self.mode == 'local':
values = self.values.unchunk()
return Im... | python | def toimages(self):
"""
Convert blocks to images.
"""
from thunder.images.images import Images
if self.mode == 'spark':
values = self.values.values_to_keys((0,)).unchunk()
if self.mode == 'local':
values = self.values.unchunk()
return Im... | [
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12,307 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.toseries | def toseries(self):
"""
Converts blocks to series.
"""
from thunder.series.series import Series
if self.mode == 'spark':
values = self.values.values_to_keys(tuple(range(1, len(self.shape)))).unchunk()
if self.mode == 'local':
values = self.values... | python | def toseries(self):
"""
Converts blocks to series.
"""
from thunder.series.series import Series
if self.mode == 'spark':
values = self.values.values_to_keys(tuple(range(1, len(self.shape)))).unchunk()
if self.mode == 'local':
values = self.values... | [
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12,308 | thunder-project/thunder | thunder/blocks/blocks.py | Blocks.toarray | def toarray(self):
"""
Convert blocks to local ndarray
"""
if self.mode == 'spark':
return self.values.unchunk().toarray()
if self.mode == 'local':
return self.values.unchunk() | python | def toarray(self):
"""
Convert blocks to local ndarray
"""
if self.mode == 'spark':
return self.values.unchunk().toarray()
if self.mode == 'local':
return self.values.unchunk() | [
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12,309 | thunder-project/thunder | thunder/series/series.py | Series.flatten | def flatten(self):
"""
Reshape all dimensions but the last into a single dimension
"""
size = prod(self.shape[:-1])
return self.reshape(size, self.shape[-1]) | python | def flatten(self):
"""
Reshape all dimensions but the last into a single dimension
"""
size = prod(self.shape[:-1])
return self.reshape(size, self.shape[-1]) | [
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12,310 | thunder-project/thunder | thunder/series/series.py | Series.tospark | def tospark(self, engine=None):
"""
Convert to spark mode.
"""
from thunder.series.readers import fromarray
if self.mode == 'spark':
logging.getLogger('thunder').warn('images already in local mode')
pass
if engine is None:
raise Value... | python | def tospark(self, engine=None):
"""
Convert to spark mode.
"""
from thunder.series.readers import fromarray
if self.mode == 'spark':
logging.getLogger('thunder').warn('images already in local mode')
pass
if engine is None:
raise Value... | [
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12,311 | thunder-project/thunder | thunder/series/series.py | Series.sample | def sample(self, n=100, seed=None):
"""
Extract random sample of records.
Parameters
----------
n : int, optional, default = 100
The number of data points to sample.
seed : int, optional, default = None
Random seed.
"""
if n < 1:
... | python | def sample(self, n=100, seed=None):
"""
Extract random sample of records.
Parameters
----------
n : int, optional, default = 100
The number of data points to sample.
seed : int, optional, default = None
Random seed.
"""
if n < 1:
... | [
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The number of data points to sample.
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12,312 | thunder-project/thunder | thunder/series/series.py | Series.map | def map(self, func, index=None, value_shape=None, dtype=None, with_keys=False):
"""
Map an array -> array function over each record.
Parameters
----------
func : function
A function of a single record.
index : array-like, optional, default = None
... | python | def map(self, func, index=None, value_shape=None, dtype=None, with_keys=False):
"""
Map an array -> array function over each record.
Parameters
----------
func : function
A function of a single record.
index : array-like, optional, default = None
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12,313 | thunder-project/thunder | thunder/series/series.py | Series.mean | def mean(self):
"""
Compute the mean across records
"""
return self._constructor(self.values.mean(axis=self.baseaxes, keepdims=True)) | python | def mean(self):
"""
Compute the mean across records
"""
return self._constructor(self.values.mean(axis=self.baseaxes, keepdims=True)) | [
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12,314 | thunder-project/thunder | thunder/series/series.py | Series.sum | def sum(self):
"""
Compute the sum across records.
"""
return self._constructor(self.values.sum(axis=self.baseaxes, keepdims=True)) | python | def sum(self):
"""
Compute the sum across records.
"""
return self._constructor(self.values.sum(axis=self.baseaxes, keepdims=True)) | [
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12,315 | thunder-project/thunder | thunder/series/series.py | Series.max | def max(self):
"""
Compute the max across records.
"""
return self._constructor(self.values.max(axis=self.baseaxes, keepdims=True)) | python | def max(self):
"""
Compute the max across records.
"""
return self._constructor(self.values.max(axis=self.baseaxes, keepdims=True)) | [
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12,316 | thunder-project/thunder | thunder/series/series.py | Series.min | def min(self):
"""
Compute the min across records.
"""
return self._constructor(self.values.min(axis=self.baseaxes, keepdims=True)) | python | def min(self):
"""
Compute the min across records.
"""
return self._constructor(self.values.min(axis=self.baseaxes, keepdims=True)) | [
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12,317 | thunder-project/thunder | thunder/series/series.py | Series.reshape | def reshape(self, *shape):
"""
Reshape the Series object
Cannot change the last dimension.
Parameters
----------
shape: one or more ints
New shape
"""
if prod(self.shape) != prod(shape):
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"""
Reshape the Series object
Cannot change the last dimension.
Parameters
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shape: one or more ints
New shape
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12,318 | thunder-project/thunder | thunder/series/series.py | Series.between | def between(self, left, right):
"""
Select subset of values within the given index range.
Inclusive on the left; exclusive on the right.
Parameters
----------
left : int
Left-most index in the desired range.
right: int
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"""
Select subset of values within the given index range.
Inclusive on the left; exclusive on the right.
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left : int
Left-most index in the desired range.
right: int
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12,319 | thunder-project/thunder | thunder/series/series.py | Series.select | def select(self, crit):
"""
Select subset of values that match a given index criterion.
Parameters
----------
crit : function, list, str, int
Criterion function to map to indices, specific index value,
or list of indices.
"""
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... | python | def select(self, crit):
"""
Select subset of values that match a given index criterion.
Parameters
----------
crit : function, list, str, int
Criterion function to map to indices, specific index value,
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"""
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12,320 | thunder-project/thunder | thunder/series/series.py | Series.center | def center(self, axis=1):
"""
Subtract the mean either within or across records.
Parameters
----------
axis : int, optional, default = 1
Which axis to center along, within (1) or across (0) records.
"""
if axis == 1:
return self.map(lambda... | python | def center(self, axis=1):
"""
Subtract the mean either within or across records.
Parameters
----------
axis : int, optional, default = 1
Which axis to center along, within (1) or across (0) records.
"""
if axis == 1:
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12,321 | thunder-project/thunder | thunder/series/series.py | Series.standardize | def standardize(self, axis=1):
"""
Divide by standard deviation either within or across records.
Parameters
----------
axis : int, optional, default = 0
Which axis to standardize along, within (1) or across (0) records
"""
if axis == 1:
re... | python | def standardize(self, axis=1):
"""
Divide by standard deviation either within or across records.
Parameters
----------
axis : int, optional, default = 0
Which axis to standardize along, within (1) or across (0) records
"""
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12,322 | thunder-project/thunder | thunder/series/series.py | Series.zscore | def zscore(self, axis=1):
"""
Subtract the mean and divide by standard deviation within or across records.
Parameters
----------
axis : int, optional, default = 0
Which axis to zscore along, within (1) or across (0) records
"""
if axis == 1:
... | python | def zscore(self, axis=1):
"""
Subtract the mean and divide by standard deviation within or across records.
Parameters
----------
axis : int, optional, default = 0
Which axis to zscore along, within (1) or across (0) records
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12,323 | thunder-project/thunder | thunder/series/series.py | Series.squelch | def squelch(self, threshold):
"""
Set all records that do not exceed the given threhsold to 0.
Parameters
----------
threshold : scalar
Level below which to set records to zero
"""
func = lambda x: zeros(x.shape) if max(x) < threshold else x
r... | python | def squelch(self, threshold):
"""
Set all records that do not exceed the given threhsold to 0.
Parameters
----------
threshold : scalar
Level below which to set records to zero
"""
func = lambda x: zeros(x.shape) if max(x) < threshold else x
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Level below which to set records to zero | [
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12,324 | thunder-project/thunder | thunder/series/series.py | Series.correlate | def correlate(self, signal):
"""
Correlate records against one or many one-dimensional arrays.
Parameters
----------
signal : array-like
One or more signals to correlate against.
"""
s = asarray(signal)
if s.ndim == 1:
if size(s) ... | python | def correlate(self, signal):
"""
Correlate records against one or many one-dimensional arrays.
Parameters
----------
signal : array-like
One or more signals to correlate against.
"""
s = asarray(signal)
if s.ndim == 1:
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12,325 | thunder-project/thunder | thunder/series/series.py | Series._check_panel | def _check_panel(self, length):
"""
Check that given fixed panel length evenly divides index.
Parameters
----------
length : int
Fixed length with which to subdivide index
"""
n = len(self.index)
if divmod(n, length)[1] != 0:
raise... | python | def _check_panel(self, length):
"""
Check that given fixed panel length evenly divides index.
Parameters
----------
length : int
Fixed length with which to subdivide index
"""
n = len(self.index)
if divmod(n, length)[1] != 0:
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12,326 | thunder-project/thunder | thunder/series/series.py | Series.mean_by_panel | def mean_by_panel(self, length):
"""
Compute the mean across fixed sized panels of each record.
Splits each record into panels of size `length`,
and then computes the mean across panels.
Panel length must subdivide record exactly.
Parameters
----------
l... | python | def mean_by_panel(self, length):
"""
Compute the mean across fixed sized panels of each record.
Splits each record into panels of size `length`,
and then computes the mean across panels.
Panel length must subdivide record exactly.
Parameters
----------
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12,327 | thunder-project/thunder | thunder/series/series.py | Series._makemasks | def _makemasks(self, index=None, level=0):
"""
Internal function for generating masks for selecting values based on multi-index values.
As all other multi-index functions will call this function, basic type-checking is also
performed at this stage.
"""
if index is None:
... | python | def _makemasks(self, index=None, level=0):
"""
Internal function for generating masks for selecting values based on multi-index values.
As all other multi-index functions will call this function, basic type-checking is also
performed at this stage.
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12,328 | thunder-project/thunder | thunder/series/series.py | Series._map_by_index | def _map_by_index(self, function, level=0):
"""
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12,329 | thunder-project/thunder | thunder/series/series.py | Series.aggregate_by_index | def aggregate_by_index(self, function, level=0):
"""
Aggregrate data in each record, grouping by index values.
For each unique value of the index, applies a function to the group
indexed by that value. Returns a Series indexed by those unique values.
For the result to be a valid... | python | def aggregate_by_index(self, function, level=0):
"""
Aggregrate data in each record, grouping by index values.
For each unique value of the index, applies a function to the group
indexed by that value. Returns a Series indexed by those unique values.
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12,330 | thunder-project/thunder | thunder/series/series.py | Series.gramian | def gramian(self):
"""
Compute gramian of a distributed matrix.
The gramian is defined as the product of the matrix
with its transpose, i.e. A^T * A.
"""
if self.mode == 'spark':
rdd = self.values.tordd()
from pyspark.accumulators import Accumula... | python | def gramian(self):
"""
Compute gramian of a distributed matrix.
The gramian is defined as the product of the matrix
with its transpose, i.e. A^T * A.
"""
if self.mode == 'spark':
rdd = self.values.tordd()
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12,331 | thunder-project/thunder | thunder/series/series.py | Series.times | def times(self, other):
"""
Multiply a matrix by another one.
Other matrix must be a numpy array, a scalar,
or another matrix in local mode.
Parameters
----------
other : Matrix, scalar, or numpy array
A matrix to multiply with
"""
if... | python | def times(self, other):
"""
Multiply a matrix by another one.
Other matrix must be a numpy array, a scalar,
or another matrix in local mode.
Parameters
----------
other : Matrix, scalar, or numpy array
A matrix to multiply with
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12,332 | thunder-project/thunder | thunder/series/series.py | Series._makewindows | def _makewindows(self, indices, window):
"""
Make masks used by windowing functions
Given a list of indices specifying window centers,
and a window size, construct a list of index arrays,
one per window, that index into the target array
Parameters
----------
... | python | def _makewindows(self, indices, window):
"""
Make masks used by windowing functions
Given a list of indices specifying window centers,
and a window size, construct a list of index arrays,
one per window, that index into the target array
Parameters
----------
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12,333 | thunder-project/thunder | thunder/series/series.py | Series.mean_by_window | def mean_by_window(self, indices, window):
"""
Average series across multiple windows specified by their centers.
Parameters
----------
indices : array-like
List of times specifying window centers
window : int
Window size
"""
mask... | python | def mean_by_window(self, indices, window):
"""
Average series across multiple windows specified by their centers.
Parameters
----------
indices : array-like
List of times specifying window centers
window : int
Window size
"""
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12,334 | thunder-project/thunder | thunder/series/series.py | Series.subsample | def subsample(self, sample_factor=2):
"""
Subsample series by an integer factor.
Parameters
----------
sample_factor : positive integer, optional, default=2
Factor for downsampling.
"""
if sample_factor < 0:
raise Exception('Factor for sub... | python | def subsample(self, sample_factor=2):
"""
Subsample series by an integer factor.
Parameters
----------
sample_factor : positive integer, optional, default=2
Factor for downsampling.
"""
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12,335 | thunder-project/thunder | thunder/series/series.py | Series.downsample | def downsample(self, sample_factor=2):
"""
Downsample series by an integer factor by averaging.
Parameters
----------
sample_factor : positive integer, optional, default=2
Factor for downsampling.
"""
if sample_factor < 0:
raise Exception(... | python | def downsample(self, sample_factor=2):
"""
Downsample series by an integer factor by averaging.
Parameters
----------
sample_factor : positive integer, optional, default=2
Factor for downsampling.
"""
if sample_factor < 0:
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12,336 | thunder-project/thunder | thunder/series/series.py | Series.fourier | def fourier(self, freq=None):
"""
Compute statistics of a Fourier decomposition on series data.
Parameters
----------
freq : int
Digital frequency at which to compute coherence and phase
"""
def get(y, freq):
y = y - mean(y)
nf... | python | def fourier(self, freq=None):
"""
Compute statistics of a Fourier decomposition on series data.
Parameters
----------
freq : int
Digital frequency at which to compute coherence and phase
"""
def get(y, freq):
y = y - mean(y)
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12,337 | thunder-project/thunder | thunder/series/series.py | Series.convolve | def convolve(self, signal, mode='full'):
"""
Convolve series data against another signal.
Parameters
----------
signal : array
Signal to convolve with (must be 1D)
mode : str, optional, default='full'
Mode of convolution, options are 'full', 'sam... | python | def convolve(self, signal, mode='full'):
"""
Convolve series data against another signal.
Parameters
----------
signal : array
Signal to convolve with (must be 1D)
mode : str, optional, default='full'
Mode of convolution, options are 'full', 'sam... | [
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signal : array
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12,338 | thunder-project/thunder | thunder/series/series.py | Series.crosscorr | def crosscorr(self, signal, lag=0):
"""
Cross correlate series data against another signal.
Parameters
----------
signal : array
Signal to correlate against (must be 1D).
lag : int
Range of lags to consider, will cover (-lag, +lag).
"""
... | python | def crosscorr(self, signal, lag=0):
"""
Cross correlate series data against another signal.
Parameters
----------
signal : array
Signal to correlate against (must be 1D).
lag : int
Range of lags to consider, will cover (-lag, +lag).
"""
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Signal to correlate against (must be 1D).
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12,339 | thunder-project/thunder | thunder/series/series.py | Series.detrend | def detrend(self, method='linear', order=5):
"""
Detrend series data with linear or nonlinear detrending.
Preserve intercept so that subsequent operations can adjust the baseline.
Parameters
----------
method : str, optional, default = 'linear'
Detrending me... | python | def detrend(self, method='linear', order=5):
"""
Detrend series data with linear or nonlinear detrending.
Preserve intercept so that subsequent operations can adjust the baseline.
Parameters
----------
method : str, optional, default = 'linear'
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Detrending method
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12,340 | thunder-project/thunder | thunder/series/series.py | Series.normalize | def normalize(self, method='percentile', window=None, perc=20, offset=0.1):
"""
Normalize by subtracting and dividing by a baseline.
Baseline can be derived from a global mean or percentile,
or a smoothed percentile estimated within a rolling window.
Windowed baselines may only ... | python | def normalize(self, method='percentile', window=None, perc=20, offset=0.1):
"""
Normalize by subtracting and dividing by a baseline.
Baseline can be derived from a global mean or percentile,
or a smoothed percentile estimated within a rolling window.
Windowed baselines may only ... | [
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12,341 | thunder-project/thunder | thunder/series/series.py | Series.toimages | def toimages(self, chunk_size='auto'):
"""
Converts to images data.
This method is equivalent to series.toblocks(size).toimages().
Parameters
----------
chunk_size : str or tuple, size of series chunk used during conversion, default = 'auto'
String interpret... | python | def toimages(self, chunk_size='auto'):
"""
Converts to images data.
This method is equivalent to series.toblocks(size).toimages().
Parameters
----------
chunk_size : str or tuple, size of series chunk used during conversion, default = 'auto'
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This method is equivalent to series.toblocks(size).toimages().
Parameters
----------
chunk_size : str or tuple, size of series chunk used during conversion, default = 'auto'
String interpreted as memory size (in kilobytes, e.g. '64').
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12,342 | thunder-project/thunder | thunder/series/series.py | Series.tobinary | def tobinary(self, path, prefix='series', overwrite=False, credentials=None):
"""
Write data to binary files.
Parameters
----------
path : string path or URI to directory to be created
Output files will be written underneath path.
Directory will be create... | python | def tobinary(self, path, prefix='series', overwrite=False, credentials=None):
"""
Write data to binary files.
Parameters
----------
path : string path or URI to directory to be created
Output files will be written underneath path.
Directory will be create... | [
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12,343 | thunder-project/thunder | thunder/readers.py | addextension | def addextension(path, ext=None):
"""
Helper function for handling of paths given separately passed file extensions.
"""
if ext:
if '*' in path:
return path
elif os.path.splitext(path)[1]:
return path
else:
if not ext.startswith('.'):
... | python | def addextension(path, ext=None):
"""
Helper function for handling of paths given separately passed file extensions.
"""
if ext:
if '*' in path:
return path
elif os.path.splitext(path)[1]:
return path
else:
if not ext.startswith('.'):
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12,344 | thunder-project/thunder | thunder/readers.py | select | def select(files, start, stop):
"""
Helper function for handling start and stop indices
"""
if start or stop:
if start is None:
start = 0
if stop is None:
stop = len(files)
files = files[start:stop]
return files | python | def select(files, start, stop):
"""
Helper function for handling start and stop indices
"""
if start or stop:
if start is None:
start = 0
if stop is None:
stop = len(files)
files = files[start:stop]
return files | [
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12,345 | thunder-project/thunder | thunder/readers.py | listrecursive | def listrecursive(path, ext=None):
"""
List files recurisvely
"""
filenames = set()
for root, dirs, files in os.walk(path):
if ext:
if ext == 'tif' or ext == 'tiff':
tmp = fnmatch.filter(files, '*.' + 'tiff')
files = tmp + fnmatch.filter(files, '*.... | python | def listrecursive(path, ext=None):
"""
List files recurisvely
"""
filenames = set()
for root, dirs, files in os.walk(path):
if ext:
if ext == 'tif' or ext == 'tiff':
tmp = fnmatch.filter(files, '*.' + 'tiff')
files = tmp + fnmatch.filter(files, '*.... | [
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12,346 | thunder-project/thunder | thunder/readers.py | listflat | def listflat(path, ext=None):
"""
List files without recursion
"""
if os.path.isdir(path):
if ext:
if ext == 'tif' or ext == 'tiff':
files = glob.glob(os.path.join(path, '*.tif'))
files = files + glob.glob(os.path.join(path, '*.tiff'))
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"""
List files without recursion
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if os.path.isdir(path):
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files = glob.glob(os.path.join(path, '*.tif'))
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12,347 | thunder-project/thunder | thunder/readers.py | normalize_scheme | def normalize_scheme(path, ext):
"""
Normalize scheme for paths related to hdfs
"""
path = addextension(path, ext)
parsed = urlparse(path)
if parsed.scheme:
# this appears to already be a fully-qualified URI
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# this looks like a local path spec
... | python | def normalize_scheme(path, ext):
"""
Normalize scheme for paths related to hdfs
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path = addextension(path, ext)
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if parsed.scheme:
# this appears to already be a fully-qualified URI
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12,348 | thunder-project/thunder | thunder/readers.py | LocalParallelReader.list | def list(path, ext=None, start=None, stop=None, recursive=False):
"""
Get sorted list of file paths matching path and extension
"""
files = listflat(path, ext) if not recursive else listrecursive(path, ext)
if len(files) < 1:
raise FileNotFoundError('Cannot find files... | python | def list(path, ext=None, start=None, stop=None, recursive=False):
"""
Get sorted list of file paths matching path and extension
"""
files = listflat(path, ext) if not recursive else listrecursive(path, ext)
if len(files) < 1:
raise FileNotFoundError('Cannot find files... | [
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12,349 | thunder-project/thunder | thunder/readers.py | LocalParallelReader.read | def read(self, path, ext=None, start=None, stop=None, recursive=False, npartitions=None):
"""
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Returns RDD of <integer file index, string buffer> k/v pairs.
"""
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"""
Sets up Spark RDD across files specified by dataPath on local filesystem.
Returns RDD of <integer file index, string buffer> k/v pairs.
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12,350 | thunder-project/thunder | thunder/readers.py | LocalFileReader.list | def list(path, filename=None, start=None, stop=None, recursive=False, directories=False):
"""
List files specified by dataPath.
Datapath may include a single wildcard ('*') in the filename specifier.
Returns sorted list of absolute path strings.
"""
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"""
List files specified by dataPath.
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Returns sorted list of absolute path strings.
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12,351 | thunder-project/thunder | thunder/readers.py | BotoClient.parse_query | def parse_query(query, delim='/'):
"""
Parse a boto query
"""
key = ''
prefix = ''
postfix = ''
parsed = urlparse(query)
query = parsed.path.lstrip(delim)
bucket = parsed.netloc
if not parsed.scheme.lower() in ('', "gs", "s3", "s3n"):
... | python | def parse_query(query, delim='/'):
"""
Parse a boto query
"""
key = ''
prefix = ''
postfix = ''
parsed = urlparse(query)
query = parsed.path.lstrip(delim)
bucket = parsed.netloc
if not parsed.scheme.lower() in ('', "gs", "s3", "s3n"):
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12,352 | thunder-project/thunder | thunder/readers.py | BotoClient.retrieve_keys | def retrieve_keys(bucket, key, prefix='', postfix='', delim='/',
directories=False, recursive=False):
"""
Retrieve keys from a bucket
"""
if key and prefix:
assert key.endswith(delim)
key += prefix
# check whether key is a directory
... | python | def retrieve_keys(bucket, key, prefix='', postfix='', delim='/',
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"""
Retrieve keys from a bucket
"""
if key and prefix:
assert key.endswith(delim)
key += prefix
# check whether key is a directory
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12,353 | thunder-project/thunder | thunder/readers.py | BotoParallelReader.getfiles | def getfiles(self, path, ext=None, start=None, stop=None, recursive=False):
"""
Get scheme, bucket, and keys for a set of files
"""
from .utils import connection_with_anon, connection_with_gs
parse = BotoClient.parse_query(path)
scheme = parse[0]
bucket_name = p... | python | def getfiles(self, path, ext=None, start=None, stop=None, recursive=False):
"""
Get scheme, bucket, and keys for a set of files
"""
from .utils import connection_with_anon, connection_with_gs
parse = BotoClient.parse_query(path)
scheme = parse[0]
bucket_name = p... | [
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12,354 | thunder-project/thunder | thunder/readers.py | BotoParallelReader.list | def list(self, dataPath, ext=None, start=None, stop=None, recursive=False):
"""
List files from remote storage
"""
scheme, bucket_name, keylist = self.getfiles(
dataPath, ext=ext, start=start, stop=stop, recursive=recursive)
return ["%s:///%s/%s" % (scheme, bucket_na... | python | def list(self, dataPath, ext=None, start=None, stop=None, recursive=False):
"""
List files from remote storage
"""
scheme, bucket_name, keylist = self.getfiles(
dataPath, ext=ext, start=start, stop=stop, recursive=recursive)
return ["%s:///%s/%s" % (scheme, bucket_na... | [
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12,355 | thunder-project/thunder | thunder/readers.py | BotoParallelReader.read | def read(self, path, ext=None, start=None, stop=None, recursive=False, npartitions=None):
"""
Sets up Spark RDD across S3 or GS objects specified by dataPath.
Returns RDD of <string bucket keyname, string buffer> k/v pairs.
"""
from .utils import connection_with_anon, connection... | python | def read(self, path, ext=None, start=None, stop=None, recursive=False, npartitions=None):
"""
Sets up Spark RDD across S3 or GS objects specified by dataPath.
Returns RDD of <string bucket keyname, string buffer> k/v pairs.
"""
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12,356 | thunder-project/thunder | thunder/readers.py | BotoFileReader.getkeys | def getkeys(self, path, filename=None, directories=False, recursive=False):
"""
Get matching keys for a path
"""
from .utils import connection_with_anon, connection_with_gs
parse = BotoClient.parse_query(path)
scheme = parse[0]
bucket_name = parse[1]
key... | python | def getkeys(self, path, filename=None, directories=False, recursive=False):
"""
Get matching keys for a path
"""
from .utils import connection_with_anon, connection_with_gs
parse = BotoClient.parse_query(path)
scheme = parse[0]
bucket_name = parse[1]
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12,357 | thunder-project/thunder | thunder/readers.py | BotoFileReader.getkey | def getkey(self, path, filename=None):
"""
Get single matching key for a path
"""
scheme, keys = self.getkeys(path, filename=filename)
try:
key = next(keys)
except StopIteration:
raise FileNotFoundError("Could not find object for: '%s'" % path)
... | python | def getkey(self, path, filename=None):
"""
Get single matching key for a path
"""
scheme, keys = self.getkeys(path, filename=filename)
try:
key = next(keys)
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raise FileNotFoundError("Could not find object for: '%s'" % path)
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12,358 | thunder-project/thunder | thunder/readers.py | BotoFileReader.list | def list(self, path, filename=None, start=None, stop=None, recursive=False, directories=False):
"""
List objects specified by path.
Returns sorted list of 'gs://' or 's3n://' URIs.
"""
storageScheme, keys = self.getkeys(
path, filename=filename, directories=directori... | python | def list(self, path, filename=None, start=None, stop=None, recursive=False, directories=False):
"""
List objects specified by path.
Returns sorted list of 'gs://' or 's3n://' URIs.
"""
storageScheme, keys = self.getkeys(
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12,359 | thunder-project/thunder | thunder/readers.py | BotoFileReader.read | def read(self, path, filename=None, offset=None, size=-1):
"""
Read a file specified by path.
"""
storageScheme, key = self.getkey(path, filename=filename)
if offset or (size > -1):
if not offset:
offset = 0
if size > -1:
s... | python | def read(self, path, filename=None, offset=None, size=-1):
"""
Read a file specified by path.
"""
storageScheme, key = self.getkey(path, filename=filename)
if offset or (size > -1):
if not offset:
offset = 0
if size > -1:
s... | [
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12,360 | thunder-project/thunder | thunder/readers.py | BotoFileReader.open | def open(self, path, filename=None):
"""
Open a file specified by path.
"""
scheme, key = self.getkey(path, filename=filename)
return BotoReadFileHandle(scheme, key) | python | def open(self, path, filename=None):
"""
Open a file specified by path.
"""
scheme, key = self.getkey(path, filename=filename)
return BotoReadFileHandle(scheme, key) | [
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12,361 | thunder-project/thunder | thunder/utils.py | check_path | def check_path(path, credentials=None):
"""
Check that specified output path does not already exist
The ValueError message will suggest calling with overwrite=True;
this function is expected to be called from the various output methods
that accept an 'overwrite' keyword argument.
"""
from t... | python | def check_path(path, credentials=None):
"""
Check that specified output path does not already exist
The ValueError message will suggest calling with overwrite=True;
this function is expected to be called from the various output methods
that accept an 'overwrite' keyword argument.
"""
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12,362 | thunder-project/thunder | thunder/utils.py | connection_with_anon | def connection_with_anon(credentials, anon=True):
"""
Connect to S3 with automatic handling for anonymous access.
Parameters
----------
credentials : dict
AWS access key ('access') and secret access key ('secret')
anon : boolean, optional, default = True
Whether to make an anon... | python | def connection_with_anon(credentials, anon=True):
"""
Connect to S3 with automatic handling for anonymous access.
Parameters
----------
credentials : dict
AWS access key ('access') and secret access key ('secret')
anon : boolean, optional, default = True
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12,363 | thunder-project/thunder | thunder/writers.py | BotoWriter.activate | def activate(self, path, isdirectory):
"""
Set up a boto connection.
"""
from .utils import connection_with_anon, connection_with_gs
parsed = BotoClient.parse_query(path)
scheme = parsed[0]
bucket_name = parsed[1]
key = parsed[2]
if scheme == 's... | python | def activate(self, path, isdirectory):
"""
Set up a boto connection.
"""
from .utils import connection_with_anon, connection_with_gs
parsed = BotoClient.parse_query(path)
scheme = parsed[0]
bucket_name = parsed[1]
key = parsed[2]
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12,364 | thunder-project/thunder | thunder/images/writers.py | topng | def topng(images, path, prefix="image", overwrite=False, credentials=None):
"""
Write out PNG files for 2d image data.
See also
--------
thunder.data.images.topng
"""
value_shape = images.value_shape
if not len(value_shape) in [2, 3]:
raise ValueError("Only 2D or 3D images can b... | python | def topng(images, path, prefix="image", overwrite=False, credentials=None):
"""
Write out PNG files for 2d image data.
See also
--------
thunder.data.images.topng
"""
value_shape = images.value_shape
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12,365 | thunder-project/thunder | thunder/images/writers.py | tobinary | def tobinary(images, path, prefix="image", overwrite=False, credentials=None):
"""
Write out images as binary files.
See also
--------
thunder.data.images.tobinary
"""
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key, img = kv
fname = prefix + "-" +... | python | def tobinary(images, path, prefix="image", overwrite=False, credentials=None):
"""
Write out images as binary files.
See also
--------
thunder.data.images.tobinary
"""
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12,366 | lidaobing/python-lunardate | lunardate.py | yearInfo2yearDay | def yearInfo2yearDay(yearInfo):
'''calculate the days in a lunar year from the lunar year's info
>>> yearInfo2yearDay(0) # no leap month, and every month has 29 days.
348
>>> yearInfo2yearDay(1) # 1 leap month, and every month has 29 days.
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>>> yearInfo2yearDay((2**12-1)*16) # no leap month,... | python | def yearInfo2yearDay(yearInfo):
'''calculate the days in a lunar year from the lunar year's info
>>> yearInfo2yearDay(0) # no leap month, and every month has 29 days.
348
>>> yearInfo2yearDay(1) # 1 leap month, and every month has 29 days.
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12,367 | plone/plone.app.mosaic | src/plone/app/mosaic/browser/upload.py | MosaicUploadView.cleanupFilename | def cleanupFilename(self, name):
"""Generate a unique id which doesn't match the system generated ids"""
context = self.context
id = ''
name = name.replace('\\', '/') # Fixup Windows filenames
name = name.split('/')[-1] # Throw away any path part.
for c in name:
... | python | def cleanupFilename(self, name):
"""Generate a unique id which doesn't match the system generated ids"""
context = self.context
id = ''
name = name.replace('\\', '/') # Fixup Windows filenames
name = name.split('/')[-1] # Throw away any path part.
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12,368 | plone/plone.app.mosaic | src/plone/app/mosaic/browser/main_template.py | parse_data_slots | def parse_data_slots(value):
"""Parse data-slots value into slots used to wrap node, prepend to node or
append to node.
>>> parse_data_slots('')
([], [], [])
>>> parse_data_slots('foo bar')
(['foo', 'bar'], [], [])
>>> parse_data_slots('foo bar > foobar')
(['foo', 'b... | python | def parse_data_slots(value):
"""Parse data-slots value into slots used to wrap node, prepend to node or
append to node.
>>> parse_data_slots('')
([], [], [])
>>> parse_data_slots('foo bar')
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12,369 | plone/plone.app.mosaic | src/plone/app/mosaic/browser/main_template.py | cook_layout | def cook_layout(layout, ajax):
"""Return main_template compatible layout"""
# Fix XHTML layouts with CR[+LF] line endings
layout = re.sub('\r', '\n', re.sub('\r\n', '\n', layout))
# Parse layout
if isinstance(layout, six.text_type):
result = getHTMLSerializer([layout.encode('utf-8')], encod... | python | def cook_layout(layout, ajax):
"""Return main_template compatible layout"""
# Fix XHTML layouts with CR[+LF] line endings
layout = re.sub('\r', '\n', re.sub('\r\n', '\n', layout))
# Parse layout
if isinstance(layout, six.text_type):
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12,370 | plone/plone.app.mosaic | src/plone/app/mosaic/browser/editor.py | ManageLayoutView.existing | def existing(self):
""" find existing content assigned to this layout"""
catalog = api.portal.get_tool('portal_catalog')
results = []
layout_path = self._get_layout_path(
self.request.form.get('layout', '')
)
for brain in catalog(layout=layout_path):
... | python | def existing(self):
""" find existing content assigned to this layout"""
catalog = api.portal.get_tool('portal_catalog')
results = []
layout_path = self._get_layout_path(
self.request.form.get('layout', '')
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12,371 | sergiocorreia/panflute | panflute/io.py | load_reader_options | def load_reader_options():
"""
Retrieve Pandoc Reader options from the environment
"""
options = os.environ['PANDOC_READER_OPTIONS']
options = json.loads(options, object_pairs_hook=OrderedDict)
return options | python | def load_reader_options():
"""
Retrieve Pandoc Reader options from the environment
"""
options = os.environ['PANDOC_READER_OPTIONS']
options = json.loads(options, object_pairs_hook=OrderedDict)
return options | [
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12,372 | sergiocorreia/panflute | panflute/tools.py | yaml_filter | def yaml_filter(element, doc, tag=None, function=None, tags=None,
strict_yaml=False):
'''
Convenience function for parsing code blocks with YAML options
This function is useful to create a filter that applies to
code blocks that have specific classes.
It is used as an argument of `... | python | def yaml_filter(element, doc, tag=None, function=None, tags=None,
strict_yaml=False):
'''
Convenience function for parsing code blocks with YAML options
This function is useful to create a filter that applies to
code blocks that have specific classes.
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12,373 | sergiocorreia/panflute | panflute/base.py | Element._set_content | def _set_content(self, value, oktypes):
"""
Similar to content.setter but when there are no existing oktypes
"""
if value is None:
value = []
self._content = ListContainer(*value, oktypes=oktypes, parent=self) | python | def _set_content(self, value, oktypes):
"""
Similar to content.setter but when there are no existing oktypes
"""
if value is None:
value = []
self._content = ListContainer(*value, oktypes=oktypes, parent=self) | [
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12,374 | sergiocorreia/panflute | panflute/base.py | Element.offset | def offset(self, n):
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:rtype: :class:`Element` | ``None``
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if idx is not None:
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if idx is not None:
sibling = idx + n
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12,375 | laike9m/pdir2 | pdir/api.py | PrettyDir.search | def search(self, term: str, case_sensitive: bool = False) -> 'PrettyDir':
"""Searches for names that match some pattern.
Args:
term: String used to match names. A name is returned if it matches
the whole search term.
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term: String used to match names. A name is returned if it matches
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12,376 | laike9m/pdir2 | pdir/api.py | PrettyDir.properties | def properties(self) -> 'PrettyDir':
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12,377 | laike9m/pdir2 | pdir/api.py | PrettyDir.methods | def methods(self) -> 'PrettyDir':
"""Returns all methods of the inspected object.
Note that "methods" can mean "functions" when inspecting a module.
"""
return PrettyDir(
self.obj,
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"""Returns all methods of the inspected object.
Note that "methods" can mean "functions" when inspecting a module.
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12,378 | laike9m/pdir2 | pdir/api.py | PrettyDir.public | def public(self) -> 'PrettyDir':
"""Returns public attributes of the inspected object."""
return PrettyDir(
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) | python | def public(self) -> 'PrettyDir':
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12,379 | laike9m/pdir2 | pdir/api.py | PrettyDir.own | def own(self) -> 'PrettyDir':
"""Returns attributes that are not inhterited from parent classes.
Now we only use a simple judgement, it is expected that many attributes
not get returned, especially invoked on a module.
For instance, there's no way to distinguish between properties that... | python | def own(self) -> 'PrettyDir':
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12,380 | laike9m/pdir2 | pdir/api.py | PrettyAttribute.get_oneline_doc | def get_oneline_doc(self) -> str:
"""
Doc doesn't necessarily mean doctring. It could be anything that
should be put after the attr's name as an explanation.
"""
attr = self.attr_obj
if self.display_group == AttrCategory.DESCRIPTOR:
if isinstance(attr, propert... | python | def get_oneline_doc(self) -> str:
"""
Doc doesn't necessarily mean doctring. It could be anything that
should be put after the attr's name as an explanation.
"""
attr = self.attr_obj
if self.display_group == AttrCategory.DESCRIPTOR:
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12,381 | laike9m/pdir2 | pdir/format.py | format_pattrs | def format_pattrs(pattrs: List['api.PrettyAttribute']) -> str:
"""Generates repr string given a list of pattrs."""
output = []
pattrs.sort(
key=lambda x: (
_FORMATTER[x.display_group].display_index,
x.display_group,
x.name,
)
)
for display_group, g... | python | def format_pattrs(pattrs: List['api.PrettyAttribute']) -> str:
"""Generates repr string given a list of pattrs."""
output = []
pattrs.sort(
key=lambda x: (
_FORMATTER[x.display_group].display_index,
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12,382 | laike9m/pdir2 | pdir/_internal_utils.py | get_attr_from_dict | def get_attr_from_dict(inspected_obj: Any, attr_name: str) -> Any:
"""Ensures we get descriptor object instead of its return value.
"""
if inspect.isclass(inspected_obj):
obj_list = [inspected_obj] + list(inspected_obj.__mro__)
else:
obj_list = [inspected_obj] + list(inspected_obj.__clas... | python | def get_attr_from_dict(inspected_obj: Any, attr_name: str) -> Any:
"""Ensures we get descriptor object instead of its return value.
"""
if inspect.isclass(inspected_obj):
obj_list = [inspected_obj] + list(inspected_obj.__mro__)
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obj_list = [inspected_obj] + list(inspected_obj.__clas... | [
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12,383 | laike9m/pdir2 | pdir/attr_category.py | attr_category_postprocess | def attr_category_postprocess(get_attr_category_func):
"""Unifies attr_category to a tuple, add AttrCategory.SLOT if needed."""
@functools.wraps(get_attr_category_func)
def wrapped(
name: str, attr: Any, obj: Any
) -> Tuple[AttrCategory, ...]:
category = get_attr_category_func(name, attr... | python | def attr_category_postprocess(get_attr_category_func):
"""Unifies attr_category to a tuple, add AttrCategory.SLOT if needed."""
@functools.wraps(get_attr_category_func)
def wrapped(
name: str, attr: Any, obj: Any
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12,384 | mattloper/chumpy | chumpy/monitor.py | get_peak_mem | def get_peak_mem():
'''
this returns peak memory use since process starts till the moment its called
'''
import resource
rusage_denom = 1024.
if sys.platform == 'darwin':
# ... it seems that in OSX the output is different units ...
rusage_denom = rusage_denom * rusage_denom
m... | python | def get_peak_mem():
'''
this returns peak memory use since process starts till the moment its called
'''
import resource
rusage_denom = 1024.
if sys.platform == 'darwin':
# ... it seems that in OSX the output is different units ...
rusage_denom = rusage_denom * rusage_denom
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12,385 | mattloper/chumpy | chumpy/utils.py | dfs_do_func_on_graph | def dfs_do_func_on_graph(node, func, *args, **kwargs):
'''
invoke func on each node of the dr graph
'''
for _node in node.tree_iterator():
func(_node, *args, **kwargs) | python | def dfs_do_func_on_graph(node, func, *args, **kwargs):
'''
invoke func on each node of the dr graph
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12,386 | mattloper/chumpy | chumpy/utils.py | sparse_is_desireable | def sparse_is_desireable(lhs, rhs):
'''
Examines a pair of matrices and determines if the result of their multiplication should be sparse or not.
'''
return False
if len(lhs.shape) == 1:
return False
else:
lhs_rows, lhs_cols = lhs.shape
if len(rhs.shape) == 1:
rhs_ro... | python | def sparse_is_desireable(lhs, rhs):
'''
Examines a pair of matrices and determines if the result of their multiplication should be sparse or not.
'''
return False
if len(lhs.shape) == 1:
return False
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lhs_rows, lhs_cols = lhs.shape
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12,387 | mattloper/chumpy | chumpy/utils.py | convert_inputs_to_sparse_if_necessary | def convert_inputs_to_sparse_if_necessary(lhs, rhs):
'''
This function checks to see if a sparse output is desireable given the inputs and if so, casts the inputs to sparse in order to make it so.
'''
if not sp.issparse(lhs) or not sp.issparse(rhs):
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... | python | def convert_inputs_to_sparse_if_necessary(lhs, rhs):
'''
This function checks to see if a sparse output is desireable given the inputs and if so, casts the inputs to sparse in order to make it so.
'''
if not sp.issparse(lhs) or not sp.issparse(rhs):
if sparse_is_desireable(lhs, rhs):
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12,388 | mattloper/chumpy | chumpy/optimization_internal.py | ChInputsStacked.dr_wrt | def dr_wrt(self, wrt, profiler=None):
'''
Loop over free variables and delete cache for the whole tree after finished each one
'''
if wrt is self.x:
jacs = []
for fvi, freevar in enumerate(self.free_variables):
tm = timer()
if isins... | python | def dr_wrt(self, wrt, profiler=None):
'''
Loop over free variables and delete cache for the whole tree after finished each one
'''
if wrt is self.x:
jacs = []
for fvi, freevar in enumerate(self.free_variables):
tm = timer()
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12,389 | mattloper/chumpy | chumpy/optimization_internal.py | ChInputsStacked.J | def J(self):
'''
Compute Jacobian. Analyze dr graph first to disable unnecessary caching
'''
result = self.dr_wrt(self.x, profiler=self.profiler).copy()
if self.profiler:
self.profiler.harvest()
return np.atleast_2d(result) if not sp.issparse(result) else resu... | python | def J(self):
'''
Compute Jacobian. Analyze dr graph first to disable unnecessary caching
'''
result = self.dr_wrt(self.x, profiler=self.profiler).copy()
if self.profiler:
self.profiler.harvest()
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12,390 | mattloper/chumpy | chumpy/ch.py | Ch.sid | def sid(self):
"""Semantic id."""
pnames = list(self.terms)+list(self.dterms)
pnames.sort()
return (self.__class__, tuple([(k, id(self.__dict__[k])) for k in pnames if k in self.__dict__])) | python | def sid(self):
"""Semantic id."""
pnames = list(self.terms)+list(self.dterms)
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12,391 | mattloper/chumpy | chumpy/ch.py | Ch.compute_dr_wrt | def compute_dr_wrt(self,wrt):
"""Default method for objects that just contain a number or ndarray"""
if wrt is self: # special base case
return sp.eye(self.x.size, self.x.size)
#return np.array([[1]])
return None | python | def compute_dr_wrt(self,wrt):
"""Default method for objects that just contain a number or ndarray"""
if wrt is self: # special base case
return sp.eye(self.x.size, self.x.size)
#return np.array([[1]])
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12,392 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils.get_ubuntu_release_from_sentry | def get_ubuntu_release_from_sentry(self, sentry_unit):
"""Get Ubuntu release codename from sentry unit.
:param sentry_unit: amulet sentry/service unit pointer
:returns: list of strings - release codename, failure message
"""
msg = None
cmd = 'lsb_release -cs'
rel... | python | def get_ubuntu_release_from_sentry(self, sentry_unit):
"""Get Ubuntu release codename from sentry unit.
:param sentry_unit: amulet sentry/service unit pointer
:returns: list of strings - release codename, failure message
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msg = None
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12,393 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils.validate_services | def validate_services(self, commands):
"""Validate that lists of commands succeed on service units. Can be
used to verify system services are running on the corresponding
service units.
:param commands: dict with sentry keys and arbitrary command list vals
:returns: None ... | python | def validate_services(self, commands):
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:param commands: dict with sentry keys and arbitrary command list vals
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:param commands: dict with sentry keys and arbitrary command list vals
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12,394 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils.validate_services_by_name | def validate_services_by_name(self, sentry_services):
"""Validate system service status by service name, automatically
detecting init system based on Ubuntu release codename.
:param sentry_services: dict with sentry keys and svc list values
:returns: None if successful, Failure strin... | python | def validate_services_by_name(self, sentry_services):
"""Validate system service status by service name, automatically
detecting init system based on Ubuntu release codename.
:param sentry_services: dict with sentry keys and svc list values
:returns: None if successful, Failure strin... | [
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12,395 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils._get_config | def _get_config(self, unit, filename):
"""Get a ConfigParser object for parsing a unit's config file."""
file_contents = unit.file_contents(filename)
# NOTE(beisner): by default, ConfigParser does not handle options
# with no value, such as the flags used in the mysql my.cnf file.
... | python | def _get_config(self, unit, filename):
"""Get a ConfigParser object for parsing a unit's config file."""
file_contents = unit.file_contents(filename)
# NOTE(beisner): by default, ConfigParser does not handle options
# with no value, such as the flags used in the mysql my.cnf file.
... | [
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12,396 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils.validate_config_data | def validate_config_data(self, sentry_unit, config_file, section,
expected):
"""Validate config file data.
Verify that the specified section of the config file contains
the expected option key:value pairs.
Compare expected dictionary data vs actual... | python | def validate_config_data(self, sentry_unit, config_file, section,
expected):
"""Validate config file data.
Verify that the specified section of the config file contains
the expected option key:value pairs.
Compare expected dictionary data vs actual... | [
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Verify that the specified section of the config file contains
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Compare expected dictionary data vs actual dictionary data.
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12,397 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils._validate_dict_data | def _validate_dict_data(self, expected, actual):
"""Validate dictionary data.
Compare expected dictionary data vs actual dictionary data.
The values in the 'expected' dictionary can be strings, bools, ints,
longs, or can be a function that evaluates a variable and returns a
... | python | def _validate_dict_data(self, expected, actual):
"""Validate dictionary data.
Compare expected dictionary data vs actual dictionary data.
The values in the 'expected' dictionary can be strings, bools, ints,
longs, or can be a function that evaluates a variable and returns a
... | [
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Compare expected dictionary data vs actual dictionary data.
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bool. | [
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] | aa785c40c3b7a8c69dbfbc7921d6b9f30142e171 | https://github.com/juju/charm-helpers/blob/aa785c40c3b7a8c69dbfbc7921d6b9f30142e171/charmhelpers/contrib/amulet/utils.py#L221-L245 |
12,398 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils.validate_relation_data | def validate_relation_data(self, sentry_unit, relation, expected):
"""Validate actual relation data based on expected relation data."""
actual = sentry_unit.relation(relation[0], relation[1])
return self._validate_dict_data(expected, actual) | python | def validate_relation_data(self, sentry_unit, relation, expected):
"""Validate actual relation data based on expected relation data."""
actual = sentry_unit.relation(relation[0], relation[1])
return self._validate_dict_data(expected, actual) | [
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12,399 | juju/charm-helpers | charmhelpers/contrib/amulet/utils.py | AmuletUtils._validate_list_data | def _validate_list_data(self, expected, actual):
"""Compare expected list vs actual list data."""
for e in expected:
if e not in actual:
return "expected item {} not found in actual list".format(e)
return None | python | def _validate_list_data(self, expected, actual):
"""Compare expected list vs actual list data."""
for e in expected:
if e not in actual:
return "expected item {} not found in actual list".format(e)
return None | [
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