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TwitchIO/TwitchIO | b5eb585b9b52d4966784f0d1ae947077a90ec0c7 | twitchio/user.py | python | PartialUser.update_extensions | (self, token: str, extensions: "ExtensionBuilder") | return {typ: {int(n): ActiveExtension(d) for n, d in vals.items()} for typ, vals in data.items()} | |coro|
Updates a users extensions. See the :class:`twitchio.ExtensionBuilder`
Parameters
-----------
token: :class:`str`
An oauth token with user:edit:broadcast scope
extensions: :class:`twitchio.ExtensionBuilder`
A :class:`twitchio.ExtensionBuilder` to be given to the twitch api
Returns
--------
Dict[:class:`str`, Dict[:class:`int`, :class:`twitchio.ActiveExtension`]] | |coro| | [
"|coro|"
] | async def update_extensions(self, token: str, extensions: "ExtensionBuilder"):
"""|coro|
Updates a users extensions. See the :class:`twitchio.ExtensionBuilder`
Parameters
-----------
token: :class:`str`
An oauth token with user:edit:broadcast scope
extensions: :class:`twitchio.ExtensionBuilder`
A :class:`twitchio.ExtensionBuilder` to be given to the twitch api
Returns
--------
Dict[:class:`str`, Dict[:class:`int`, :class:`twitchio.ActiveExtension`]]
"""
from .models import ActiveExtension
data = await self._http.put_user_extensions(token, extensions._to_dict())
return {typ: {int(n): ActiveExtension(d) for n, d in vals.items()} for typ, vals in data.items()} | [
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gramps-project/gramps | 04d4651a43eb210192f40a9f8c2bad8ee8fa3753 | gramps/gen/lib/family.py | python | Family.get_handle_referents | (self) | return self.media_list + self.attribute_list + \
self.lds_ord_list + self.child_ref_list + self.event_ref_list | Return the list of child objects which may, directly or through their
children, reference primary objects..
:returns: Returns the list of objects referencing primary objects.
:rtype: list | Return the list of child objects which may, directly or through their
children, reference primary objects.. | [
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] | def get_handle_referents(self):
"""
Return the list of child objects which may, directly or through their
children, reference primary objects..
:returns: Returns the list of objects referencing primary objects.
:rtype: list
"""
return self.media_list + self.attribute_list + \
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bookwyrm-social/bookwyrm | 0c2537e27a2cdbc0136880dfbbf170d5fec72986 | bookwyrm/models/activitypub_mixin.py | python | OrderedCollectionPageMixin.to_ordered_collection | (
self, queryset, remote_id=None, page=False, collection_only=False, **kwargs
) | return serializer(**activity) | an ordered collection of whatevers | an ordered collection of whatevers | [
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] | def to_ordered_collection(
self, queryset, remote_id=None, page=False, collection_only=False, **kwargs
):
"""an ordered collection of whatevers"""
if not queryset.ordered:
raise RuntimeError("queryset must be ordered")
remote_id = remote_id or self.remote_id
if page:
if isinstance(page, list) and len(page) > 0:
page = page[0]
return to_ordered_collection_page(queryset, remote_id, page=page, **kwargs)
if collection_only or not hasattr(self, "activity_serializer"):
serializer = activitypub.OrderedCollection
activity = {}
else:
serializer = self.activity_serializer
# a dict from the model fields
activity = generate_activity(self)
if remote_id:
activity["id"] = remote_id
paginated = Paginator(queryset, PAGE_LENGTH)
# add computed fields specific to orderd collections
activity["totalItems"] = paginated.count
activity["first"] = f"{remote_id}?page=1"
activity["last"] = f"{remote_id}?page={paginated.num_pages}"
return serializer(**activity) | [
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InsaneLife/dssm | 1d32e137654e03994f7ba6cfde52e1d47601027c | util.py | python | _truncate_seq_pair | (tokens_a, tokens_b, max_length) | Truncates a sequence pair in place to the maximum length. | Truncates a sequence pair in place to the maximum length. | [
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"""Truncates a sequence pair in place to the maximum length."""
while True:
total_length = len(tokens_a) + len(tokens_b)
if total_length <= max_length:
break
if len(tokens_a) > len(tokens_b):
tokens_a.pop()
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nil0x42/phpsploit | ee83c3260616a874877a904e732408b915ff272e | src/core/session/settings/REQ_ZLIB_TRY_LIMIT.py | python | default_value | () | return "20 MiB" | [] | def default_value():
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quantumlib/OpenFermion | 6187085f2a7707012b68370b625acaeed547e62b | src/openfermion/chem/molecular_data.py | python | MolecularData.get_active_space_integrals | (self,
occupied_indices=None,
active_indices=None) | return reps.get_active_space_integrals(one_body_integrals,
two_body_integrals,
occupied_indices, active_indices) | Restricts a molecule at a spatial orbital level to an active space
This active space may be defined by a list of active indices and
doubly occupied indices. Note that one_body_integrals and
two_body_integrals must be defined
n an orthonormal basis set.
Args:
occupied_indices: A list of spatial orbital indices
indicating which orbitals should be considered doubly occupied.
active_indices: A list of spatial orbital indices indicating
which orbitals should be considered active.
Returns:
tuple: Tuple with the following entries:
**core_constant**: Adjustment to constant shift in Hamiltonian
from integrating out core orbitals
**one_body_integrals_new**: one-electron integrals over active
space.
**two_body_integrals_new**: two-electron integrals over active
space. | Restricts a molecule at a spatial orbital level to an active space | [
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"spatial",
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] | def get_active_space_integrals(self,
occupied_indices=None,
active_indices=None):
"""Restricts a molecule at a spatial orbital level to an active space
This active space may be defined by a list of active indices and
doubly occupied indices. Note that one_body_integrals and
two_body_integrals must be defined
n an orthonormal basis set.
Args:
occupied_indices: A list of spatial orbital indices
indicating which orbitals should be considered doubly occupied.
active_indices: A list of spatial orbital indices indicating
which orbitals should be considered active.
Returns:
tuple: Tuple with the following entries:
**core_constant**: Adjustment to constant shift in Hamiltonian
from integrating out core orbitals
**one_body_integrals_new**: one-electron integrals over active
space.
**two_body_integrals_new**: two-electron integrals over active
space.
"""
# Fix data type for a few edge cases
occupied_indices = [] if occupied_indices is None else occupied_indices
if (len(active_indices) < 1):
raise ValueError('Some active indices required for reduction.')
# Get integrals.
one_body_integrals, two_body_integrals = self.get_integrals()
return reps.get_active_space_integrals(one_body_integrals,
two_body_integrals,
occupied_indices, active_indices) | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-windows/x86/ldap3/extend/microsoft/dirSync.py | python | DirSync.loop | (self) | [] | def loop(self):
result = self.connection.search(search_base=self.base,
search_filter=self.filter,
search_scope=SUBTREE,
attributes=self.attributes,
dereference_aliases=DEREF_NEVER,
controls=[dir_sync_control(criticality=True,
object_security=self.object_security,
ancestors_first=self.ancestors_first,
public_data_only=self.public_data_only,
incremental_values=self.incremental_values,
max_length=self.max_length, cookie=self.cookie),
extended_dn_control(criticality=False, hex_format=self.hex_guid),
show_deleted_control(criticality=False)]
)
if not self.connection.strategy.sync:
response, result = self.connection.get_response(result)
else:
response = self.connection.response
result = self.connection.result
if result['description'] == 'success' and 'controls' in result and '1.2.840.113556.1.4.841' in result['controls']:
self.more_results = result['controls']['1.2.840.113556.1.4.841']['value']['more_results']
self.cookie = result['controls']['1.2.840.113556.1.4.841']['value']['cookie']
return response
elif 'controls' in result:
raise LDAPExtensionError('Missing DirSync control in response from server')
else:
raise LDAPExtensionError('error %r in DirSync' % result) | [
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morganstanley/treadmill | f18267c665baf6def4374d21170198f63ff1cde4 | lib/python/treadmill/cli/app_dns.py | python | init | () | return appdns | Configures App DNS | Configures App DNS | [
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"App",
"DNS"
] | def init():
"""Configures App DNS
"""
# pylint: disable=too-many-statements
formatter = cli.make_formatter('app-dns')
@click.group(name='app-dns')
def appdns():
"""Manage Treadmill App DNS configuration.
"""
def configure_base(name, cell, pattern, endpoints, alias, scope, id_group):
"""Create, modify or get Treadmill App DNS entry"""
restapi = context.GLOBAL.admin_api()
url = _REST_PATH + name
data = {}
if cell:
data['cells'] = cell
if pattern is not None:
data['pattern'] = pattern
if endpoints is not None:
data['endpoints'] = endpoints
if alias is not None:
data['alias'] = alias
if scope is not None:
data['scope'] = scope
if id_group is not None:
data['identity-group'] = id_group
if data:
try:
_LOGGER.debug('Trying to create app-dns entry %s', name)
restclient.post(restapi, url, data)
except restclient.AlreadyExistsError:
_LOGGER.debug('Updating app-dns entry %s', name)
restclient.put(restapi, url, data)
_LOGGER.debug('Retrieving App DNS entry %s', name)
app_dns_entry = restclient.get(restapi, url).json()
cli.out(formatter(app_dns_entry))
@appdns.command()
@click.argument('name', nargs=1, required=True)
@click.option('--cell', help='List of cells',
type=cli.LIST)
@click.option('--pattern', help='App pattern')
@click.option('--endpoints', help='Endpoints to be included in SRV rec',
type=cli.LIST)
@click.option('--alias', help='App DNS alias')
@click.option('--scope', help='DNS scope')
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def configure(name, cell, pattern, endpoints, alias, scope):
"""Create, modify or get DNS SRV entry"""
configure_base(name, cell, pattern, endpoints, alias, scope, None)
@appdns.group(name='cname')
def cname():
"""Manage DNS CNAME configuration.
"""
@cname.command(name='configure')
@click.argument('name', nargs=1, required=True)
@click.option('--cell', help='List of cells',
type=cli.LIST)
@click.option('--pattern', help='App pattern')
@click.option('--alias', help='App DNS alias')
@click.option('--scope', help='DNS scope')
@click.option('--identity-group', 'id_group', help='Identity group to '
'create alias(es) pointing to the instances\' hosts')
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def configure_cname(name, cell, pattern, alias, scope, id_group):
"""Create, modify or get DNS CNAME configuration"""
configure_base(name, cell, pattern, None, alias, scope, id_group)
@appdns.group(name='srv')
def srv():
"""Manage DNS SRV configuration.
"""
@srv.command(name='configure')
@click.argument('name', nargs=1, required=True)
@click.option('--cell', help='List of cells',
type=cli.LIST)
@click.option('--pattern', help='App pattern')
@click.option('--endpoints', help='Endpoints to be included in SRV rec',
type=cli.LIST)
@click.option('--alias', help='App DNS alias')
@click.option('--scope', help='DNS scope')
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def configure_srv(name, cell, pattern, endpoints, alias, scope):
"""Create, modify or get DNS SRV entry"""
configure_base(name, cell, pattern, endpoints, alias, scope, None)
@appdns.command()
@click.argument('name', nargs=1, required=True)
@click.option('--add', help='Cells to to add.', type=cli.LIST)
@click.option('--remove', help='Cells to to remove.', type=cli.LIST)
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def cells(add, remove, name):
"""Add or remove cells from the app-dns."""
url = _REST_PATH + name
restapi = context.GLOBAL.admin_api()
existing = restclient.get(restapi, url).json()
cells = set(existing['cells'])
if add:
cells.update(add)
if remove:
cells = cells - set(remove)
if '_id' in existing:
del existing['_id']
existing['cells'] = list(cells)
restclient.put(restapi, url, existing)
@appdns.command(name='list')
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def _list():
"""List out App Group entries"""
restapi = context.GLOBAL.admin_api()
response = restclient.get(restapi, _REST_PATH)
cli.out(formatter(response.json()))
@appdns.command()
@click.argument('name', nargs=1, required=True)
@cli.handle_exceptions(restclient.CLI_REST_EXCEPTIONS)
def delete(name):
"""Delete Treadmill App Group entry"""
restapi = context.GLOBAL.admin_api()
url = _REST_PATH + name
restclient.delete(restapi, url)
del delete
del cells
del _list
del configure
del configure_cname
del configure_srv
del cname
del srv
return appdns | [
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jupyterhub/jupyterhub | e58cf0670690d11631f9dc6e1ab702c60f7bfd13 | jupyterhub/apihandlers/groups.py | python | GroupListAPIHandler.get | (self) | List groups | List groups | [
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query = full_query = self.db.query(orm.Group)
sub_scope = self.parsed_scopes['list:groups']
if sub_scope != Scope.ALL:
if not set(sub_scope).issubset({'group'}):
# the only valid filter is group=...
# don't expand invalid !server=x to all groups!
self.log.warning(
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)
raise web.HTTPError(403)
query = query.filter(orm.Group.name.in_(sub_scope['group']))
offset, limit = self.get_api_pagination()
query = query.order_by(orm.Group.id.asc()).offset(offset).limit(limit)
group_list = [self.group_model(g) for g in query]
total_count = full_query.count()
if self.accepts_pagination:
data = self.paginated_model(group_list, offset, limit, total_count)
else:
query_count = query.count()
if offset == 0 and total_count > query_count:
self.log.warning(
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data = group_list
self.write(json.dumps(data)) | [
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python-telegram-bot/python-telegram-bot | ade1529986f5b6d394a65372d6a27045a70725b2 | telegram/ext/filters.py | python | BaseFilter.__or__ | (self, other: 'BaseFilter') | return MergedFilter(self, or_filter=other) | [] | def __or__(self, other: 'BaseFilter') -> 'BaseFilter':
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masthoon/pwintools | e62634e99bf33d6745d8c642d3c7f028699c1958 | pwintools.py | python | Remote.recvline | (self, keepends = True, timeout = None) | return self.recvuntil(self.newline, not keepends, timeout) | recvline(keepends = True, timeout = None) reads one line on the socket before timeout | recvline(keepends = True, timeout = None) reads one line on the socket before timeout | [
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] | def recvline(self, keepends = True, timeout = None):
"""recvline(keepends = True, timeout = None) reads one line on the socket before timeout"""
return self.recvuntil(self.newline, not keepends, timeout) | [
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beeware/ouroboros | a29123c6fab6a807caffbb7587cf548e0c370296 | ouroboros/decimal.py | python | Context.max_mag | (self, a, b) | return a.max_mag(b, context=self) | Compares the values numerically with their sign ignored.
>>> ExtendedContext.max_mag(Decimal('7'), Decimal('NaN'))
Decimal('7')
>>> ExtendedContext.max_mag(Decimal('7'), Decimal('-10'))
Decimal('-10')
>>> ExtendedContext.max_mag(1, -2)
Decimal('-2')
>>> ExtendedContext.max_mag(Decimal(1), -2)
Decimal('-2')
>>> ExtendedContext.max_mag(1, Decimal(-2))
Decimal('-2') | Compares the values numerically with their sign ignored. | [
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] | def max_mag(self, a, b):
"""Compares the values numerically with their sign ignored.
>>> ExtendedContext.max_mag(Decimal('7'), Decimal('NaN'))
Decimal('7')
>>> ExtendedContext.max_mag(Decimal('7'), Decimal('-10'))
Decimal('-10')
>>> ExtendedContext.max_mag(1, -2)
Decimal('-2')
>>> ExtendedContext.max_mag(Decimal(1), -2)
Decimal('-2')
>>> ExtendedContext.max_mag(1, Decimal(-2))
Decimal('-2')
"""
a = _convert_other(a, raiseit=True)
return a.max_mag(b, context=self) | [
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CouchPotato/CouchPotatoV1 | 135b3331d1b88ef645e29b76f2d4cc4a732c9232 | library/hachoir_core/tools.py | python | alignValue | (value, align) | Align a value to next 'align' multiple.
>>> alignValue(31, 4)
32
>>> alignValue(32, 4)
32
>>> alignValue(33, 4)
36
Note: alignValue(value, align) == (value + paddingSize(value, align)) | Align a value to next 'align' multiple. | [
"Align",
"a",
"value",
"to",
"next",
"align",
"multiple",
"."
] | def alignValue(value, align):
"""
Align a value to next 'align' multiple.
>>> alignValue(31, 4)
32
>>> alignValue(32, 4)
32
>>> alignValue(33, 4)
36
Note: alignValue(value, align) == (value + paddingSize(value, align))
"""
if value % align != 0:
return value + align - (value % align)
else:
return value | [
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davepeck/game-of-go | a75267f9ba0f47beda7a490824d99e0f5cf91f7b | www/go.py | python | GameBoard.is_dead | (self, x, y, color=CONST.Both_Colors) | return self.is_stone_of_color(x, y, color) | [] | def is_dead(self, x, y, color=CONST.Both_Colors):
if self.get_owner(x, y) == CONST.No_Color:
return False
return self.is_stone_of_color(x, y, color) | [
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SCSSoftware/BlenderTools | 96f323d3bdf2d8cb8ed7f882dcdf036277a802dd | addon/io_scs_tools/exp/pip/curve.py | python | Curve.set_length | (self, value) | Set curve length.
:param value: curve length
:type value: float | Set curve length. | [
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] | def set_length(self, value):
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:param value: curve length
:type value: float
"""
self.__length = value | [
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mikgroup/sigpy | 85739eee0a2db4c14074b670e63e36de0cc5a8f2 | sigpy/mri/samp.py | python | poisson | (img_shape, accel, calib=(0, 0), dtype=np.complex,
crop_corner=True, return_density=False, seed=0,
max_attempts=30, tol=0.1) | return mask | Generate variable-density Poisson-disc sampling pattern.
The function generates a variable density Poisson-disc sampling
mask with density proportional to :math:`1 / (1 + s |r|)`,
where :math:`r` represents the k-space radius, and :math:`s`
represents the slope. A binary search is performed on the slope :math:`s`
such that the resulting acceleration factor is close to the
prescribed acceleration factor `accel`. The parameter `tol`
determines how much they can deviate.
Args:
img_shape (tuple of ints): length-2 image shape.
accel (float): Target acceleration factor. Must be greater than 1.
calib (tuple of ints): length-2 calibration shape.
dtype (Dtype): data type.
crop_corner (bool): Toggle whether to crop sampling corners.
seed (int): Random seed.
max_attempts (float): maximum number of samples to reject in Poisson
disc calculation.
tol (float): Tolerance for how much the resulting acceleration can
deviate form `accel`.
Returns:
array: Poisson-disc sampling mask.
References:
Bridson, Robert. "Fast Poisson disk sampling in arbitrary dimensions."
SIGGRAPH sketches. 2007. | Generate variable-density Poisson-disc sampling pattern. | [
"Generate",
"variable",
"-",
"density",
"Poisson",
"-",
"disc",
"sampling",
"pattern",
"."
] | def poisson(img_shape, accel, calib=(0, 0), dtype=np.complex,
crop_corner=True, return_density=False, seed=0,
max_attempts=30, tol=0.1):
"""Generate variable-density Poisson-disc sampling pattern.
The function generates a variable density Poisson-disc sampling
mask with density proportional to :math:`1 / (1 + s |r|)`,
where :math:`r` represents the k-space radius, and :math:`s`
represents the slope. A binary search is performed on the slope :math:`s`
such that the resulting acceleration factor is close to the
prescribed acceleration factor `accel`. The parameter `tol`
determines how much they can deviate.
Args:
img_shape (tuple of ints): length-2 image shape.
accel (float): Target acceleration factor. Must be greater than 1.
calib (tuple of ints): length-2 calibration shape.
dtype (Dtype): data type.
crop_corner (bool): Toggle whether to crop sampling corners.
seed (int): Random seed.
max_attempts (float): maximum number of samples to reject in Poisson
disc calculation.
tol (float): Tolerance for how much the resulting acceleration can
deviate form `accel`.
Returns:
array: Poisson-disc sampling mask.
References:
Bridson, Robert. "Fast Poisson disk sampling in arbitrary dimensions."
SIGGRAPH sketches. 2007.
"""
if accel <= 1:
raise ValueError(f'accel must be greater than 1, got {accel}')
if seed is not None:
rand_state = np.random.get_state()
ny, nx = img_shape
y, x = np.mgrid[:ny, :nx]
x = np.maximum(abs(x - img_shape[-1] / 2) - calib[-1] / 2, 0)
x /= x.max()
y = np.maximum(abs(y - img_shape[-2] / 2) - calib[-2] / 2, 0)
y /= y.max()
r = np.sqrt(x**2 + y**2)
slope_max = max(nx, ny)
slope_min = 0
while slope_min < slope_max:
slope = (slope_max + slope_min) / 2
radius_x = np.clip((1 + r * slope) * nx / max(nx, ny), 1, None)
radius_y = np.clip((1 + r * slope) * ny / max(nx, ny), 1, None)
mask = _poisson(
img_shape[-1], img_shape[-2], max_attempts,
radius_x, radius_y, calib, seed)
if crop_corner:
mask *= r < 1
actual_accel = img_shape[-1] * img_shape[-2] / np.sum(mask)
if abs(actual_accel - accel) < tol:
break
if actual_accel < accel:
slope_min = slope
else:
slope_max = slope
if abs(actual_accel - accel) >= tol:
raise ValueError(f'Cannot generate mask to satisfy accel={accel}.')
mask = mask.reshape(img_shape).astype(dtype)
if seed is not None:
np.random.set_state(rand_state)
return mask | [
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zhang-can/ECO-pytorch | 355c3866b35cdaa5d451263c1f3291c150e22eeb | tf_model_zoo/models/im2txt/im2txt/show_and_tell_model.py | python | ShowAndTellModel.build_inputs | (self) | Input prefetching, preprocessing and batching.
Outputs:
self.images
self.input_seqs
self.target_seqs (training and eval only)
self.input_mask (training and eval only) | Input prefetching, preprocessing and batching. | [
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"."
] | def build_inputs(self):
"""Input prefetching, preprocessing and batching.
Outputs:
self.images
self.input_seqs
self.target_seqs (training and eval only)
self.input_mask (training and eval only)
"""
if self.mode == "inference":
# In inference mode, images and inputs are fed via placeholders.
image_feed = tf.placeholder(dtype=tf.string, shape=[], name="image_feed")
input_feed = tf.placeholder(dtype=tf.int64,
shape=[None], # batch_size
name="input_feed")
# Process image and insert batch dimensions.
images = tf.expand_dims(self.process_image(image_feed), 0)
input_seqs = tf.expand_dims(input_feed, 1)
# No target sequences or input mask in inference mode.
target_seqs = None
input_mask = None
else:
# Prefetch serialized SequenceExample protos.
input_queue = input_ops.prefetch_input_data(
self.reader,
self.config.input_file_pattern,
is_training=self.is_training(),
batch_size=self.config.batch_size,
values_per_shard=self.config.values_per_input_shard,
input_queue_capacity_factor=self.config.input_queue_capacity_factor,
num_reader_threads=self.config.num_input_reader_threads)
# Image processing and random distortion. Split across multiple threads
# with each thread applying a slightly different distortion.
assert self.config.num_preprocess_threads % 2 == 0
images_and_captions = []
for thread_id in range(self.config.num_preprocess_threads):
serialized_sequence_example = input_queue.dequeue()
encoded_image, caption = input_ops.parse_sequence_example(
serialized_sequence_example,
image_feature=self.config.image_feature_name,
caption_feature=self.config.caption_feature_name)
image = self.process_image(encoded_image, thread_id=thread_id)
images_and_captions.append([image, caption])
# Batch inputs.
queue_capacity = (2 * self.config.num_preprocess_threads *
self.config.batch_size)
images, input_seqs, target_seqs, input_mask = (
input_ops.batch_with_dynamic_pad(images_and_captions,
batch_size=self.config.batch_size,
queue_capacity=queue_capacity))
self.images = images
self.input_seqs = input_seqs
self.target_seqs = target_seqs
self.input_mask = input_mask | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/sympy/polys/rings.py | python | PolyElement.diff | (f, x) | return g | Computes partial derivative in ``x``.
Examples
========
>>> from sympy.polys.rings import ring
>>> from sympy.polys.domains import ZZ
>>> _, x, y = ring("x,y", ZZ)
>>> p = x + x**2*y**3
>>> p.diff(x)
2*x*y**3 + 1 | Computes partial derivative in ``x``. | [
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"."
] | def diff(f, x):
"""Computes partial derivative in ``x``.
Examples
========
>>> from sympy.polys.rings import ring
>>> from sympy.polys.domains import ZZ
>>> _, x, y = ring("x,y", ZZ)
>>> p = x + x**2*y**3
>>> p.diff(x)
2*x*y**3 + 1
"""
ring = f.ring
i = ring.index(x)
m = ring.monomial_basis(i)
g = ring.zero
for expv, coeff in f.iterterms():
if expv[i]:
e = ring.monomial_ldiv(expv, m)
g[e] = ring.domain_new(coeff*expv[i])
return g | [
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researchmm/SiamDW | c82b0599920e1fbd67ada9271aa4a63405e2d316 | lib/models/modules.py | python | ResNet._make_layer | (self, block, planes, blocks, last_relu, stride=1, stride2pool=False, dilation=1) | return nn.Sequential(*layers) | :param block:
:param planes:
:param blocks:
:param stride:
:param stride2pool: translate (3,2) conv to (3, 1)conv + (2, 2)pool
:return: | :param block:
:param planes:
:param blocks:
:param stride:
:param stride2pool: translate (3,2) conv to (3, 1)conv + (2, 2)pool
:return: | [
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:param blocks:
:param stride:
:param stride2pool: translate (3,2) conv to (3, 1)conv + (2, 2)pool
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"""
downsample = None
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layers = []
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layers.append(self.maxpool)
self.inplanes = planes * block.expansion
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if i == blocks - 1:
layers.append(block(self.inplanes, planes, last_relu=last_relu, dilation=dilation))
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layers.append(block(self.inplanes, planes, last_relu=True, dilation=dilation))
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lunixbochs/ActualVim | 1f555ce719e49d6584f0e35e9f0db2f216b98fa5 | lib/neovim/msgpack_rpc/session.py | python | Session.threadsafe_call | (self, fn, *args, **kwargs) | Wrapper around `AsyncSession.threadsafe_call`. | Wrapper around `AsyncSession.threadsafe_call`. | [
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self.async_dispatch(fn, *args, **kwargs)
self._async_session.threadsafe_call(async_wrapper) | [
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ranaroussi/quantstats | 6aaa65c20bad4c364efa7623375901925c036b45 | quantstats/stats.py | python | sortino | (returns, rf=0, periods=252, annualize=True, smart=False) | return res | Calculates the sortino ratio of access returns
If rf is non-zero, you must specify periods.
In this case, rf is assumed to be expressed in yearly (annualized) terms
Calculation is based on this paper by Red Rock Capital
http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf | Calculates the sortino ratio of access returns | [
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"the",
"sortino",
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"of",
"access",
"returns"
] | def sortino(returns, rf=0, periods=252, annualize=True, smart=False):
"""
Calculates the sortino ratio of access returns
If rf is non-zero, you must specify periods.
In this case, rf is assumed to be expressed in yearly (annualized) terms
Calculation is based on this paper by Red Rock Capital
http://www.redrockcapital.com/Sortino__A__Sharper__Ratio_Red_Rock_Capital.pdf
"""
if rf != 0 and periods is None:
raise Exception('Must provide periods if rf != 0')
returns = _utils._prepare_returns(returns, rf, periods)
downside = _np.sqrt((returns[returns < 0] ** 2).sum() / len(returns))
if smart:
# penalize sortino with auto correlation
downside = downside * autocorr_penalty(returns)
res = returns.mean() / downside
if annualize:
return res * _np.sqrt(
1 if periods is None else periods)
return res | [
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ninthDevilHAUNSTER/ArknightsAutoHelper | a27a930502d6e432368d9f62595a1d69a992f4e6 | vendor/penguin_client/penguin_client/models/exist_conditions.py | python | ExistConditions.to_str | (self) | return pprint.pformat(self.to_dict()) | Returns the string representation of the model | Returns the string representation of the model | [
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tomoncle/Python-notes | ce675486290c3d1c7c2e4890b57e3d0c8a1228cc | skills/httpserver.py | python | simple_app | (environ, start_response) | return ['Hello world!\n'] | [] | def simple_app(environ, start_response):
status = '200 OK'
response_headers = [('Content-type', 'text/plain')]
start_response(status, response_headers)
# print environ, start_response
return ['Hello world!\n'] | [
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mesonbuild/meson | a22d0f9a0a787df70ce79b05d0c45de90a970048 | mesonbuild/compilers/c.py | python | GnuCCompiler.get_pch_use_args | (self, pch_dir: str, header: str) | return ['-fpch-preprocess', '-include', os.path.basename(header)] | [] | def get_pch_use_args(self, pch_dir: str, header: str) -> T.List[str]:
return ['-fpch-preprocess', '-include', os.path.basename(header)] | [
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mjwestcott/Goodrich | dc2516591bd28488516c0337a62e64248debe47c | ch14/graph_examples.py | python | graph_from_edgelist | (E, directed=False) | return g | Make a graph instance based on a sequence of edge tuples.
Edges can be either of from (origin,destination) or
(origin,destination,element). Vertex set is presume to be those
incident to at least one edge.
vertex labels are assumed to be hashable. | Make a graph instance based on a sequence of edge tuples. | [
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Edges can be either of from (origin,destination) or
(origin,destination,element). Vertex set is presume to be those
incident to at least one edge.
vertex labels are assumed to be hashable.
"""
g = Graph(directed)
V = set()
for e in E:
V.add(e[0])
V.add(e[1])
verts = {} # map from vertex label to Vertex instance
for v in V:
verts[v] = g.insert_vertex(v)
for e in E:
src = e[0]
dest = e[1]
element = e[2] if len(e) > 2 else None
g.insert_edge(verts[src],verts[dest],element)
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baidu/Senta | e5294c00a6ffc4b1284f38000f0fbf24d6554c22 | senta/data/data_set_reader/roberta_pretrain_dataset_reader_en.py | python | RobertaPretrainDataReaderEnglish.create_reader | (self) | return py_reader | 初始化paddle_py_reader，必须要初始化，否则会抛出异常
create reader 定义的这些 dtypes 要和 prepare_batch_data 一一对应
:return: | 初始化paddle_py_reader，必须要初始化，否则会抛出异常
create reader 定义的这些 dtypes 要和 prepare_batch_data 一一对应
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""" 初始化paddle_py_reader，必须要初始化，否则会抛出异常
create reader 定义的这些 dtypes 要和 prepare_batch_data 一一对应
:return:
"""
py_reader = fluid.layers.py_reader(
capacity=70,
shapes=[f.shape for f in self.data_types.values()],
dtypes=[f.dtype for f in self.data_types.values()],
lod_levels=[f.lod_level for f in self.data_types.values()],
name=self.pyreader_name,
use_double_buffer=True)
self.paddle_py_reader = py_reader
self.fields_dict_ = collections.OrderedDict()
input_placeholders = fluid.layers.read_file(py_reader)
assert len(input_placeholders) == len(self.data_types)
for op, (name, _) in zip(input_placeholders, self.data_types.items()):
self.fields_dict_[name] = op
return py_reader | [
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hzlzh/AlfredWorkflow.com | 7055f14f6922c80ea5943839eb0caff11ae57255 | Sources/Workflows/nuomituangou/alp/request/bs4/element.py | python | Tag.decode | (self, indent_level=None,
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formatter="minimal") | return s | Returns a Unicode representation of this tag and its contents.
:param eventual_encoding: The tag is destined to be
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formatter="minimal"):
"""Returns a Unicode representation of this tag and its contents.
:param eventual_encoding: The tag is destined to be
encoded into this encoding. This method is _not_
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"""
attrs = []
if self.attrs:
for key, val in sorted(self.attrs.items()):
if val is None:
decoded = key
else:
if isinstance(val, list) or isinstance(val, tuple):
val = ' '.join(val)
elif not isinstance(val, basestring):
val = unicode(val)
elif (
isinstance(val, AttributeValueWithCharsetSubstitution)
and eventual_encoding is not None):
val = val.encode(eventual_encoding)
text = self.format_string(val, formatter)
decoded = (
unicode(key) + '='
+ EntitySubstitution.quoted_attribute_value(text))
attrs.append(decoded)
close = ''
closeTag = ''
prefix = ''
if self.prefix:
prefix = self.prefix + ":"
if self.is_empty_element:
close = '/'
else:
closeTag = '</%s%s>' % (prefix, self.name)
pretty_print = (indent_level is not None)
if pretty_print:
space = (' ' * (indent_level - 1))
indent_contents = indent_level + 1
else:
space = ''
indent_contents = None
contents = self.decode_contents(
indent_contents, eventual_encoding, formatter)
if self.hidden:
# This is the 'document root' object.
s = contents
else:
s = []
attribute_string = ''
if attrs:
attribute_string = ' ' + ' '.join(attrs)
if pretty_print:
s.append(space)
s.append('<%s%s%s%s>' % (
prefix, self.name, attribute_string, close))
if pretty_print:
s.append("\n")
s.append(contents)
if pretty_print and contents and contents[-1] != "\n":
s.append("\n")
if pretty_print and closeTag:
s.append(space)
s.append(closeTag)
if pretty_print and closeTag and self.next_sibling:
s.append("\n")
s = ''.join(s)
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log2timeline/plaso | fe2e316b8c76a0141760c0f2f181d84acb83abc2 | plaso/filters/parser_filter.py | python | ParserFilterExpressionHelper._ExpandPresets | (self, presets_manager, preset_names, parsers_and_plugins) | Expands the presets in the parsers and plugins.
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and plugin or preset names defined by the presets.
Args:
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preset_names (set[str]): names of the presets defined by the presets
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parsers_and_plugins (dict[str, set[str]]): parsers, plugins and presets.
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for preset_name in preset_names:
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vrenkens/tfkaldi | 30e8f7a32582a82a58cea66c2c52bcb66c06c326 | neuralNetworks/trainer.py | python | Trainer.save_model | (self, filename) | Save the model
Args:
filename: path to the model file | Save the model | [
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] | def save_model(self, filename):
'''
Save the model
Args:
filename: path to the model file
'''
self.modelsaver.save(tf.get_default_session(), filename) | [
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oracle/oci-python-sdk | 3c1604e4e212008fb6718e2f68cdb5ef71fd5793 | src/oci/_vendor/urllib3/util/ssltransport.py | python | SSLTransport.recv_into | (self, buffer, nbytes=None, flags=0) | return self.read(nbytes, buffer) | [] | def recv_into(self, buffer, nbytes=None, flags=0):
if flags != 0:
raise ValueError("non-zero flags not allowed in calls to recv_into")
if buffer and (nbytes is None):
nbytes = len(buffer)
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kedro-org/kedro | e78990c6b606a27830f0d502afa0f639c0830950 | features/steps/cli_steps.py | python | commit_changes_to_git | (context) | Commit changes to git | Commit changes to git | [
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"""Commit changes to git"""
with util.chdir(context.root_project_dir):
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missionpinball/mpf | 8e6b74cff4ba06d2fec9445742559c1068b88582 | mpf/core/config_loader.py | python | ConfigLoader.load_mpf_config | (self) | Load and return a MPF config. | Load and return a MPF config. | [
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zhl2008/awd-platform | 0416b31abea29743387b10b3914581fbe8e7da5e | web_hxb2/lib/python3.5/site-packages/pip/_vendor/distlib/util.py | python | is_string_sequence | (seq) | return result | [] | def is_string_sequence(seq):
result = True
i = None
for i, s in enumerate(seq):
if not isinstance(s, string_types):
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OpenShot/openshot-qt | bbd2dd040a4e2a6120791e6c65ae0ddf212cb73d | src/classes/ui_util.py | python | get_icon | (theme_name) | return None | Get either the current theme icon or fallback to default theme (for custom icons). Returns None if none
found or empty name. | Get either the current theme icon or fallback to default theme (for custom icons). Returns None if none
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if theme_name:
has_icon = QIcon.hasThemeIcon(theme_name)
fallback_icon, fallback_path = get_default_icon(theme_name)
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tensorflow/datasets | 2e496976d7d45550508395fb2f35cf958c8a3414 | tensorflow_datasets/scripts/documentation/dataset_markdown_builder.py | python | Section.display | (self, builder: tfds.core.DatasetBuilder) | return content | Returns the section content. | Returns the section content. | [
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header = f'* **{self.NAME}**{self.EXTRA_DOC}'
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oanda/v20-python | f28192f4a31bce038cf6dfa302f5878bec192fe5 | src/v20/transaction.py | python | DelayedTradeClosureTransaction.__init__ | (self, **kwargs) | Create a new DelayedTradeClosureTransaction instance | Create a new DelayedTradeClosureTransaction instance | [
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"""
Create a new DelayedTradeClosureTransaction instance
"""
super(DelayedTradeClosureTransaction, self).__init__()
#
# The Transaction's Identifier.
#
self.id = kwargs.get("id")
#
# The date/time when the Transaction was created.
#
self.time = kwargs.get("time")
#
# The ID of the user that initiated the creation of the Transaction.
#
self.userID = kwargs.get("userID")
#
# The ID of the Account the Transaction was created for.
#
self.accountID = kwargs.get("accountID")
#
# The ID of the "batch" that the Transaction belongs to. Transactions
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#
self.batchID = kwargs.get("batchID")
#
# The Request ID of the request which generated the transaction.
#
self.requestID = kwargs.get("requestID")
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self.type = kwargs.get("type", "DELAYED_TRADE_CLOSURE")
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# The reason for the delayed trade closure
#
self.reason = kwargs.get("reason")
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#
self.tradeIDs = kwargs.get("tradeIDs") | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-linux/x64/PIL/TiffImagePlugin.py | python | AppendingTiffWriter.__enter__ | (self) | return self | [] | def __enter__(self):
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pypa/pip | 7f8a6844037fb7255cfd0d34ff8e8cf44f2598d4 | src/pip/_vendor/html5lib/_inputstream.py | python | EncodingBytes.skip | (self, chars=spaceCharactersBytes) | return None | Skip past a list of characters | Skip past a list of characters | [
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modin-project/modin | 0d9d14e6669be3dd6bb3b72222dbe6a6dffe1bee | modin/core/dataframe/pandas/dataframe/dataframe.py | python | PandasDataframe.map | (self, func, dtypes=None) | return self.__constructor__(
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dtypes : dtypes of the result, default: None
The data types for the result. This is an optimization
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Perform a function that maps across the entire dataset.
Parameters
----------
func : callable
The function to apply.
dtypes : dtypes of the result, default: None
The data types for the result. This is an optimization
because there are functions that always result in a particular data
type, and this allows us to avoid (re)computing it.
Returns
-------
PandasDataframe
A new dataframe.
"""
new_partitions = self._partition_mgr_cls.map_partitions(self._partitions, func)
if dtypes == "copy":
dtypes = self._dtypes
elif dtypes is not None:
dtypes = pandas.Series(
[np.dtype(dtypes)] * len(self.columns), index=self.columns
)
return self.__constructor__(
new_partitions,
self.axes[0],
self.axes[1],
self._row_lengths_cache,
self._column_widths_cache,
dtypes=dtypes,
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qiucheng025/zao- | 3a5edf3607b3a523f95746bc69b688090c76d89a | plugins/train/model/realface.py | python | Model.add_networks | (self) | Add the realface model weights | Add the realface model weights | [
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logger.debug("Adding networks")
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self.add_network("decoder", "b", self.decoder_b(), is_output=True)
self.add_network("encoder", None, self.encoder())
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cannatag/ldap3 | 040e09fe37cf06801960d494dfadf0a6ed94e38f | setup-binary.py | python | BuildWheels.initialize_options | (self) | Abstract method that is required to be overwritten | Abstract method that is required to be overwritten | [
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tosher/Mediawiker | 81bf97cace59bedcb1668e7830b85c36e014428e | mwcommands/mw_category_list.py | python | MediawikerCategoryListCommand.get_category_current | (self) | return self.category_path[-1] | return current category name in format Category:CategoryName | return current category name in format Category:CategoryName | [
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sfepy/sfepy | 02ec7bb2ab39ee1dfe1eb4cd509f0ffb7dcc8b25 | sfepy/discrete/fem/fields_base.py | python | FEField.restore_substituted | (self, vec) | return vec.ravel() | Restore values of the unused DOFs using the transpose of the applied
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windelbouwman/ppci | 915c069e0667042c085ec42c78e9e3c9a5295324 | ppci/format/hexfile.py | python | HexLine.to_line | (self) | return line | Create an ascii hex line | Create an ascii hex line | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/mpmath/math2.py | python | erf | (x) | return _erf_taylor(x) | erf of a real number. | erf of a real number. | [
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"""
erf of a real number.
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if x >= 1.0:
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return 1.0 - _erfc_mid(x)
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hacktoolspack/hack-tools | c2b1e324f4b24a2c5b4f111e7ef84e9c547159c2 | BruteXSS/mechanize/_form.py | python | Control.pairs | (self) | return [(k, v) for (i, k, v) in self._totally_ordered_pairs()] | Return list of (key, value) pairs suitable for passing to urlencode. | Return list of (key, value) pairs suitable for passing to urlencode. | [
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jliljebl/flowblade | 995313a509b80e99eb1ad550d945bdda5995093b | flowblade-trunk/Flowblade/rendergui.py | python | RenderArgsPanelSmall.open_edit_window | (self) | [] | def open_edit_window(self):
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ckan/ckan | b3b01218ad88ed3fb914b51018abe8b07b07bff3 | ckan/views/util.py | python | internal_redirect | () | u''' Redirect to the url parameter.
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home-assistant/supervisor | 69c2517d5211b483fdfe968b0a2b36b672ee7ab2 | supervisor/updater.py | python | Updater.version_multicast | (self) | return self._data.get(ATTR_MULTICAST) | Return latest version of Multicast. | Return latest version of Multicast. | [
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viniciuschiele/flask-apscheduler | 5f878c41417824a4f37b353cb4b22973a81746f2 | flask_apscheduler/utils.py | python | pop_trigger | (data) | return trigger_name, trigger_args | Pops trigger and trigger args from a given dict. | Pops trigger and trigger args from a given dict. | [
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trigger_name = data.pop('trigger')
trigger_args = {}
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trigger_arg_names = ('run_date', 'timezone')
elif trigger_name == 'interval':
trigger_arg_names = ('weeks', 'days', 'hours', 'minutes', 'seconds', 'start_date', 'end_date', 'timezone')
elif trigger_name == 'cron':
trigger_arg_names = ('year', 'month', 'day', 'week', 'day_of_week', 'hour', 'minute', 'second', 'start_date', 'end_date', 'timezone')
else:
raise Exception('Trigger %s is not supported.' % trigger_name)
for arg_name in trigger_arg_names:
if arg_name in data:
trigger_args[arg_name] = data.pop(arg_name)
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pytorch/benchmark | 5c93a5389563a5b6ccfa17d265d60f4fe7272f31 | torchbenchmark/models/pytorch_stargan/data_loader.py | python | CelebA.__init__ | (self, image_dir, attr_path, selected_attrs, transform, mode) | Initialize and preprocess the CelebA dataset. | Initialize and preprocess the CelebA dataset. | [
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vaidik/sherlock | c56a87e987e561850d2fbe8534aa69d9dd397e24 | sherlock/__init__.py | python | _Configuration.update | (self, **kwargs) | Update configuration. Provide keyword arguments where the keyword
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Blizzard/s2protocol | 4bfe857bb832eee12cc6307dd699e3b74bd7e1b2 | s2protocol/versions/protocol63454.py | python | decode_replay_tracker_events | (contents) | Decodes and yields each tracker event from the contents byte string. | Decodes and yields each tracker event from the contents byte string. | [
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holzschu/Carnets | 44effb10ddfc6aa5c8b0687582a724ba82c6b547 | Library/lib/python3.7/site-packages/lxml-4.4.2-py3.7-macosx-10.9-x86_64.egg/lxml/html/__init__.py | python | Classes.remove | (self, value) | Remove a class; it must currently be present.
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mozillazg/pypy | 2ff5cd960c075c991389f842c6d59e71cf0cb7d0 | pypy/module/cpyext/unicodeobject.py | python | PyUnicode_Replace | (space, w_str, w_substr, w_replstr, maxcount) | return space.call_method(w_str, "replace", w_substr, w_replstr,
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cloudera/hue | 23f02102d4547c17c32bd5ea0eb24e9eadd657a4 | desktop/libs/liboozie/src/liboozie/oozie_api.py | python | OozieApi.submit_job | (self, properties=None) | return resp['id'] | submit_job(properties=None, id=None) -> jobid
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"""
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Raise RestException on error.
"""
defaults = {
'user.name': self.user,
}
if properties is not None:
defaults.update(properties)
properties = defaults
params = self._get_params()
resp = self._root.post('jobs', params, data=config_gen(properties), contenttype=_XML_CONTENT_TYPE)
return resp['id'] | [
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guildai/guildai | 1665985a3d4d788efc1a3180ca51cc417f71ca78 | guild/external/pip/_vendor/urllib3/util/ssl_.py | python | create_urllib3_context | (ssl_version=None, cert_reqs=None,
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By default, this function does a lot of the same work that
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- Disables SSLv2, SSLv3, and compression
- Sets a restricted set of server ciphers
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context = ssl_.create_urllib3_context()
context.options &= ~ssl_.OP_NO_SSLv3
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Whether to require the certificate verification. This defaults to
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Specific OpenSSL options. These default to ``ssl.OP_NO_SSLv2``,
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:param ciphers:
Which cipher suites to allow the server to select.
:returns:
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"""All arguments have the same meaning as ``ssl_wrap_socket``.
By default, this function does a lot of the same work that
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from pip._vendor.urllib3.util import ssl_
context = ssl_.create_urllib3_context()
context.options &= ~ssl_.OP_NO_SSLv3
You can do the same to enable compression (substituting ``COMPRESSION``
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:param ciphers:
Which cipher suites to allow the server to select.
:returns:
Constructed SSLContext object with specified options
:rtype: SSLContext
"""
context = SSLContext(ssl_version or ssl.PROTOCOL_SSLv23)
# Setting the default here, as we may have no ssl module on import
cert_reqs = ssl.CERT_REQUIRED if cert_reqs is None else cert_reqs
if options is None:
options = 0
# SSLv2 is easily broken and is considered harmful and dangerous
options |= OP_NO_SSLv2
# SSLv3 has several problems and is now dangerous
options |= OP_NO_SSLv3
# Disable compression to prevent CRIME attacks for OpenSSL 1.0+
# (issue #309)
options |= OP_NO_COMPRESSION
context.options |= options
if getattr(context, 'supports_set_ciphers', True): # Platform-specific: Python 2.6
context.set_ciphers(ciphers or DEFAULT_CIPHERS)
context.verify_mode = cert_reqs
if getattr(context, 'check_hostname', None) is not None: # Platform-specific: Python 3.2
# We do our own verification, including fingerprints and alternative
# hostnames. So disable it here
context.check_hostname = False
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Azure/azure-linux-extensions | a42ef718c746abab2b3c6a21da87b29e76364558 | Common/libpsutil/py2.6-glibc-2.12-pre/psutil/_psbsd.py | python | cpu_count_logical | () | return cext.cpu_count_logical() | Return the number of logical CPUs in the system. | Return the number of logical CPUs in the system. | [
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TencentCloud/tencentcloud-sdk-python | 3677fd1cdc8c5fd626ce001c13fd3b59d1f279d2 | tencentcloud/bmeip/v20180625/models.py | python | EipAclRule.__init__ | (self) | r"""
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:type Port: str
:param Protocol: 协议(TCP/UDP/ICMP/ANY)
:type Protocol: str
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:type Action: str
:param Description: 备注
:type Description: str | r"""
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lovelylain/pyctp | fd304de4b50c4ddc31a4190b1caaeb5dec66bc5d | futures/ctp/ApiStruct.py | python | ForQuote.__init__ | (self, BrokerID='', InvestorID='', InstrumentID='', ForQuoteRef='', UserID='', ForQuoteLocalID='', ExchangeID='', ParticipantID='', ClientID='', ExchangeInstID='', TraderID='', InstallID=0, InsertDate='', InsertTime='', ForQuoteStatus=FQST_Submitted, FrontID=0, SessionID=0, StatusMsg='', ActiveUserID='', BrokerForQutoSeq=0) | [] | def __init__(self, BrokerID='', InvestorID='', InstrumentID='', ForQuoteRef='', UserID='', ForQuoteLocalID='', ExchangeID='', ParticipantID='', ClientID='', ExchangeInstID='', TraderID='', InstallID=0, InsertDate='', InsertTime='', ForQuoteStatus=FQST_Submitted, FrontID=0, SessionID=0, StatusMsg='', ActiveUserID='', BrokerForQutoSeq=0):
self.BrokerID = '' #经纪公司代码, char[11]
self.InvestorID = '' #投资者代码, char[13]
self.InstrumentID = '' #合约代码, char[31]
self.ForQuoteRef = 'OrderRef' #询价引用, char[13]
self.UserID = '' #用户代码, char[16]
self.ForQuoteLocalID = 'OrderLocalID' #本地询价编号, char[13]
self.ExchangeID = '' #交易所代码, char[9]
self.ParticipantID = '' #会员代码, char[11]
self.ClientID = '' #客户代码, char[11]
self.ExchangeInstID = '' #合约在交易所的代码, char[31]
self.TraderID = '' #交易所交易员代码, char[21]
self.InstallID = '' #安装编号, int
self.InsertDate = 'Date' #报单日期, char[9]
self.InsertTime = 'Time' #插入时间, char[9]
self.ForQuoteStatus = '' #询价状态, char
self.FrontID = '' #前置编号, int
self.SessionID = '' #会话编号, int
self.StatusMsg = 'ErrorMsg' #状态信息, char[81]
self.ActiveUserID = 'UserID' #操作用户代码, char[16]
self.BrokerForQutoSeq = 'SequenceNo' | [
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seppius-xbmc-repo/ru | d0879d56ec8243b2c7af44fda5cf3d1ff77fd2e2 | plugin.audio.tracksflow/resources/lib/tracksflow/api.py | python | TracksFlow.getTopPlaylists | (self, pagenum = 0, pagesize = 25, days = 1) | return json.loads(data) | [] | def getTopPlaylists(self, pagenum = 0, pagesize = 25, days = 1):
data = self.GET('top_playlists', {
'pagesize': pagesize,
'pagenum': pagenum,
'days': days
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Anaconda-Platform/anaconda-project | df5ec33c12591e6512436d38d36c6132fa2e9618 | anaconda_project/prepare.py | python | PrepareResult.__nonzero__ | (self) | return self.__bool__() | True if we were successful. | True if we were successful. | [
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okfn-brasil/serenata-de-amor | 9e76e2e887802ff7e25f37000611af0bd1f6bd22 | research/src/fetch_sex_places.py | python | fetch_place | (company, output, semaphore) | Gets a company (dict), finds the closest place nearby and write the result
to a CSV file. | Gets a company (dict), finds the closest place nearby and write the result
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"""
Gets a company (dict), finds the closest place nearby and write the result
to a CSV file.
"""
with (await semaphore):
places = SexPlacesNearBy(company)
await places.get_closest()
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airspeed-velocity/asv | 9d5af5713357ccea00a518758fae6822cc69f539 | asv/extern/asizeof.py | python | _len_bytearray | (obj) | return obj.__alloc__() | Bytearray size. | Bytearray size. | [
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sqall01/alertR | e1d1a83e54f876cc4cd7bd87387e05cb75d4dc13 | alertClientTemplate/lib/client/watchdog.py | python | ConnectionWatchdog.run | (self) | Connection watchdog loop that checks the communication channel to the server.
:return: | Connection watchdog loop that checks the communication channel to the server.
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"""
Connection watchdog loop that checks the communication channel to the server.
:return:
"""
# check every 5 seconds if the client is still connected
# and the time of the last received data
# from the server lies too far in the past
while True:
# wait 5 seconds before checking time of last received data
for i in range(5):
if self._exit_flag:
logging.info("[%s]: Exiting Connection Watchdog." % self._log_tag)
return
time.sleep(1)
utc_timestamp = int(time.time())
# Connect to server if communication channel is not connected anymore.
if not self._connection.is_connected:
logging.error("[%s]: Connection to server has died. " % self._log_tag)
# Reconnect to the server.
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# => send eMail alert
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# => send email that communication problems are solved
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logging.error("[%s]: Reconnecting failed. Retrying in 5 seconds." % self._log_tag)
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elif (utc_timestamp - self._connection.last_communication) > self._ping_interval:
logging.debug("[%s]: Ping interval exceeded." % self._log_tag)
# check if PING failed
promise = self._connection.send_ping() # type: Promise
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# get a deadlock in which we do not re-connect to the server anymore).
is_finished = False
for _ in range(self._ping_delay_warning):
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is_finished = True
break
time.sleep(1)
if is_finished:
if not promise.was_successful():
logging.error("[%s]: Connection to server has died." % self._log_tag)
else:
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nipy/nipype | cd4c34d935a43812d1756482fdc4034844e485b8 | nipype/pipeline/engine/utils.py | python | _transpose_iterables | (fields, values) | return list(
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rspeer/langcodes | 49beea8e20ae26c2dead7bd77f41cfba0e0ab533 | langcodes/tag_parser.py | python | _is_ascii | (s) | Determine whether a tag consists of ASCII characters. | Determine whether a tag consists of ASCII characters. | [
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Determine whether a tag consists of ASCII characters.
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try:
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return True
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mongodb-labs/edda | 5acaf9918d9aae6a6acbbfe48741d8a20aae1f21 | edda/filters/init_and_listen.py | python | starting_up | (msg, doc) | return doc | Generate a document for a server startup event. | Generate a document for a server startup event. | [
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doc["info"]["subtype"] = "startup"
# what type of server is this?
if ('MongoS' in msg) or ('mongos' in msg):
doc["info"]["type"] = "mongos"
# mongos startup does not provide an address
doc["info"]["addr"] = "unknown"
LOGGER.debug("Returning mongos startup doc")
return doc
elif msg.find("MongoDB") > -1:
doc["info"]["type"] = "mongod"
# isolate port number
m = PORT_NUMBER.search(msg)
if m is None:
LOGGER.debug("malformed starting_up message: no port number found")
return None
port = m.group(0)[5:]
host = msg[msg.find("host=") + 5:].split()[0]
addr = host + ":" + port
addr = addr.replace('\n', "")
addr = addr.replace(" ", "")
doc["info"]["addr"] = addr
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IronLanguages/main | a949455434b1fda8c783289e897e78a9a0caabb5 | External.LCA_RESTRICTED/Languages/IronPython/repackage/pip/pip/_vendor/ipaddress.py | python | IPv4Address.is_private | (self) | return any(self in net for net in self._constants._private_networks) | Test if this address is allocated for private networks.
Returns:
A boolean, True if the address is reserved per
iana-ipv4-special-registry. | Test if this address is allocated for private networks. | [
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] | def is_private(self):
"""Test if this address is allocated for private networks.
Returns:
A boolean, True if the address is reserved per
iana-ipv4-special-registry.
"""
return any(self in net for net in self._constants._private_networks) | [
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Nitrate/Nitrate | 7eacef697a15dcbb7ae90c8a1dbf769cba6d1bb1 | src/tcms/xmlrpc/api/product.py | python | filter_categories | (request, query) | return TestCaseCategory.to_xmlrpc(query) | Performs a search and returns the resulting list of categories.
:param dict query: a mapping containing following criteria.
* id: (int) category ID.
* name: (str) category name.
* product: ForeignKey: :class:`Product`.
* description: (str) category description.
:return: a mapping representing found category.
:rtype: dict
Example::
# Get all of categories named like 'libvirt'
Product.filter_categories({'name__icontains': 'regression'})
# Get all of categories named in product 'product name'
Product.filter_categories({'product__name': 'product name'}) | Performs a search and returns the resulting list of categories. | [
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"""Performs a search and returns the resulting list of categories.
:param dict query: a mapping containing following criteria.
* id: (int) category ID.
* name: (str) category name.
* product: ForeignKey: :class:`Product`.
* description: (str) category description.
:return: a mapping representing found category.
:rtype: dict
Example::
# Get all of categories named like 'libvirt'
Product.filter_categories({'name__icontains': 'regression'})
# Get all of categories named in product 'product name'
Product.filter_categories({'product__name': 'product name'})
"""
from tcms.testcases.models import TestCaseCategory
return TestCaseCategory.to_xmlrpc(query) | [
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pypa/setuptools | 9f37366aab9cd8f6baa23e6a77cfdb8daf97757e | setuptools/_vendor/more_itertools/recipes.py | python | dotproduct | (vec1, vec2) | return sum(map(operator.mul, vec1, vec2)) | Returns the dot product of the two iterables.
>>> dotproduct([10, 10], [20, 20])
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"""Returns the dot product of the two iterables.
>>> dotproduct([10, 10], [20, 20])
400
"""
return sum(map(operator.mul, vec1, vec2)) | [
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FederatedAI/FATE | 32540492623568ecd1afcb367360133616e02fa3 | examples/pipeline/hetero_sbt/pipeline-hetero-sbt-regression-multi-host.py | python | main | (config="../../config.yaml", namespace="") | [] | def main(config="../../config.yaml", namespace=""):
# obtain config
if isinstance(config, str):
config = load_job_config(config)
parties = config.parties
guest = parties.guest[0]
hosts = parties.host
# data sets
guest_train_data = {"name": "motor_hetero_guest", "namespace": f"experiment{namespace}"}
host_train_data_0 = {"name": "motor_hetero_host_1", "namespace": f"experiment{namespace}"}
host_train_data_1 = {"name": "motor_hetero_host_2", "namespace": f"experiment{namespace}"}
guest_validate_data = {"name": "motor_hetero_guest", "namespace": f"experiment{namespace}"}
host_validate_data_0 = {"name": "motor_hetero_host_1", "namespace": f"experiment{namespace}"}
host_validate_data_1 = {"name": "motor_hetero_host_2", "namespace": f"experiment{namespace}"}
# init pipeline
pipeline = PipeLine().set_initiator(role="guest", party_id=guest).set_roles(guest=guest, host=hosts,)
# set data reader and data-io
reader_0, reader_1 = Reader(name="reader_0"), Reader(name="reader_1")
reader_0.get_party_instance(role="guest", party_id=guest).component_param(table=guest_train_data)
reader_0.get_party_instance(role="host", party_id=hosts[0]).component_param(table=host_train_data_0)
reader_0.get_party_instance(role="host", party_id=hosts[1]).component_param(table=host_train_data_1)
reader_1.get_party_instance(role="guest", party_id=guest).component_param(table=guest_validate_data)
reader_1.get_party_instance(role="host", party_id=hosts[0]).component_param(table=host_validate_data_0)
reader_1.get_party_instance(role="host", party_id=hosts[1]).component_param(table=host_validate_data_1)
data_transform_0, data_transform_1 = DataTransform(name="data_transform_0"), DataTransform(name="data_transform_1")
data_transform_0.get_party_instance(role="guest", party_id=guest).component_param(with_label=True, output_format="dense",
label_name='motor_speed', label_type="float")
data_transform_0.get_party_instance(role="host", party_id=hosts[0]).component_param(with_label=False)
data_transform_0.get_party_instance(role="host", party_id=hosts[1]).component_param(with_label=False)
data_transform_1.get_party_instance(role="guest", party_id=guest).component_param(with_label=True, output_format="dense",
label_name="motor_speed", label_type="float")
data_transform_1.get_party_instance(role="host", party_id=hosts[0]).component_param(with_label=False)
data_transform_1.get_party_instance(role="host", party_id=hosts[1]).component_param(with_label=False)
# data intersect component
intersect_0 = Intersection(name="intersection_0")
intersect_1 = Intersection(name="intersection_1")
# secure boost component
hetero_secure_boost_0 = HeteroSecureBoost(name="hetero_secure_boost_0",
num_trees=3,
task_type="regression",
objective_param={"objective": "lse"},
encrypt_param={"method": "iterativeAffine"},
tree_param={"max_depth": 3},
validation_freqs=1)
# evaluation component
evaluation_0 = Evaluation(name="evaluation_0", eval_type="regression")
pipeline.add_component(reader_0)
pipeline.add_component(reader_1)
pipeline.add_component(data_transform_0, data=Data(data=reader_0.output.data))
pipeline.add_component(data_transform_1, data=Data(data=reader_1.output.data), model=Model(data_transform_0.output.model))
pipeline.add_component(intersect_0, data=Data(data=data_transform_0.output.data))
pipeline.add_component(intersect_1, data=Data(data=data_transform_1.output.data))
pipeline.add_component(hetero_secure_boost_0, data=Data(train_data=intersect_0.output.data,
validate_data=intersect_1.output.data))
pipeline.add_component(evaluation_0, data=Data(data=hetero_secure_boost_0.output.data))
pipeline.compile()
pipeline.fit()
print("fitting hetero secureboost done, result:")
print(pipeline.get_component("hetero_secure_boost_0").get_summary()) | [
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fluentpython/example-code-2e | 80f7f84274a47579e59c29a4657691525152c9d5 | 13-protocol-abc/tombola_subhook.py | python | Tombola.__subclasshook__ | (cls, other_cls) | return NotImplemented | [] | def __subclasshook__(cls, other_cls):
if cls is Tombola:
interface_names = function_names(cls)
found_names = set()
for a_cls in other_cls.__mro__:
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aws-cloudformation/cfn-lint | 16df5d0ca0d8ebcf9330ebea701e83d883b47217 | src/cfnlint/rules/resources/iam/Permissions.py | python | Permissions.match_resource_properties | (self, properties, resourcetype, path, cfn) | return matches | Check CloudFormation Properties | Check CloudFormation Properties | [
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] | def match_resource_properties(self, properties, resourcetype, path, cfn):
"""Check CloudFormation Properties"""
matches = []
key = self.IAM_PERMISSION_RESOURCE_TYPES.get(resourcetype)
for key, value in properties.items():
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for index, policy in enumerate(properties.get(key, [])):
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matches.extend(
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triaquae/triaquae | bbabf736b3ba56a0c6498e7f04e16c13b8b8f2b9 | TriAquae/models/Ubuntu_12/paramiko/channel.py | python | Channel._log | (self, level, msg, *args) | [] | def _log(self, level, msg, *args):
self.logger.log(level, "[chan " + self._name + "] " + msg, *args) | [
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joelgrus/data-science-from-scratch | d5d0f117f41b3ccab3b07f1ee1fa21cfcf69afa1 | scratch/machine_learning.py | python | accuracy | (tp: int, fp: int, fn: int, tn: int) | return correct / total | [] | def accuracy(tp: int, fp: int, fn: int, tn: int) -> float:
correct = tp + tn
total = tp + fp + fn + tn
return correct / total | [
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nicolargo/glances | 00c65933ae1d0ebd3e72dc30fc3c215a83dfaae2 | glances/web_list.py | python | GlancesWebList.get_web_list | (self) | return self._web_list | Return the current server list (dict of dict). | Return the current server list (dict of dict). | [
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return self._web_list | [
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pyg-team/pytorch_geometric | b920e9a3a64e22c8356be55301c88444ff051cae | torch_geometric/datasets/last_fm.py | python | LastFM.processed_file_names | (self) | return 'data.pt' | [] | def processed_file_names(self) -> str:
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kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-modules/twisted/twisted/web/http.py | python | HTTPFactory.log | (self, request) | Log a request's result to the logfile, by default in combined log format. | Log a request's result to the logfile, by default in combined log format. | [
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"""
Log a request's result to the logfile, by default in combined log format.
"""
if hasattr(self, "logFile"):
line = '%s - - %s "%s" %d %s "%s" "%s"\n' % (
request.getClientIP(),
# request.getUser() or "-", # the remote user is almost never important
_logDateTime,
'%s %s %s' % (self._escape(request.method),
self._escape(request.uri),
self._escape(request.clientproto)),
request.code,
request.sentLength or "-",
self._escape(request.getHeader("referer") or "-"),
self._escape(request.getHeader("user-agent") or "-"))
self.logFile.write(line) | [
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ni/nidaqmx-python | 62fc6b48cbbb330fe1bcc9aedadc86610a1269b6 | nidaqmx/_task_modules/triggering/start_trigger.py | python | StartTrigger.dig_edge_dig_fltr_timebase_src | (self) | [] | def dig_edge_dig_fltr_timebase_src(self):
cfunc = (lib_importer.windll.
DAQmxResetDigEdgeStartTrigDigFltrTimebaseSrc)
if cfunc.argtypes is None:
with cfunc.arglock:
if cfunc.argtypes is None:
cfunc.argtypes = [
lib_importer.task_handle]
error_code = cfunc(
self._handle)
check_for_error(error_code) | [
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sametmax/Django--an-app-at-a-time | 99eddf12ead76e6dfbeb09ce0bae61e282e22f8a | ignore_this_directory/django/contrib/gis/geos/polygon.py | python | Polygon._get_ext_ring | (self) | return self[0] | Get the exterior ring of the Polygon. | Get the exterior ring of the Polygon. | [
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JetBrains/python-skeletons | 95ad24b666e475998e5d1cc02ed53a2188036167 | numpy/core/__init__.py | python | generic.conjugate | (self, *args, **kwargs) | Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest. | Not implemented (virtual attribute) | [
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")"
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"""
Not implemented (virtual attribute)
Class generic exists solely to derive numpy scalars from, and possesses,
albeit unimplemented, all the attributes of the ndarray class
so as to provide a uniform API.
See Also
--------
The corresponding attribute of the derived class of interest.
"""
pass | [
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csparpa/pyowm | 0474b61cc67fa3c95f9e572b96d3248031828fce | pyowm/commons/enums.py | python | ImageTypeEnum.items | (cls) | return [
cls.PNG,
cls.GEOTIFF
] | All values for this enum
:return: list of `pyowm.commons.enums.ImageType` | All values for this enum
:return: list of `pyowm.commons.enums.ImageType` | [
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"""
All values for this enum
:return: list of `pyowm.commons.enums.ImageType`
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machinalis/iepy | d7353e18d647d1657010d15fad09a4ea8d570089 | iepy/extraction/features.py | python | total_number_of_entities | (datapoint) | return len(datapoint.all_eos) | Returns the number of entity in the text segment | Returns the number of entity in the text segment | [
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Returns the number of entity in the text segment
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] | https://github.com/machinalis/iepy/blob/d7353e18d647d1657010d15fad09a4ea8d570089/iepy/extraction/features.py#L182-L186 | |
deepmind/rlax | 58b3672b2f7ac1a400b3934ae9888c677f39b9e2 | docs/conf.py | python | linkcode_resolve | (domain, info) | return 'https://github.com/deepmind/rlax/tree/master/rlax/%s#L%d#L%d' % (
os.path.relpath(filename, start=os.path.dirname(
rlax.__file__)), lineno, lineno + len(source) - 1) | Resolve a GitHub URL corresponding to Python object. | Resolve a GitHub URL corresponding to Python object. | [
"Resolve",
"a",
"GitHub",
"URL",
"corresponding",
"to",
"Python",
"object",
"."
] | def linkcode_resolve(domain, info):
"""Resolve a GitHub URL corresponding to Python object."""
if domain != 'py':
return None
try:
mod = sys.modules[info['module']]
except ImportError:
return None
obj = mod
try:
for attr in info['fullname'].split('.'):
obj = getattr(obj, attr)
except AttributeError:
return None
else:
obj = inspect.unwrap(obj)
try:
filename = inspect.getsourcefile(obj)
except TypeError:
return None
try:
source, lineno = inspect.getsourcelines(obj)
except OSError:
return None
# TODO(slebedev): support tags after we release an initial version.
return 'https://github.com/deepmind/rlax/tree/master/rlax/%s#L%d#L%d' % (
os.path.relpath(filename, start=os.path.dirname(
rlax.__file__)), lineno, lineno + len(source) - 1) | [
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replit-archive/empythoned | 977ec10ced29a3541a4973dc2b59910805695752 | cpython/Lib/os2emxpath.py | python | join | (a, *p) | return path | Join two or more pathname components, inserting sep as needed | Join two or more pathname components, inserting sep as needed | [
"Join",
"two",
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"pathname",
"components",
"inserting",
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] | def join(a, *p):
"""Join two or more pathname components, inserting sep as needed"""
path = a
for b in p:
if isabs(b):
path = b
elif path == '' or path[-1:] in '/\\:':
path = path + b
else:
path = path + '/' + b
return path | [
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EmuKit/emukit | cdcb0d070d7f1c5585260266160722b636786859 | emukit/model_wrappers/gpy_model_wrappers.py | python | GPyModelWrapper.predict_noiseless | (self, X: np.ndarray) | return self.model.predict(X, include_likelihood=False) | :param X: (n_points x n_dimensions) array containing locations at which to get predictions
:return: (mean, variance) Arrays of size n_points x 1 of the predictive distribution at each input location | :param X: (n_points x n_dimensions) array containing locations at which to get predictions
:return: (mean, variance) Arrays of size n_points x 1 of the predictive distribution at each input location | [
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"""
:param X: (n_points x n_dimensions) array containing locations at which to get predictions
:return: (mean, variance) Arrays of size n_points x 1 of the predictive distribution at each input location
"""
return self.model.predict(X, include_likelihood=False) | [
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kuri65536/python-for-android | 26402a08fc46b09ef94e8d7a6bbc3a54ff9d0891 | python-modules/twisted/twisted/python/log.py | python | _ignore | (*types) | PRIVATE. DEPRECATED. DON'T USE. | PRIVATE. DEPRECATED. DON'T USE. | [
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] | def _ignore(*types):
"""
PRIVATE. DEPRECATED. DON'T USE.
"""
for type in types:
_ignoreErrors.append(type) | [
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JiYou/openstack | 8607dd488bde0905044b303eb6e52bdea6806923 | packages/source/cinder/cinder/db/api.py | python | volume_type_get | (context, id) | return IMPL.volume_type_get(context, id) | Get volume type by id. | Get volume type by id. | [
"Get",
"volume",
"type",
"by",
"id",
"."
] | def volume_type_get(context, id):
"""Get volume type by id."""
return IMPL.volume_type_get(context, id) | [
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tp4a/teleport | 1fafd34f1f775d2cf80ea4af6e44468d8e0b24ad | server/www/packages/packages-darwin/x64/ldap3/core/connection.py | python | Connection.abandon | (self,
message_id,
controls=None) | Abandon the operation indicated by message_id | Abandon the operation indicated by message_id | [
"Abandon",
"the",
"operation",
"indicated",
"by",
"message_id"
] | def abandon(self,
message_id,
controls=None):
"""
Abandon the operation indicated by message_id
"""
if log_enabled(BASIC):
log(BASIC, 'start ABANDON operation via <%s>', self)
self.last_error = None
with self.connection_lock:
self._fire_deferred()
return_value = False
if self.strategy._outstanding or message_id == 0:
# only current operation should be abandoned, abandon, bind and unbind cannot ever be abandoned,
# messagiId 0 is invalid and should be used as a "ping" to keep alive the connection
if (self.strategy._outstanding and message_id in self.strategy._outstanding and self.strategy._outstanding[message_id]['type'] not in ['abandonRequest', 'bindRequest', 'unbindRequest']) or message_id == 0:
request = abandon_operation(message_id)
if log_enabled(PROTOCOL):
log(PROTOCOL, 'ABANDON request: <%s> sent via <%s>', abandon_request_to_dict(request), self)
self.send('abandonRequest', request, controls)
self.result = None
self.response = None
self._entries = []
return_value = True
else:
if log_enabled(ERROR):
log(ERROR, 'cannot abandon a Bind, an Unbind or an Abandon operation or message ID %s not found via <%s>', str(message_id), self)
if log_enabled(BASIC):
log(BASIC, 'done ABANDON operation, result <%s>', return_value)
return return_value | [
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mtivadar/qiew | 87a3b96b43f1745a6b3f1fcfebce5164d2a40a14 | plugins/unpack/basic.py | python | basic.getUI | (self) | return self.ui | [] | def getUI(self):
return self.ui | [
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] | https://github.com/mtivadar/qiew/blob/87a3b96b43f1745a6b3f1fcfebce5164d2a40a14/plugins/unpack/basic.py#L143-L144 | |||
cuthbertLab/music21 | bd30d4663e52955ed922c10fdf541419d8c67671 | music21/meter/base.py | python | TimeSignature.numerator | (self) | return self.beamSequence.numerator | Return the numerator of the TimeSignature as a number.
Can set the numerator for a simple TimeSignature.
To set the numerator of a complex TimeSignature, change beatCount.
(for complex TimeSignatures, note that this comes from the .beamSequence
of the TimeSignature)
>>> ts = meter.TimeSignature('3/4')
>>> ts.numerator
3
>>> ts.numerator = 5
>>> ts
<music21.meter.TimeSignature 5/4>
In this case, the TimeSignature is silently being converted to 9/8
to get a single digit numerator:
>>> ts = meter.TimeSignature('2/4+5/8')
>>> ts.numerator
9
Setting a summed time signature's numerator will change to a
simple time signature
>>> ts.numerator = 11
>>> ts
<music21.meter.TimeSignature 11/8> | Return the numerator of the TimeSignature as a number. | [
"Return",
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"of",
"the",
"TimeSignature",
"as",
"a",
"number",
"."
] | def numerator(self):
'''
Return the numerator of the TimeSignature as a number.
Can set the numerator for a simple TimeSignature.
To set the numerator of a complex TimeSignature, change beatCount.
(for complex TimeSignatures, note that this comes from the .beamSequence
of the TimeSignature)
>>> ts = meter.TimeSignature('3/4')
>>> ts.numerator
3
>>> ts.numerator = 5
>>> ts
<music21.meter.TimeSignature 5/4>
In this case, the TimeSignature is silently being converted to 9/8
to get a single digit numerator:
>>> ts = meter.TimeSignature('2/4+5/8')
>>> ts.numerator
9
Setting a summed time signature's numerator will change to a
simple time signature
>>> ts.numerator = 11
>>> ts
<music21.meter.TimeSignature 11/8>
'''
return self.beamSequence.numerator | [
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] | https://github.com/cuthbertLab/music21/blob/bd30d4663e52955ed922c10fdf541419d8c67671/music21/meter/base.py#L626-L659 | |
sagemath/sage | f9b2db94f675ff16963ccdefba4f1a3393b3fe0d | src/sage/categories/examples/sets_with_grading.py | python | NonNegativeIntegers._repr_ | (self) | return "Non negative integers" | r"""
TESTS::
sage: SetsWithGrading().example() # indirect example
Non negative integers | r"""
TESTS:: | [
"r",
"TESTS",
"::"
] | def _repr_(self):
r"""
TESTS::
sage: SetsWithGrading().example() # indirect example
Non negative integers
"""
return "Non negative integers" | [
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google/grr | 8ad8a4d2c5a93c92729206b7771af19d92d4f915 | grr/client/grr_response_client/client_actions/osx/firmware.py | python | EficheckCollectHashes.Run | (self, args) | Use eficheck to extract hash files in plaintext.
Args:
args: EficheckConfig
Returns:
CollectEfiHashesResponse
This action executes eficheck multiple times:
* First to get the binary version, using --version.
* Then with the --generate-hashes option. This will create one or more
.ealf files. Each file contains a binary representation of the hashes
extracted from a part of the flash image (e.g, EFI, SEC).
* For each file generated, we use the --show-hashes option to get a
plaintext representation of the hashes. This raw output is sent to the
server which will perform further parsing. | Use eficheck to extract hash files in plaintext. | [
"Use",
"eficheck",
"to",
"extract",
"hash",
"files",
"in",
"plaintext",
"."
] | def Run(self, args):
"""Use eficheck to extract hash files in plaintext.
Args:
args: EficheckConfig
Returns:
CollectEfiHashesResponse
This action executes eficheck multiple times:
* First to get the binary version, using --version.
* Then with the --generate-hashes option. This will create one or more
.ealf files. Each file contains a binary representation of the hashes
extracted from a part of the flash image (e.g, EFI, SEC).
* For each file generated, we use the --show-hashes option to get a
plaintext representation of the hashes. This raw output is sent to the
server which will perform further parsing.
"""
eficheck_version = self._GetVersion(args)
if not eficheck_version:
return False
with tempfiles.TemporaryDirectory() as tmp_dir:
res = client_utils_common.Execute(
args.cmd_path, ["--generate-hashes"], cwd=tmp_dir.path)
stdout, stderr, exit_status, time_used = res
# If something went wrong, forward the output directly.
if exit_status:
binary_response = rdf_client_action.ExecuteBinaryResponse(
stdout=stdout,
stderr=stderr,
exit_status=exit_status,
time_used=time_used)
self.SendReply(
rdf_apple_firmware.CollectEfiHashesResponse(
response=binary_response))
return
# Otherwise, convert all the files generated and forward the output.
for filename in glob.glob(os.path.join(tmp_dir.path, "*.ealf")):
cmd_args = ["--show-hashes", "-h", filename]
# Get the boot rom version from the filename.
basename = os.path.basename(filename)
if not self._FILENAME_RE.match(basename):
continue
boot_rom_version, _ = os.path.splitext(basename)
stdout, stderr, exit_status, time_used = client_utils_common.Execute(
args.cmd_path, cmd_args, bypass_allowlist=True)
binary_response = rdf_client_action.ExecuteBinaryResponse(
stdout=stdout,
stderr=stderr,
exit_status=exit_status,
time_used=time_used)
self.SendReply(
rdf_apple_firmware.CollectEfiHashesResponse(
eficheck_version=eficheck_version,
boot_rom_version=boot_rom_version,
response=binary_response))
tempfiles.DeleteGRRTempFile(filename) | [
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unknown-horizons/unknown-horizons | 7397fb333006d26c3d9fe796c7bd9cb8c3b43a49 | horizons/world/island.py | python | Island.__init__ | (self, db, island_id, session, preview=False) | @param db: db instance with island table
@param island_id: id of island in that table
@param session: reference to Session instance
@param preview: flag, map preview mode | [] | def __init__(self, db, island_id, session, preview=False):
"""
@param db: db instance with island table
@param island_id: id of island in that table
@param session: reference to Session instance
@param preview: flag, map preview mode
"""
super().__init__(worldid=island_id)
self.session = session
self.terrain_cache = None
self.available_land_cache = None
self.__init(db, island_id, preview)
if not preview:
# Create building indexers.
from horizons.world.units.animal import WildAnimal
self.building_indexers = {}
self.building_indexers[BUILDINGS.TREE] = BuildingIndexer(WildAnimal.walking_range, self, self.session.random)
# Load settlements.
for (settlement_id,) in db("SELECT rowid FROM settlement WHERE island = ?", island_id):
settlement = Settlement.load(db, settlement_id, self.session, self)
self.settlements.append(settlement)
if preview:
# Caches and buildings are not required for map preview.
return
self.terrain_cache = TerrainBuildabilityCache(self)
flat_land_set = self.terrain_cache.cache[TerrainRequirement.LAND][(1, 1)]
self.available_flat_land = len(flat_land_set)
available_coords_set = set(self.terrain_cache.land_or_coast)
for settlement in self.settlements:
settlement.init_buildability_cache(self.terrain_cache)
for coords in settlement.ground_map:
available_coords_set.discard(coords)
if coords in flat_land_set:
self.available_flat_land -= 1
self.available_land_cache = FreeIslandBuildabilityCache(self)
# Load buildings.
from horizons.world import load_building
buildings = db("SELECT rowid, type FROM building WHERE location = ?", island_id)
for (building_worldid, building_typeid) in buildings:
load_building(self.session, db, building_typeid, building_worldid) | [
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plotly/plotly.py | cfad7862594b35965c0e000813bd7805e8494a5b | packages/python/plotly/plotly/graph_objs/_contour.py | python | Contour.autocontour | (self) | return self["autocontour"] | Determines whether or not the contour level attributes are
picked by an algorithm. If True, the number of contour levels
can be set in `ncontours`. If False, set the contour level
attributes in `contours`.
The 'autocontour' property must be specified as a bool
(either True, or False)
Returns
-------
bool | Determines whether or not the contour level attributes are
picked by an algorithm. If True, the number of contour levels
can be set in `ncontours`. If False, set the contour level
attributes in `contours`.
The 'autocontour' property must be specified as a bool
(either True, or False) | [
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"""
Determines whether or not the contour level attributes are
picked by an algorithm. If True, the number of contour levels
can be set in `ncontours`. If False, set the contour level
attributes in `contours`.
The 'autocontour' property must be specified as a bool
(either True, or False)
Returns
-------
bool
"""
return self["autocontour"] | [
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eggnogdb/eggnog-mapper | d6e6cdf0a829f2bd85480f3f3f16e38c213cd091 | eggnogmapper/annotation/annotator.py | python | Annotator._annotate_ondisk | (self, hits_gen_func, annots_parser) | return | [] | def _annotate_ondisk(self, hits_gen_func, annots_parser):
pool = multiprocessing.Pool(self.cpu)
chunk_size = 1
# "my recommendation is targeting 10 ms chunk processing time"
# https://stackoverflow.com/a/43817408/2361653
# As our tasks take no less than 0.1 secs, a large chunk_size makes no sense at all
# Note that this makes q/s an approximation until all tasks have been finished
try:
for result in pool.imap(annotate_hit_line_ondisk,
self.iter_hit_lines(hits_gen_func, annots_parser),
chunk_size):
yield result
except EmapperException:
raise
except Exception as e:
import traceback
traceback.print_exc()
raise EmapperException(f"Error: annotation failed. "+str(e))
finally:
pool.close()
pool.terminate() # it should remove the global eggnog_db variables also
return | [
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OpenMDAO/OpenMDAO | f47eb5485a0bb5ea5d2ae5bd6da4b94dc6b296bd | openmdao/vectors/vector.py | python | Vector.set_vals | (self, vals) | Set the data array of this vector using a value or iter of values, one for each variable.
The values must be in the same order as the variables appear in this Vector.
Parameters
----------
vals : ndarray, float, or iter of ndarrays and/or floats
Values for each variable contained in this vector, in the proper order. | Set the data array of this vector using a value or iter of values, one for each variable. | [
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] | def set_vals(self, vals):
"""
Set the data array of this vector using a value or iter of values, one for each variable.
The values must be in the same order as the variables appear in this Vector.
Parameters
----------
vals : ndarray, float, or iter of ndarrays and/or floats
Values for each variable contained in this vector, in the proper order.
"""
arr = self.asarray()
if self.nvars() == 1:
if isscalar(vals):
arr[:] = vals
else:
arr[:] = vals.ravel()
else:
start = end = 0
for v in vals:
if isscalar(v):
end += 1
arr[start] = v
else:
end += v.size
arr[start:end] = v.ravel()
start = end | [
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":"... | https://github.com/OpenMDAO/OpenMDAO/blob/f47eb5485a0bb5ea5d2ae5bd6da4b94dc6b296bd/openmdao/vectors/vector.py#L558-L585 | ||
ChenRocks/fast_abs_rl | a3cd65016082ab842be4e42b0b26b7bc046f4ad5 | metric.py | python | _lcs_dp | (a, b) | return dp | compute the len dp of lcs | compute the len dp of lcs | [
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"dp",
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"lcs"
] | def _lcs_dp(a, b):
""" compute the len dp of lcs"""
dp = [[0 for _ in range(0, len(b)+1)]
for _ in range(0, len(a)+1)]
# dp[i][j]: lcs_len(a[:i], b[:j])
for i in range(1, len(a)+1):
for j in range(1, len(b)+1):
if a[i-1] == b[j-1]:
dp[i][j] = dp[i-1][j-1] + 1
else:
dp[i][j] = max(dp[i-1][j], dp[i][j-1])
return dp | [
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")... | https://github.com/ChenRocks/fast_abs_rl/blob/a3cd65016082ab842be4e42b0b26b7bc046f4ad5/metric.py#L42-L53 | |
aliyun/aliyun-oss-python-sdk | 5f2afa0928a58c7c1cc6317ac147f3637481f6fd | oss2/resumable.py | python | _ResumableOperation.__init__ | (self, bucket, key, filename, size, store,
progress_callback=None, versionid=None) | [] | def __init__(self, bucket, key, filename, size, store,
progress_callback=None, versionid=None):
self.bucket = bucket
self.key = to_string(key)
self.filename = filename
self.size = size
self._abspath = os.path.abspath(filename)
self.__store = store
if versionid is None:
self.__record_key = self.__store.make_store_key(bucket.bucket_name, self.key, self._abspath)
else:
self.__record_key = self.__store.make_store_key(bucket.bucket_name, self.key, self._abspath, versionid)
logger.debug("Init _ResumableOperation, record_key: {0}".format(self.__record_key))
# protect self.__progress_callback
self.__plock = threading.Lock()
self.__progress_callback = progress_callback | [
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