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LISE-B26/pylabcontrol | build/lib/pylabcontrol/src/core/probe.py | Probe.value | def value(self):
"""
reads the value from the instrument
"""
value = getattr(self.instrument, self.probe_name)
self.buffer.append(value)
return value | python | def value(self):
"""
reads the value from the instrument
"""
value = getattr(self.instrument, self.probe_name)
self.buffer.append(value)
return value | [
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LISE-B26/pylabcontrol | build/lib/pylabcontrol/src/core/probe.py | Probe.load_and_append | def load_and_append(probe_dict, probes, instruments={}):
"""
load probes from probe_dict and append to probes, if additional instruments are required create them and add them to instruments
Args:
probe_dict: dictionary of form
probe_dict = {
inst... | python | def load_and_append(probe_dict, probes, instruments={}):
"""
load probes from probe_dict and append to probes, if additional instruments are required create them and add them to instruments
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probe_dict: dictionary of form
probe_dict = {
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bennylope/smartystreets.py | smartystreets/data.py | AddressCollection.get | def get(self, key):
"""
Returns an address by user controlled input ID
:param key: an input_id used to tag a lookup address
:return: a matching Address
"""
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"""
Returns an address by user controlled input ID
:param key: an input_id used to tag a lookup address
:return: a matching Address
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etal/biofrills | biofrills/stats/chisq.py | _igamc | def _igamc(a, x):
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SYNOPSIS:
double a, x, y, igamc();
y = igamc( a, x );
DESCRIPTION:
The function is defined by::
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inf.
-
... | python | def _igamc(a, x):
"""Complemented incomplete Gamma integral.
SYNOPSIS:
double a, x, y, igamc();
y = igamc( a, x );
DESCRIPTION:
The function is defined by::
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lreis2415/PyGeoC | examples/ex04_watershed_delineation.py | main | def main():
"""The simplest usage of watershed delineation based on TauDEM."""
dem = '../tests/data/Jamaica_dem.tif'
num_proc = 2
wp = '../tests/data/tmp_results/wtsd_delineation'
TauDEMWorkflow.watershed_delineation(num_proc, dem, workingdir=wp) | python | def main():
"""The simplest usage of watershed delineation based on TauDEM."""
dem = '../tests/data/Jamaica_dem.tif'
num_proc = 2
wp = '../tests/data/tmp_results/wtsd_delineation'
TauDEMWorkflow.watershed_delineation(num_proc, dem, workingdir=wp) | [
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser._get_line | def _get_line(self, search_string, search_file, return_string=True, case_sens=True):
'''Return the first line containing a set of strings in a file.
If return_string is False, we just return whether such a line
was found. If case_sens is False, the search is case
insensitive.
'... | python | def _get_line(self, search_string, search_file, return_string=True, case_sens=True):
'''Return the first line containing a set of strings in a file.
If return_string is False, we just return whether such a line
was found. If case_sens is False, the search is case
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_cutoff_energy | def get_cutoff_energy(self):
'''Determine the cutoff energy from the output'''
return Value(
scalars=[Scalar(value=self.settings["kinetic-energy cutoff"])],
units=self.settings['kinetic-energy cutoff units']
) | python | def get_cutoff_energy(self):
'''Determine the cutoff energy from the output'''
return Value(
scalars=[Scalar(value=self.settings["kinetic-energy cutoff"])],
units=self.settings['kinetic-energy cutoff units']
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_pp_name | def get_pp_name(self):
'''Determine the pseudopotential names from the output'''
ppnames = []
# Find the number of atom types
natomtypes = int(self._get_line('number of atomic types', self.outputf).split()[5])
# Find the pseudopotential names
with open(self.outputf) as fp... | python | def get_pp_name(self):
'''Determine the pseudopotential names from the output'''
ppnames = []
# Find the number of atom types
natomtypes = int(self._get_line('number of atomic types', self.outputf).split()[5])
# Find the pseudopotential names
with open(self.outputf) as fp... | [
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_U_settings | def get_U_settings(self):
'''Determine the DFT+U type and parameters from the output'''
with open(self.outputf) as fp:
for line in fp:
if "LDA+U calculation" in line:
U_param = {}
U_param['Type'] = line.split()[0]
U_... | python | def get_U_settings(self):
'''Determine the DFT+U type and parameters from the output'''
with open(self.outputf) as fp:
for line in fp:
if "LDA+U calculation" in line:
U_param = {}
U_param['Type'] = line.split()[0]
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_vdW_settings | def get_vdW_settings(self):
'''Determine the vdW type if using vdW xc functional or correction
scheme from the input otherwise'''
xc = self.get_xc_functional().scalars[0].value
if 'vdw' in xc.lower(): # vdW xc functional
return Value(scalars=[Scalar(value=xc)])
else:
... | python | def get_vdW_settings(self):
'''Determine the vdW type if using vdW xc functional or correction
scheme from the input otherwise'''
xc = self.get_xc_functional().scalars[0].value
if 'vdw' in xc.lower(): # vdW xc functional
return Value(scalars=[Scalar(value=xc)])
else:
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_stresses | def get_stresses(self):
'''Determine the stress tensor from the output'''
if "stress" not in self.settings:
return None
wrapped = [[Scalar(value=x) for x in y] for y in self.settings["stress"]]
return Property(matrices=[wrapped], units=self.settings["stress units"]) | python | def get_stresses(self):
'''Determine the stress tensor from the output'''
if "stress" not in self.settings:
return None
wrapped = [[Scalar(value=x) for x in y] for y in self.settings["stress"]]
return Property(matrices=[wrapped], units=self.settings["stress units"]) | [
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_dos | def get_dos(self):
'''Find the total DOS shifted by the Fermi energy'''
# find the dos file
fildos = ''
for f in self._files:
with open(f, 'r') as fp:
first_line = next(fp)
if "E (eV)" in first_line and "Int dos(E)" in first_line:
... | python | def get_dos(self):
'''Find the total DOS shifted by the Fermi energy'''
# find the dos file
fildos = ''
for f in self._files:
with open(f, 'r') as fp:
first_line = next(fp)
if "E (eV)" in first_line and "Int dos(E)" in first_line:
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CitrineInformatics/pif-dft | dfttopif/parsers/pwscf.py | PwscfParser.get_band_gap | def get_band_gap(self):
'''Compute the band gap from the DOS'''
dosdata = self.get_dos()
if type(dosdata) == type(None):
return None # cannot find DOS
else:
energy = dosdata.conditions.scalars
dos = dosdata.scalars
step_size = energy[1].val... | python | def get_band_gap(self):
'''Compute the band gap from the DOS'''
dosdata = self.get_dos()
if type(dosdata) == type(None):
return None # cannot find DOS
else:
energy = dosdata.conditions.scalars
dos = dosdata.scalars
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idlesign/django-sitecats | sitecats/toolbox.py | get_category_aliases_under | def get_category_aliases_under(parent_alias=None):
"""Returns a list of category aliases under the given parent.
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:param str|None parent_alias: Parent alias or None to categories under... | python | def get_category_aliases_under(parent_alias=None):
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idlesign/django-sitecats | sitecats/toolbox.py | get_category_lists | def get_category_lists(init_kwargs=None, additional_parents_aliases=None, obj=None):
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idlesign/django-sitecats | sitecats/toolbox.py | CategoryRequestHandler.register_lists | def register_lists(self, category_lists, lists_init_kwargs=None, editor_init_kwargs=None):
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idlesign/django-sitecats | sitecats/toolbox.py | CategoryRequestHandler.action_remove | def action_remove(cls, request, category_list):
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idlesign/django-sitecats | sitecats/toolbox.py | CategoryRequestHandler.action_add | def action_add(cls, request, category_list):
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vasilcovsky/pytinypng | pytinypng/api.py | shrink | def shrink(image, apikey):
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koszullab/metaTOR | metator/metator.py | download_and_install_dependencies | def download_and_install_dependencies():
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raise ValueError("Python 3.6+ is required.")
dependencies = {"hmm_databases": HMM_URL}
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raise ValueError("Python 3.6+ is required.")
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MacHu-GWU/single_file_module-project | sfm/rerecipe.py | extract_by_prefix_surfix | def extract_by_prefix_surfix(text,
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MacHu-GWU/single_file_module-project | sfm/rerecipe.py | extract_number | def extract_number(text):
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PSPC-SPAC-buyandsell/didauth | didauth/headers.py | HeaderSigner.sign | def sign(self, headers: Mapping, method=None, path=None):
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TylerTemp/docpie | docpie/pie.py | Docpie.docpie | def docpie(self, argv=None):
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TylerTemp/docpie | docpie/pie.py | Docpie.clone_exception | def clone_exception(error, args):
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```
try:
do_sth()
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handle(e)
def handle(error):
# do sth with error
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TylerTemp/docpie | docpie/pie.py | Docpie.to_dict | def to_dict(self): # cls, self):
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pie = Docpie(__doc__)
json.dumps(pie.convert_2_dict())
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TylerTemp/docpie | docpie/pie.py | Docpie.from_dict | def from_dict(cls, dic):
"""Convert dict generated by `convert_2_dict` into Docpie instance
You can do this:
pie = Docpie(__doc__)
clone_pie = json.loads(pie.convert_2_docpie(
json.dumps(pie.convert_2_dict())
))
Note if you changed `extra`, it will be lost.
... | python | def from_dict(cls, dic):
"""Convert dict generated by `convert_2_dict` into Docpie instance
You can do this:
pie = Docpie(__doc__)
clone_pie = json.loads(pie.convert_2_docpie(
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TylerTemp/docpie | docpie/pie.py | Docpie.preview | def preview(self, stream=sys.stdout):
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write('\n')
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"""A quick preview of docpie. Print all the parsed object"""
write = stream.write
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nugget/python-anthemav | anthemav/protocol.py | AVR.refresh_core | def refresh_core(self):
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nugget/python-anthemav | anthemav/protocol.py | AVR.poweron_refresh | def poweron_refresh(self):
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nugget/python-anthemav | anthemav/protocol.py | AVR.refresh_all | def refresh_all(self):
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This does not return any data, it just ... | python | def refresh_all(self):
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nugget/python-anthemav | anthemav/protocol.py | AVR.connection_made | def connection_made(self, transport):
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self.log.info('Connection established to AVR')
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#self.transport.set_write_buffer_limits(0)
limit_low, limit_high = self.transport.get_write_buff... | python | def connection_made(self, transport):
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nugget/python-anthemav | anthemav/protocol.py | AVR.data_received | def data_received(self, data):
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nugget/python-anthemav | anthemav/protocol.py | AVR.connection_lost | def connection_lost(self, exc):
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nugget/python-anthemav | anthemav/protocol.py | AVR._assemble_buffer | def _assemble_buffer(self):
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nugget/python-anthemav | anthemav/protocol.py | AVR._populate_inputs | def _populate_inputs(self, total):
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nugget/python-anthemav | anthemav/protocol.py | AVR.dump_rawdata | def dump_rawdata(self):
"""Return contents of transport object for debugging forensics."""
if hasattr(self, 'transport'):
attrs = vars(self.transport)
return ', '.join("%s: %s" % item for item in attrs.items()) | python | def dump_rawdata(self):
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Batch.add_upsert | def add_upsert(self, value, criteria):
"""Add a tag or populator to the batch by value and criteria"""
value = value.strip()
v = value.lower()
self.lower_val_to_val[v] = value
criteria_array = self.upserts.get(v)
if criteria_array is None:
criteria_array = []... | python | def add_upsert(self, value, criteria):
"""Add a tag or populator to the batch by value and criteria"""
value = value.strip()
v = value.lower()
self.lower_val_to_val[v] = value
criteria_array = self.upserts.get(v)
if criteria_array is None:
criteria_array = []... | [
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Batch.parts | def parts(self):
"""Return an array of batch parts to submit"""
parts = []
upserts = dict()
deletes = []
# we keep track of the batch size as we go (pretty close approximation!) so we can chunk it small enough
# to limit the HTTP posts to under 700KB - server limits to... | python | def parts(self):
"""Return an array of batch parts to submit"""
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kentik/kentikapi-py | kentikapi/v5/tagging.py | BatchPart.build_json | def build_json(self, guid):
"""Build JSON with the input guid"""
upserts = []
for value in self.upserts:
upserts.append({"value": value, "criteria": self.upserts[value]})
return json.dumps({'replace_all': self.replace_all, 'guid': guid,
'complete': ... | python | def build_json(self, guid):
"""Build JSON with the input guid"""
upserts = []
for value in self.upserts:
upserts.append({"value": value, "criteria": self.upserts[value]})
return json.dumps({'replace_all': self.replace_all, 'guid': guid,
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Criteria._ensure_field | def _ensure_field(self, key):
"""Ensure a non-array field"""
if self._has_field:
self._size += 2 # comma, space
self._has_field = True
self._size += len(key) + 4 | python | def _ensure_field(self, key):
"""Ensure a non-array field"""
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Criteria._ensure_array | def _ensure_array(self, key, value):
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Criteria.add_tcp_flag | def add_tcp_flag(self, tcp_flag):
"""Add a single TCP flag - will be OR'd into the existing bitmask"""
if tcp_flag not in [1, 2, 4, 8, 16, 32, 64, 128]:
raise ValueError("Invalid TCP flag. Valid: [1, 2, 4, 8, 16,32, 64, 128]")
prev_size = 0
if self._json_dict.get('tcp_flag... | python | def add_tcp_flag(self, tcp_flag):
"""Add a single TCP flag - will be OR'd into the existing bitmask"""
if tcp_flag not in [1, 2, 4, 8, 16, 32, 64, 128]:
raise ValueError("Invalid TCP flag. Valid: [1, 2, 4, 8, 16,32, 64, 128]")
prev_size = 0
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Criteria.set_tcp_flags | def set_tcp_flags(self, tcp_flags):
"""Set the complete tcp flag bitmask"""
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raise ValueError("Invalid tcp_flags. Valid: 0-255.")
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"""Set the complete tcp flag bitmask"""
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Client._submit_batch | def _submit_batch(self, url, batch):
"""Submit the batch, returning the JSON->dict from the last HTTP response"""
# TODO: validate column_name
batch_parts = batch.parts()
guid = ""
headers = {
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Client.submit_populator_batch | def submit_populator_batch(self, column_name, batch):
"""Submit a populator batch
Submit a populator batch as a series of HTTP requests in small chunks,
returning the batch GUID, or raising exception on error."""
if not set(column_name).issubset(_allowedCustomDimensionChars):
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"""Submit a populator batch
Submit a populator batch as a series of HTTP requests in small chunks,
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if not set(column_name).issubset(_allowedCustomDimensionChars):
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Client.submit_tag_batch | def submit_tag_batch(self, batch):
"""Submit a tag batch"""
url = '%s/api/v5/batch/tags' % self.base_url
self._submit_batch(url, batch) | python | def submit_tag_batch(self, batch):
"""Submit a tag batch"""
url = '%s/api/v5/batch/tags' % self.base_url
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kentik/kentikapi-py | kentikapi/v5/tagging.py | Client.fetch_batch_status | def fetch_batch_status(self, guid):
"""Fetch the status of a batch, given the guid"""
url = '%s/api/v5/batch/%s/status' % (self.base_url, guid)
headers = {
'User-Agent': 'kentik-python-api/0.1',
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"""Fetch the status of a batch, given the guid"""
url = '%s/api/v5/batch/%s/status' % (self.base_url, guid)
headers = {
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SMAPPNYU/pysmap | pysmap/mltools/crowd_model.py | CrowdModel.predict_files | def predict_files(self, files):
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koszullab/metaTOR | metator/scripts/fasta_utils.py | rename_genome | def rename_genome(genome_in, genome_out=None):
"""Rename genome and slugify headers
Rename genomes according to a simple naming scheme; this
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----------
genome_in : file, str or pathlib.Path
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Filter a fasta file according to size and/or an explicit list of records
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----------
genome_in: file, str or pathlib.Path
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koszullab/metaTOR | metator/scripts/fasta_utils.py | rename_proteins | def rename_proteins(prot_in, prot_out=None, chunk_size=DEFAULT_CHUNK_SIZE):
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Rename output files from prodigal according to the following naming
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vasilcovsky/pytinypng | pytinypng/utils.py | write_binary | def write_binary(filename, data):
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ariebovenberg/snug | examples/slack/channels.py | list_ | def list_(*, cursor: str=None,
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igorcoding/asynctnt-queue | asynctnt_queue/queue.py | Queue.tube | def tube(self, name):
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eclipse/unide.python | src/unide/measurement.py | device_measurement | def device_measurement(device,
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eclipse/unide.python | src/unide/measurement.py | Measurement.add_sample | def add_sample(self, ts, **kwargs):
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thebigmunch/audio-metadata | src/audio_metadata/api.py | determine_format | def determine_format(data, extension=None):
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MacHu-GWU/single_file_module-project | sfm/lines_count.py | count_lines | def count_lines(abspath):
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"""Count how many lines in a pure text file.
"""
with open(abspath, "rb") as f:
i = 0
for line in f:
i += 1
pass
return i | [
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MacHu-GWU/single_file_module-project | sfm/lines_count.py | lines_stats | def lines_stats(dir_path, file_filter):
"""Lines count of selected files under a directory.
:return n_files: number of files
:return n_lines: number of lines
"""
n_files = 0
n_lines = 0
for p in Path(dir_path).select_file(file_filter):
n_files += 1
n_lines += count_lines(p.a... | python | def lines_stats(dir_path, file_filter):
"""Lines count of selected files under a directory.
:return n_files: number of files
:return n_lines: number of lines
"""
n_files = 0
n_lines = 0
for p in Path(dir_path).select_file(file_filter):
n_files += 1
n_lines += count_lines(p.a... | [
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TylerTemp/docpie | docpie/parser.py | UsageParser.parse_content | def parse_content(self, text):
"""get Usage section and set to `raw_content`, `formal_content` of no
title and empty-line version"""
match = re.search(
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flags=(re.DOTALL
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"""get Usage section and set to `raw_content`, `formal_content` of no
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koszullab/metaTOR | metator/scripts/figures.py | spaceless_pdf_plot_maker | def spaceless_pdf_plot_maker(array, filename, vmax=None, dpi=DEFAULT_DPI):
"""Draw a pretty plot from an array
A function that performs all the tedious matplotlib
magic to draw a 2D array with as few parameters and
as little whitespace as possible.
Parameters
----------
array : array_like
... | python | def spaceless_pdf_plot_maker(array, filename, vmax=None, dpi=DEFAULT_DPI):
"""Draw a pretty plot from an array
A function that performs all the tedious matplotlib
magic to draw a 2D array with as few parameters and
as little whitespace as possible.
Parameters
----------
array : array_like
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array : array_like
The input array to draw.
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koszullab/metaTOR | metator/scripts/figures.py | draw_sparse_matrix | def draw_sparse_matrix(
array_filename,
output_image,
vmax=DEFAULT_SATURATION_THRESHOLD,
max_size_matrix=DEFAULT_MAX_SIZE_MATRIX,
):
"""Draw a quick preview of a sparse matrix with automated
binning and normalization.
"""
matrix = np.loadtxt(array_filename, dtype=np.int32, skiprows=1)
... | python | def draw_sparse_matrix(
array_filename,
output_image,
vmax=DEFAULT_SATURATION_THRESHOLD,
max_size_matrix=DEFAULT_MAX_SIZE_MATRIX,
):
"""Draw a quick preview of a sparse matrix with automated
binning and normalization.
"""
matrix = np.loadtxt(array_filename, dtype=np.int32, skiprows=1)
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MacHu-GWU/single_file_module-project | sfm/iterable.py | nth | def nth(iterable, n, default=None):
"""Returns the nth item or a default value.
Example::
>>> nth([0, 1, 2], 1)
1
>>> nth([0, 1, 2], 100)
None
**中文文档**
取出一个可循环对象中的第n个元素。等效于list(iterable)[n], 但占用极小的内存。
因为list(iterable)要将所有元素放在内存中并生成一个新列表。该方法常用语对于
那些取index操作被改写... | python | def nth(iterable, n, default=None):
"""Returns the nth item or a default value.
Example::
>>> nth([0, 1, 2], 1)
1
>>> nth([0, 1, 2], 100)
None
**中文文档**
取出一个可循环对象中的第n个元素。等效于list(iterable)[n], 但占用极小的内存。
因为list(iterable)要将所有元素放在内存中并生成一个新列表。该方法常用语对于
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>>> nth([0, 1, 2], 1)
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>>> nth([0, 1, 2], 100)
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**中文文档**
取出一个可循环对象中的第n个元素。等效于list(iterable)[n], 但占用极小的内存。
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MacHu-GWU/single_file_module-project | sfm/iterable.py | pull | def pull(iterable, n):
"""Return last n items of the iterable as a list.
Example::
>>> pull([0, 1, 2], 3)
[1, 2]
**中文文档**
取出可循环对象中的最后n个元素。等效于list(iterable)[-n:], 但占用极小的内存。
因为list(iterable)要将所有元素放在内存中并生成一个新列表。该方法常用语对于
那些取index操作被改写了的可循环对象。
"""
fifo = collections.deque(... | python | def pull(iterable, n):
"""Return last n items of the iterable as a list.
Example::
>>> pull([0, 1, 2], 3)
[1, 2]
**中文文档**
取出可循环对象中的最后n个元素。等效于list(iterable)[-n:], 但占用极小的内存。
因为list(iterable)要将所有元素放在内存中并生成一个新列表。该方法常用语对于
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取出可循环对象中的最后n个元素。等效于list(iterable)[-n:], 但占用极小的内存。
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MacHu-GWU/single_file_module-project | sfm/iterable.py | running_window | def running_window(iterable, size):
"""Generate n-size running window.
Example::
>>> for i in running_windows([1, 2, 3, 4, 5], size=3):
... print(i)
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
**中文文档**
简单滑窗函数。
"""
if size > len(iterable):
raise ValueErro... | python | def running_window(iterable, size):
"""Generate n-size running window.
Example::
>>> for i in running_windows([1, 2, 3, 4, 5], size=3):
... print(i)
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
**中文文档**
简单滑窗函数。
"""
if size > len(iterable):
raise ValueErro... | [
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MacHu-GWU/single_file_module-project | sfm/iterable.py | cycle_running_window | def cycle_running_window(iterable, size):
"""Generate n-size cycle running window.
Example::
>>> for i in running_windows([1, 2, 3, 4, 5], size=3):
... print(i)
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
[4, 5, 1]
[5, 1, 2]
**中文文档**
循环位移滑窗函数。
"""
... | python | def cycle_running_window(iterable, size):
"""Generate n-size cycle running window.
Example::
>>> for i in running_windows([1, 2, 3, 4, 5], size=3):
... print(i)
[1, 2, 3]
[2, 3, 4]
[3, 4, 5]
[4, 5, 1]
[5, 1, 2]
**中文文档**
循环位移滑窗函数。
"""
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MacHu-GWU/single_file_module-project | sfm/iterable.py | shift_and_trim | def shift_and_trim(array, dist):
"""Shift and trim unneeded item.
:params array: list like iterable object
:params dist: int
Example::
>>> array = [0, 1, 2]
>>> shift_and_trim(array, 0)
[0, 1, 2]
>>> shift_and_trim(array, 1)
[0, 1]
>>> shift_and_trim(... | python | def shift_and_trim(array, dist):
"""Shift and trim unneeded item.
:params array: list like iterable object
:params dist: int
Example::
>>> array = [0, 1, 2]
>>> shift_and_trim(array, 0)
[0, 1, 2]
>>> shift_and_trim(array, 1)
[0, 1]
>>> shift_and_trim(... | [
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MacHu-GWU/single_file_module-project | sfm/iterable.py | shift_and_pad | def shift_and_pad(array, dist, pad="__null__"):
"""Shift and pad with item.
:params array: list like iterable object
:params dist: int
:params pad: any value
Example::
>>> array = [0, 1, 2]
>>> shift_and_pad(array, 0)
[0, 1, 2]
>>> shift_and_pad(array, 1)
... | python | def shift_and_pad(array, dist, pad="__null__"):
"""Shift and pad with item.
:params array: list like iterable object
:params dist: int
:params pad: any value
Example::
>>> array = [0, 1, 2]
>>> shift_and_pad(array, 0)
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>>> shift_and_pad(array, 1)
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>>> shift_and_pad(array, 1)
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