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google-research/batch-ppo | agents/tools/loop.py | Loop._find_current_phase | def _find_current_phase(self, global_step):
"""Determine the current phase based on the global step.
This ensures continuing the correct phase after restoring checkoints.
Args:
global_step: The global number of steps performed across all phases.
Returns:
Tuple of phase object, epoch numbe... | python | def _find_current_phase(self, global_step):
"""Determine the current phase based on the global step.
This ensures continuing the correct phase after restoring checkoints.
Args:
global_step: The global number of steps performed across all phases.
Returns:
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google-research/batch-ppo | agents/tools/loop.py | Loop._define_step | def _define_step(self, done, score, summary):
"""Combine operations of a phase.
Keeps track of the mean score and when to report it.
Args:
done: Tensor indicating whether current score can be used.
score: Tensor holding the current, possibly intermediate, score.
summary: Tensor holding s... | python | def _define_step(self, done, score, summary):
"""Combine operations of a phase.
Keeps track of the mean score and when to report it.
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done: Tensor indicating whether current score can be used.
score: Tensor holding the current, possibly intermediate, score.
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google-research/batch-ppo | agents/tools/loop.py | Loop._store_checkpoint | def _store_checkpoint(self, sess, saver, global_step):
"""Store a checkpoint if a log directory was provided to the constructor.
The directory will be created if needed.
Args:
sess: Session containing variables to store.
saver: Saver used for checkpointing.
global_step: Step number of th... | python | def _store_checkpoint(self, sess, saver, global_step):
"""Store a checkpoint if a log directory was provided to the constructor.
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Args:
sess: Session containing variables to store.
saver: Saver used for checkpointing.
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google-research/batch-ppo | agents/scripts/train.py | _define_loop | def _define_loop(graph, logdir, train_steps, eval_steps):
"""Create and configure a training loop with training and evaluation phases.
Args:
graph: Object providing graph elements via attributes.
logdir: Log directory for storing checkpoints and summaries.
train_steps: Number of training steps per epoc... | python | def _define_loop(graph, logdir, train_steps, eval_steps):
"""Create and configure a training loop with training and evaluation phases.
Args:
graph: Object providing graph elements via attributes.
logdir: Log directory for storing checkpoints and summaries.
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google-research/batch-ppo | agents/scripts/train.py | train | def train(config, env_processes):
"""Training and evaluation entry point yielding scores.
Resolves some configuration attributes, creates environments, graph, and
training loop. By default, assigns all operations to the CPU.
Args:
config: Object providing configurations via attributes.
env_processes: ... | python | def train(config, env_processes):
"""Training and evaluation entry point yielding scores.
Resolves some configuration attributes, creates environments, graph, and
training loop. By default, assigns all operations to the CPU.
Args:
config: Object providing configurations via attributes.
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google-research/batch-ppo | agents/scripts/train.py | main | def main(_):
"""Create or load configuration and launch the trainer."""
utility.set_up_logging()
if not FLAGS.config:
raise KeyError('You must specify a configuration.')
logdir = FLAGS.logdir and os.path.expanduser(os.path.join(
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try:
... | python | def main(_):
"""Create or load configuration and launch the trainer."""
utility.set_up_logging()
if not FLAGS.config:
raise KeyError('You must specify a configuration.')
logdir = FLAGS.logdir and os.path.expanduser(os.path.join(
FLAGS.logdir, '{}-{}'.format(FLAGS.timestamp, FLAGS.config)))
try:
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google-research/batch-ppo | agents/parts/iterate_sequences.py | iterate_sequences | def iterate_sequences(
consumer_fn, output_template, sequences, length, chunk_length=None,
batch_size=None, num_epochs=1, padding_value=0):
"""Iterate over batches of chunks of sequences for multiple epochs.
The batch dimension of the length tensor must be set because it is used to
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batch_size=None, num_epochs=1, padding_value=0):
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The batch dimension of the length tensor must be set because it is used to
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google-research/batch-ppo | agents/parts/iterate_sequences.py | chunk_sequence | def chunk_sequence(sequence, chunk_length=200, padding_value=0):
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This function does not expect a batch of sequences, but a single sequence. A
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"""Split a nested dict of sequence tensors into a batch of chunks.
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google-research/batch-ppo | agents/parts/iterate_sequences.py | remove_padding | def remove_padding(sequence):
"""Selects the used frames of a sequence, up to its length.
This function does not expect a batch of sequences, but a single sequence.
The sequence must be a dict with `length` key, which will removed from the
result.
Args:
sequence: Nested dict of tensors with time dimensi... | python | def remove_padding(sequence):
"""Selects the used frames of a sequence, up to its length.
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize.transform | def transform(self, value):
"""Normalize a single or batch tensor.
Applies the activated transformations in the constructor using current
estimates of mean and variance.
Args:
value: Batch or single value tensor.
Returns:
Normalized batch or single value tensor.
"""
with tf.na... | python | def transform(self, value):
"""Normalize a single or batch tensor.
Applies the activated transformations in the constructor using current
estimates of mean and variance.
Args:
value: Batch or single value tensor.
Returns:
Normalized batch or single value tensor.
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize.update | def update(self, value):
"""Update the mean and variance estimates.
Args:
value: Batch or single value tensor.
Returns:
Summary tensor.
"""
with tf.name_scope(self._name + '/update'):
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# Add a batch dimension if necessary.
... | python | def update(self, value):
"""Update the mean and variance estimates.
Args:
value: Batch or single value tensor.
Returns:
Summary tensor.
"""
with tf.name_scope(self._name + '/update'):
if value.shape.ndims == self._mean.shape.ndims:
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize.reset | def reset(self):
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self... | python | def reset(self):
"""Reset the estimates of mean and variance.
Resets the full state of this class.
Returns:
Operation.
"""
with tf.name_scope(self._name + '/reset'):
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize.summary | def summary(self):
"""Summary string of mean and standard deviation.
Returns:
Summary tensor.
"""
with tf.name_scope(self._name + '/summary'):
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self._coun... | python | def summary(self):
"""Summary string of mean and standard deviation.
Returns:
Summary tensor.
"""
with tf.name_scope(self._name + '/summary'):
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize._std | def _std(self):
"""Computes the current estimate of the standard deviation.
Note that the standard deviation is not defined until at least two samples
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Returns:
Tensor of current variance.
"""
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Note that the standard deviation is not defined until at least two samples
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Returns:
Tensor of current variance.
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google-research/batch-ppo | agents/parts/normalize.py | StreamingNormalize._summary | def _summary(self, name, tensor):
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Args:
name: Name for the summary.
tensor: Tensor to summarize.
Returns:
Summary tensor.
"""
if tensor.shape.ndims == 0:
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else... | python | def _summary(self, name, tensor):
"""Create a scalar or histogram summary matching the rank of the tensor.
Args:
name: Name for the summary.
tensor: Tensor to summarize.
Returns:
Summary tensor.
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google-research/batch-ppo | agents/parts/memory.py | EpisodeMemory.length | def length(self, rows=None):
"""Tensor holding the current length of episodes.
Args:
rows: Episodes to select length from, defaults to all.
Returns:
Batch tensor of sequence lengths.
"""
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Args:
rows: Episodes to select length from, defaults to all.
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space: Gym space.
Raises:
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Returns:
Shape tuple.
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"""Get a tensor shape from a OpenAI Gym space.
Args:
space: Gym space.
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO.begin_episode | def begin_episode(self, agent_indices):
"""Reset the recurrent states and stored episode.
Args:
agent_indices: Tensor containing current batch indices.
Returns:
Summary tensor.
"""
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Args:
agent_indices: Tensor containing current batch indices.
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Summary tensor.
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agent_indices: Tensor containing current batch indices.
observ: Tensor of a batch of observations for all agents.
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._initialize_policy | def _initialize_policy(self):
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"""Initialize the policy.
Run the policy network on dummy data to initialize its parameters for later
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._training | def _training(self):
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Returns:
Summary tensor.
"""
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Summary tensor.
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._update_step | def _update_step(self, sequence):
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._value_loss | def _value_loss(self, observ, reward, length):
"""Compute the loss function for the value baseline.
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._policy_loss | def _policy_loss(
self, old_policy, policy, action, advantage, length):
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._adjust_penalty | def _adjust_penalty(self, observ, old_policy_params, length):
"""Adjust the KL policy between the behavioral and current policy.
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"""Adjust the KL policy between the behavioral and current policy.
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google-research/batch-ppo | agents/algorithms/ppo/ppo.py | PPO._mask | def _mask(self, tensor, length, padding_value=0):
"""Set padding elements of a batch of sequences to a constant.
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celery/cell | cell/workflow/entities.py | Server.main | def main(self, *args, **kwargs):
"""Implement the actor main loop by waiting forever for messages."""
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"""Implement the actor main loop by waiting forever for messages."""
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celery/cell | cell/actors.py | Actor.send | def send(self, method, args={}, to=None, nowait=False, **kwargs):
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celery/cell | cell/actors.py | Actor.throw | def throw(self, method, args={}, nowait=False, **kwargs):
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celery/cell | cell/actors.py | Actor.scatter | def scatter(self, method, args={}, nowait=False, timeout=None, **kwargs):
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celery/cell | cell/actors.py | Actor.call_or_cast | def call_or_cast(self, method, args={}, nowait=False, **kwargs):
"""Apply remote `method` asynchronously or synchronously depending
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:param method: The name of the remote method to perform.
:param args: Dictionary of arguments for the method.
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celery/cell | cell/actors.py | Actor.cast | def cast(self, method, args={}, declare=None, retry=None,
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retry = self.retry if retry is None else retry
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celery/cell | cell/actors.py | Actor.handle_call | def handle_call(self, body, message):
"""Handle call message."""
try:
r = self._DISPATCH(body, ticket=message.properties['reply_to'])
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# don't reply, delegate to other agents.
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self.reply(message, r) | python | def handle_call(self, body, message):
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try:
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celery/cell | cell/bin/base.py | Command.parse_options | def parse_options(self, prog_name, arguments):
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# Don't want to load configuration to just print the version,
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parser = ... | python | def parse_options(self, prog_name, arguments):
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celery/cell | cell/results.py | AsyncResult.get | def get(self, **kwargs):
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celery/cell | cell/results.py | AsyncResult._gather | def _gather(self, *args, **kwargs):
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yhat/pandasql | pandasql/sqldf.py | extract_table_names | def extract_table_names(query):
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bsmurphy/PyKrige | benchmarks/kriging_benchmarks.py | make_benchark | def make_benchark(n_train, n_test, n_dim=2):
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----------
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number of points in the training set
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number of points in the test set
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bsmurphy/PyKrige | benchmarks/kriging_benchmarks.py | print_benchmark | def print_benchmark(n_train, n_test, n_dim, res):
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number of points in the test set
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bsmurphy/PyKrige | pykrige/core.py | _adjust_for_anisotropy | def _adjust_for_anisotropy(X, center, scaling, angle):
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Can also be used to take into account data scaling. Angles are CCW about
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X : ndarray
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bsmurphy/PyKrige | pykrige/core.py | _calculate_variogram_model | def _calculate_variogram_model(lags, semivariance, variogram_model,
variogram_function, weight):
"""Function that fits a variogram model when parameters are not specified.
Returns variogram model parameters that minimize the RMSE between the
specified variogram function and th... | python | def _calculate_variogram_model(lags, semivariance, variogram_model,
variogram_function, weight):
"""Function that fits a variogram model when parameters are not specified.
Returns variogram model parameters that minimize the RMSE between the
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bsmurphy/PyKrige | pykrige/core.py | _krige | def _krige(X, y, coords, variogram_function,
variogram_model_parameters, coordinates_type):
"""Sets up and solves the ordinary kriging system for the given
coordinate pair. This function is only used for the statistics calculations.
Parameters
----------
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float array [n... | python | def _krige(X, y, coords, variogram_function,
variogram_model_parameters, coordinates_type):
"""Sets up and solves the ordinary kriging system for the given
coordinate pair. This function is only used for the statistics calculations.
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bsmurphy/PyKrige | pykrige/core.py | _find_statistics | def _find_statistics(X, y, variogram_function,
variogram_model_parameters, coordinates_type):
"""Calculates variogram fit statistics.
Returns the delta, sigma, and epsilon values for the variogram fit.
These arrays are used for statistics calculations.
Parameters
----------
... | python | def _find_statistics(X, y, variogram_function,
variogram_model_parameters, coordinates_type):
"""Calculates variogram fit statistics.
Returns the delta, sigma, and epsilon values for the variogram fit.
These arrays are used for statistics calculations.
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bsmurphy/PyKrige | pykrige/rk.py | RegressionKriging.fit | def fit(self, p, x, y):
"""
fit the regression method and also Krige the residual
Parameters
----------
p: ndarray
(Ns, d) array of predictor variables (Ns samples, d dimensions)
for regression
x: ndarray
ndarray of (x, y) points. Need... | python | def fit(self, p, x, y):
"""
fit the regression method and also Krige the residual
Parameters
----------
p: ndarray
(Ns, d) array of predictor variables (Ns samples, d dimensions)
for regression
x: ndarray
ndarray of (x, y) points. Need... | [
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bsmurphy/PyKrige | pykrige/rk.py | RegressionKriging.score | def score(self, p, x, y, sample_weight=None):
"""
Overloading default regression score method
Parameters
----------
p: ndarray
(Ns, d) array of predictor variables (Ns samples, d dimensions)
for regression
x: ndarray
ndarray of (x, y) ... | python | def score(self, p, x, y, sample_weight=None):
"""
Overloading default regression score method
Parameters
----------
p: ndarray
(Ns, d) array of predictor variables (Ns samples, d dimensions)
for regression
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bsmurphy/PyKrige | pykrige/ok3d.py | OrdinaryKriging3D._exec_loop_moving_window | def _exec_loop_moving_window(self, a_all, bd_all, mask, bd_idx):
"""Solves the kriging system by looping over all specified points.
Uses only a certain number of closest points. Not very memory intensive,
but the loop is done in pure Python.
"""
import scipy.linalg.lapack
... | python | def _exec_loop_moving_window(self, a_all, bd_all, mask, bd_idx):
"""Solves the kriging system by looping over all specified points.
Uses only a certain number of closest points. Not very memory intensive,
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import scipy.linalg.lapack
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limodou/uliweb | uliweb/lib/werkzeug/debug/util.py | get_frame_info | def get_frame_info(tb, context_lines=7, simple=False):
"""
Return a dict of information about a given traceback.
"""
# line numbers / function / variables
lineno = tb.tb_lineno
function = tb.tb_frame.f_code.co_name
variables = tb.tb_frame.f_locals
files = {}
# get filename
if s... | python | def get_frame_info(tb, context_lines=7, simple=False):
"""
Return a dict of information about a given traceback.
"""
# line numbers / function / variables
lineno = tb.tb_lineno
function = tb.tb_frame.f_code.co_name
variables = tb.tb_frame.f_locals
files = {}
# get filename
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limodou/uliweb | uliweb/lib/werkzeug/debug/util.py | PythonParser.get_html_output | def get_html_output(self):
""" Return line generator. """
def html_splitlines(lines):
# this cool function was taken from trac.
# http://projects.edgewall.com/trac/
open_tag_re = re.compile(r'<(\w+)(\s.*)?[^/]?>')
close_tag_re = re.compile(r'</(\w+)>')
... | python | def get_html_output(self):
""" Return line generator. """
def html_splitlines(lines):
# this cool function was taken from trac.
# http://projects.edgewall.com/trac/
open_tag_re = re.compile(r'<(\w+)(\s.*)?[^/]?>')
close_tag_re = re.compile(r'</(\w+)>')
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limodou/uliweb | uliweb/utils/generic.py | get_columns | def get_columns(model=None, fields=None, meta=None):
"""
Get model columns list
"""
if model:
M = get_model(model)
else:
M = None
if fields is not None:
f = fields
if M:
if meta and hasattr(M, meta):
m = getattr(model, meta)
... | python | def get_columns(model=None, fields=None, meta=None):
"""
Get model columns list
"""
if model:
M = get_model(model)
else:
M = None
if fields is not None:
f = fields
if M:
if meta and hasattr(M, meta):
m = getattr(model, meta)
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limodou/uliweb | uliweb/utils/generic.py | get_field | def get_field(name, model=None):
"""
get model field according to name, the name can be like `model.column`
"""
if '.' in name:
m, name = name.split('.')
model = get_model(m)
if model:
return getattr(model, name, None) | python | def get_field(name, model=None):
"""
get model field according to name, the name can be like `model.column`
"""
if '.' in name:
m, name = name.split('.')
model = get_model(m)
if model:
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limodou/uliweb | uliweb/utils/generic.py | get_column | def get_column(name, model=None):
"""
get table column according to name, the name can be like `model.column`
"""
if '.' in name:
m, name = name.split('.')
model = get_model(m)
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return model.c.get(name) | python | def get_column(name, model=None):
"""
get table column according to name, the name can be like `model.column`
"""
if '.' in name:
m, name = name.split('.')
model = get_model(m)
if model:
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limodou/uliweb | uliweb/utils/generic.py | AddView._process_file | def _process_file(self, obj, fobj, field):
"""
obj is record object
fobj is data
field is FileField instance
"""
from uliweb import settings
paths = []
upload_to = self.upload_to or self._get_upload_path(field, 'upload_to', obj)
... | python | def _process_file(self, obj, fobj, field):
"""
obj is record object
fobj is data
field is FileField instance
"""
from uliweb import settings
paths = []
upload_to = self.upload_to or self._get_upload_path(field, 'upload_to', obj)
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limodou/uliweb | uliweb/utils/generic.py | SimpleListView.count | def count(self, query):
"""
If query is Select object, this function will try to get count of select
"""
if self.manual:
return self.total
if isinstance(query, Select):
q = query.with_only_columns([func.count()]).order_by(None).limit(None)... | python | def count(self, query):
"""
If query is Select object, this function will try to get count of select
"""
if self.manual:
return self.total
if isinstance(query, Select):
q = query.with_only_columns([func.count()]).order_by(None).limit(None)... | [
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limodou/uliweb | uliweb/utils/generic.py | SimpleListView.get_data | def get_data(self, query, fields_convert_map, encoding='utf-8', auto_convert=True,
include_hidden=False, header=None):
"""
If convert=True, will convert field value
"""
fields_convert_map = fields_convert_map or {}
d = self.fields_convert_map.copy()
... | python | def get_data(self, query, fields_convert_map, encoding='utf-8', auto_convert=True,
include_hidden=False, header=None):
"""
If convert=True, will convert field value
"""
fields_convert_map = fields_convert_map or {}
d = self.fields_convert_map.copy()
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limodou/uliweb | uliweb/utils/generic.py | SimpleListView.objects | def objects(self, json_result=False):
"""
Return a generator of all processed data, it just like render
but it'll not return a table or json format data but just
data. And the data will be processed by fields_convert_map if passed.
"""
self.rows_num = 0
que... | python | def objects(self, json_result=False):
"""
Return a generator of all processed data, it just like render
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limodou/uliweb | uliweb/utils/generic.py | ListView.query_all | def query_all(self):
"""
Query all records without limit and offset.
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"""
Query all records without limit and offset.
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limodou/uliweb | uliweb/lib/werkzeug/contrib/sessions.py | ModificationTrackingDict.copy | def copy(self):
"""Create a flat copy of the dict."""
missing = object()
result = object.__new__(self.__class__)
for name in self.__slots__:
val = getattr(self, name, missing)
if val is not missing:
setattr(result, name, val)
return result | python | def copy(self):
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missing = object()
result = object.__new__(self.__class__)
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limodou/uliweb | uliweb/lib/werkzeug/contrib/sessions.py | FilesystemSessionStore.list | def list(self):
"""Lists all sessions in the store.
.. versionadded:: 0.6
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filename_re = re.compile(r'%s(.{5,})%s$' % (re.escape(before),
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.. versionadded:: 0.6
"""
before, after = self.filename_template.split('%s', 1)
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limodou/uliweb | uliweb/utils/date.py | to_timezone | def to_timezone(dt, tzinfo=None):
"""
Convert a datetime to timezone
"""
if not dt:
return dt
tz = pick_timezone(tzinfo, __timezone__)
if not tz:
return dt
dttz = getattr(dt, 'tzinfo', None)
if not dttz:
return dt.replace(tzinfo=tz)
else:
return dt.ast... | python | def to_timezone(dt, tzinfo=None):
"""
Convert a datetime to timezone
"""
if not dt:
return dt
tz = pick_timezone(tzinfo, __timezone__)
if not tz:
return dt
dttz = getattr(dt, 'tzinfo', None)
if not dttz:
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limodou/uliweb | uliweb/utils/date.py | to_date | def to_date(dt, tzinfo=None, format=None):
"""
Convert a datetime to date with tzinfo
"""
d = to_datetime(dt, tzinfo, format)
if not d:
return d
return date(d.year, d.month, d.day) | python | def to_date(dt, tzinfo=None, format=None):
"""
Convert a datetime to date with tzinfo
"""
d = to_datetime(dt, tzinfo, format)
if not d:
return d
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limodou/uliweb | uliweb/utils/date.py | to_time | def to_time(dt, tzinfo=None, format=None):
"""
Convert a datetime to time with tzinfo
"""
d = to_datetime(dt, tzinfo, format)
if not d:
return d
return time_(d.hour, d.minute, d.second, d.microsecond, tzinfo=d.tzinfo) | python | def to_time(dt, tzinfo=None, format=None):
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Convert a datetime to time with tzinfo
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d = to_datetime(dt, tzinfo, format)
if not d:
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limodou/uliweb | uliweb/utils/date.py | to_datetime | def to_datetime(dt, tzinfo=None, format=None):
"""
Convert a date or time to datetime with tzinfo
"""
if not dt:
return dt
tz = pick_timezone(tzinfo, __timezone__)
if isinstance(dt, (str, unicode)):
if not format:
formats = DEFAULT_DATETIME_INPUT_FORMATS
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"""
Convert a date or time to datetime with tzinfo
"""
if not dt:
return dt
tz = pick_timezone(tzinfo, __timezone__)
if isinstance(dt, (str, unicode)):
if not format:
formats = DEFAULT_DATETIME_INPUT_FORMATS
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limodou/uliweb | uliweb/utils/date.py | parse_time | def parse_time(t):
"""
Parse string time format to microsecond
"""
if isinstance(t, (str, unicode)):
b = re_time.match(t)
if b:
v, unit = int(b.group(1)), b.group(2)
if unit == 's':
return v*1000
elif unit == 'm':
return... | python | def parse_time(t):
"""
Parse string time format to microsecond
"""
if isinstance(t, (str, unicode)):
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if b:
v, unit = int(b.group(1)), b.group(2)
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limodou/uliweb | uliweb/contrib/session/middle_session.py | SessionMiddle.process_exception | def process_exception(self, request, e):
"""
Still process session data when specially Exception
"""
if isinstance(e, RedirectException):
response = e.get_response()
self.process_response(request, response) | python | def process_exception(self, request, e):
"""
Still process session data when specially Exception
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if isinstance(e, RedirectException):
response = e.get_response()
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limodou/uliweb | uliweb/core/SimpleFrame.py | jsonp | def jsonp(data, **json_kwargs):
"""
jsonp is callback key name
"""
from uliweb import request
if 'jsonp' in json_kwargs:
cb = json_kwargs.pop('jsonp')
else:
cb = 'callback'
begin = str(request.GET.get(cb))
if not begin:
raise BadRequest("Can't found ... | python | def jsonp(data, **json_kwargs):
"""
jsonp is callback key name
"""
from uliweb import request
if 'jsonp' in json_kwargs:
cb = json_kwargs.pop('jsonp')
else:
cb = 'callback'
begin = str(request.GET.get(cb))
if not begin:
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limodou/uliweb | uliweb/core/SimpleFrame.py | get_url_adapter | def get_url_adapter(_domain_name):
"""
Fetch a domain url_adapter object, and bind it to according domain
"""
from werkzeug._compat import wsgi_decoding_dance
domain = application.domains.get(_domain_name, {})
server_name = None
if domain.get('domain', ''):
server_name = domain['dom... | python | def get_url_adapter(_domain_name):
"""
Fetch a domain url_adapter object, and bind it to according domain
"""
from werkzeug._compat import wsgi_decoding_dance
domain = application.domains.get(_domain_name, {})
server_name = None
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limodou/uliweb | uliweb/core/SimpleFrame.py | get_app_dir | def get_app_dir(app):
"""
Get an app's directory
"""
path = __app_dirs__.get(app)
if path is not None:
return path
else:
p = app.split('.')
try:
path = pkg.resource_filename(p[0], '')
except ImportError as e:
log.error("Can't import app %s"... | python | def get_app_dir(app):
"""
Get an app's directory
"""
path = __app_dirs__.get(app)
if path is not None:
return path
else:
p = app.split('.')
try:
path = pkg.resource_filename(p[0], '')
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limodou/uliweb | uliweb/core/SimpleFrame.py | Dispatcher.get_file | def get_file(self, filename, dir='static'):
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"""
if os.path.exists(filename):
return filename
dirs = self.apps
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fname = os.path.join(dir, filename)
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fname = filename
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"""
get_file will search from apps directory
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if os.path.exists(filename):
return filename
dirs = self.apps
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fname = os.path.join(dir, filename)
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limodou/uliweb | uliweb/core/SimpleFrame.py | Dispatcher.get_template_dirs | def get_template_dirs(self):
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"""
def if_not_empty(dir):
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for root, dirs,... | python | def get_template_dirs(self):
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Get templates directory from apps, but in reversed order, so the same named template
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def if_not_empty(dir):
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limodou/uliweb | uliweb/contrib/redis_cli/__init__.py | get_lock | def get_lock(key, value=None, expiry_time=60):
"""Get a distribute lock"""
from uliweb.utils.common import get_uuid
redis = get_redis()
value = value or get_uuid()
return redis.set(key, value, ex=expiry_time, nx=True) | python | def get_lock(key, value=None, expiry_time=60):
"""Get a distribute lock"""
from uliweb.utils.common import get_uuid
redis = get_redis()
value = value or get_uuid()
return redis.set(key, value, ex=expiry_time, nx=True) | [
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] | 34472f25e4bc0b954a35346672f94e84ef18b076 | https://github.com/limodou/uliweb/blob/34472f25e4bc0b954a35346672f94e84ef18b076/uliweb/contrib/redis_cli/__init__.py#L40-L46 | train |
limodou/uliweb | uliweb/contrib/redis_cli/__init__.py | set_lock | def set_lock(key, value=None, expiry_time=60):
"""Force to set a distribute lock"""
from uliweb.utils.common import get_uuid
redis = get_redis()
value = value or get_uuid()
return redis.set(key, value, ex=expiry_time, xx=True) | python | def set_lock(key, value=None, expiry_time=60):
"""Force to set a distribute lock"""
from uliweb.utils.common import get_uuid
redis = get_redis()
value = value or get_uuid()
return redis.set(key, value, ex=expiry_time, xx=True) | [
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limodou/uliweb | uliweb/contrib/redis_cli/__init__.py | after_init_apps | def after_init_apps(sender):
"""
Check redis version
"""
from uliweb import settings
from uliweb.utils.common import log
check = settings.get_var('REDIS/check_version')
if check:
client = get_redis()
try:
info = client.info()
except Exception as e:
... | python | def after_init_apps(sender):
"""
Check redis version
"""
from uliweb import settings
from uliweb.utils.common import log
check = settings.get_var('REDIS/check_version')
if check:
client = get_redis()
try:
info = client.info()
except Exception as e:
... | [
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limodou/uliweb | uliweb/lib/werkzeug/contrib/atom.py | _make_text_block | def _make_text_block(name, content, content_type=None):
"""Helper function for the builder that creates an XML text block."""
if content_type == 'xhtml':
return u'<%s type="xhtml"><div xmlns="%s">%s</div></%s>\n' % \
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if not content_type:
... | python | def _make_text_block(name, content, content_type=None):
"""Helper function for the builder that creates an XML text block."""
if content_type == 'xhtml':
return u'<%s type="xhtml"><div xmlns="%s">%s</div></%s>\n' % \
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if not content_type:
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limodou/uliweb | uliweb/utils/xltools.py | SimpleWriter._style_range | def _style_range(self, cell, cell_range, border=None, fill=None, font=None, alignment=None):
"""
Apply styles to a range of cells as if they were a single cell.
:param ws: Excel worksheet instance
:param range: An excel range to style (e.g. A1:F20)
:param border: An openpyxl Bo... | python | def _style_range(self, cell, cell_range, border=None, fill=None, font=None, alignment=None):
"""
Apply styles to a range of cells as if they were a single cell.
:param ws: Excel worksheet instance
:param range: An excel range to style (e.g. A1:F20)
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limodou/uliweb | uliweb/lib/werkzeug/urls.py | url_unquote | def url_unquote(string, charset='utf-8', errors='replace', unsafe=''):
"""URL decode a single string with a given encoding. If the charset
is set to `None` no unicode decoding is performed and raw bytes
are returned.
:param s: the string to unquote.
:param charset: the charset of the query string.... | python | def url_unquote(string, charset='utf-8', errors='replace', unsafe=''):
"""URL decode a single string with a given encoding. If the charset
is set to `None` no unicode decoding is performed and raw bytes
are returned.
:param s: the string to unquote.
:param charset: the charset of the query string.... | [
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:param charset: the charset of the query string. If set to `None`
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limodou/uliweb | uliweb/lib/werkzeug/urls.py | _URLMixin.decode_netloc | def decode_netloc(self):
"""Decodes the netloc part into a string."""
rv = _decode_idna(self.host or '')
if ':' in rv:
rv = '[%s]' % rv
port = self.port
if port is not None:
rv = '%s:%d' % (rv, port)
auth = ':'.join(filter(None, [
_url... | python | def decode_netloc(self):
"""Decodes the netloc part into a string."""
rv = _decode_idna(self.host or '')
if ':' in rv:
rv = '[%s]' % rv
port = self.port
if port is not None:
rv = '%s:%d' % (rv, port)
auth = ':'.join(filter(None, [
_url... | [
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limodou/uliweb | uliweb/lib/werkzeug/urls.py | BytesURL.decode | def decode(self, charset='utf-8', errors='replace'):
"""Decodes the URL to a tuple made out of strings. The charset is
only being used for the path, query and fragment.
"""
return URL(
self.scheme.decode('ascii'),
self.decode_netloc(),
self.path.decod... | python | def decode(self, charset='utf-8', errors='replace'):
"""Decodes the URL to a tuple made out of strings. The charset is
only being used for the path, query and fragment.
"""
return URL(
self.scheme.decode('ascii'),
self.decode_netloc(),
self.path.decod... | [
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limodou/uliweb | uliweb/lib/werkzeug/contrib/iterio.py | _mixed_join | def _mixed_join(iterable, sentinel):
"""concatenate any string type in an intelligent way."""
iterator = iter(iterable)
first_item = next(iterator, sentinel)
if isinstance(first_item, bytes):
return first_item + b''.join(iterator)
return first_item + u''.join(iterator) | python | def _mixed_join(iterable, sentinel):
"""concatenate any string type in an intelligent way."""
iterator = iter(iterable)
first_item = next(iterator, sentinel)
if isinstance(first_item, bytes):
return first_item + b''.join(iterator)
return first_item + u''.join(iterator) | [
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limodou/uliweb | uliweb/lib/werkzeug/contrib/iterio.py | IterO._buf_append | def _buf_append(self, string):
'''Replace string directly without appending to an empty string,
avoiding type issues.'''
if not self._buf:
self._buf = string
else:
self._buf += string | python | def _buf_append(self, string):
'''Replace string directly without appending to an empty string,
avoiding type issues.'''
if not self._buf:
self._buf = string
else:
self._buf += string | [
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limodou/uliweb | uliweb/lib/werkzeug/http.py | quote_etag | def quote_etag(etag, weak=False):
"""Quote an etag.
:param etag: the etag to quote.
:param weak: set to `True` to tag it "weak".
"""
if '"' in etag:
raise ValueError('invalid etag')
etag = '"%s"' % etag
if weak:
etag = 'w/' + etag
return etag | python | def quote_etag(etag, weak=False):
"""Quote an etag.
:param etag: the etag to quote.
:param weak: set to `True` to tag it "weak".
"""
if '"' in etag:
raise ValueError('invalid etag')
etag = '"%s"' % etag
if weak:
etag = 'w/' + etag
return etag | [
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limodou/uliweb | uliweb/lib/werkzeug/http.py | parse_etags | def parse_etags(value):
"""Parse an etag header.
:param value: the tag header to parse
:return: an :class:`~werkzeug.datastructures.ETags` object.
"""
if not value:
return ETags()
strong = []
weak = []
end = len(value)
pos = 0
while pos < end:
match = _etag_re.ma... | python | def parse_etags(value):
"""Parse an etag header.
:param value: the tag header to parse
:return: an :class:`~werkzeug.datastructures.ETags` object.
"""
if not value:
return ETags()
strong = []
weak = []
end = len(value)
pos = 0
while pos < end:
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