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pmacosta/ptrie
ptrie/ptrie.py
https://github.com/pmacosta/ptrie/blob/c176d3ee810b7b5243c7ff2bbf2f1af0b0fff2a8/ptrie/ptrie.py#L937-L975
def get_subtree(self, name): # noqa: D302 r""" Get all node names in a sub-tree. :param name: Sub-tree root node name :type name: :ref:`NodeName` :rtype: list of :ref:`NodeName` :raises: * RuntimeError (Argument \`name\` is not valid) * RuntimeError (Node *[name]* not in tree) Using the same example tree created in :py:meth:`ptrie.Trie.add_nodes`:: >>> from __future__ import print_function >>> import docs.support.ptrie_example, pprint >>> tobj = docs.support.ptrie_example.create_tree() >>> print(tobj) root ├branch1 (*) │├leaf1 ││└subleaf1 (*) │└leaf2 (*) │ └subleaf2 └branch2 >>> pprint.pprint(tobj.get_subtree('root.branch1')) ['root.branch1', 'root.branch1.leaf1', 'root.branch1.leaf1.subleaf1', 'root.branch1.leaf2', 'root.branch1.leaf2.subleaf2'] """ if self._validate_node_name(name): raise RuntimeError("Argument `name` is not valid") self._node_in_tree(name) return self._get_subtree(name)
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r""" Get all node names in a sub-tree. :param name: Sub-tree root node name :type name: :ref:`NodeName` :rtype: list of :ref:`NodeName` :raises: * RuntimeError (Argument \`name\` is not valid) * RuntimeError (Node *[name]* not in tree) Using the same example tree created in :py:meth:`ptrie.Trie.add_nodes`:: >>> from __future__ import print_function >>> import docs.support.ptrie_example, pprint >>> tobj = docs.support.ptrie_example.create_tree() >>> print(tobj) root ├branch1 (*) │├leaf1 ││└subleaf1 (*) │└leaf2 (*) │ └subleaf2 └branch2 >>> pprint.pprint(tobj.get_subtree('root.branch1')) ['root.branch1', 'root.branch1.leaf1', 'root.branch1.leaf1.subleaf1', 'root.branch1.leaf2', 'root.branch1.leaf2.subleaf2']
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python
train
saltstack/salt
salt/modules/btrfs.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/btrfs.py#L195-L212
def _usage_overall(raw): ''' Parse usage/overall. ''' data = {} for line in raw.split("\n")[1:]: keyset = [item.strip() for item in re.sub(r"\s+", " ", line).split(":", 1) if item.strip()] if len(keyset) == 2: key = re.sub(r"[()]", "", keyset[0]).replace(" ", "_").lower() if key in ['free_estimated', 'global_reserve']: # An extra field subk = keyset[1].split("(") data[key] = subk[0].strip() subk = subk[1].replace(")", "").split(": ") data["{0}_{1}".format(key, subk[0])] = subk[1] else: data[key] = keyset[1] return data
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Parse usage/overall.
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python
train
dustinmm80/healthy
package_utils.py
https://github.com/dustinmm80/healthy/blob/b59016c3f578ca45b6ce857a2d5c4584b8542288/package_utils.py#L14-L24
def create_sandbox(name='healthybox'): """ Create a temporary sandbox directory :param name: name of the directory to create :return: The directory created """ sandbox = tempfile.mkdtemp(prefix=name) if not os.path.isdir(sandbox): os.mkdir(sandbox) return sandbox
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Create a temporary sandbox directory :param name: name of the directory to create :return: The directory created
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python
train
cloudendpoints/endpoints-management-python
endpoints_management/control/distribution.py
https://github.com/cloudendpoints/endpoints-management-python/blob/ec3c4a330ae9d65738861ce6df4dd6c3cb9f7731/endpoints_management/control/distribution.py#L99-L118
def create_explicit(bounds): """Creates a new instance of distribution with explicit buckets. bounds is an iterable of ordered floats that define the explicit buckets Args: bounds (iterable[float]): initializes the bounds Return: :class:`endpoints_management.gen.servicecontrol_v1_messages.Distribution` Raises: ValueError: if the args are invalid for creating an instance """ safe_bounds = sorted(float(x) for x in bounds) if len(safe_bounds) != len(set(safe_bounds)): raise ValueError(u'Detected two elements of bounds that are the same') return sc_messages.Distribution( bucketCounts=[0] * (len(safe_bounds) + 1), explicitBuckets=sc_messages.ExplicitBuckets(bounds=safe_bounds))
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Creates a new instance of distribution with explicit buckets. bounds is an iterable of ordered floats that define the explicit buckets Args: bounds (iterable[float]): initializes the bounds Return: :class:`endpoints_management.gen.servicecontrol_v1_messages.Distribution` Raises: ValueError: if the args are invalid for creating an instance
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python
train
aliyun/aliyun-odps-python-sdk
odps/df/expr/strings.py
https://github.com/aliyun/aliyun-odps-python-sdk/blob/4b0de18f5864386df6068f26f026e62f932c41e4/odps/df/expr/strings.py#L671-L684
def _strptime(expr, date_format): """ Return datetimes specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in python string format doc :param expr: :param date_format: date format string (e.g. “%Y-%m-%d”) :type date_format: str :return: """ return _string_op(expr, Strptime, _date_format=date_format, output_type=types.datetime)
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Return datetimes specified by date_format, which supports the same string format as the python standard library. Details of the string format can be found in python string format doc :param expr: :param date_format: date format string (e.g. “%Y-%m-%d”) :type date_format: str :return:
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python
train
dodger487/dplython
dplython/dplython.py
https://github.com/dodger487/dplython/blob/09c2a5f4ca67221b2a59928366ca8274357f7234/dplython/dplython.py#L203-L232
def select(*args): """Select specific columns from DataFrame. Output will be DplyFrame type. Order of columns will be the same as input into select. >>> diamonds >> select(X.color, X.carat) >> head(3) Out: color carat 0 E 0.23 1 E 0.21 2 E 0.23 Grouping variables are implied in selection. >>> df >> group_by(X.a, X.b) >> select(X.c) returns a dataframe like `df[[X.a, X.b, X.c]]` with the variables appearing in grouped order before the selected column(s), unless a grouped variable is explicitly selected >>> df >> group_by(X.a, X.b) >> select(X.c, X.b) returns a dataframe like `df[[X.a, X.c, X.b]]` """ def select_columns(df, args): columns = [column._name for column in args] if df._grouped_on: for col in df._grouped_on[::-1]: if col not in columns: columns.insert(0, col) return columns return lambda df: df[select_columns(df, args)]
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Select specific columns from DataFrame. Output will be DplyFrame type. Order of columns will be the same as input into select. >>> diamonds >> select(X.color, X.carat) >> head(3) Out: color carat 0 E 0.23 1 E 0.21 2 E 0.23 Grouping variables are implied in selection. >>> df >> group_by(X.a, X.b) >> select(X.c) returns a dataframe like `df[[X.a, X.b, X.c]]` with the variables appearing in grouped order before the selected column(s), unless a grouped variable is explicitly selected >>> df >> group_by(X.a, X.b) >> select(X.c, X.b) returns a dataframe like `df[[X.a, X.c, X.b]]`
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python
train
RPi-Distro/python-gpiozero
gpiozero/boards.py
https://github.com/RPi-Distro/python-gpiozero/blob/7b67374fd0c8c4fde5586d9bad9531f076db9c0c/gpiozero/boards.py#L1601-L1633
def forward(self, speed=1, **kwargs): """ Drive the robot forward by running both motors forward. :param float speed: Speed at which to drive the motors, as a value between 0 (stopped) and 1 (full speed). The default is 1. :param float curve_left: The amount to curve left while moving forwards, by driving the left motor at a slower speed. Maximum *curve_left* is 1, the default is 0 (no curve). This parameter can only be specified as a keyword parameter, and is mutually exclusive with *curve_right*. :param float curve_right: The amount to curve right while moving forwards, by driving the right motor at a slower speed. Maximum *curve_right* is 1, the default is 0 (no curve). This parameter can only be specified as a keyword parameter, and is mutually exclusive with *curve_left*. """ curve_left = kwargs.pop('curve_left', 0) curve_right = kwargs.pop('curve_right', 0) if kwargs: raise TypeError('unexpected argument %s' % kwargs.popitem()[0]) if not 0 <= curve_left <= 1: raise ValueError('curve_left must be between 0 and 1') if not 0 <= curve_right <= 1: raise ValueError('curve_right must be between 0 and 1') if curve_left != 0 and curve_right != 0: raise ValueError("curve_left and curve_right can't be used at " "the same time") self.left_motor.forward(speed * (1 - curve_left)) self.right_motor.forward(speed * (1 - curve_right))
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Drive the robot forward by running both motors forward. :param float speed: Speed at which to drive the motors, as a value between 0 (stopped) and 1 (full speed). The default is 1. :param float curve_left: The amount to curve left while moving forwards, by driving the left motor at a slower speed. Maximum *curve_left* is 1, the default is 0 (no curve). This parameter can only be specified as a keyword parameter, and is mutually exclusive with *curve_right*. :param float curve_right: The amount to curve right while moving forwards, by driving the right motor at a slower speed. Maximum *curve_right* is 1, the default is 0 (no curve). This parameter can only be specified as a keyword parameter, and is mutually exclusive with *curve_left*.
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python
train
RudolfCardinal/pythonlib
cardinal_pythonlib/subproc.py
https://github.com/RudolfCardinal/pythonlib/blob/0b84cb35f38bd7d8723958dae51b480a829b7227/cardinal_pythonlib/subproc.py#L301-L454
def mimic_user_input( args: List[str], source_challenge_response: List[Tuple[SubprocSource, str, Union[str, SubprocCommand]]], line_terminators: List[str] = None, print_stdout: bool = False, print_stderr: bool = False, print_stdin: bool = False, stdin_encoding: str = None, stdout_encoding: str = None, suppress_decoding_errors: bool = True, sleep_time_s: float = 0.1) -> None: r""" Run an external command. Pretend to be a human by sending text to the subcommand (responses) when the external command sends us triggers (challenges). This is a bit nasty. Args: args: command-line arguments source_challenge_response: list of tuples of the format ``(challsrc, challenge, response)``; see below line_terminators: valid line terminators print_stdout: print_stderr: print_stdin: stdin_encoding: stdout_encoding: suppress_decoding_errors: trap any ``UnicodeDecodeError``? sleep_time_s: The ``(challsrc, challenge, response)`` tuples have this meaning: - ``challsrc``: where is the challenge coming from? Must be one of the objects :data:`SOURCE_STDOUT` or :data:`SOURCE_STDERR`; - ``challenge``: text of challenge - ``response``: text of response (send to the subcommand's ``stdin``). Example (modified from :class:`CorruptedZipReader`): .. code-block:: python from cardinal_pythonlib.subproc import * SOURCE_FILENAME = "corrupt.zip" TMP_DIR = "/tmp" OUTPUT_FILENAME = "rescued.zip" cmdargs = [ "zip", # Linux zip tool "-FF", # or "--fixfix": "fix very broken things" SOURCE_FILENAME, # input file "--temp-path", TMP_DIR, # temporary storage path "--out", OUTPUT_FILENAME # output file ] # We would like to be able to say "y" automatically to # "Is this a single-disk archive? (y/n):" # The source code (api.c, zip.c, zipfile.c), from # ftp://ftp.info-zip.org/pub/infozip/src/ , suggests that "-q" # should do this (internally "-q" sets "noisy = 0") - but in # practice it doesn't work. This is a critical switch. # Therefore we will do something very ugly, and send raw text via # stdin. ZIP_PROMPTS_RESPONSES = [ (SOURCE_STDOUT, "Is this a single-disk archive? (y/n): ", "y\n"), (SOURCE_STDOUT, " or ENTER (try reading this split again): ", "q\n"), (SOURCE_STDERR, "zip: malloc.c:2394: sysmalloc: Assertion `(old_top == initial_top (av) " "&& old_size == 0) || ((unsigned long) (old_size) >= MINSIZE && " "prev_inuse (old_top) && ((unsigned long) old_end & (pagesize - 1)) " "== 0)' failed.", TERMINATE_SUBPROCESS), ] ZIP_STDOUT_TERMINATORS = ["\n", "): "] mimic_user_input(cmdargs, source_challenge_response=ZIP_PROMPTS_RESPONSES, line_terminators=ZIP_STDOUT_TERMINATORS, print_stdout=show_zip_output, print_stdin=show_zip_output) """ # noqa line_terminators = line_terminators or ["\n"] # type: List[str] stdin_encoding = stdin_encoding or sys.getdefaultencoding() stdout_encoding = stdout_encoding or sys.getdefaultencoding() # Launch the command p = Popen(args, stdin=PIPE, stdout=PIPE, stderr=PIPE, bufsize=0) # Launch the asynchronous readers of stdout and stderr stdout_queue = Queue() # noinspection PyTypeChecker stdout_reader = AsynchronousFileReader( fd=p.stdout, queue=stdout_queue, encoding=stdout_encoding, line_terminators=line_terminators, cmdargs=args, suppress_decoding_errors=suppress_decoding_errors ) stdout_reader.start() stderr_queue = Queue() # noinspection PyTypeChecker stderr_reader = AsynchronousFileReader( fd=p.stderr, queue=stderr_queue, encoding=stdout_encoding, # same as stdout line_terminators=line_terminators, cmdargs=args, suppress_decoding_errors=suppress_decoding_errors ) stderr_reader.start() while not stdout_reader.eof() or not stderr_reader.eof(): lines_with_source = [] # type: List[Tuple[SubprocSource, str]] while not stdout_queue.empty(): lines_with_source.append((SOURCE_STDOUT, stdout_queue.get())) while not stderr_queue.empty(): lines_with_source.append((SOURCE_STDERR, stderr_queue.get())) for src, line in lines_with_source: if src is SOURCE_STDOUT and print_stdout: print(line, end="") # terminator already in line if src is SOURCE_STDERR and print_stderr: print(line, end="") # terminator already in line for challsrc, challenge, response in source_challenge_response: # log.critical("challsrc={!r}", challsrc) # log.critical("challenge={!r}", challenge) # log.critical("line={!r}", line) # log.critical("response={!r}", response) if challsrc != src: continue if challenge in line: if response is TERMINATE_SUBPROCESS: log.warning("Terminating subprocess {!r} because input " "{!r} received", args, challenge) p.kill() return else: p.stdin.write(response.encode(stdin_encoding)) p.stdin.flush() if print_stdin: print(response, end="") # Sleep a bit before asking the readers again. sleep(sleep_time_s) stdout_reader.join() stderr_reader.join() p.stdout.close() p.stderr.close()
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r""" Run an external command. Pretend to be a human by sending text to the subcommand (responses) when the external command sends us triggers (challenges). This is a bit nasty. Args: args: command-line arguments source_challenge_response: list of tuples of the format ``(challsrc, challenge, response)``; see below line_terminators: valid line terminators print_stdout: print_stderr: print_stdin: stdin_encoding: stdout_encoding: suppress_decoding_errors: trap any ``UnicodeDecodeError``? sleep_time_s: The ``(challsrc, challenge, response)`` tuples have this meaning: - ``challsrc``: where is the challenge coming from? Must be one of the objects :data:`SOURCE_STDOUT` or :data:`SOURCE_STDERR`; - ``challenge``: text of challenge - ``response``: text of response (send to the subcommand's ``stdin``). Example (modified from :class:`CorruptedZipReader`): .. code-block:: python from cardinal_pythonlib.subproc import * SOURCE_FILENAME = "corrupt.zip" TMP_DIR = "/tmp" OUTPUT_FILENAME = "rescued.zip" cmdargs = [ "zip", # Linux zip tool "-FF", # or "--fixfix": "fix very broken things" SOURCE_FILENAME, # input file "--temp-path", TMP_DIR, # temporary storage path "--out", OUTPUT_FILENAME # output file ] # We would like to be able to say "y" automatically to # "Is this a single-disk archive? (y/n):" # The source code (api.c, zip.c, zipfile.c), from # ftp://ftp.info-zip.org/pub/infozip/src/ , suggests that "-q" # should do this (internally "-q" sets "noisy = 0") - but in # practice it doesn't work. This is a critical switch. # Therefore we will do something very ugly, and send raw text via # stdin. ZIP_PROMPTS_RESPONSES = [ (SOURCE_STDOUT, "Is this a single-disk archive? (y/n): ", "y\n"), (SOURCE_STDOUT, " or ENTER (try reading this split again): ", "q\n"), (SOURCE_STDERR, "zip: malloc.c:2394: sysmalloc: Assertion `(old_top == initial_top (av) " "&& old_size == 0) || ((unsigned long) (old_size) >= MINSIZE && " "prev_inuse (old_top) && ((unsigned long) old_end & (pagesize - 1)) " "== 0)' failed.", TERMINATE_SUBPROCESS), ] ZIP_STDOUT_TERMINATORS = ["\n", "): "] mimic_user_input(cmdargs, source_challenge_response=ZIP_PROMPTS_RESPONSES, line_terminators=ZIP_STDOUT_TERMINATORS, print_stdout=show_zip_output, print_stdin=show_zip_output)
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python
train
python-xlib/python-xlib
Xlib/display.py
https://github.com/python-xlib/python-xlib/blob/8901e831737e79fe5645f48089d70e1d1046d2f2/Xlib/display.py#L490-L495
def get_atom_name(self, atom): """Look up the name of atom, returning it as a string. Will raise BadAtom if atom does not exist.""" r = request.GetAtomName(display = self.display, atom = atom) return r.name
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Look up the name of atom, returning it as a string. Will raise BadAtom if atom does not exist.
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python
train
tensorflow/tensor2tensor
tensor2tensor/models/image_transformer.py
https://github.com/tensorflow/tensor2tensor/blob/272500b6efe353aeb638d2745ed56e519462ca31/tensor2tensor/models/image_transformer.py#L1147-L1157
def imagetransformer_b10l_4h_big_uncond_dr01_tpu(): """big 1d model for conditional image generation.""" hparams = imagetransformer_b12l_4h_big_uncond_dr03_tpu() # num_hidden_layers hparams.num_decoder_layers = 10 hparams.num_heads = 4 hparams.hidden_size = 1024 hparams.filter_size = 4096 hparams.batch_size = 1 hparams.layer_prepostprocess_dropout = 0.1 return hparams
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big 1d model for conditional image generation.
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python
train
mozilla/amo-validator
validator/submain.py
https://github.com/mozilla/amo-validator/blob/0251bfbd7d93106e01ecdb6de5fcd1dc1a180664/validator/submain.py#L279-L354
def populate_chrome_manifest(err, xpi_package): "Loads the chrome.manifest if it's present" if 'chrome.manifest' in xpi_package: chrome_data = xpi_package.read('chrome.manifest') chrome = ChromeManifest(chrome_data, 'chrome.manifest') chrome_recursion_buster = set() # Handle the case of manifests linked from the manifest. def get_linked_manifest(path, from_path, from_chrome, from_triple): if path in chrome_recursion_buster: err.warning( err_id=('submain', 'populate_chrome_manifest', 'recursion'), warning='Linked manifest recursion detected.', description='A chrome registration file links back to ' 'itself. This can cause a multitude of ' 'issues.', filename=path) return # Make sure the manifest is properly linked if path not in xpi_package: err.notice( err_id=('submain', 'populate_chrome_manifest', 'linkerr'), notice='Linked manifest could not be found.', description=('A linked manifest file could not be found ' 'in the package.', 'Path: %s' % path), filename=from_path, line=from_triple['line'], context=from_chrome.context) return chrome_recursion_buster.add(path) manifest = ChromeManifest(xpi_package.read(path), path) for triple in manifest.triples: yield triple if triple['subject'] == 'manifest': subpath = triple['predicate'] # If the path is relative, make it relative to the current # file. if not subpath.startswith('/'): subpath = '%s/%s' % ( '/'.join(path.split('/')[:-1]), subpath) subpath = subpath.lstrip('/') for subtriple in get_linked_manifest( subpath, path, manifest, triple): yield subtriple chrome_recursion_buster.discard(path) chrome_recursion_buster.add('chrome.manifest') # Search for linked manifests in the base manifest. for extra_manifest in chrome.get_triples(subject='manifest'): # When one is found, add its triples to our own. for triple in get_linked_manifest(extra_manifest['predicate'], 'chrome.manifest', chrome, extra_manifest): chrome.triples.append(triple) chrome_recursion_buster.discard('chrome.manifest') # Create a reference so we can get the chrome manifest later, but make # it pushable so we don't run chrome manifests in JAR files. err.save_resource('chrome.manifest', chrome, pushable=True) # Create a non-pushable reference for tests that need to access the # chrome manifest from within JAR files. err.save_resource('chrome.manifest_nopush', chrome, pushable=False)
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Loads the chrome.manifest if it's present
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python
train
onnx/onnxmltools
onnxmltools/convert/coreml/shape_calculators/neural_network/Upsample.py
https://github.com/onnx/onnxmltools/blob/d4e4c31990fc2d9fd1f92139f497d360914c9df2/onnxmltools/convert/coreml/shape_calculators/neural_network/Upsample.py#L13-L27
def calculate_upsample_output_shapes(operator): ''' Allowed input/output patterns are 1. [N, C, H, W] ---> [N, C, H', W'] ''' check_input_and_output_numbers(operator, input_count_range=1, output_count_range=1) check_input_and_output_types(operator, good_input_types=[FloatTensorType]) scales = operator.raw_operator.upsample.scalingFactor output_shape = copy.deepcopy(operator.inputs[0].type.shape) output_shape[2] *= scales[0] output_shape[3] *= scales[1] operator.outputs[0].type = FloatTensorType(output_shape, doc_string=operator.outputs[0].type.doc_string)
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Allowed input/output patterns are 1. [N, C, H, W] ---> [N, C, H', W']
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python
train
codelv/enaml-native
src/enamlnative/android/android_date_picker.py
https://github.com/codelv/enaml-native/blob/c33986e9eda468c508806e0a3e73c771401e5718/src/enamlnative/android/android_date_picker.py#L46-L52
def create_widget(self): """ Create the underlying widget. """ d = self.declaration self.widget = DatePicker(self.get_context(), None, d.style or "@attr/datePickerStyle")
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Create the underlying widget.
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python
train
JdeRobot/base
src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v10/matrixpilot.py
https://github.com/JdeRobot/base/blob/303b18992785b2fe802212f2d758a60873007f1f/src/drivers/MAVLinkServer/MAVProxy/pymavlink/dialects/v10/matrixpilot.py#L9321-L9341
def rc_channels_raw_encode(self, time_boot_ms, port, chan1_raw, chan2_raw, chan3_raw, chan4_raw, chan5_raw, chan6_raw, chan7_raw, chan8_raw, rssi): ''' The RAW values of the RC channels received. The standard PPM modulation is as follows: 1000 microseconds: 0%, 2000 microseconds: 100%. Individual receivers/transmitters might violate this specification. time_boot_ms : Timestamp (milliseconds since system boot) (uint32_t) port : Servo output port (set of 8 outputs = 1 port). Most MAVs will just use one, but this allows for more than 8 servos. (uint8_t) chan1_raw : RC channel 1 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan2_raw : RC channel 2 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan3_raw : RC channel 3 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan4_raw : RC channel 4 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan5_raw : RC channel 5 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan6_raw : RC channel 6 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan7_raw : RC channel 7 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan8_raw : RC channel 8 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) rssi : Receive signal strength indicator, 0: 0%, 100: 100%, 255: invalid/unknown. (uint8_t) ''' return MAVLink_rc_channels_raw_message(time_boot_ms, port, chan1_raw, chan2_raw, chan3_raw, chan4_raw, chan5_raw, chan6_raw, chan7_raw, chan8_raw, rssi)
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The RAW values of the RC channels received. The standard PPM modulation is as follows: 1000 microseconds: 0%, 2000 microseconds: 100%. Individual receivers/transmitters might violate this specification. time_boot_ms : Timestamp (milliseconds since system boot) (uint32_t) port : Servo output port (set of 8 outputs = 1 port). Most MAVs will just use one, but this allows for more than 8 servos. (uint8_t) chan1_raw : RC channel 1 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan2_raw : RC channel 2 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan3_raw : RC channel 3 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan4_raw : RC channel 4 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan5_raw : RC channel 5 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan6_raw : RC channel 6 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan7_raw : RC channel 7 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) chan8_raw : RC channel 8 value, in microseconds. A value of UINT16_MAX implies the channel is unused. (uint16_t) rssi : Receive signal strength indicator, 0: 0%, 100: 100%, 255: invalid/unknown. (uint8_t)
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python
train
sebp/scikit-survival
sksurv/svm/survival_svm.py
https://github.com/sebp/scikit-survival/blob/cfc99fd20454cdd6f4f20fe331b39f2191ccaabc/sksurv/svm/survival_svm.py#L702-L717
def _argsort_and_resolve_ties(time, random_state): """Like numpy.argsort, but resolves ties uniformly at random""" n_samples = len(time) order = numpy.argsort(time, kind="mergesort") i = 0 while i < n_samples - 1: inext = i + 1 while inext < n_samples and time[order[i]] == time[order[inext]]: inext += 1 if i + 1 != inext: # resolve ties randomly random_state.shuffle(order[i:inext]) i = inext return order
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Like numpy.argsort, but resolves ties uniformly at random
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python
train
lreis2415/PyGeoC
pygeoc/utils.py
https://github.com/lreis2415/PyGeoC/blob/9a92d1a229bb74298e3c57f27c97079980b5f729/pygeoc/utils.py#L494-L527
def extract_numeric_values_from_string(str_contains_values): # type: (AnyStr) -> Optional[List[Union[int, float]]] """ Find numeric values from string, e.g., 1, .7, 1.2, 4e2, 3e-3, -9, etc. Reference: `how-to-extract-a-floating-number-from-a-string-in-python`_ Examples: >>> input_str = '.1 .12 9.1 98.1 1. 12. 1 12' >>> StringClass.extract_numeric_values_from_string(input_str) [0.1, 0.12, 9.1, 98.1, 1, 12, 1, 12] >>> input_str = '-1 +1 2e9 +2E+09 -2e-9' >>> StringClass.extract_numeric_values_from_string(input_str) [-1, 1, 2000000000, 2000000000, -2e-09] >>> input_str = 'current level: -2.03e+2db' >>> StringClass.extract_numeric_values_from_string(input_str) [-203] Args: str_contains_values: string which may contains numeric values Returns: list of numeric values .. _how-to-extract-a-floating-number-from-a-string-in-python: https://stackoverflow.com/questions/4703390/how-to-extract-a-floating-number-from-a-string-in-python/4703508#4703508 """ numeric_const_pattern = r'[-+]?(?:(?:\d*\.\d+)|(?:\d+\.?))(?:[Ee][+-]?\d+)?' rx = re.compile(numeric_const_pattern, re.VERBOSE) value_strs = rx.findall(str_contains_values) if len(value_strs) == 0: return None else: return [int(float(v)) if float(v) % 1. == 0 else float(v) for v in value_strs]
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Find numeric values from string, e.g., 1, .7, 1.2, 4e2, 3e-3, -9, etc. Reference: `how-to-extract-a-floating-number-from-a-string-in-python`_ Examples: >>> input_str = '.1 .12 9.1 98.1 1. 12. 1 12' >>> StringClass.extract_numeric_values_from_string(input_str) [0.1, 0.12, 9.1, 98.1, 1, 12, 1, 12] >>> input_str = '-1 +1 2e9 +2E+09 -2e-9' >>> StringClass.extract_numeric_values_from_string(input_str) [-1, 1, 2000000000, 2000000000, -2e-09] >>> input_str = 'current level: -2.03e+2db' >>> StringClass.extract_numeric_values_from_string(input_str) [-203] Args: str_contains_values: string which may contains numeric values Returns: list of numeric values .. _how-to-extract-a-floating-number-from-a-string-in-python: https://stackoverflow.com/questions/4703390/how-to-extract-a-floating-number-from-a-string-in-python/4703508#4703508
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python
train
quasipedia/swaggery
examples/async/async.py
https://github.com/quasipedia/swaggery/blob/89a2e1b2bebbc511c781c9e63972f65aef73cc2f/examples/async/async.py#L187-L195
def form_echo(cls, request, foo: (Ptypes.form, String('A form parameter'))) -> [ (200, 'Ok', String)]: '''Echo the form parameter.''' log.info('Echoing form param, value is: {}'.format(foo)) for i in range(randint(0, MAX_LOOP_DURATION)): yield msg = 'The value sent was: {}'.format(foo) Respond(200, msg)
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Echo the form parameter.
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python
train
saltstack/salt
salt/modules/boto_route53.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/boto_route53.py#L285-L337
def create_zone(zone, private=False, vpc_id=None, vpc_region=None, region=None, key=None, keyid=None, profile=None): ''' Create a Route53 hosted zone. .. versionadded:: 2015.8.0 zone DNS zone to create private True/False if the zone will be a private zone vpc_id VPC ID to associate the zone to (required if private is True) vpc_region VPC Region (required if private is True) region region endpoint to connect to key AWS key keyid AWS keyid profile AWS pillar profile CLI Example:: salt myminion boto_route53.create_zone example.org ''' if region is None: region = 'universal' if private: if not vpc_id or not vpc_region: msg = 'vpc_id and vpc_region must be specified for a private zone' raise SaltInvocationError(msg) conn = _get_conn(region=region, key=key, keyid=keyid, profile=profile) _zone = conn.get_zone(zone) if _zone: return False conn.create_zone(zone, private_zone=private, vpc_id=vpc_id, vpc_region=vpc_region) return True
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Create a Route53 hosted zone. .. versionadded:: 2015.8.0 zone DNS zone to create private True/False if the zone will be a private zone vpc_id VPC ID to associate the zone to (required if private is True) vpc_region VPC Region (required if private is True) region region endpoint to connect to key AWS key keyid AWS keyid profile AWS pillar profile CLI Example:: salt myminion boto_route53.create_zone example.org
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python
train
sosreport/sos
sos/plugins/__init__.py
https://github.com/sosreport/sos/blob/2ebc04da53dc871c8dd5243567afa4f8592dca29/sos/plugins/__init__.py#L754-L827
def add_copy_spec(self, copyspecs, sizelimit=None, tailit=True, pred=None): """Add a file or glob but limit it to sizelimit megabytes. If fname is a single file the file will be tailed to meet sizelimit. If the first file in a glob is too large it will be tailed to meet the sizelimit. """ if not self.test_predicate(pred=pred): self._log_info("skipped copy spec '%s' due to predicate (%s)" % (copyspecs, self.get_predicate(pred=pred))) return if sizelimit is None: sizelimit = self.get_option("log_size") if self.get_option('all_logs'): sizelimit = None if sizelimit: sizelimit *= 1024 * 1024 # in MB if not copyspecs: return False if isinstance(copyspecs, six.string_types): copyspecs = [copyspecs] for copyspec in copyspecs: if not (copyspec and len(copyspec)): return False if self.use_sysroot(): copyspec = self.join_sysroot(copyspec) files = self._expand_copy_spec(copyspec) if len(files) == 0: continue # Files hould be sorted in most-recently-modified order, so that # we collect the newest data first before reaching the limit. def getmtime(path): try: return os.path.getmtime(path) except OSError: return 0 files.sort(key=getmtime, reverse=True) current_size = 0 limit_reached = False _file = None for _file in files: if self._is_forbidden_path(_file): self._log_debug("skipping forbidden path '%s'" % _file) continue try: current_size += os.stat(_file)[stat.ST_SIZE] except OSError: self._log_info("failed to stat '%s'" % _file) if sizelimit and current_size > sizelimit: limit_reached = True break self._add_copy_paths([_file]) if limit_reached and tailit and not _file_is_compressed(_file): file_name = _file if file_name[0] == os.sep: file_name = file_name.lstrip(os.sep) strfile = file_name.replace(os.path.sep, ".") + ".tailed" self.add_string_as_file(tail(_file, sizelimit), strfile) rel_path = os.path.relpath('/', os.path.dirname(_file)) link_path = os.path.join(rel_path, 'sos_strings', self.name(), strfile) self.archive.add_link(link_path, _file)
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Add a file or glob but limit it to sizelimit megabytes. If fname is a single file the file will be tailed to meet sizelimit. If the first file in a glob is too large it will be tailed to meet the sizelimit.
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python
train
ewels/MultiQC
multiqc/modules/fastqc/fastqc.py
https://github.com/ewels/MultiQC/blob/2037d6322b2554146a74efbf869156ad20d4c4ec/multiqc/modules/fastqc/fastqc.py#L117-L188
def parse_fastqc_report(self, file_contents, s_name=None, f=None): """ Takes contents from a fastq_data.txt file and parses out required statistics and data. Returns a dict with keys 'stats' and 'data'. Data is for plotting graphs, stats are for top table. """ # Make the sample name from the input filename if we find it fn_search = re.search(r"Filename\s+(.+)", file_contents) if fn_search: s_name = self.clean_s_name(fn_search.group(1) , f['root']) if s_name in self.fastqc_data.keys(): log.debug("Duplicate sample name found! Overwriting: {}".format(s_name)) self.add_data_source(f, s_name) self.fastqc_data[s_name] = { 'statuses': dict() } # Parse the report section = None s_headers = None self.dup_keys = [] for l in file_contents.splitlines(): if l == '>>END_MODULE': section = None s_headers = None elif l.startswith('>>'): (section, status) = l[2:].split("\t", 1) section = section.lower().replace(' ', '_') self.fastqc_data[s_name]['statuses'][section] = status elif section is not None: if l.startswith('#'): s_headers = l[1:].split("\t") # Special case: Total Deduplicated Percentage header line if s_headers[0] == 'Total Deduplicated Percentage': self.fastqc_data[s_name]['basic_statistics'].append({ 'measure': 'total_deduplicated_percentage', 'value': float(s_headers[1]) }) else: # Special case: Rename dedup header in old versions of FastQC (v10) if s_headers[1] == 'Relative count': s_headers[1] = 'Percentage of total' s_headers = [s.lower().replace(' ', '_') for s in s_headers] self.fastqc_data[s_name][section] = list() elif s_headers is not None: s = l.split("\t") row = dict() for (i, v) in enumerate(s): v.replace('NaN','0') try: v = float(v) except ValueError: pass row[s_headers[i]] = v self.fastqc_data[s_name][section].append(row) # Special case - need to remember order of duplication keys if section == 'sequence_duplication_levels': try: self.dup_keys.append(float(s[0])) except ValueError: self.dup_keys.append(s[0]) # Tidy up the Basic Stats self.fastqc_data[s_name]['basic_statistics'] = {d['measure']: d['value'] for d in self.fastqc_data[s_name]['basic_statistics']} # Calculate the average sequence length (Basic Statistics gives a range) length_bp = 0 total_count = 0 for d in self.fastqc_data[s_name].get('sequence_length_distribution', {}): length_bp += d['count'] * self.avg_bp_from_range(d['length']) total_count += d['count'] if total_count > 0: self.fastqc_data[s_name]['basic_statistics']['avg_sequence_length'] = length_bp / total_count
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python
train
belbio/bel
bel/utils.py
https://github.com/belbio/bel/blob/60333e8815625b942b4836903f3b618cf44b3771/bel/utils.py#L27-L56
def get_url(url: str, params: dict = {}, timeout: float = 5.0, cache: bool = True): """Wrapper for requests.get(url) Args: url: url to retrieve params: query string parameters timeout: allow this much time for the request and time it out if over cache: Cache for up to a day unless this is false Returns: Requests Result obj or None if timed out """ try: if not cache: with requests_cache.disabled(): r = requests.get(url, params=params, timeout=timeout) else: r = requests.get(url, params=params, timeout=timeout) log.debug(f"Response headers {r.headers} From cache {r.from_cache}") return r except requests.exceptions.Timeout: log.warn(f"Timed out getting url in get_url: {url}") return None except Exception as e: log.warn(f"Error getting url: {url} error: {e}") return None
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python
train
marcomusy/vtkplotter
vtkplotter/plotter.py
https://github.com/marcomusy/vtkplotter/blob/692c3396782722ec525bc1346a26999868c650c6/vtkplotter/plotter.py#L661-L696
def moveCamera(self, camstart, camstop, fraction): """ Takes as input two ``vtkCamera`` objects and returns a new ``vtkCamera`` that is at an intermediate position: fraction=0 -> camstart, fraction=1 -> camstop. Press ``shift-C`` key in interactive mode to dump a python snipplet of parameters for the current camera view. """ if isinstance(fraction, int): colors.printc("~lightning Warning in moveCamera(): fraction should not be an integer", c=1) if fraction > 1: colors.printc("~lightning Warning in moveCamera(): fraction is > 1", c=1) cam = vtk.vtkCamera() cam.DeepCopy(camstart) p1 = numpy.array(camstart.GetPosition()) f1 = numpy.array(camstart.GetFocalPoint()) v1 = numpy.array(camstart.GetViewUp()) c1 = numpy.array(camstart.GetClippingRange()) s1 = camstart.GetDistance() p2 = numpy.array(camstop.GetPosition()) f2 = numpy.array(camstop.GetFocalPoint()) v2 = numpy.array(camstop.GetViewUp()) c2 = numpy.array(camstop.GetClippingRange()) s2 = camstop.GetDistance() cam.SetPosition(p2 * fraction + p1 * (1 - fraction)) cam.SetFocalPoint(f2 * fraction + f1 * (1 - fraction)) cam.SetViewUp(v2 * fraction + v1 * (1 - fraction)) cam.SetDistance(s2 * fraction + s1 * (1 - fraction)) cam.SetClippingRange(c2 * fraction + c1 * (1 - fraction)) self.camera = cam save_int = self.interactive self.show(resetcam=0, interactive=0) self.interactive = save_int
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python
train
jaraco/irc
irc/server.py
https://github.com/jaraco/irc/blob/571c1f448d5d5bb92bbe2605c33148bf6e698413/irc/server.py#L346-L355
def _send_to_others(self, message, channel): """ Send the message to all clients in the specified channel except for self. """ other_clients = [ client for client in channel.clients if not client == self] for client in other_clients: client.send_queue.append(message)
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Send the message to all clients in the specified channel except for self.
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python
train
datajoint/datajoint-python
datajoint/table.py
https://github.com/datajoint/datajoint-python/blob/4f29bb154a7ed2b8b64b4d3a9c8be4c16b39621c/datajoint/table.py#L58-L74
def declare(self, context=None): """ Use self.definition to declare the table in the schema. """ try: sql, uses_external = declare(self.full_table_name, self.definition, context) if uses_external: sql = sql.format(external_table=self.external_table.full_table_name) self.connection.query(sql) except pymysql.OperationalError as error: # skip if no create privilege if error.args[0] == server_error_codes['command denied']: logger.warning(error.args[1]) else: raise else: self._log('Declared ' + self.full_table_name)
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Use self.definition to declare the table in the schema.
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python
train
ronaldguillen/wave
wave/views.py
https://github.com/ronaldguillen/wave/blob/20bb979c917f7634d8257992e6d449dc751256a9/wave/views.py#L343-L351
def determine_version(self, request, *args, **kwargs): """ If versioning is being used, then determine any API version for the incoming request. Returns a two-tuple of (version, versioning_scheme) """ if self.versioning_class is None: return (None, None) scheme = self.versioning_class() return (scheme.determine_version(request, *args, **kwargs), scheme)
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If versioning is being used, then determine any API version for the incoming request. Returns a two-tuple of (version, versioning_scheme)
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python
train
ishepard/pydriller
pydriller/git_repository.py
https://github.com/ishepard/pydriller/blob/71facb32afa085d5ddf0081beba34d00d57b8080/pydriller/git_repository.py#L144-L156
def files(self) -> List[str]: """ Obtain the list of the files (excluding .git directory). :return: List[str], the list of the files """ _all = [] for path, _, files in os.walk(str(self.path)): if '.git' in path: continue for name in files: _all.append(os.path.join(path, name)) return _all
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Obtain the list of the files (excluding .git directory). :return: List[str], the list of the files
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python
train
apache/airflow
airflow/hooks/mysql_hook.py
https://github.com/apache/airflow/blob/b69c686ad8a0c89b9136bb4b31767257eb7b2597/airflow/hooks/mysql_hook.py#L62-L105
def get_conn(self): """ Returns a mysql connection object """ conn = self.get_connection(self.mysql_conn_id) conn_config = { "user": conn.login, "passwd": conn.password or '', "host": conn.host or 'localhost', "db": self.schema or conn.schema or '' } if not conn.port: conn_config["port"] = 3306 else: conn_config["port"] = int(conn.port) if conn.extra_dejson.get('charset', False): conn_config["charset"] = conn.extra_dejson["charset"] if (conn_config["charset"]).lower() == 'utf8' or\ (conn_config["charset"]).lower() == 'utf-8': conn_config["use_unicode"] = True if conn.extra_dejson.get('cursor', False): if (conn.extra_dejson["cursor"]).lower() == 'sscursor': conn_config["cursorclass"] = MySQLdb.cursors.SSCursor elif (conn.extra_dejson["cursor"]).lower() == 'dictcursor': conn_config["cursorclass"] = MySQLdb.cursors.DictCursor elif (conn.extra_dejson["cursor"]).lower() == 'ssdictcursor': conn_config["cursorclass"] = MySQLdb.cursors.SSDictCursor local_infile = conn.extra_dejson.get('local_infile', False) if conn.extra_dejson.get('ssl', False): # SSL parameter for MySQL has to be a dictionary and in case # of extra/dejson we can get string if extra is passed via # URL parameters dejson_ssl = conn.extra_dejson['ssl'] if isinstance(dejson_ssl, six.string_types): dejson_ssl = json.loads(dejson_ssl) conn_config['ssl'] = dejson_ssl if conn.extra_dejson.get('unix_socket'): conn_config['unix_socket'] = conn.extra_dejson['unix_socket'] if local_infile: conn_config["local_infile"] = 1 conn = MySQLdb.connect(**conn_config) return conn
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Returns a mysql connection object
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python
test
GoogleCloudPlatform/cloud-debug-python
src/googleclouddebugger/gcp_hub_client.py
https://github.com/GoogleCloudPlatform/cloud-debug-python/blob/89ce3782c98b814838a3ecb5479ed3882368cbee/src/googleclouddebugger/gcp_hub_client.py#L303-L340
def _RegisterDebuggee(self, service): """Single attempt to register the debuggee. If the registration succeeds, sets self._debuggee_id to the registered debuggee ID. Args: service: client to use for API calls Returns: (registration_required, delay) tuple """ try: request = {'debuggee': self._GetDebuggee()} try: response = service.debuggees().register(body=request).execute() # self._project_number will refer to the project id on initialization if # the project number is not available. The project field in the debuggee # will always refer to the project number. Update so the server will not # have to do id->number translations in the future. project_number = response['debuggee'].get('project') self._project_number = project_number or self._project_number self._debuggee_id = response['debuggee']['id'] native.LogInfo('Debuggee registered successfully, ID: %s' % ( self._debuggee_id)) self.register_backoff.Succeeded() return (False, 0) # Proceed immediately to list active breakpoints. except BaseException: native.LogInfo('Failed to register debuggee: %s, %s' % (request, traceback.format_exc())) except BaseException: native.LogWarning('Debuggee information not available: ' + traceback.format_exc()) return (True, self.register_backoff.Failed())
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Single attempt to register the debuggee. If the registration succeeds, sets self._debuggee_id to the registered debuggee ID. Args: service: client to use for API calls Returns: (registration_required, delay) tuple
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python
train
ttinies/sc2common
sc2common/containers.py
https://github.com/ttinies/sc2common/blob/469623c319c7ab7af799551055839ea3b3f87d54/sc2common/containers.py#L270-L274
def magnitude(self, allow3d=True): """determine the magnitude of this location from the origin (presume values represent a Vector)""" ret = self.x**2 + self.y**2 if allow3d: ret += self.z**2 return ret**0.5 # square root
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determine the magnitude of this location from the origin (presume values represent a Vector)
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python
train
djordon/queueing-tool
queueing_tool/graph/graph_wrapper.py
https://github.com/djordon/queueing-tool/blob/ccd418cf647ac03a54f78ba5e3725903f541b808/queueing_tool/graph/graph_wrapper.py#L73-L181
def adjacency2graph(adjacency, edge_type=None, adjust=1, **kwargs): """Takes an adjacency list, dict, or matrix and returns a graph. The purpose of this function is take an adjacency list (or matrix) and return a :class:`.QueueNetworkDiGraph` that can be used with a :class:`.QueueNetwork` instance. The Graph returned has the ``edge_type`` edge property set for each edge. Note that the graph may be altered. Parameters ---------- adjacency : dict or :class:`~numpy.ndarray` An adjacency list as either a dict, or an adjacency matrix. adjust : int ``{1, 2}`` (optional, default: 1) Specifies what to do when the graph has terminal vertices (nodes with no out-edges). Note that if ``adjust`` is not 2 then it is assumed to be 1. There are two choices: * ``adjust = 1``: A loop is added to each terminal node in the graph, and their ``edge_type`` of that loop is set to 0. * ``adjust = 2``: All edges leading to terminal nodes have their ``edge_type`` set to 0. **kwargs : Unused. Returns ------- out : :any:`networkx.DiGraph` A directed graph with the ``edge_type`` edge property. Raises ------ TypeError Is raised if ``adjacency`` is not a dict or :class:`~numpy.ndarray`. Examples -------- If terminal nodes are such that all in-edges have edge type ``0`` then nothing is changed. However, if a node is a terminal node then a loop is added with edge type 0. >>> import queueing_tool as qt >>> adj = { ... 0: {1: {}}, ... 1: {2: {}, ... 3: {}}, ... 3: {0: {}}} >>> eTy = {0: {1: 1}, 1: {2: 2, 3: 4}, 3: {0: 1}} >>> # A loop will be added to vertex 2 >>> g = qt.adjacency2graph(adj, edge_type=eTy) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 2}, 3: {'edge_type': 4}}), (2, {2: {'edge_type': 0}}), (3, {0: {'edge_type': 1}})] You can use a dict of lists to represent the adjacency list. >>> adj = {0 : [1], 1: [2, 3], 3: [0]} >>> g = qt.adjacency2graph(adj, edge_type=eTy) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 2}, 3: {'edge_type': 4}}), (2, {2: {'edge_type': 0}}), (3, {0: {'edge_type': 1}})] Alternatively, you could have this function adjust the edges that lead to terminal vertices by changing their edge type to 0: >>> # The graph is unaltered >>> g = qt.adjacency2graph(adj, edge_type=eTy, adjust=2) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 0}, 3: {'edge_type': 4}}), (2, {}), (3, {0: {'edge_type': 1}})] """ if isinstance(adjacency, np.ndarray): adjacency = _matrix2dict(adjacency) elif isinstance(adjacency, dict): adjacency = _dict2dict(adjacency) else: msg = ("If the adjacency parameter is supplied it must be a " "dict, or a numpy.ndarray.") raise TypeError(msg) if edge_type is None: edge_type = {} else: if isinstance(edge_type, np.ndarray): edge_type = _matrix2dict(edge_type, etype=True) elif isinstance(edge_type, dict): edge_type = _dict2dict(edge_type) for u, ty in edge_type.items(): for v, et in ty.items(): adjacency[u][v]['edge_type'] = et g = nx.from_dict_of_dicts(adjacency, create_using=nx.DiGraph()) adjacency = nx.to_dict_of_dicts(g) adjacency = _adjacency_adjust(adjacency, adjust, True) return nx.from_dict_of_dicts(adjacency, create_using=nx.DiGraph())
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Takes an adjacency list, dict, or matrix and returns a graph. The purpose of this function is take an adjacency list (or matrix) and return a :class:`.QueueNetworkDiGraph` that can be used with a :class:`.QueueNetwork` instance. The Graph returned has the ``edge_type`` edge property set for each edge. Note that the graph may be altered. Parameters ---------- adjacency : dict or :class:`~numpy.ndarray` An adjacency list as either a dict, or an adjacency matrix. adjust : int ``{1, 2}`` (optional, default: 1) Specifies what to do when the graph has terminal vertices (nodes with no out-edges). Note that if ``adjust`` is not 2 then it is assumed to be 1. There are two choices: * ``adjust = 1``: A loop is added to each terminal node in the graph, and their ``edge_type`` of that loop is set to 0. * ``adjust = 2``: All edges leading to terminal nodes have their ``edge_type`` set to 0. **kwargs : Unused. Returns ------- out : :any:`networkx.DiGraph` A directed graph with the ``edge_type`` edge property. Raises ------ TypeError Is raised if ``adjacency`` is not a dict or :class:`~numpy.ndarray`. Examples -------- If terminal nodes are such that all in-edges have edge type ``0`` then nothing is changed. However, if a node is a terminal node then a loop is added with edge type 0. >>> import queueing_tool as qt >>> adj = { ... 0: {1: {}}, ... 1: {2: {}, ... 3: {}}, ... 3: {0: {}}} >>> eTy = {0: {1: 1}, 1: {2: 2, 3: 4}, 3: {0: 1}} >>> # A loop will be added to vertex 2 >>> g = qt.adjacency2graph(adj, edge_type=eTy) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 2}, 3: {'edge_type': 4}}), (2, {2: {'edge_type': 0}}), (3, {0: {'edge_type': 1}})] You can use a dict of lists to represent the adjacency list. >>> adj = {0 : [1], 1: [2, 3], 3: [0]} >>> g = qt.adjacency2graph(adj, edge_type=eTy) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 2}, 3: {'edge_type': 4}}), (2, {2: {'edge_type': 0}}), (3, {0: {'edge_type': 1}})] Alternatively, you could have this function adjust the edges that lead to terminal vertices by changing their edge type to 0: >>> # The graph is unaltered >>> g = qt.adjacency2graph(adj, edge_type=eTy, adjust=2) >>> ans = qt.graph2dict(g) >>> sorted(ans.items()) # doctest: +NORMALIZE_WHITESPACE [(0, {1: {'edge_type': 1}}), (1, {2: {'edge_type': 0}, 3: {'edge_type': 4}}), (2, {}), (3, {0: {'edge_type': 1}})]
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python
valid
EventTeam/beliefs
src/beliefs/cells/lists.py
https://github.com/EventTeam/beliefs/blob/c07d22b61bebeede74a72800030dde770bf64208/src/beliefs/cells/lists.py#L304-L323
def merge(self, other): """ Merges two prefixes """ other = PrefixCell.coerce(other) if self.is_equal(other): # pick among dependencies return self elif other.is_entailed_by(self): return self elif self.is_entailed_by(other): self.value = other.value elif self.is_contradictory(other): raise Contradiction("Cannot merge prefix '%s' with '%s'" % \ (self, other)) else: if len(self.value) > len(other.value): self.value = other.value[:] # otherwise, return self return self
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Merges two prefixes
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python
train
StackStorm/pybind
pybind/slxos/v17r_1_01a/__init__.py
https://github.com/StackStorm/pybind/blob/44c467e71b2b425be63867aba6e6fa28b2cfe7fb/pybind/slxos/v17r_1_01a/__init__.py#L13373-L13396
def _set_loam_state(self, v, load=False): """ Setter method for loam_state, mapped from YANG variable /loam_state (container) If this variable is read-only (config: false) in the source YANG file, then _set_loam_state is considered as a private method. Backends looking to populate this variable should do so via calling thisObj._set_loam_state() directly. YANG Description: LINK-OAM Operational Information """ if hasattr(v, "_utype"): v = v._utype(v) try: t = YANGDynClass(v,base=loam_state.loam_state, is_container='container', presence=False, yang_name="loam-state", rest_name="loam-state", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'dot1ag-loam', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-dot1ag-operational', defining_module='brocade-dot1ag-operational', yang_type='container', is_config=True) except (TypeError, ValueError): raise ValueError({ 'error-string': """loam_state must be of a type compatible with container""", 'defined-type': "container", 'generated-type': """YANGDynClass(base=loam_state.loam_state, is_container='container', presence=False, yang_name="loam-state", rest_name="loam-state", parent=self, path_helper=self._path_helper, extmethods=self._extmethods, register_paths=True, extensions={u'tailf-common': {u'callpoint': u'dot1ag-loam', u'cli-suppress-show-path': None}}, namespace='urn:brocade.com:mgmt:brocade-dot1ag-operational', defining_module='brocade-dot1ag-operational', yang_type='container', is_config=True)""", }) self.__loam_state = t if hasattr(self, '_set'): self._set()
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python
train
d0c-s4vage/pfp
pfp/interp.py
https://github.com/d0c-s4vage/pfp/blob/32f2d34fdec1c70019fa83c7006d5e3be0f92fcd/pfp/interp.py#L951-L972
def _handle_file_ast(self, node, scope, ctxt, stream): """TODO: Docstring for _handle_file_ast. :node: TODO :scope: TODO :ctxt: TODO :stream: TODO :returns: TODO """ self._root = ctxt = fields.Dom(stream) ctxt._pfp__scope = scope self._root._pfp__name = "__root" self._root._pfp__interp = self self._dlog("handling file AST with {} children".format(len(node.children()))) for child in node.children(): self._handle_node(child, scope, ctxt, stream) ctxt._pfp__process_fields_metadata() return ctxt
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TODO: Docstring for _handle_file_ast. :node: TODO :scope: TODO :ctxt: TODO :stream: TODO :returns: TODO
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python
train
ewiger/mlab
src/mlab/awmstools.py
https://github.com/ewiger/mlab/blob/72a98adf6499f548848ad44c604f74d68f07fe4f/src/mlab/awmstools.py#L655-L669
def unweave(iterable, n=2): r"""Divide `iterable` in `n` lists, so that every `n`th element belongs to list `n`. Example: >>> unweave((1,2,3,4,5), 3) [[1, 4], [2, 5], [3]] """ res = [[] for i in range(n)] i = 0 for x in iterable: res[i % n].append(x) i += 1 return res
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r"""Divide `iterable` in `n` lists, so that every `n`th element belongs to list `n`. Example: >>> unweave((1,2,3,4,5), 3) [[1, 4], [2, 5], [3]]
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python
train
blackecho/Deep-Learning-TensorFlow
yadlt/utils/tf_utils.py
https://github.com/blackecho/Deep-Learning-TensorFlow/blob/ddeb1f2848da7b7bee166ad2152b4afc46bb2086/yadlt/utils/tf_utils.py#L53-L93
def run_summaries( sess, merged_summaries, summary_writer, epoch, feed, tens): """Run the summaries and error computation on the validation set. Parameters ---------- sess : tf.Session Tensorflow session object. merged_summaries : tf obj Tensorflow merged summaries obj. summary_writer : tf.summary.FileWriter Tensorflow summary writer obj. epoch : int Current training epoch. feed : dict Validation feed dict. tens : tf.Tensor Tensor to display and evaluate during training. Can be self.accuracy for SupervisedModel or self.cost for UnsupervisedModel. Returns ------- err : float, mean error over the validation set. """ try: result = sess.run([merged_summaries, tens], feed_dict=feed) summary_str = result[0] out = result[1] summary_writer.add_summary(summary_str, epoch) except tf.errors.InvalidArgumentError: out = sess.run(tens, feed_dict=feed) return out
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Run the summaries and error computation on the validation set. Parameters ---------- sess : tf.Session Tensorflow session object. merged_summaries : tf obj Tensorflow merged summaries obj. summary_writer : tf.summary.FileWriter Tensorflow summary writer obj. epoch : int Current training epoch. feed : dict Validation feed dict. tens : tf.Tensor Tensor to display and evaluate during training. Can be self.accuracy for SupervisedModel or self.cost for UnsupervisedModel. Returns ------- err : float, mean error over the validation set.
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python
train
mrstephenneal/mysql-toolkit
mysql/toolkit/components/structure/__init__.py
https://github.com/mrstephenneal/mysql-toolkit/blob/6964f718f4b72eb30f2259adfcfaf3090526c53d/mysql/toolkit/components/structure/__init__.py#L55-L58
def get_duplicate_vals(self, table, column): """Retrieve duplicate values in a column of a table.""" query = 'SELECT {0} FROM {1} GROUP BY {0} HAVING COUNT(*) > 1'.format(join_cols(column), wrap(table)) return self.fetch(query)
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Retrieve duplicate values in a column of a table.
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python
train
PmagPy/PmagPy
SPD/lib/lib_ptrm_statistics.py
https://github.com/PmagPy/PmagPy/blob/c7984f8809bf40fe112e53dcc311a33293b62d0b/SPD/lib/lib_ptrm_statistics.py#L198-L212
def get_b_star(x_star, y_err, y_mean, y_segment): """ input: x_star, y_err, y_mean, y_segment output: b_star (corrected slope for delta_pal statistic) """ #print "x_star, should be same as Xcorr / NRM" #print x_star x_star_mean = numpy.mean(x_star) x_err = x_star - x_star_mean b_star = -1* numpy.sqrt( old_div(sum(numpy.array(y_err)**2), sum(numpy.array(x_err)**2)) ) # averaged slope #print "y_segment", y_segment b_star = numpy.sign(sum(x_err * y_err)) * numpy.std(y_segment, ddof=1) / numpy.std(x_star, ddof=1) #print "b_star (should be same as corr_slope)" #print b_star return b_star
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input: x_star, y_err, y_mean, y_segment output: b_star (corrected slope for delta_pal statistic)
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python
train
DataBiosphere/toil
src/toil/__init__.py
https://github.com/DataBiosphere/toil/blob/a8252277ff814e7bee0971139c2344f88e44b644/src/toil/__init__.py#L384-L410
def requestCheckDockerIo(origAppliance, imageName, tag): """ Checks docker.io to see if an image exists using the requests library. URL is based on the docker v2 schema. Requires that an access token be fetched first. :param str origAppliance: The full url of the docker image originally specified by the user (or the default). e.g. "ubuntu:latest" :param str imageName: The image, including path and excluding the tag. e.g. "ubuntu" :param str tag: The tag used at that docker image's registry. e.g. "latest" :return: Return True if match found. Raise otherwise. """ # only official images like 'busybox' or 'ubuntu' if '/' not in imageName: imageName = 'library/' + imageName token_url = 'https://auth.docker.io/token?service=registry.docker.io&scope=repository:{repo}:pull'.format(repo=imageName) requests_url = 'https://registry-1.docker.io/v2/{repo}/manifests/{tag}'.format(repo=imageName, tag=tag) token = requests.get(token_url) jsonToken = token.json() bearer = jsonToken["token"] response = requests.head(requests_url, headers={'Authorization': 'Bearer {}'.format(bearer)}) if not response.ok: raise ApplianceImageNotFound(origAppliance, requests_url, response.status_code) else: return origAppliance
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Checks docker.io to see if an image exists using the requests library. URL is based on the docker v2 schema. Requires that an access token be fetched first. :param str origAppliance: The full url of the docker image originally specified by the user (or the default). e.g. "ubuntu:latest" :param str imageName: The image, including path and excluding the tag. e.g. "ubuntu" :param str tag: The tag used at that docker image's registry. e.g. "latest" :return: Return True if match found. Raise otherwise.
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python
train
Karaage-Cluster/karaage
karaage/datastores/slurm.py
https://github.com/Karaage-Cluster/karaage/blob/2f4c8b4e2d728b3fcbb151160c49000f1c04f5c9/karaage/datastores/slurm.py#L401-L411
def delete_project(self, project): """ Called when project is deleted. """ pid = project.pid # project deleted ds_project = self.get_project(pid) if ds_project is not None: self._call(["delete", "account", "name=%s" % pid]) return
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Called when project is deleted.
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python
train
GNS3/gns3-server
gns3server/controller/udp_link.py
https://github.com/GNS3/gns3-server/blob/a221678448fb5d24e977ef562f81d56aacc89ab1/gns3server/controller/udp_link.py#L165-L172
def stop_capture(self): """ Stop capture on a link """ if self._capture_node: yield from self._capture_node["node"].post("/adapters/{adapter_number}/ports/{port_number}/stop_capture".format(adapter_number=self._capture_node["adapter_number"], port_number=self._capture_node["port_number"])) self._capture_node = None yield from super().stop_capture()
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Stop capture on a link
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python
train
seleniumbase/SeleniumBase
seleniumbase/fixtures/page_utils.py
https://github.com/seleniumbase/SeleniumBase/blob/62e5b43ee1f90a9ed923841bdd53b1b38358f43a/seleniumbase/fixtures/page_utils.py#L132-L145
def _get_link_status_code(link, allow_redirects=False, timeout=5): """ Get the status code of a link. If the timeout is exceeded, will return a 404. For a list of available status codes, see: https://en.wikipedia.org/wiki/List_of_HTTP_status_codes """ status_code = None try: response = requests.get( link, allow_redirects=allow_redirects, timeout=timeout) status_code = response.status_code except Exception: status_code = 404 return status_code
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Get the status code of a link. If the timeout is exceeded, will return a 404. For a list of available status codes, see: https://en.wikipedia.org/wiki/List_of_HTTP_status_codes
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python
train
pantsbuild/pants
src/python/pants/backend/jvm/tasks/jar_task.py
https://github.com/pantsbuild/pants/blob/b72e650da0df685824ffdcc71988b8c282d0962d/src/python/pants/backend/jvm/tasks/jar_task.py#L160-L181
def write(self, src, dest=None): """Schedules a write of the file at ``src`` to the ``dest`` path in this jar. If the ``src`` is a file, then ``dest`` must be specified. If the ``src`` is a directory then by default all descendant files will be added to the jar as entries carrying their relative path. If ``dest`` is specified it will be prefixed to each descendant's relative path to form its jar entry path. :param string src: the path to the pre-existing source file or directory :param string dest: the path the source file or directory should have in this jar """ if not src or not isinstance(src, string_types): raise ValueError('The src path must be a non-empty string, got {} of type {}.'.format( src, type(src))) if dest and not isinstance(dest, string_types): raise ValueError('The dest entry path must be a non-empty string, got {} of type {}.'.format( dest, type(dest))) if not os.path.isdir(src) and not dest: raise self.Error('Source file {} must have a jar destination specified'.format(src)) self._add_entry(self.FileSystemEntry(src, dest))
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Schedules a write of the file at ``src`` to the ``dest`` path in this jar. If the ``src`` is a file, then ``dest`` must be specified. If the ``src`` is a directory then by default all descendant files will be added to the jar as entries carrying their relative path. If ``dest`` is specified it will be prefixed to each descendant's relative path to form its jar entry path. :param string src: the path to the pre-existing source file or directory :param string dest: the path the source file or directory should have in this jar
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python
train
welbornprod/colr
colr/colr.py
https://github.com/welbornprod/colr/blob/417117fdbddbc53142096685ac2af006b2bd0220/colr/colr.py#L1605-L1664
def gradient_black( self, text=None, fore=None, back=None, style=None, start=None, step=1, reverse=False, linemode=True, movefactor=2, rgb_mode=False): """ Return a black and white gradient. Arguments: text : String to colorize. This will always be greater than 0. fore : Foreground color, background will be gradient. back : Background color, foreground will be gradient. style : Name of style to use for the gradient. start : Starting 256-color number. The `start` will be adjusted if it is not within bounds. This will always be > 15. This will be adjusted to fit within a 6-length gradient, or the 24-length black/white gradient. step : Number of characters to colorize per color. This allows a "wider" gradient. linemode : Colorize each line in the input. Default: True movefactor : Factor for offset increase on each line when using linemode. Minimum value: 0 Default: 2 rgb_mode : Use true color (rgb) method and codes. """ gradargs = { 'step': step, 'fore': fore, 'back': back, 'style': style, 'reverse': reverse, 'rgb_mode': rgb_mode, } if linemode: gradargs['movefactor'] = 2 if movefactor is None else movefactor method = self._gradient_black_lines else: method = self._gradient_black_line if text: return self.__class__( ''.join(( self.data or '', method( text, start or (255 if reverse else 232), **gradargs) )) ) # Operating on self.data. return self.__class__( method( self.stripped(), start or (255 if reverse else 232), **gradargs) )
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Return a black and white gradient. Arguments: text : String to colorize. This will always be greater than 0. fore : Foreground color, background will be gradient. back : Background color, foreground will be gradient. style : Name of style to use for the gradient. start : Starting 256-color number. The `start` will be adjusted if it is not within bounds. This will always be > 15. This will be adjusted to fit within a 6-length gradient, or the 24-length black/white gradient. step : Number of characters to colorize per color. This allows a "wider" gradient. linemode : Colorize each line in the input. Default: True movefactor : Factor for offset increase on each line when using linemode. Minimum value: 0 Default: 2 rgb_mode : Use true color (rgb) method and codes.
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python
train
sdispater/orator
orator/orm/relations/has_one_or_many.py
https://github.com/sdispater/orator/blob/bd90bf198ee897751848f9a92e49d18e60a74136/orator/orm/relations/has_one_or_many.py#L297-L312
def update(self, _attributes=None, **attributes): """ Perform an update on all the related models. :param attributes: The attributes :type attributes: dict :rtype: int """ if _attributes is not None: attributes.update(_attributes) if self._related.uses_timestamps(): attributes[self.get_related_updated_at()] = self._related.fresh_timestamp() return self._query.update(attributes)
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Perform an update on all the related models. :param attributes: The attributes :type attributes: dict :rtype: int
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python
train
quantopian/zipline
zipline/data/loader.py
https://github.com/quantopian/zipline/blob/77ad15e6dc4c1cbcdc133653bac8a63fc704f7fe/zipline/data/loader.py#L78-L87
def has_data_for_dates(series_or_df, first_date, last_date): """ Does `series_or_df` have data on or before first_date and on or after last_date? """ dts = series_or_df.index if not isinstance(dts, pd.DatetimeIndex): raise TypeError("Expected a DatetimeIndex, but got %s." % type(dts)) first, last = dts[[0, -1]] return (first <= first_date) and (last >= last_date)
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Does `series_or_df` have data on or before first_date and on or after last_date?
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python
train
pystorm/pystorm
pystorm/spout.py
https://github.com/pystorm/pystorm/blob/0f853e007c79e03cefdb4a0794423f84dce4c2f3/pystorm/spout.py#L183-L206
def emit( self, tup, tup_id=None, stream=None, direct_task=None, need_task_ids=False ): """Emit a spout Tuple & add metadata about it to `unacked_tuples`. In order for this to work, `tup_id` is a required parameter. See :meth:`Bolt.emit`. """ if tup_id is None: raise ValueError( "You must provide a tuple ID when emitting with a " "ReliableSpout in order for the tuple to be " "tracked." ) args = (tup, stream, direct_task, need_task_ids) self.unacked_tuples[tup_id] = args return super(ReliableSpout, self).emit( tup, tup_id=tup_id, stream=stream, direct_task=direct_task, need_task_ids=need_task_ids, )
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Emit a spout Tuple & add metadata about it to `unacked_tuples`. In order for this to work, `tup_id` is a required parameter. See :meth:`Bolt.emit`.
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python
train
jcrist/skein
skein/objects.py
https://github.com/jcrist/skein/blob/16f8b1d3b3d9f79f36e2f152e45893339a1793e8/skein/objects.py#L247-L250
def to_yaml(self, skip_nulls=True): """Convert object to a yaml string""" return yaml.safe_dump(self.to_dict(skip_nulls=skip_nulls), default_flow_style=False)
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Convert object to a yaml string
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python
train
ejeschke/ginga
ginga/gtkw/ImageViewGtk.py
https://github.com/ejeschke/ginga/blob/a78c893ec6f37a837de851947e9bb4625c597915/ginga/gtkw/ImageViewGtk.py#L83-L91
def save_plain_image_as_file(self, filepath, format='png', quality=90): """Used for generating thumbnails. Does not include overlaid graphics. """ pixbuf = self.get_plain_image_as_pixbuf() options = {} if format == 'jpeg': options['quality'] = str(quality) pixbuf.save(filepath, format, options)
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Used for generating thumbnails. Does not include overlaid graphics.
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python
train
iotile/coretools
iotileemulate/iotile/emulate/reference/controller_features/sensor_log.py
https://github.com/iotile/coretools/blob/2d794f5f1346b841b0dcd16c9d284e9bf2f3c6ec/iotileemulate/iotile/emulate/reference/controller_features/sensor_log.py#L104-L119
def clear_to_reset(self, config_vars): """Clear all volatile information across a reset.""" self._logger.info("Config vars in sensor log reset: %s", config_vars) super(SensorLogSubsystem, self).clear_to_reset(config_vars) self.storage.destroy_all_walkers() self.dump_walker = None if config_vars.get('storage_fillstop', False): self._logger.debug("Marking storage log fill/stop") self.storage.set_rollover('storage', False) if config_vars.get('streaming_fillstop', False): self._logger.debug("Marking streaming log fill/stop") self.storage.set_rollover('streaming', False)
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Clear all volatile information across a reset.
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python
train
nlppln/nlppln
nlppln/commands/frog_to_saf.py
https://github.com/nlppln/nlppln/blob/1155191921289a65ba2becd2bf8dfabb48eaf1f1/nlppln/commands/frog_to_saf.py#L53-L59
def _add_pos1(token): """ Adds a 'pos1' element to a frog token. """ result = token.copy() result['pos1'] = _POSMAP[token['pos'].split("(")[0]] return result
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Adds a 'pos1' element to a frog token.
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python
train
Yelp/kafka-utils
kafka_utils/kafka_cluster_manager/cluster_info/display.py
https://github.com/Yelp/kafka-utils/blob/cdb4d64308f3079ee0873250bf7b34d0d94eca50/kafka_utils/kafka_cluster_manager/cluster_info/display.py#L190-L254
def display_leader_imbalance(cluster_topologies): """Display leader count and weight imbalance statistics. :param cluster_topologies: A dictionary mapping a string name to a ClusterTopology object. """ broker_ids = list(next(six.itervalues(cluster_topologies)).brokers.keys()) assert all( set(broker_ids) == set(cluster_topology.brokers.keys()) for cluster_topology in six.itervalues(cluster_topologies) ) broker_leader_counts = [ stats.get_broker_leader_counts( cluster_topology.brokers[broker_id] for broker_id in broker_ids ) for cluster_topology in six.itervalues(cluster_topologies) ] broker_leader_weights = [ stats.get_broker_leader_weights( cluster_topology.brokers[broker_id] for broker_id in broker_ids ) for cluster_topology in six.itervalues(cluster_topologies) ] _display_table_title_multicolumn( 'Leader Count', 'Brokers', broker_ids, list(cluster_topologies.keys()), broker_leader_counts, ) print('') _display_table_title_multicolumn( 'Leader weight', 'Brokers', broker_ids, list(cluster_topologies.keys()), broker_leader_weights, ) for name, blc, blw in zip( list(cluster_topologies.keys()), broker_leader_counts, broker_leader_weights ): print( '\n' '{name}' 'Leader count imbalance: {net_imbalance}\n' 'Broker leader weight mean: {weight_mean}\n' 'Broker leader weight stdev: {weight_stdev}\n' 'Broker leader weight cv: {weight_cv}' .format( name='' if len(cluster_topologies) == 1 else name + '\n', net_imbalance=stats.get_net_imbalance(blc), weight_mean=stats.mean(blw), weight_stdev=stats.stdevp(blw), weight_cv=stats.coefficient_of_variation(blw), ) )
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Display leader count and weight imbalance statistics. :param cluster_topologies: A dictionary mapping a string name to a ClusterTopology object.
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python
train
PyCQA/pylint
pylint/lint.py
https://github.com/PyCQA/pylint/blob/2bf5c61a3ff6ae90613b81679de42c0f19aea600/pylint/lint.py#L898-L905
def get_checkers(self): """return all available checkers as a list""" return [self] + [ c for _checkers in self._checkers.values() for c in _checkers if c is not self ]
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return all available checkers as a list
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python
test
DarkEnergySurvey/ugali
ugali/isochrone/model.py
https://github.com/DarkEnergySurvey/ugali/blob/21e890b4117fc810afb6fb058e8055d564f03382/ugali/isochrone/model.py#L1158-L1203
def download(self,age=None,metallicity=None,outdir=None,force=False): """ Check valid parameter range and download isochrones from: http://stev.oapd.inaf.it/cgi-bin/cmd """ try: from urllib.error import URLError except ImportError: from urllib2 import URLError if age is None: age = float(self.age) if metallicity is None: metallicity = float(self.metallicity) if outdir is None: outdir = './' basename = self.params2filename(age,metallicity) outfile = os.path.join(outdir,basename) if os.path.exists(outfile) and not force: try: self.verify(outfile,self.survey,age,metallicity) logger.info("Found %s; skipping..."%(outfile)) return except Exception as e: msg = "Overwriting corrupted %s..."%(outfile) logger.warn(msg) os.remove(outfile) mkdir(outdir) self.print_info(age,metallicity) self.query_server(outfile,age,metallicity) if not os.path.exists(outfile): raise RuntimeError('Download failed') try: self.verify(outfile,self.survey,age,metallicity) except Exception as e: msg = "Output file is corrupted." logger.error(msg) msg = "Removing %s."%outfile logger.info(msg) os.remove(outfile) raise(e) return outfile
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Check valid parameter range and download isochrones from: http://stev.oapd.inaf.it/cgi-bin/cmd
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python
train
awslabs/serverless-application-model
samtranslator/translator/translator.py
https://github.com/awslabs/serverless-application-model/blob/cccb0c96b5c91e53355ebc07e542467303a5eedd/samtranslator/translator/translator.py#L34-L122
def translate(self, sam_template, parameter_values): """Loads the SAM resources from the given SAM manifest, replaces them with their corresponding CloudFormation resources, and returns the resulting CloudFormation template. :param dict sam_template: the SAM manifest, as loaded by json.load() or yaml.load(), or as provided by \ CloudFormation transforms. :param dict parameter_values: Map of template parameter names to their values. It is a required parameter that should at least be an empty map. By providing an empty map, the caller explicitly opts-into the idea that some functionality that relies on resolving parameter references might not work as expected (ex: auto-creating new Lambda Version when CodeUri contains reference to template parameter). This is why this parameter is required :returns: a copy of the template with SAM resources replaced with the corresponding CloudFormation, which may \ be dumped into a valid CloudFormation JSON or YAML template """ sam_parameter_values = SamParameterValues(parameter_values) sam_parameter_values.add_default_parameter_values(sam_template) sam_parameter_values.add_pseudo_parameter_values() parameter_values = sam_parameter_values.parameter_values # Create & Install plugins sam_plugins = prepare_plugins(self.plugins, parameter_values) self.sam_parser.parse( sam_template=sam_template, parameter_values=parameter_values, sam_plugins=sam_plugins ) template = copy.deepcopy(sam_template) macro_resolver = ResourceTypeResolver(sam_resources) intrinsics_resolver = IntrinsicsResolver(parameter_values) deployment_preference_collection = DeploymentPreferenceCollection() supported_resource_refs = SupportedResourceReferences() document_errors = [] changed_logical_ids = {} for logical_id, resource_dict in self._get_resources_to_iterate(sam_template, macro_resolver): try: macro = macro_resolver\ .resolve_resource_type(resource_dict)\ .from_dict(logical_id, resource_dict, sam_plugins=sam_plugins) kwargs = macro.resources_to_link(sam_template['Resources']) kwargs['managed_policy_map'] = self.managed_policy_map kwargs['intrinsics_resolver'] = intrinsics_resolver kwargs['deployment_preference_collection'] = deployment_preference_collection translated = macro.to_cloudformation(**kwargs) supported_resource_refs = macro.get_resource_references(translated, supported_resource_refs) # Some resources mutate their logical ids. Track those to change all references to them: if logical_id != macro.logical_id: changed_logical_ids[logical_id] = macro.logical_id del template['Resources'][logical_id] for resource in translated: if verify_unique_logical_id(resource, sam_template['Resources']): template['Resources'].update(resource.to_dict()) else: document_errors.append(DuplicateLogicalIdException( logical_id, resource.logical_id, resource.resource_type)) except (InvalidResourceException, InvalidEventException) as e: document_errors.append(e) if deployment_preference_collection.any_enabled(): template['Resources'].update(deployment_preference_collection.codedeploy_application.to_dict()) if not deployment_preference_collection.can_skip_service_role(): template['Resources'].update(deployment_preference_collection.codedeploy_iam_role.to_dict()) for logical_id in deployment_preference_collection.enabled_logical_ids(): template['Resources'].update(deployment_preference_collection.deployment_group(logical_id).to_dict()) # Run the after-transform plugin target try: sam_plugins.act(LifeCycleEvents.after_transform_template, template) except (InvalidDocumentException, InvalidResourceException) as e: document_errors.append(e) # Cleanup if 'Transform' in template: del template['Transform'] if len(document_errors) == 0: template = intrinsics_resolver.resolve_sam_resource_id_refs(template, changed_logical_ids) template = intrinsics_resolver.resolve_sam_resource_refs(template, supported_resource_refs) return template else: raise InvalidDocumentException(document_errors)
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Loads the SAM resources from the given SAM manifest, replaces them with their corresponding CloudFormation resources, and returns the resulting CloudFormation template. :param dict sam_template: the SAM manifest, as loaded by json.load() or yaml.load(), or as provided by \ CloudFormation transforms. :param dict parameter_values: Map of template parameter names to their values. It is a required parameter that should at least be an empty map. By providing an empty map, the caller explicitly opts-into the idea that some functionality that relies on resolving parameter references might not work as expected (ex: auto-creating new Lambda Version when CodeUri contains reference to template parameter). This is why this parameter is required :returns: a copy of the template with SAM resources replaced with the corresponding CloudFormation, which may \ be dumped into a valid CloudFormation JSON or YAML template
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python
train
idlesign/django-siteprefs
siteprefs/toolbox.py
https://github.com/idlesign/django-siteprefs/blob/3d6bf5e64220fe921468a36fce68e15d7947cf92/siteprefs/toolbox.py#L249-L279
def register_prefs(*args, **kwargs): """Registers preferences that should be handled by siteprefs. Expects preferences as *args. Use keyword arguments to batch apply params supported by ``PrefProxy`` to all preferences not constructed by ``pref`` and ``pref_group``. Batch kwargs: :param str|unicode help_text: Field help text. :param bool static: Leave this preference static (do not store in DB). :param bool readonly: Make this field read only. :param bool swap_settings_module: Whether to automatically replace settings module with a special ``ProxyModule`` object to access dynamic values of settings transparently (so not to bother with calling ``.value`` of ``PrefProxy`` object). """ swap_settings_module = bool(kwargs.get('swap_settings_module', True)) if __PATCHED_LOCALS_SENTINEL not in get_frame_locals(2): raise SitePrefsException('Please call `patch_locals()` right before the `register_prefs()`.') bind_proxy(args, **kwargs) unpatch_locals() swap_settings_module and proxy_settings_module()
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Registers preferences that should be handled by siteprefs. Expects preferences as *args. Use keyword arguments to batch apply params supported by ``PrefProxy`` to all preferences not constructed by ``pref`` and ``pref_group``. Batch kwargs: :param str|unicode help_text: Field help text. :param bool static: Leave this preference static (do not store in DB). :param bool readonly: Make this field read only. :param bool swap_settings_module: Whether to automatically replace settings module with a special ``ProxyModule`` object to access dynamic values of settings transparently (so not to bother with calling ``.value`` of ``PrefProxy`` object).
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python
valid
boriel/zxbasic
zxbasmpplex.py
https://github.com/boriel/zxbasic/blob/23b28db10e41117805bdb3c0f78543590853b132/zxbasmpplex.py#L295-L298
def put_current_line(self, prefix=''): """ Returns line and file for include / end of include sequences. """ return '%s#line %i "%s"\n' % (prefix, self.lex.lineno, os.path.basename(self.filestack[-1][0]))
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Returns line and file for include / end of include sequences.
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python
train
evandempsey/fp-growth
pyfpgrowth/pyfpgrowth.py
https://github.com/evandempsey/fp-growth/blob/6bf4503024e86c5bbea8a05560594f2f7f061c15/pyfpgrowth/pyfpgrowth.py#L135-L146
def tree_has_single_path(self, node): """ If there is a single path in the tree, return True, else return False. """ num_children = len(node.children) if num_children > 1: return False elif num_children == 0: return True else: return True and self.tree_has_single_path(node.children[0])
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If there is a single path in the tree, return True, else return False.
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python
train
pandas-dev/pandas
pandas/core/groupby/groupby.py
https://github.com/pandas-dev/pandas/blob/9feb3ad92cc0397a04b665803a49299ee7aa1037/pandas/core/groupby/groupby.py#L1474-L1505
def _fill(self, direction, limit=None): """ Shared function for `pad` and `backfill` to call Cython method. Parameters ---------- direction : {'ffill', 'bfill'} Direction passed to underlying Cython function. `bfill` will cause values to be filled backwards. `ffill` and any other values will default to a forward fill limit : int, default None Maximum number of consecutive values to fill. If `None`, this method will convert to -1 prior to passing to Cython Returns ------- `Series` or `DataFrame` with filled values See Also -------- pad backfill """ # Need int value for Cython if limit is None: limit = -1 return self._get_cythonized_result('group_fillna_indexer', self.grouper, needs_mask=True, cython_dtype=np.int64, result_is_index=True, direction=direction, limit=limit)
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Shared function for `pad` and `backfill` to call Cython method. Parameters ---------- direction : {'ffill', 'bfill'} Direction passed to underlying Cython function. `bfill` will cause values to be filled backwards. `ffill` and any other values will default to a forward fill limit : int, default None Maximum number of consecutive values to fill. If `None`, this method will convert to -1 prior to passing to Cython Returns ------- `Series` or `DataFrame` with filled values See Also -------- pad backfill
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python
train
saltstack/salt
salt/modules/jenkinsmod.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/jenkinsmod.py#L222-L251
def build_job(name=None, parameters=None): ''' Initiate a build for the provided job. :param name: The name of the job is check if it exists. :param parameters: Parameters to send to the job. :return: True is successful, otherwise raise an exception. CLI Example: .. code-block:: bash salt '*' jenkins.build_job jobname ''' if not name: raise SaltInvocationError('Required parameter \'name\' is missing') server = _connect() if not job_exists(name): raise CommandExecutionError('Job \'{0}\' does not exist.'.format(name)) try: server.build_job(name, parameters) except jenkins.JenkinsException as err: raise CommandExecutionError( 'Encountered error building job \'{0}\': {1}'.format(name, err) ) return True
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Initiate a build for the provided job. :param name: The name of the job is check if it exists. :param parameters: Parameters to send to the job. :return: True is successful, otherwise raise an exception. CLI Example: .. code-block:: bash salt '*' jenkins.build_job jobname
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python
train
pybel/pybel
src/pybel/manager/models.py
https://github.com/pybel/pybel/blob/c8a7a1bdae4c475fa2a8c77f3a9a5f6d79556ca0/src/pybel/manager/models.py#L166-L184
def to_json(self, include_id: bool = False) -> Mapping[str, str]: """Describe the namespaceEntry as dictionary of Namespace-Keyword and Name. :param include_id: If true, includes the model identifier """ result = { NAMESPACE: self.namespace.keyword, } if self.name: result[NAME] = self.name if self.identifier: result[IDENTIFIER] = self.identifier if include_id: result['id'] = self.id return result
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Describe the namespaceEntry as dictionary of Namespace-Keyword and Name. :param include_id: If true, includes the model identifier
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python
train
manns/pyspread
pyspread/src/lib/vlc.py
https://github.com/manns/pyspread/blob/0e2fd44c2e0f06605efc3058c20a43a8c1f9e7e0/pyspread/src/lib/vlc.py#L2727-L2740
def set_mrl(self, mrl, *options): """Set the MRL to play. Warning: most audio and video options, such as text renderer, have no effects on an individual media. These options must be set at the vlc.Instance or vlc.MediaPlayer instanciation. @param mrl: The MRL @param options: optional media option=value strings @return: the Media object """ m = self.get_instance().media_new(mrl, *options) self.set_media(m) return m
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Set the MRL to play. Warning: most audio and video options, such as text renderer, have no effects on an individual media. These options must be set at the vlc.Instance or vlc.MediaPlayer instanciation. @param mrl: The MRL @param options: optional media option=value strings @return: the Media object
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python
train
ArangoDB-Community/pyArango
pyArango/document.py
https://github.com/ArangoDB-Community/pyArango/blob/dd72e5f6c540e5e148943d615ddf7553bb78ce0b/pyArango/document.py#L214-L224
def setPrivates(self, fieldDict) : """will set self._id, self._rev and self._key field.""" for priv in self.privates : if priv in fieldDict : setattr(self, priv, fieldDict[priv]) else : setattr(self, priv, None) if self._id is not None : self.URL = "%s/%s" % (self.documentsURL, self._id)
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will set self._id, self._rev and self._key field.
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python
train
eqcorrscan/EQcorrscan
eqcorrscan/utils/catalog_utils.py
https://github.com/eqcorrscan/EQcorrscan/blob/3121b4aca801ee5d38f56ca297ce1c0f9515d9ff/eqcorrscan/utils/catalog_utils.py#L166-L209
def spatial_clip(catalog, corners, mindepth=None, maxdepth=None): """ Clip the catalog to a spatial box, can be irregular. Can only be irregular in 2D, depth must be between bounds. :type catalog: :class:`obspy.core.catalog.Catalog` :param catalog: Catalog to clip. :type corners: :class:`matplotlib.path.Path` :param corners: Corners to clip the catalog to :type mindepth: float :param mindepth: Minimum depth for earthquakes in km. :type maxdepth: float :param maxdepth: Maximum depth for earthquakes in km. .. Note:: Corners is expected to be a :class:`matplotlib.path.Path` in the form of tuples of (lat, lon) in decimal degrees. """ cat_out = catalog.copy() if mindepth is not None: for event in cat_out: try: origin = _get_origin(event) except IOError: continue if origin.depth < mindepth * 1000: cat_out.events.remove(event) if maxdepth is not None: for event in cat_out: try: origin = _get_origin(event) except IOError: continue if origin.depth > maxdepth * 1000: cat_out.events.remove(event) for event in cat_out: try: origin = _get_origin(event) except IOError: continue if not corners.contains_point((origin.latitude, origin.longitude)): cat_out.events.remove(event) return cat_out
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Clip the catalog to a spatial box, can be irregular. Can only be irregular in 2D, depth must be between bounds. :type catalog: :class:`obspy.core.catalog.Catalog` :param catalog: Catalog to clip. :type corners: :class:`matplotlib.path.Path` :param corners: Corners to clip the catalog to :type mindepth: float :param mindepth: Minimum depth for earthquakes in km. :type maxdepth: float :param maxdepth: Maximum depth for earthquakes in km. .. Note:: Corners is expected to be a :class:`matplotlib.path.Path` in the form of tuples of (lat, lon) in decimal degrees.
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python
train
trevisanj/a99
a99/config.py
https://github.com/trevisanj/a99/blob/193e6e3c9b3e4f4a0ba7eb3eece846fe7045c539/a99/config.py#L87-L94
def get_config_obj(filename): """Reads/creates filename at user **home** folder and returns a AAConfigObj object""" if not filename.startswith("."): a99.get_python_logger().warning("Configuration filename '{}' does not start with a '.'".format(filename)) path_ = os.path.join(os.path.expanduser("~"), filename) return AAConfigObj(path_, encoding="UTF8")
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Reads/creates filename at user **home** folder and returns a AAConfigObj object
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python
train
biocore/burrito-fillings
bfillings/usearch.py
https://github.com/biocore/burrito-fillings/blob/02ab71a46119b40793bd56a4ae00ca15f6dc3329/bfillings/usearch.py#L991-L1036
def get_fasta_from_uc_file(fasta_filepath, uc_filepath, hit_type="H", output_fna_filepath=None, label_prefix="", output_dir=None): """ writes fasta of sequences from uc file of type hit_type fasta_filepath: Filepath of original query fasta file uc_filepath: Filepath of .uc file created by usearch post error filtering hit_type: type to read from first field of .uc file, "H" for hits, "N" for no hits. output_fna_filepath = fasta output filepath label_prefix = Added before each fasta label, important when doing ref based OTU picking plus de novo clustering to preserve label matching. output_dir: output directory """ hit_type_index = 0 seq_label_index = 8 target_label_index = 9 labels_hits = {} labels_to_keep = [] for line in open(uc_filepath, "U"): if line.startswith("#") or len(line.strip()) == 0: continue curr_line = line.split('\t') if curr_line[0] == hit_type: labels_hits[curr_line[seq_label_index]] =\ curr_line[target_label_index].strip() labels_to_keep.append(curr_line[seq_label_index]) labels_to_keep = set(labels_to_keep) out_fna = open(output_fna_filepath, "w") for label, seq in parse_fasta(open(fasta_filepath, "U")): if label in labels_to_keep: if hit_type == "H": out_fna.write(">" + labels_hits[label] + "\n%s\n" % seq) if hit_type == "N": out_fna.write(">" + label + "\n%s\n" % seq) return output_fna_filepath, labels_hits
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writes fasta of sequences from uc file of type hit_type fasta_filepath: Filepath of original query fasta file uc_filepath: Filepath of .uc file created by usearch post error filtering hit_type: type to read from first field of .uc file, "H" for hits, "N" for no hits. output_fna_filepath = fasta output filepath label_prefix = Added before each fasta label, important when doing ref based OTU picking plus de novo clustering to preserve label matching. output_dir: output directory
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python
train
zhanglab/psamm
psamm/lpsolver/lp.py
https://github.com/zhanglab/psamm/blob/dc427848c4f9d109ca590f0afa024c63b685b3f4/psamm/lpsolver/lp.py#L605-L612
def set(self, names): """Return a variable set of the given names in the namespace. >>> v = prob.namespace(name='v') >>> v.define([1, 2, 5], lower=0, upper=10) >>> prob.add_linear_constraints(v.set([1, 2]) >= 4) """ return self._problem.set((self, name) for name in names)
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Return a variable set of the given names in the namespace. >>> v = prob.namespace(name='v') >>> v.define([1, 2, 5], lower=0, upper=10) >>> prob.add_linear_constraints(v.set([1, 2]) >= 4)
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python
train
gwastro/pycbc
pycbc/waveform/ringdown.py
https://github.com/gwastro/pycbc/blob/7a64cdd104d263f1b6ea0b01e6841837d05a4cb3/pycbc/waveform/ringdown.py#L96-L116
def lm_freqs_taus(**kwargs): """ Take input_params and return dictionaries with frequencies and damping times of each overtone of a specific lm mode, checking that all of them are given. """ lmns = kwargs['lmns'] freqs, taus = {}, {} for lmn in lmns: l, m, nmodes = int(lmn[0]), int(lmn[1]), int(lmn[2]) for n in range(nmodes): try: freqs['%d%d%d' %(l,m,n)] = kwargs['f_%d%d%d' %(l,m,n)] except KeyError: raise ValueError('f_%d%d%d is required' %(l,m,n)) try: taus['%d%d%d' %(l,m,n)] = kwargs['tau_%d%d%d' %(l,m,n)] except KeyError: raise ValueError('tau_%d%d%d is required' %(l,m,n)) return freqs, taus
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Take input_params and return dictionaries with frequencies and damping times of each overtone of a specific lm mode, checking that all of them are given.
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python
train
pvlib/pvlib-python
pvlib/iotools/tmy.py
https://github.com/pvlib/pvlib-python/blob/2e844a595b820b43d1170269781fa66bd0ccc8a3/pvlib/iotools/tmy.py#L273-L420
def read_tmy2(filename): ''' Read a TMY2 file in to a DataFrame. Note that values contained in the DataFrame are unchanged from the TMY2 file (i.e. units are retained). Time/Date and location data imported from the TMY2 file have been modified to a "friendlier" form conforming to modern conventions (e.g. N latitude is postive, E longitude is positive, the "24th" hour of any day is technically the "0th" hour of the next day). In the case of any discrepencies between this documentation and the TMY2 User's Manual [1], the TMY2 User's Manual takes precedence. Parameters ---------- filename : None or string If None, attempts to use a Tkinter file browser. A string can be a relative file path, absolute file path, or url. Returns ------- Tuple of the form (data, metadata). data : DataFrame A dataframe with the columns described in the table below. For a more detailed descriptions of each component, please consult the TMY2 User's Manual ([1]), especially tables 3-1 through 3-6, and Appendix B. metadata : dict The site metadata available in the file. Notes ----- The returned structures have the following fields. ============= ================================== key description ============= ================================== WBAN Site identifier code (WBAN number) City Station name State Station state 2 letter designator TZ Hours from Greenwich latitude Latitude in decimal degrees longitude Longitude in decimal degrees altitude Site elevation in meters ============= ================================== ============================ ========================================================================================================================================================================== TMYData field description ============================ ========================================================================================================================================================================== index Pandas timeseries object containing timestamps year month day hour ETR Extraterrestrial horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 ETRN Extraterrestrial normal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 GHI Direct and diffuse horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 GHISource See [1], Table 3-3 GHIUncertainty See [1], Table 3-4 DNI Amount of direct normal radiation (modeled) recv'd during 60 mintues prior to timestamp, Wh/m^2 DNISource See [1], Table 3-3 DNIUncertainty See [1], Table 3-4 DHI Amount of diffuse horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 DHISource See [1], Table 3-3 DHIUncertainty See [1], Table 3-4 GHillum Avg. total horizontal illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux (e.g. value of 50 = 5000 lux) GHillumSource See [1], Table 3-3 GHillumUncertainty See [1], Table 3-4 DNillum Avg. direct normal illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux DNillumSource See [1], Table 3-3 DNillumUncertainty See [1], Table 3-4 DHillum Avg. horizontal diffuse illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux DHillumSource See [1], Table 3-3 DHillumUncertainty See [1], Table 3-4 Zenithlum Avg. luminance at the sky's zenith during the 60 minutes prior to timestamp, units of 10 Cd/m^2 (e.g. value of 700 = 7,000 Cd/m^2) ZenithlumSource See [1], Table 3-3 ZenithlumUncertainty See [1], Table 3-4 TotCld Amount of sky dome covered by clouds or obscuring phenonema at time stamp, tenths of sky TotCldSource See [1], Table 3-5, 8760x1 cell array of strings TotCldUnertainty See [1], Table 3-6 OpqCld Amount of sky dome covered by clouds or obscuring phenonema that prevent observing the sky at time stamp, tenths of sky OpqCldSource See [1], Table 3-5, 8760x1 cell array of strings OpqCldUncertainty See [1], Table 3-6 DryBulb Dry bulb temperature at the time indicated, in tenths of degree C (e.g. 352 = 35.2 C). DryBulbSource See [1], Table 3-5, 8760x1 cell array of strings DryBulbUncertainty See [1], Table 3-6 DewPoint Dew-point temperature at the time indicated, in tenths of degree C (e.g. 76 = 7.6 C). DewPointSource See [1], Table 3-5, 8760x1 cell array of strings DewPointUncertainty See [1], Table 3-6 RHum Relative humidity at the time indicated, percent RHumSource See [1], Table 3-5, 8760x1 cell array of strings RHumUncertainty See [1], Table 3-6 Pressure Station pressure at the time indicated, 1 mbar PressureSource See [1], Table 3-5, 8760x1 cell array of strings PressureUncertainty See [1], Table 3-6 Wdir Wind direction at time indicated, degrees from east of north (360 = 0 = north; 90 = East; 0 = undefined,calm) WdirSource See [1], Table 3-5, 8760x1 cell array of strings WdirUncertainty See [1], Table 3-6 Wspd Wind speed at the time indicated, in tenths of meters/second (e.g. 212 = 21.2 m/s) WspdSource See [1], Table 3-5, 8760x1 cell array of strings WspdUncertainty See [1], Table 3-6 Hvis Distance to discernable remote objects at time indicated (7777=unlimited, 9999=missing data), in tenths of kilometers (e.g. 341 = 34.1 km). HvisSource See [1], Table 3-5, 8760x1 cell array of strings HvisUncertainty See [1], Table 3-6 CeilHgt Height of cloud base above local terrain (7777=unlimited, 88888=cirroform, 99999=missing data), in meters CeilHgtSource See [1], Table 3-5, 8760x1 cell array of strings CeilHgtUncertainty See [1], Table 3-6 Pwat Total precipitable water contained in a column of unit cross section from Earth to top of atmosphere, in millimeters PwatSource See [1], Table 3-5, 8760x1 cell array of strings PwatUncertainty See [1], Table 3-6 AOD The broadband aerosol optical depth (broadband turbidity) in thousandths on the day indicated (e.g. 114 = 0.114) AODSource See [1], Table 3-5, 8760x1 cell array of strings AODUncertainty See [1], Table 3-6 SnowDepth Snow depth in centimeters on the day indicated, (999 = missing data). SnowDepthSource See [1], Table 3-5, 8760x1 cell array of strings SnowDepthUncertainty See [1], Table 3-6 LastSnowfall Number of days since last snowfall (maximum value of 88, where 88 = 88 or greater days; 99 = missing data) LastSnowfallSource See [1], Table 3-5, 8760x1 cell array of strings LastSnowfallUncertainty See [1], Table 3-6 PresentWeather See [1], Appendix B, an 8760x1 cell array of strings. Each string contains 10 numeric values. The string can be parsed to determine each of 10 observed weather metrics. ============================ ========================================================================================================================================================================== References ---------- [1] Marion, W and Urban, K. "Wilcox, S and Marion, W. "User's Manual for TMY2s". NREL 1995. ''' if filename is None: try: filename = _interactive_load() except ImportError: raise ImportError('Interactive load failed. Tkinter not supported ' 'on this system. Try installing X-Quartz and ' 'reloading') # paste in the column info as one long line string = '%2d%2d%2d%2d%4d%4d%4d%1s%1d%4d%1s%1d%4d%1s%1d%4d%1s%1d%4d%1s%1d%4d%1s%1d%4d%1s%1d%2d%1s%1d%2d%1s%1d%4d%1s%1d%4d%1s%1d%3d%1s%1d%4d%1s%1d%3d%1s%1d%3d%1s%1d%4d%1s%1d%5d%1s%1d%10d%3d%1s%1d%3d%1s%1d%3d%1s%1d%2d%1s%1d' # noqa: E501 columns = 'year,month,day,hour,ETR,ETRN,GHI,GHISource,GHIUncertainty,DNI,DNISource,DNIUncertainty,DHI,DHISource,DHIUncertainty,GHillum,GHillumSource,GHillumUncertainty,DNillum,DNillumSource,DNillumUncertainty,DHillum,DHillumSource,DHillumUncertainty,Zenithlum,ZenithlumSource,ZenithlumUncertainty,TotCld,TotCldSource,TotCldUnertainty,OpqCld,OpqCldSource,OpqCldUncertainty,DryBulb,DryBulbSource,DryBulbUncertainty,DewPoint,DewPointSource,DewPointUncertainty,RHum,RHumSource,RHumUncertainty,Pressure,PressureSource,PressureUncertainty,Wdir,WdirSource,WdirUncertainty,Wspd,WspdSource,WspdUncertainty,Hvis,HvisSource,HvisUncertainty,CeilHgt,CeilHgtSource,CeilHgtUncertainty,PresentWeather,Pwat,PwatSource,PwatUncertainty,AOD,AODSource,AODUncertainty,SnowDepth,SnowDepthSource,SnowDepthUncertainty,LastSnowfall,LastSnowfallSource,LastSnowfallUncertaint' # noqa: E501 hdr_columns = 'WBAN,City,State,TZ,latitude,longitude,altitude' tmy2, tmy2_meta = _read_tmy2(string, columns, hdr_columns, filename) return tmy2, tmy2_meta
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Read a TMY2 file in to a DataFrame. Note that values contained in the DataFrame are unchanged from the TMY2 file (i.e. units are retained). Time/Date and location data imported from the TMY2 file have been modified to a "friendlier" form conforming to modern conventions (e.g. N latitude is postive, E longitude is positive, the "24th" hour of any day is technically the "0th" hour of the next day). In the case of any discrepencies between this documentation and the TMY2 User's Manual [1], the TMY2 User's Manual takes precedence. Parameters ---------- filename : None or string If None, attempts to use a Tkinter file browser. A string can be a relative file path, absolute file path, or url. Returns ------- Tuple of the form (data, metadata). data : DataFrame A dataframe with the columns described in the table below. For a more detailed descriptions of each component, please consult the TMY2 User's Manual ([1]), especially tables 3-1 through 3-6, and Appendix B. metadata : dict The site metadata available in the file. Notes ----- The returned structures have the following fields. ============= ================================== key description ============= ================================== WBAN Site identifier code (WBAN number) City Station name State Station state 2 letter designator TZ Hours from Greenwich latitude Latitude in decimal degrees longitude Longitude in decimal degrees altitude Site elevation in meters ============= ================================== ============================ ========================================================================================================================================================================== TMYData field description ============================ ========================================================================================================================================================================== index Pandas timeseries object containing timestamps year month day hour ETR Extraterrestrial horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 ETRN Extraterrestrial normal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 GHI Direct and diffuse horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 GHISource See [1], Table 3-3 GHIUncertainty See [1], Table 3-4 DNI Amount of direct normal radiation (modeled) recv'd during 60 mintues prior to timestamp, Wh/m^2 DNISource See [1], Table 3-3 DNIUncertainty See [1], Table 3-4 DHI Amount of diffuse horizontal radiation recv'd during 60 minutes prior to timestamp, Wh/m^2 DHISource See [1], Table 3-3 DHIUncertainty See [1], Table 3-4 GHillum Avg. total horizontal illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux (e.g. value of 50 = 5000 lux) GHillumSource See [1], Table 3-3 GHillumUncertainty See [1], Table 3-4 DNillum Avg. direct normal illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux DNillumSource See [1], Table 3-3 DNillumUncertainty See [1], Table 3-4 DHillum Avg. horizontal diffuse illuminance recv'd during the 60 minutes prior to timestamp, units of 100 lux DHillumSource See [1], Table 3-3 DHillumUncertainty See [1], Table 3-4 Zenithlum Avg. luminance at the sky's zenith during the 60 minutes prior to timestamp, units of 10 Cd/m^2 (e.g. value of 700 = 7,000 Cd/m^2) ZenithlumSource See [1], Table 3-3 ZenithlumUncertainty See [1], Table 3-4 TotCld Amount of sky dome covered by clouds or obscuring phenonema at time stamp, tenths of sky TotCldSource See [1], Table 3-5, 8760x1 cell array of strings TotCldUnertainty See [1], Table 3-6 OpqCld Amount of sky dome covered by clouds or obscuring phenonema that prevent observing the sky at time stamp, tenths of sky OpqCldSource See [1], Table 3-5, 8760x1 cell array of strings OpqCldUncertainty See [1], Table 3-6 DryBulb Dry bulb temperature at the time indicated, in tenths of degree C (e.g. 352 = 35.2 C). DryBulbSource See [1], Table 3-5, 8760x1 cell array of strings DryBulbUncertainty See [1], Table 3-6 DewPoint Dew-point temperature at the time indicated, in tenths of degree C (e.g. 76 = 7.6 C). DewPointSource See [1], Table 3-5, 8760x1 cell array of strings DewPointUncertainty See [1], Table 3-6 RHum Relative humidity at the time indicated, percent RHumSource See [1], Table 3-5, 8760x1 cell array of strings RHumUncertainty See [1], Table 3-6 Pressure Station pressure at the time indicated, 1 mbar PressureSource See [1], Table 3-5, 8760x1 cell array of strings PressureUncertainty See [1], Table 3-6 Wdir Wind direction at time indicated, degrees from east of north (360 = 0 = north; 90 = East; 0 = undefined,calm) WdirSource See [1], Table 3-5, 8760x1 cell array of strings WdirUncertainty See [1], Table 3-6 Wspd Wind speed at the time indicated, in tenths of meters/second (e.g. 212 = 21.2 m/s) WspdSource See [1], Table 3-5, 8760x1 cell array of strings WspdUncertainty See [1], Table 3-6 Hvis Distance to discernable remote objects at time indicated (7777=unlimited, 9999=missing data), in tenths of kilometers (e.g. 341 = 34.1 km). HvisSource See [1], Table 3-5, 8760x1 cell array of strings HvisUncertainty See [1], Table 3-6 CeilHgt Height of cloud base above local terrain (7777=unlimited, 88888=cirroform, 99999=missing data), in meters CeilHgtSource See [1], Table 3-5, 8760x1 cell array of strings CeilHgtUncertainty See [1], Table 3-6 Pwat Total precipitable water contained in a column of unit cross section from Earth to top of atmosphere, in millimeters PwatSource See [1], Table 3-5, 8760x1 cell array of strings PwatUncertainty See [1], Table 3-6 AOD The broadband aerosol optical depth (broadband turbidity) in thousandths on the day indicated (e.g. 114 = 0.114) AODSource See [1], Table 3-5, 8760x1 cell array of strings AODUncertainty See [1], Table 3-6 SnowDepth Snow depth in centimeters on the day indicated, (999 = missing data). SnowDepthSource See [1], Table 3-5, 8760x1 cell array of strings SnowDepthUncertainty See [1], Table 3-6 LastSnowfall Number of days since last snowfall (maximum value of 88, where 88 = 88 or greater days; 99 = missing data) LastSnowfallSource See [1], Table 3-5, 8760x1 cell array of strings LastSnowfallUncertainty See [1], Table 3-6 PresentWeather See [1], Appendix B, an 8760x1 cell array of strings. Each string contains 10 numeric values. The string can be parsed to determine each of 10 observed weather metrics. ============================ ========================================================================================================================================================================== References ---------- [1] Marion, W and Urban, K. "Wilcox, S and Marion, W. "User's Manual for TMY2s". NREL 1995.
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python
train
PyCQA/astroid
astroid/node_classes.py
https://github.com/PyCQA/astroid/blob/e0a298df55b15abcb77c2a93253f5ab7be52d0fb/astroid/node_classes.py#L2966-L2979
def catch(self, exceptions): # pylint: disable=redefined-outer-name """Check if this node handles any of the given exceptions. If ``exceptions`` is empty, this will default to ``True``. :param exceptions: The name of the exceptions to check for. :type exceptions: list(str) """ if self.type is None or exceptions is None: return True for node in self.type._get_name_nodes(): if node.name in exceptions: return True return False
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Check if this node handles any of the given exceptions. If ``exceptions`` is empty, this will default to ``True``. :param exceptions: The name of the exceptions to check for. :type exceptions: list(str)
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python
train
dw/mitogen
ansible_mitogen/services.py
https://github.com/dw/mitogen/blob/a7fdb55e1300a7e0a5e404b09eb730cf9a525da7/ansible_mitogen/services.py#L343-L403
def _connect(self, key, spec, via=None): """ Actual connect implementation. Arranges for the Mitogen connection to be created and enqueues an asynchronous call to start the forked task parent in the remote context. :param key: Deduplication key representing the connection configuration. :param spec: Connection specification. :returns: Dict like:: { 'context': mitogen.core.Context or None, 'via': mitogen.core.Context or None, 'init_child_result': { 'fork_context': mitogen.core.Context, 'home_dir': str or None, }, 'msg': str or None } Where `context` is a reference to the newly constructed context, `init_child_result` is the result of executing :func:`ansible_mitogen.target.init_child` in that context, `msg` is an error message and the remaining fields are :data:`None`, or `msg` is :data:`None` and the remaining fields are set. """ try: method = getattr(self.router, spec['method']) except AttributeError: raise Error('unsupported method: %(transport)s' % spec) context = method(via=via, unidirectional=True, **spec['kwargs']) if via and spec.get('enable_lru'): self._update_lru(context, spec, via) # Forget the context when its disconnect event fires. mitogen.core.listen(context, 'disconnect', lambda: self._on_context_disconnect(context)) self._send_module_forwards(context) init_child_result = context.call( ansible_mitogen.target.init_child, log_level=LOG.getEffectiveLevel(), candidate_temp_dirs=self._get_candidate_temp_dirs(), ) if os.environ.get('MITOGEN_DUMP_THREAD_STACKS'): from mitogen import debug context.call(debug.dump_to_logger) self._key_by_context[context] = key self._refs_by_context[context] = 0 return { 'context': context, 'via': via, 'init_child_result': init_child_result, 'msg': None, }
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Actual connect implementation. Arranges for the Mitogen connection to be created and enqueues an asynchronous call to start the forked task parent in the remote context. :param key: Deduplication key representing the connection configuration. :param spec: Connection specification. :returns: Dict like:: { 'context': mitogen.core.Context or None, 'via': mitogen.core.Context or None, 'init_child_result': { 'fork_context': mitogen.core.Context, 'home_dir': str or None, }, 'msg': str or None } Where `context` is a reference to the newly constructed context, `init_child_result` is the result of executing :func:`ansible_mitogen.target.init_child` in that context, `msg` is an error message and the remaining fields are :data:`None`, or `msg` is :data:`None` and the remaining fields are set.
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python
train
fermiPy/fermipy
fermipy/jobs/link.py
https://github.com/fermiPy/fermipy/blob/9df5e7e3728307fd58c5bba36fd86783c39fbad4/fermipy/jobs/link.py#L850-L860
def missing_input_files(self): """Make and return a dictionary of the missing input files. This returns a dictionary mapping filepath to list of `Link` that use the file as input. """ missing = self.check_input_files(return_found=False) ret_dict = {} for miss_file in missing: ret_dict[miss_file] = [self.linkname] return ret_dict
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Make and return a dictionary of the missing input files. This returns a dictionary mapping filepath to list of `Link` that use the file as input.
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python
train
druids/django-chamber
chamber/utils/decorators.py
https://github.com/druids/django-chamber/blob/eef4169923557e96877a664fa254e8c0814f3f23/chamber/utils/decorators.py#L26-L44
def translation_activate_block(function=None, language=None): """ Activate language only for one method or function """ def _translation_activate_block(function): def _decorator(*args, **kwargs): tmp_language = translation.get_language() try: translation.activate(language or settings.LANGUAGE_CODE) return function(*args, **kwargs) finally: translation.activate(tmp_language) return wraps(function)(_decorator) if function: return _translation_activate_block(function) else: return _translation_activate_block
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Activate language only for one method or function
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python
train
RedFantom/ttkwidgets
ttkwidgets/color/colorpicker.py
https://github.com/RedFantom/ttkwidgets/blob/02150322060f867b6e59a175522ef84b09168019/ttkwidgets/color/colorpicker.py#L332-L340
def _update_preview(self): """Update color preview.""" color = self.hexa.get() if self.alpha_channel: prev = overlay(self._transparent_bg, hexa_to_rgb(color)) self._im_color = ImageTk.PhotoImage(prev, master=self) self.color_preview.configure(image=self._im_color) else: self.color_preview.configure(background=color)
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Update color preview.
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python
train
saltstack/salt
salt/runners/cache.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/runners/cache.py#L388-L405
def store(bank, key, data, cachedir=None): ''' Lists entries stored in the specified bank. CLI Example: .. code-block:: bash salt-run cache.store mycache mykey 'The time has come the walrus said' ''' if cachedir is None: cachedir = __opts__['cachedir'] try: cache = salt.cache.Cache(__opts__, cachedir=cachedir) except TypeError: cache = salt.cache.Cache(__opts__) return cache.store(bank, key, data)
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Lists entries stored in the specified bank. CLI Example: .. code-block:: bash salt-run cache.store mycache mykey 'The time has come the walrus said'
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python
train
saltstack/salt
salt/modules/portage_config.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/portage_config.py#L68-L93
def _get_config_file(conf, atom): ''' Parse the given atom, allowing access to its parts Success does not mean that the atom exists, just that it is in the correct format. Returns none if the atom is invalid. ''' if '*' in atom: parts = portage.dep.Atom(atom, allow_wildcard=True) if not parts: return if parts.cp == '*/*': # parts.repo will be empty if there is no repo part relative_path = parts.repo or "gentoo" elif six.text_type(parts.cp).endswith('/*'): relative_path = six.text_type(parts.cp).split("/")[0] + "_" else: relative_path = os.path.join(*[x for x in os.path.split(parts.cp) if x != '*']) else: relative_path = _p_to_cp(atom) if not relative_path: return complete_file_path = BASE_PATH.format(conf) + '/' + relative_path return complete_file_path
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Parse the given atom, allowing access to its parts Success does not mean that the atom exists, just that it is in the correct format. Returns none if the atom is invalid.
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python
train
ronhanson/python-tbx
tbx/code.py
https://github.com/ronhanson/python-tbx/blob/87f72ae0cadecafbcd144f1e930181fba77f6b83/tbx/code.py#L313-L327
def sort_dictionary_list(dict_list, sort_key): """ sorts a list of dictionaries based on the value of the sort_key dict_list - a list of dictionaries sort_key - a string that identifies the key to sort the dictionaries with. Test sorting a list of dictionaries: >>> sort_dictionary_list([{'b' : 1, 'value' : 2}, {'c' : 2, 'value' : 3}, {'a' : 3, 'value' : 1}], 'value') [{'a': 3, 'value': 1}, {'b': 1, 'value': 2}, {'c': 2, 'value': 3}] """ if not dict_list or len(dict_list) == 0: return dict_list dict_list.sort(key=itemgetter(sort_key)) return dict_list
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sorts a list of dictionaries based on the value of the sort_key dict_list - a list of dictionaries sort_key - a string that identifies the key to sort the dictionaries with. Test sorting a list of dictionaries: >>> sort_dictionary_list([{'b' : 1, 'value' : 2}, {'c' : 2, 'value' : 3}, {'a' : 3, 'value' : 1}], 'value') [{'a': 3, 'value': 1}, {'b': 1, 'value': 2}, {'c': 2, 'value': 3}]
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python
train
timkpaine/pyEX
pyEX/stocks.py
https://github.com/timkpaine/pyEX/blob/91cf751dafdb208a0c8b5377945e5808b99f94ba/pyEX/stocks.py#L12-L28
def balanceSheet(symbol, token='', version=''): '''Pulls balance sheet data. Available quarterly (4 quarters) and annually (4 years) https://iexcloud.io/docs/api/#balance-sheet Updates at 8am, 9am UTC daily Args: symbol (string); Ticker to request token (string); Access token version (string); API version Returns: dict: result ''' _raiseIfNotStr(symbol) return _getJson('stock/' + symbol + '/balance-sheet', token, version)
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Pulls balance sheet data. Available quarterly (4 quarters) and annually (4 years) https://iexcloud.io/docs/api/#balance-sheet Updates at 8am, 9am UTC daily Args: symbol (string); Ticker to request token (string); Access token version (string); API version Returns: dict: result
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python
valid
senaite/senaite.core
bika/lims/browser/reports/selection_macros/__init__.py
https://github.com/senaite/senaite.core/blob/7602ce2ea2f9e81eb34e20ce17b98a3e70713f85/bika/lims/browser/reports/selection_macros/__init__.py#L167-L172
def _cache_key_select_sample_type(method, self, allow_blank=True, multiselect=False, style=None): """ This function returns the key used to decide if method select_sample_type has to be recomputed """ key = update_timer(), allow_blank, multiselect, style return key
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This function returns the key used to decide if method select_sample_type has to be recomputed
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python
train
saltstack/salt
salt/states/ssh_auth.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/states/ssh_auth.py#L512-L605
def manage( name, ssh_keys, user, enc='ssh-rsa', comment='', source='', options=None, config='.ssh/authorized_keys', fingerprint_hash_type=None, **kwargs): ''' .. versionadded:: Neon Ensures that only the specified ssh_keys are present for the specified user ssh_keys The SSH key to manage user The user who owns the SSH authorized keys file to modify enc Defines what type of key is being used; can be ed25519, ecdsa, ssh-rsa or ssh-dss comment The comment to be placed with the SSH public key source The source file for the key(s). Can contain any number of public keys, in standard "authorized_keys" format. If this is set, comment and enc will be ignored. .. note:: The source file must contain keys in the format ``<enc> <key> <comment>``. If you have generated a keypair using PuTTYgen, then you will need to do the following to retrieve an OpenSSH-compatible public key. 1. In PuTTYgen, click ``Load``, and select the *private* key file (not the public key), and click ``Open``. 2. Copy the public key from the box labeled ``Public key for pasting into OpenSSH authorized_keys file``. 3. Paste it into a new file. options The options passed to the keys, pass a list object config The location of the authorized keys file relative to the user's home directory, defaults to ".ssh/authorized_keys". Token expansion %u and %h for username and home path supported. fingerprint_hash_type The public key fingerprint hash type that the public key fingerprint was originally hashed with. This defaults to ``sha256`` if not specified. ''' ret = {'name': '', 'changes': {}, 'result': True, 'comment': ''} all_potential_keys = [] for ssh_key in ssh_keys: # gather list potential ssh keys for removal comparison # options, enc, and comments could be in the mix all_potential_keys.extend(ssh_key.split(' ')) existing_keys = __salt__['ssh.auth_keys'](user=user).keys() remove_keys = set(existing_keys).difference(all_potential_keys) for remove_key in remove_keys: if __opts__['test']: remove_comment = '{0} Key set for removal'.format(remove_key) ret['comment'] = remove_comment ret['result'] = None else: remove_comment = absent(remove_key, user)['comment'] ret['changes'][remove_key] = remove_comment for ssh_key in ssh_keys: run_return = present(ssh_key, user, enc, comment, source, options, config, fingerprint_hash_type, **kwargs) if run_return['changes']: ret['changes'].update(run_return['changes']) else: ret['comment'] += '\n' + run_return['comment'] ret['comment'].strip() if run_return['result'] is None: ret['result'] = None elif not run_return['result']: ret['result'] = False return ret
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.. versionadded:: Neon Ensures that only the specified ssh_keys are present for the specified user ssh_keys The SSH key to manage user The user who owns the SSH authorized keys file to modify enc Defines what type of key is being used; can be ed25519, ecdsa, ssh-rsa or ssh-dss comment The comment to be placed with the SSH public key source The source file for the key(s). Can contain any number of public keys, in standard "authorized_keys" format. If this is set, comment and enc will be ignored. .. note:: The source file must contain keys in the format ``<enc> <key> <comment>``. If you have generated a keypair using PuTTYgen, then you will need to do the following to retrieve an OpenSSH-compatible public key. 1. In PuTTYgen, click ``Load``, and select the *private* key file (not the public key), and click ``Open``. 2. Copy the public key from the box labeled ``Public key for pasting into OpenSSH authorized_keys file``. 3. Paste it into a new file. options The options passed to the keys, pass a list object config The location of the authorized keys file relative to the user's home directory, defaults to ".ssh/authorized_keys". Token expansion %u and %h for username and home path supported. fingerprint_hash_type The public key fingerprint hash type that the public key fingerprint was originally hashed with. This defaults to ``sha256`` if not specified.
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python
train
b3j0f/annotation
b3j0f/annotation/oop.py
https://github.com/b3j0f/annotation/blob/738035a974e4092696d9dc1bbd149faa21c8c51f/b3j0f/annotation/oop.py#L151-L194
def mixin_function_or_method(target, routine, name=None, isbound=False): """Mixin a routine into the target. :param routine: routine to mix in target. :param str name: mixin name. Routine name by default. :param bool isbound: If True (False by default), the mixin result is a bound method to target. """ function = None if isfunction(routine): function = routine elif ismethod(routine): function = get_method_function(routine) else: raise Mixin.MixInError( "{0} must be a function or a method.".format(routine)) if name is None: name = routine.__name__ if not isclass(target) or isbound: _type = type(target) method_args = [function, target] if PY2: method_args += _type result = MethodType(*method_args) else: if PY2: result = MethodType(function, None, target) else: result = function Mixin.set_mixin(target, result, name) return result
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Mixin a routine into the target. :param routine: routine to mix in target. :param str name: mixin name. Routine name by default. :param bool isbound: If True (False by default), the mixin result is a bound method to target.
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python
train
Qiskit/qiskit-terra
qiskit/pulse/pulse_lib/discrete.py
https://github.com/Qiskit/qiskit-terra/blob/d4f58d903bc96341b816f7c35df936d6421267d1/qiskit/pulse/pulse_lib/discrete.py#L227-L251
def drag(duration: int, amp: complex, sigma: float, beta: float, name: str = None) -> SamplePulse: r"""Generates Y-only correction DRAG `SamplePulse` for standard nonlinear oscillator (SNO) [1]. Centered at `duration/2` and zeroed at `t=-1` to prevent large initial discontinuity. Applies `left` sampling strategy to generate discrete pulse from continuous function. [1] Gambetta, J. M., Motzoi, F., Merkel, S. T. & Wilhelm, F. K. Analytic control methods for high-fidelity unitary operations in a weakly nonlinear oscillator. Phys. Rev. A 83, 012308 (2011). Args: duration: Duration of pulse. Must be greater than zero. amp: Pulse amplitude at `center`. sigma: Width (standard deviation) of pulse. beta: Y correction amplitude. For the SNO this is $\beta=-\frac{\lambda_1^2}{4\Delta_2}$. Where $\lambds_1$ is the relative coupling strength between the first excited and second excited states and $\Delta_2$ is the detuning between the resepective excited states. name: Name of pulse. """ center = duration/2 zeroed_width = duration + 2 return _sampled_drag_pulse(duration, amp, center, sigma, beta, zeroed_width=zeroed_width, rescale_amp=True, name=name)
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r"""Generates Y-only correction DRAG `SamplePulse` for standard nonlinear oscillator (SNO) [1]. Centered at `duration/2` and zeroed at `t=-1` to prevent large initial discontinuity. Applies `left` sampling strategy to generate discrete pulse from continuous function. [1] Gambetta, J. M., Motzoi, F., Merkel, S. T. & Wilhelm, F. K. Analytic control methods for high-fidelity unitary operations in a weakly nonlinear oscillator. Phys. Rev. A 83, 012308 (2011). Args: duration: Duration of pulse. Must be greater than zero. amp: Pulse amplitude at `center`. sigma: Width (standard deviation) of pulse. beta: Y correction amplitude. For the SNO this is $\beta=-\frac{\lambda_1^2}{4\Delta_2}$. Where $\lambds_1$ is the relative coupling strength between the first excited and second excited states and $\Delta_2$ is the detuning between the resepective excited states. name: Name of pulse.
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python
test
jkitzes/macroeco
macroeco/misc/misc.py
https://github.com/jkitzes/macroeco/blob/ee5fac5560a2d64de3a64738b5bc6833e2d7ff2e/macroeco/misc/misc.py#L36-L57
def inherit_docstring_from(cls): """ This decorator modifies the decorated function's docstring by replacing occurrences of '%(super)s' with the docstring of the method of the same name from the class `cls`. If the decorated method has no docstring, it is simply given the docstring of cls method. Extracted from scipy.misc.doccer. """ def _doc(func): cls_docstring = getattr(cls, func.__name__).__doc__ func_docstring = func.__doc__ if func_docstring is None: func.__doc__ = cls_docstring else: new_docstring = func_docstring % dict(super=cls_docstring) func.__doc__ = new_docstring return func return _doc
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This decorator modifies the decorated function's docstring by replacing occurrences of '%(super)s' with the docstring of the method of the same name from the class `cls`. If the decorated method has no docstring, it is simply given the docstring of cls method. Extracted from scipy.misc.doccer.
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python
train
chaoss/grimoirelab-perceval
perceval/backends/core/gitlab.py
https://github.com/chaoss/grimoirelab-perceval/blob/41c908605e88b7ebc3a536c643fa0f212eaf9e0e/perceval/backends/core/gitlab.py#L533-L552
def fetch(self, url, payload=None, headers=None, method=HttpClient.GET, stream=False): """Fetch the data from a given URL. :param url: link to the resource :param payload: payload of the request :param headers: headers of the request :param method: type of request call (GET or POST) :param stream: defer downloading the response body until the response content is available :returns a response object """ if not self.from_archive: self.sleep_for_rate_limit() response = super().fetch(url, payload, headers, method, stream) if not self.from_archive: self.update_rate_limit(response) return response
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Fetch the data from a given URL. :param url: link to the resource :param payload: payload of the request :param headers: headers of the request :param method: type of request call (GET or POST) :param stream: defer downloading the response body until the response content is available :returns a response object
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python
test
ejeschke/ginga
experimental/plugins/IRAF.py
https://github.com/ejeschke/ginga/blob/a78c893ec6f37a837de851947e9bb4625c597915/experimental/plugins/IRAF.py#L389-L410
def init_frame(self, n): """ NOTE: this is called from the IIS_RequestHandler """ self.logger.debug("initializing frame %d" % (n)) # create the frame, if needed try: fb = self.get_frame(n) except KeyError: fb = iis.framebuffer() self.fb[n] = fb fb.width = None fb.height = None fb.wcs = '' fb.image = None fb.bitmap = None fb.zoom = 1.0 fb.buffer = array.array('B') fb.ct = iis.coord_tran() #fb.chname = None return fb
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NOTE: this is called from the IIS_RequestHandler
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python
train
jason-weirather/py-seq-tools
seqtools/errors.py
https://github.com/jason-weirather/py-seq-tools/blob/f642c2c73ffef2acc83656a78059a476fc734ca1/seqtools/errors.py#L425-L458
def get_string(self): """ Get a string representation of this single base error. :returns: report :rtype: string """ ostr = '' ostr += 'BaseError for ['+self._type+'] base: '+self.get_base()+"\n" if self._observable.get_error_probability() > 0: ostr += ' Homopolymer set:'+"\n" ostr += ' '+str(self.get_homopolymer())+"\n" ostr += ' Observable:'+"\n" ostr += ' type is: '+str(self.get_observable_type())+"\n" ostr += ' P(error): '+str(self._observable.get_error_probability())+"\n" ostr += ' Elength: '+str(self._observable.get_attributable_length())+"\n" before = self._unobservable.get_before_type() after = self._unobservable.get_after_type() if before or after: ostr += ' Unobservable ' if self._type == 'query': ostr += 'deletion:'+"\n" else: ostr += 'insertion:'+"\n" ostr += ' P(error): '+str(self._unobservable.get_error_probability())+"\n" ostr += ' Elength: '+str(self._unobservable.get_attributable_length())+"\n" if before: ostr += ' before: '+"\n" ostr += ' P(error): '+str(self._unobservable.get_before_probability())+"\n" ostr += ' '+str(before)+"\n" if after: ostr += ' after:'+"\n" ostr += ' P(error): '+str(self._unobservable.get_after_probability())+"\n" ostr += ' '+str(after)+"\n" return ostr
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Get a string representation of this single base error. :returns: report :rtype: string
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python
train
twilio/twilio-python
twilio/rest/taskrouter/v1/workspace/worker/__init__.py
https://github.com/twilio/twilio-python/blob/c867895f55dcc29f522e6e8b8868d0d18483132f/twilio/rest/taskrouter/v1/workspace/worker/__init__.py#L213-L225
def statistics(self): """ Access the statistics :returns: twilio.rest.taskrouter.v1.workspace.worker.workers_statistics.WorkersStatisticsList :rtype: twilio.rest.taskrouter.v1.workspace.worker.workers_statistics.WorkersStatisticsList """ if self._statistics is None: self._statistics = WorkersStatisticsList( self._version, workspace_sid=self._solution['workspace_sid'], ) return self._statistics
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Access the statistics :returns: twilio.rest.taskrouter.v1.workspace.worker.workers_statistics.WorkersStatisticsList :rtype: twilio.rest.taskrouter.v1.workspace.worker.workers_statistics.WorkersStatisticsList
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python
train
SUSE-Enceladus/ipa
ipa/ipa_gce.py
https://github.com/SUSE-Enceladus/ipa/blob/0845eed0ea25a27dbb059ad1016105fa60002228/ipa/ipa_gce.py#L274-L286
def _set_instance_ip(self): """Retrieve and set the instance ip address.""" instance = self._get_instance() if instance.public_ips: self.instance_ip = instance.public_ips[0] elif instance.private_ips: self.instance_ip = instance.private_ips[0] else: raise GCECloudException( 'IP address for instance: %s cannot be found.' % self.running_instance_id )
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Retrieve and set the instance ip address.
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python
train
saltstack/salt
salt/modules/parallels.py
https://github.com/saltstack/salt/blob/e8541fd6e744ab0df786c0f76102e41631f45d46/salt/modules/parallels.py#L688-L742
def delete_snapshot(name, snap_name, runas=None, all=False): ''' Delete a snapshot .. note:: Deleting a snapshot from which other snapshots are dervied will not delete the derived snapshots :param str name: Name/ID of VM whose snapshot will be deleted :param str snap_name: Name/ID of snapshot to delete :param str runas: The user that the prlctl command will be run as :param bool all: Delete all snapshots having the name given .. versionadded:: 2016.11.0 Example: .. code-block:: bash salt '*' parallels.delete_snapshot macvm 'unneeded snapshot' runas=macdev salt '*' parallels.delete_snapshot macvm 'Snapshot for linked clone' all=True runas=macdev ''' # strict means raise an error if multiple snapshot IDs found for the name given strict = not all # Validate VM and snapshot names name = salt.utils.data.decode(name) snap_ids = _validate_snap_name(name, snap_name, strict=strict, runas=runas) if isinstance(snap_ids, six.string_types): snap_ids = [snap_ids] # Delete snapshot(s) ret = {} for snap_id in snap_ids: snap_id = snap_id.strip('{}') # Construct argument list args = [name, '--id', snap_id] # Execute command ret[snap_id] = prlctl('snapshot-delete', args, runas=runas) # Return results ret_keys = list(ret.keys()) if len(ret_keys) == 1: return ret[ret_keys[0]] else: return ret
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Delete a snapshot .. note:: Deleting a snapshot from which other snapshots are dervied will not delete the derived snapshots :param str name: Name/ID of VM whose snapshot will be deleted :param str snap_name: Name/ID of snapshot to delete :param str runas: The user that the prlctl command will be run as :param bool all: Delete all snapshots having the name given .. versionadded:: 2016.11.0 Example: .. code-block:: bash salt '*' parallels.delete_snapshot macvm 'unneeded snapshot' runas=macdev salt '*' parallels.delete_snapshot macvm 'Snapshot for linked clone' all=True runas=macdev
[ "Delete", "a", "snapshot" ]
python
train
SergeySatskiy/cdm-pythonparser
cdmpyparser.py
https://github.com/SergeySatskiy/cdm-pythonparser/blob/7e933aca899b1853d744082313ffc3a8b1154505/cdmpyparser.py#L562-L569
def _onDecorator(self, name, line, pos, absPosition): """Memorizes a function or a class decorator""" # A class or a function must be on the top of the stack d = Decorator(name, line, pos, absPosition) if self.__lastDecorators is None: self.__lastDecorators = [d] else: self.__lastDecorators.append(d)
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Memorizes a function or a class decorator
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python
train
log2timeline/plaso
plaso/parsers/manager.py
https://github.com/log2timeline/plaso/blob/9c564698d2da3ffbe23607a3c54c0582ea18a6cc/plaso/parsers/manager.py#L283-L301
def GetParserPluginsInformation(cls, parser_filter_expression=None): """Retrieves the parser plugins information. Args: parser_filter_expression (Optional[str]): parser filter expression, where None represents all parsers and plugins. Returns: list[tuple[str, str]]: pairs of parser plugin names and descriptions. """ parser_plugins_information = [] for _, parser_class in cls.GetParsers( parser_filter_expression=parser_filter_expression): if parser_class.SupportsPlugins(): for plugin_name, plugin_class in parser_class.GetPlugins(): description = getattr(plugin_class, 'DESCRIPTION', '') parser_plugins_information.append((plugin_name, description)) return parser_plugins_information
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Retrieves the parser plugins information. Args: parser_filter_expression (Optional[str]): parser filter expression, where None represents all parsers and plugins. Returns: list[tuple[str, str]]: pairs of parser plugin names and descriptions.
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python
train
barryp/py-amqplib
amqplib/client_0_8/transport.py
https://github.com/barryp/py-amqplib/blob/2b3a47de34b4712c111d0a55d7ff109dffc2a7b2/amqplib/client_0_8/transport.py#L245-L252
def _setup_transport(self): """ Setup to _write() directly to the socket, and do our own buffered reads. """ self._write = self.sock.sendall self._read_buffer = bytes()
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Setup to _write() directly to the socket, and do our own buffered reads.
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python
train
kensho-technologies/graphql-compiler
graphql_compiler/compiler/ir_lowering_gremlin/ir_lowering.py
https://github.com/kensho-technologies/graphql-compiler/blob/f6079c6d10f64932f6b3af309b79bcea2123ca8f/graphql_compiler/compiler/ir_lowering_gremlin/ir_lowering.py#L319-L355
def lower_folded_outputs(ir_blocks): """Lower standard folded output fields into GremlinFoldedContextField objects.""" folds, remaining_ir_blocks = extract_folds_from_ir_blocks(ir_blocks) if not remaining_ir_blocks: raise AssertionError(u'Expected at least one non-folded block to remain: {} {} ' u'{}'.format(folds, remaining_ir_blocks, ir_blocks)) output_block = remaining_ir_blocks[-1] if not isinstance(output_block, ConstructResult): raise AssertionError(u'Expected the last non-folded block to be ConstructResult, ' u'but instead was: {} {} ' u'{}'.format(type(output_block), output_block, ir_blocks)) # Turn folded Filter blocks into GremlinFoldedFilter blocks. converted_folds = { base_fold_location.get_location_name()[0]: _convert_folded_blocks(folded_ir_blocks) for base_fold_location, folded_ir_blocks in six.iteritems(folds) } new_output_fields = dict() for output_name, output_expression in six.iteritems(output_block.fields): new_output_expression = output_expression # Turn FoldedContextField expressions into GremlinFoldedContextField ones. if isinstance(output_expression, FoldedContextField): # Get the matching folded IR blocks and put them in the new context field. base_fold_location_name = output_expression.fold_scope_location.get_location_name()[0] folded_ir_blocks = converted_folds[base_fold_location_name] new_output_expression = GremlinFoldedContextField( output_expression.fold_scope_location, folded_ir_blocks, output_expression.field_type) new_output_fields[output_name] = new_output_expression new_ir_blocks = remaining_ir_blocks[:-1] new_ir_blocks.append(ConstructResult(new_output_fields)) return new_ir_blocks
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Lower standard folded output fields into GremlinFoldedContextField objects.
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python
train
swharden/SWHLab
doc/oldcode/swhlab/core/ap.py
https://github.com/swharden/SWHLab/blob/a86c3c65323cec809a4bd4f81919644927094bf5/doc/oldcode/swhlab/core/ap.py#L323-L332
def stats_first(abf): """provide all stats on the first AP.""" msg="" for sweep in range(abf.sweeps): for AP in abf.APs[sweep]: for key in sorted(AP.keys()): if key[-1] is "I" or key[-2:] in ["I1","I2"]: continue msg+="%s = %s\n"%(key,AP[key]) return msg
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provide all stats on the first AP.
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python
valid
mlperf/training
reinforcement/tensorflow/minigo/bigtable_input.py
https://github.com/mlperf/training/blob/1c6ae725a81d15437a2b2df05cac0673fde5c3a4/reinforcement/tensorflow/minigo/bigtable_input.py#L331-L363
def trim_games_since(self, t, max_games=500000): """Trim off the games since the given time. Search back no more than max_games for this time point, locate the game there, and remove all games since that game, resetting the latest game counter. If `t` is a `datetime.timedelta`, then the target time will be found by subtracting that delta from the time of the last game. Otherwise, it will be the target time. """ latest = self.latest_game_number earliest = int(latest - max_games) gbt = self.games_by_time(earliest, latest) if not gbt: utils.dbg('No games between %d and %d' % (earliest, latest)) return most_recent = gbt[-1] if isinstance(t, datetime.timedelta): target = most_recent[0] - t else: target = t i = bisect.bisect_right(gbt, (target,)) if i >= len(gbt): utils.dbg('Last game is already at %s' % gbt[-1][0]) return when, which = gbt[i] utils.dbg('Most recent: %s %s' % most_recent) utils.dbg(' Target: %s %s' % (when, which)) which = int(which) self.delete_row_range(ROW_PREFIX, which, latest) self.delete_row_range(ROWCOUNT_PREFIX, which, latest) self.latest_game_number = which
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Trim off the games since the given time. Search back no more than max_games for this time point, locate the game there, and remove all games since that game, resetting the latest game counter. If `t` is a `datetime.timedelta`, then the target time will be found by subtracting that delta from the time of the last game. Otherwise, it will be the target time.
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python
train
cloud9ers/gurumate
environment/share/doc/ipython/examples/parallel/rmt/rmtkernel.py
https://github.com/cloud9ers/gurumate/blob/075dc74d1ee62a8c6b7a8bf2b271364f01629d1e/environment/share/doc/ipython/examples/parallel/rmt/rmtkernel.py#L24-L30
def ensemble_diffs(num, N): """Return num eigenvalue diffs for the NxN GOE ensemble.""" diffs = np.empty(num) for i in xrange(num): mat = GOE(N) diffs[i] = center_eigenvalue_diff(mat) return diffs
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Return num eigenvalue diffs for the NxN GOE ensemble.
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python
test
carpedm20/fbchat
fbchat/_client.py
https://github.com/carpedm20/fbchat/blob/f480d68b5773473e6daba7f66075ee30e8d737a8/fbchat/_client.py#L1949-L1964
def changeThreadColor(self, color, thread_id=None): """ Changes thread color :param color: New thread color :param thread_id: User/Group ID to change color of. See :ref:`intro_threads` :type color: models.ThreadColor :raises: FBchatException if request failed """ thread_id, thread_type = self._getThread(thread_id, None) data = { "color_choice": color.value if color != ThreadColor.MESSENGER_BLUE else "", "thread_or_other_fbid": thread_id, } j = self._post(self.req_url.THREAD_COLOR, data, fix_request=True, as_json=True)
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Changes thread color :param color: New thread color :param thread_id: User/Group ID to change color of. See :ref:`intro_threads` :type color: models.ThreadColor :raises: FBchatException if request failed
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python
train
DLR-RM/RAFCON
share/examples/plugins/templates/gtkmvc_template_observer.py
https://github.com/DLR-RM/RAFCON/blob/24942ef1a904531f49ab8830a1dbb604441be498/share/examples/plugins/templates/gtkmvc_template_observer.py#L36-L46
def relieve_state_machines(self, model, prop_name, info): """ The method relieves observed models before those get removed from the list of state_machines hold by observed StateMachineMangerModel. The method register as observer of observable StateMachineMangerModel.state_machines.""" if info['method_name'] == '__setitem__': pass elif info['method_name'] == '__delitem__': self.relieve_model(self.state_machine_manager_model.state_machines[info['args'][0]]) self.logger.info(NotificationOverview(info)) else: self.logger.warning(NotificationOverview(info))
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The method relieves observed models before those get removed from the list of state_machines hold by observed StateMachineMangerModel. The method register as observer of observable StateMachineMangerModel.state_machines.
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python
train
csparpa/pyowm
pyowm/weatherapi25/owm25.py
https://github.com/csparpa/pyowm/blob/cdd59eb72f32f7238624ceef9b2e2329a5ebd472/pyowm/weatherapi25/owm25.py#L1090-L1111
def uvindex_around_coords(self, lat, lon): """ Queries the OWM Weather API for Ultra Violet value sampled in the surroundings of the provided geocoordinates and in the specified time interval. A *UVIndex* object instance is returned, encapsulating a *Location* object and the UV intensity value. :param lat: the location's latitude, must be between -90.0 and 90.0 :type lat: int/float :param lon: the location's longitude, must be between -180.0 and 180.0 :type lon: int/float :return: a *UVIndex* instance or ``None`` if data is not available :raises: *ParseResponseException* when OWM Weather API responses' data cannot be parsed, *APICallException* when OWM Weather API can not be reached, *ValueError* for wrong input values """ geo.assert_is_lon(lon) geo.assert_is_lat(lat) params = {'lon': lon, 'lat': lat} json_data = self._uvapi.get_uvi(params) uvindex = self._parsers['uvindex'].parse_JSON(json_data) return uvindex
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Queries the OWM Weather API for Ultra Violet value sampled in the surroundings of the provided geocoordinates and in the specified time interval. A *UVIndex* object instance is returned, encapsulating a *Location* object and the UV intensity value. :param lat: the location's latitude, must be between -90.0 and 90.0 :type lat: int/float :param lon: the location's longitude, must be between -180.0 and 180.0 :type lon: int/float :return: a *UVIndex* instance or ``None`` if data is not available :raises: *ParseResponseException* when OWM Weather API responses' data cannot be parsed, *APICallException* when OWM Weather API can not be reached, *ValueError* for wrong input values
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python
train
bwhite/hadoopy
hadoopy/thirdparty/pyinstaller/PyInstaller/loader/archive.py
https://github.com/bwhite/hadoopy/blob/ff39b4e6d4e6efaf1f571cf0f2c0e0d7ab28c2d6/hadoopy/thirdparty/pyinstaller/PyInstaller/loader/archive.py#L177-L206
def build(self, path, lTOC): """ Create an archive file of name 'path'. lTOC is a 'logical TOC' - a list of (name, path, ...) where name is the internal name, eg 'a' and path is a file to get the object from, eg './a.pyc'. """ self.path = path self.lib = open(path, 'wb') #reserve space for the header if self.HDRLEN: self.lib.write('\0' * self.HDRLEN) #create an empty toc if type(self.TOCTMPLT) == type({}): self.toc = {} else: # assume callable self.toc = self.TOCTMPLT() for tocentry in lTOC: self.add(tocentry) # the guts of the archive tocpos = self.lib.tell() self.save_toc(tocpos) if self.TRLLEN: self.save_trailer(tocpos) if self.HDRLEN: self.update_headers(tocpos) self.lib.close()
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Create an archive file of name 'path'. lTOC is a 'logical TOC' - a list of (name, path, ...) where name is the internal name, eg 'a' and path is a file to get the object from, eg './a.pyc'.
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python
train
atlassian-api/atlassian-python-api
atlassian/jira.py
https://github.com/atlassian-api/atlassian-python-api/blob/540d269905c3e7547b666fe30c647b2d512cf358/atlassian/jira.py#L1131-L1138
def get_agile_board(self, board_id): """ Get agile board info by id :param board_id: :return: """ url = 'rest/agile/1.0/board/{}'.format(str(board_id)) return self.get(url)
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Get agile board info by id :param board_id: :return:
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python
train