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edoburu/django-slug-preview | slug_preview/models.py | SlugPreviewField.pre_save | def pre_save(self, instance, add):
"""
Auto-generate the slug if needed.
"""
# get currently entered slug
value = self.value_from_object(instance)
slug = None
# auto populate (if the form didn't do that already).
# If you want unique_with logic, use django-autoslug instead.
# This model field only allows parameters which can be passed to the form widget too.
if self.populate_from and (self.always_update or not value):
value = getattr(instance, self.populate_from)
# Make sure the slugify logic is applied,
# even on manually entered input.
if value:
value = force_text(value)
slug = self.slugify(value)
if self.max_length < len(slug):
slug = slug[:self.max_length]
# make the updated slug available as instance attribute
setattr(instance, self.name, slug)
return slug | python | def pre_save(self, instance, add):
"""
Auto-generate the slug if needed.
"""
# get currently entered slug
value = self.value_from_object(instance)
slug = None
# auto populate (if the form didn't do that already).
# If you want unique_with logic, use django-autoslug instead.
# This model field only allows parameters which can be passed to the form widget too.
if self.populate_from and (self.always_update or not value):
value = getattr(instance, self.populate_from)
# Make sure the slugify logic is applied,
# even on manually entered input.
if value:
value = force_text(value)
slug = self.slugify(value)
if self.max_length < len(slug):
slug = slug[:self.max_length]
# make the updated slug available as instance attribute
setattr(instance, self.name, slug)
return slug | [
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theonion/django-bulbs | bulbs/reading_list/slicers.py | FirstSlotSlicer | def FirstSlotSlicer(primary_query, secondary_query, limit=30): # noqa
"""
Inject the first object from a queryset into the first position of a reading list.
:param primary_queryset: djes.LazySearch object. Default queryset for reading list.
:param secondary_queryset: djes.LazySearch object. first result leads the reading_list.
:return list: mixed reading list.
"""
reading_list = SearchSlicer(limit=limit)
reading_list.register_queryset(primary_query)
reading_list.register_queryset(secondary_query, validator=lambda x: bool(x == 0))
return reading_list | python | def FirstSlotSlicer(primary_query, secondary_query, limit=30): # noqa
"""
Inject the first object from a queryset into the first position of a reading list.
:param primary_queryset: djes.LazySearch object. Default queryset for reading list.
:param secondary_queryset: djes.LazySearch object. first result leads the reading_list.
:return list: mixed reading list.
"""
reading_list = SearchSlicer(limit=limit)
reading_list.register_queryset(primary_query)
reading_list.register_queryset(secondary_query, validator=lambda x: bool(x == 0))
return reading_list | [
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theonion/django-bulbs | bulbs/reading_list/slicers.py | SearchSlicer.register_queryset | def register_queryset(self, queryset, validator=None, default=False):
"""
Add a given queryset to the iterator with custom logic for iteration.
:param queryset: List of objects included in the reading list.
:param validator: Custom logic to determine a queryset's position in a reading_list.
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:param default: Sets the given queryset as the primary queryset when no validator applies.
"""
if default or self.default_queryset is None:
self.default_queryset = queryset
return
if validator:
self.querysets[validator] = queryset
else:
raise ValueError(
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"""
Add a given queryset to the iterator with custom logic for iteration.
:param queryset: List of objects included in the reading list.
:param validator: Custom logic to determine a queryset's position in a reading_list.
Validators must accept an index as an argument and return a truthy value.
:param default: Sets the given queryset as the primary queryset when no validator applies.
"""
if default or self.default_queryset is None:
self.default_queryset = queryset
return
if validator:
self.querysets[validator] = queryset
else:
raise ValueError(
"""Querysets require validation logic to integrate with reading lists."""
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theonion/django-bulbs | bulbs/special_coverage/management/commands/migrate_active_to_published.py | Command.get_month_start_date | def get_month_start_date(self):
"""Returns the first day of the current month"""
now = timezone.now()
return timezone.datetime(day=1, month=now.month, year=now.year, tzinfo=now.tzinfo) | python | def get_month_start_date(self):
"""Returns the first day of the current month"""
now = timezone.now()
return timezone.datetime(day=1, month=now.month, year=now.year, tzinfo=now.tzinfo) | [
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arpitbbhayani/flasksr | flasksr/sr/basesr.py | BaseSR._yield_all | def _yield_all(self, l):
'''
Given a iterable like list or tuple the function yields each of its
items with _yield
'''
if l is not None:
if type(l) in [list, tuple]:
for f in l:
for x in self._yield(f): yield x
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for x in self._yield(l): yield x | python | def _yield_all(self, l):
'''
Given a iterable like list or tuple the function yields each of its
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if l is not None:
if type(l) in [list, tuple]:
for f in l:
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jjkester/moneybird-python | moneybird/api.py | MoneyBird.post | def post(self, resource_path: str, data: dict, administration_id: int = None):
"""
Performs a POST request to the endpoint identified by the resource path. POST requests are usually used to add
new data.
Example:
>>> from moneybird import MoneyBird, TokenAuthentication
>>> moneybird = MoneyBird(TokenAuthentication('access_token'))
>>> data = {'url': 'http://www.mocky.io/v2/5185415ba171ea3a00704eed'}
>>> moneybird.post('webhooks', data, 123)
{'id': '143274315994891267', 'url': 'http://www.mocky.io/v2/5185415ba171ea3a00704eed', ...
:param resource_path: The resource path.
:param data: The data to send to the server.
:param administration_id: The administration id (optional, depending on the resource path).
:return: The decoded JSON response for the request.
"""
response = self.session.post(
url=self._get_url(administration_id, resource_path),
json=data,
)
return self._process_response(response) | python | def post(self, resource_path: str, data: dict, administration_id: int = None):
"""
Performs a POST request to the endpoint identified by the resource path. POST requests are usually used to add
new data.
Example:
>>> from moneybird import MoneyBird, TokenAuthentication
>>> moneybird = MoneyBird(TokenAuthentication('access_token'))
>>> data = {'url': 'http://www.mocky.io/v2/5185415ba171ea3a00704eed'}
>>> moneybird.post('webhooks', data, 123)
{'id': '143274315994891267', 'url': 'http://www.mocky.io/v2/5185415ba171ea3a00704eed', ...
:param resource_path: The resource path.
:param data: The data to send to the server.
:param administration_id: The administration id (optional, depending on the resource path).
:return: The decoded JSON response for the request.
"""
response = self.session.post(
url=self._get_url(administration_id, resource_path),
json=data,
)
return self._process_response(response) | [
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jjkester/moneybird-python | moneybird/api.py | MoneyBird.delete | def delete(self, resource_path: str, administration_id: int = None):
"""
Performs a DELETE request to the endpoint identified by the resource path. DELETE requests are usually used to
(permanently) delete existing data. USE THIS METHOD WITH CAUTION.
From a client perspective, DELETE requests behave similarly to GET requests.
:param resource_path: The resource path.
:param administration_id: The administration id (optional, depending on the resource path).
:return: The decoded JSON response for the request.
"""
response = self.session.delete(
url=self._get_url(administration_id, resource_path),
)
return self._process_response(response) | python | def delete(self, resource_path: str, administration_id: int = None):
"""
Performs a DELETE request to the endpoint identified by the resource path. DELETE requests are usually used to
(permanently) delete existing data. USE THIS METHOD WITH CAUTION.
From a client perspective, DELETE requests behave similarly to GET requests.
:param resource_path: The resource path.
:param administration_id: The administration id (optional, depending on the resource path).
:return: The decoded JSON response for the request.
"""
response = self.session.delete(
url=self._get_url(administration_id, resource_path),
)
return self._process_response(response) | [
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jjkester/moneybird-python | moneybird/api.py | MoneyBird.renew_session | def renew_session(self):
"""
Clears all session data and starts a new session using the same settings as before.
This method can be used to clear session data, e.g., cookies. Future requests will use a new session initiated
with the same settings and authentication method.
"""
logger.debug("API session renewed")
self.session = self.authentication.get_session()
self.session.headers.update({
'User-Agent': 'MoneyBird for Python %s' % VERSION,
'Accept': 'application/json',
}) | python | def renew_session(self):
"""
Clears all session data and starts a new session using the same settings as before.
This method can be used to clear session data, e.g., cookies. Future requests will use a new session initiated
with the same settings and authentication method.
"""
logger.debug("API session renewed")
self.session = self.authentication.get_session()
self.session.headers.update({
'User-Agent': 'MoneyBird for Python %s' % VERSION,
'Accept': 'application/json',
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jjkester/moneybird-python | moneybird/api.py | MoneyBird._get_url | def _get_url(cls, administration_id: int, resource_path: str):
"""
Builds the URL to the API endpoint specified by the given parameters.
:param administration_id: The ID of the administration (may be None).
:param resource_path: The path to the resource.
:return: The absolute URL to the endpoint.
"""
url = urljoin(cls.base_url, '%s/' % cls.version)
if administration_id is not None:
url = urljoin(url, '%s/' % administration_id)
url = urljoin(url, '%s.json' % resource_path)
return url | python | def _get_url(cls, administration_id: int, resource_path: str):
"""
Builds the URL to the API endpoint specified by the given parameters.
:param administration_id: The ID of the administration (may be None).
:param resource_path: The path to the resource.
:return: The absolute URL to the endpoint.
"""
url = urljoin(cls.base_url, '%s/' % cls.version)
if administration_id is not None:
url = urljoin(url, '%s/' % administration_id)
url = urljoin(url, '%s.json' % resource_path)
return url | [
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jjkester/moneybird-python | moneybird/api.py | MoneyBird._process_response | def _process_response(response: requests.Response, expected: list = []) -> dict:
"""
Processes an API response. Raises an exception when appropriate.
The exception that will be raised is MoneyBird.APIError. This exception is subclassed so implementing programs
can easily react appropriately to different exceptions.
The following subclasses of MoneyBird.APIError are likely to be raised:
- MoneyBird.Unauthorized: No access to the resource or invalid authentication
- MoneyBird.Throttled: Access (temporarily) denied, please try again
- MoneyBird.NotFound: Resource not found, check resource path
- MoneyBird.InvalidData: Validation errors occured while processing your input
- MoneyBird.ServerError: Error on the server
:param response: The response to process.
:param expected: A list of expected status codes which won't raise an exception.
:return: The useful data in the response (may be None).
"""
responses = {
200: None,
201: None,
204: None,
400: MoneyBird.Unauthorized,
401: MoneyBird.Unauthorized,
403: MoneyBird.Throttled,
404: MoneyBird.NotFound,
406: MoneyBird.NotFound,
422: MoneyBird.InvalidData,
429: MoneyBird.Throttled,
500: MoneyBird.ServerError,
}
logger.debug("API request: %s %s\n" % (response.request.method, response.request.url) +
"Response: %s %s" % (response.status_code, response.text))
if response.status_code not in expected:
if response.status_code not in responses:
logger.error("API response contained unknown status code")
raise MoneyBird.APIError(response, "API response contained unknown status code")
elif responses[response.status_code] is not None:
try:
description = response.json()['error']
except (AttributeError, TypeError, KeyError, ValueError):
description = None
raise responses[response.status_code](response, description)
try:
data = response.json()
except ValueError:
logger.error("API response is not JSON decodable")
data = None
return data | python | def _process_response(response: requests.Response, expected: list = []) -> dict:
"""
Processes an API response. Raises an exception when appropriate.
The exception that will be raised is MoneyBird.APIError. This exception is subclassed so implementing programs
can easily react appropriately to different exceptions.
The following subclasses of MoneyBird.APIError are likely to be raised:
- MoneyBird.Unauthorized: No access to the resource or invalid authentication
- MoneyBird.Throttled: Access (temporarily) denied, please try again
- MoneyBird.NotFound: Resource not found, check resource path
- MoneyBird.InvalidData: Validation errors occured while processing your input
- MoneyBird.ServerError: Error on the server
:param response: The response to process.
:param expected: A list of expected status codes which won't raise an exception.
:return: The useful data in the response (may be None).
"""
responses = {
200: None,
201: None,
204: None,
400: MoneyBird.Unauthorized,
401: MoneyBird.Unauthorized,
403: MoneyBird.Throttled,
404: MoneyBird.NotFound,
406: MoneyBird.NotFound,
422: MoneyBird.InvalidData,
429: MoneyBird.Throttled,
500: MoneyBird.ServerError,
}
logger.debug("API request: %s %s\n" % (response.request.method, response.request.url) +
"Response: %s %s" % (response.status_code, response.text))
if response.status_code not in expected:
if response.status_code not in responses:
logger.error("API response contained unknown status code")
raise MoneyBird.APIError(response, "API response contained unknown status code")
elif responses[response.status_code] is not None:
try:
description = response.json()['error']
except (AttributeError, TypeError, KeyError, ValueError):
description = None
raise responses[response.status_code](response, description)
try:
data = response.json()
except ValueError:
logger.error("API response is not JSON decodable")
data = None
return data | [
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The following subclasses of MoneyBird.APIError are likely to be raised:
- MoneyBird.Unauthorized: No access to the resource or invalid authentication
- MoneyBird.Throttled: Access (temporarily) denied, please try again
- MoneyBird.NotFound: Resource not found, check resource path
- MoneyBird.InvalidData: Validation errors occured while processing your input
- MoneyBird.ServerError: Error on the server
:param response: The response to process.
:param expected: A list of expected status codes which won't raise an exception.
:return: The useful data in the response (may be None). | [
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theonion/django-bulbs | bulbs/videos/models.py | VideohubVideo.search_videohub | def search_videohub(cls, query, filters=None, status=None, sort=None, size=None, page=None):
"""searches the videohub given a query and applies given filters and other bits
:see: https://github.com/theonion/videohub/blob/master/docs/search/post.md
:see: https://github.com/theonion/videohub/blob/master/docs/search/get.md
:param query: query terms to search by
:type query: str
:example query: "brooklyn hipsters" # although, this is a little redundant...
:param filters: video field value restrictions
:type filters: dict
:default filters: None
:example filters: {"channel": "onion"} or {"series": "Today NOW"}
:param status: limit the results to videos that are published, scheduled, draft
:type status: str
:default status: None
:example status: "published" or "draft" or "scheduled"
:param sort: video field related sorting
:type sort: dict
:default sort: None
:example sort: {"title": "desc"} or {"description": "asc"}
:param size: the page size (number of results)
:type size: int
:default size: None
:example size": {"size": 20}
:param page: the page number of the results
:type page: int
:default page: None
:example page: {"page": 2} # note, you should use `size` in conjunction with `page`
:return: a dictionary of results and meta information
:rtype: dict
"""
# construct url
url = getattr(settings, "VIDEOHUB_API_SEARCH_URL", cls.DEFAULT_VIDEOHUB_API_SEARCH_URL)
# construct auth headers
headers = {
"Content-Type": "application/json",
"Authorization": settings.VIDEOHUB_API_TOKEN,
}
# construct payload
payload = {
"query": query,
}
if filters:
assert isinstance(filters, dict)
payload["filters"] = filters
if status:
assert isinstance(status, six.string_types)
payload.setdefault("filters", {})
payload["filters"]["status"] = status
if sort:
assert isinstance(sort, dict)
payload["sort"] = sort
if size:
assert isinstance(size, (six.string_types, int))
payload["size"] = size
if page:
assert isinstance(page, (six.string_types, int))
payload["page"] = page
# send request
res = requests.post(url, data=json.dumps(payload), headers=headers)
# raise if not 200
if res.status_code != 200:
res.raise_for_status()
# parse and return response
return json.loads(res.content) | python | def search_videohub(cls, query, filters=None, status=None, sort=None, size=None, page=None):
"""searches the videohub given a query and applies given filters and other bits
:see: https://github.com/theonion/videohub/blob/master/docs/search/post.md
:see: https://github.com/theonion/videohub/blob/master/docs/search/get.md
:param query: query terms to search by
:type query: str
:example query: "brooklyn hipsters" # although, this is a little redundant...
:param filters: video field value restrictions
:type filters: dict
:default filters: None
:example filters: {"channel": "onion"} or {"series": "Today NOW"}
:param status: limit the results to videos that are published, scheduled, draft
:type status: str
:default status: None
:example status: "published" or "draft" or "scheduled"
:param sort: video field related sorting
:type sort: dict
:default sort: None
:example sort: {"title": "desc"} or {"description": "asc"}
:param size: the page size (number of results)
:type size: int
:default size: None
:example size": {"size": 20}
:param page: the page number of the results
:type page: int
:default page: None
:example page: {"page": 2} # note, you should use `size` in conjunction with `page`
:return: a dictionary of results and meta information
:rtype: dict
"""
# construct url
url = getattr(settings, "VIDEOHUB_API_SEARCH_URL", cls.DEFAULT_VIDEOHUB_API_SEARCH_URL)
# construct auth headers
headers = {
"Content-Type": "application/json",
"Authorization": settings.VIDEOHUB_API_TOKEN,
}
# construct payload
payload = {
"query": query,
}
if filters:
assert isinstance(filters, dict)
payload["filters"] = filters
if status:
assert isinstance(status, six.string_types)
payload.setdefault("filters", {})
payload["filters"]["status"] = status
if sort:
assert isinstance(sort, dict)
payload["sort"] = sort
if size:
assert isinstance(size, (six.string_types, int))
payload["size"] = size
if page:
assert isinstance(page, (six.string_types, int))
payload["page"] = page
# send request
res = requests.post(url, data=json.dumps(payload), headers=headers)
# raise if not 200
if res.status_code != 200:
res.raise_for_status()
# parse and return response
return json.loads(res.content) | [
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theonion/django-bulbs | bulbs/videos/models.py | VideohubVideo.get_hub_url | def get_hub_url(self):
"""gets a canonical path to the detail page of the video on the hub
:return: the path to the consumer ui detail page of the video
:rtype: str
"""
url = getattr(settings, "VIDEOHUB_VIDEO_URL", self.DEFAULT_VIDEOHUB_VIDEO_URL)
# slugify needs ascii
ascii_title = ""
if isinstance(self.title, str):
ascii_title = self.title
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# Legacy unicode conversion
ascii_title = self.title.encode('ascii', 'replace')
path = slugify("{}-{}".format(ascii_title, self.id))
return url.format(path) | python | def get_hub_url(self):
"""gets a canonical path to the detail page of the video on the hub
:return: the path to the consumer ui detail page of the video
:rtype: str
"""
url = getattr(settings, "VIDEOHUB_VIDEO_URL", self.DEFAULT_VIDEOHUB_VIDEO_URL)
# slugify needs ascii
ascii_title = ""
if isinstance(self.title, str):
ascii_title = self.title
elif six.PY2 and isinstance(self.title, six.text_type):
# Legacy unicode conversion
ascii_title = self.title.encode('ascii', 'replace')
path = slugify("{}-{}".format(ascii_title, self.id))
return url.format(path) | [
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theonion/django-bulbs | bulbs/videos/models.py | VideohubVideo.get_embed_url | def get_embed_url(self, targeting=None, recirc=None):
"""gets a canonical path to an embedded iframe of the video from the hub
:return: the path to create an embedded iframe of the video
:rtype: str
"""
url = getattr(settings, "VIDEOHUB_EMBED_URL", self.DEFAULT_VIDEOHUB_EMBED_URL)
url = url.format(self.id)
if targeting is not None:
for k, v in sorted(targeting.items()):
url += '&{0}={1}'.format(k, v)
if recirc is not None:
url += '&recirc={0}'.format(recirc)
return url | python | def get_embed_url(self, targeting=None, recirc=None):
"""gets a canonical path to an embedded iframe of the video from the hub
:return: the path to create an embedded iframe of the video
:rtype: str
"""
url = getattr(settings, "VIDEOHUB_EMBED_URL", self.DEFAULT_VIDEOHUB_EMBED_URL)
url = url.format(self.id)
if targeting is not None:
for k, v in sorted(targeting.items()):
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url += '&recirc={0}'.format(recirc)
return url | [
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theonion/django-bulbs | bulbs/videos/models.py | VideohubVideo.get_api_url | def get_api_url(self):
"""gets a canonical path to the api detail url of the video on the hub
:return: the path to the api detail of the video
:rtype: str
"""
url = getattr(settings, 'VIDEOHUB_API_URL', None)
# Support alternate setting (used by most client projects)
if not url:
url = getattr(settings, 'VIDEOHUB_API_BASE_URL', None)
if url:
url = url.rstrip('/') + '/videos/{}'
if not url:
url = self.DEFAULT_VIDEOHUB_API_URL
return url.format(self.id) | python | def get_api_url(self):
"""gets a canonical path to the api detail url of the video on the hub
:return: the path to the api detail of the video
:rtype: str
"""
url = getattr(settings, 'VIDEOHUB_API_URL', None)
# Support alternate setting (used by most client projects)
if not url:
url = getattr(settings, 'VIDEOHUB_API_BASE_URL', None)
if url:
url = url.rstrip('/') + '/videos/{}'
if not url:
url = self.DEFAULT_VIDEOHUB_API_URL
return url.format(self.id) | [
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geertj/pyskiplist | pyskiplist/dllist.py | dllist.remove | def remove(self, node):
"""Remove a node from the list.
The *node* argument must be a node that was previously inserted in the
list
"""
if node is None or node._prev == -1:
return
if node._next is None:
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if node._prev is None:
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node._prev._next = node._next
node._prev = node._next = -1
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"""Remove a node from the list.
The *node* argument must be a node that was previously inserted in the
list
"""
if node is None or node._prev == -1:
return
if node._next is None:
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.get_all_outcome_links_for_context_accounts | def get_all_outcome_links_for_context_accounts(self, account_id, outcome_group_style=None, outcome_style=None):
"""
Get all outcome links for context.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# OPTIONAL - outcome_style
"""The detail level of the outcomes. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_style is not None:
params["outcome_style"] = outcome_style
# OPTIONAL - outcome_group_style
"""The detail level of the outcome groups. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_group_style is not None:
params["outcome_group_style"] = outcome_group_style
self.logger.debug("GET /api/v1/accounts/{account_id}/outcome_group_links with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/accounts/{account_id}/outcome_group_links".format(**path), data=data, params=params, all_pages=True) | python | def get_all_outcome_links_for_context_accounts(self, account_id, outcome_group_style=None, outcome_style=None):
"""
Get all outcome links for context.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# OPTIONAL - outcome_style
"""The detail level of the outcomes. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_style is not None:
params["outcome_style"] = outcome_style
# OPTIONAL - outcome_group_style
"""The detail level of the outcome groups. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_group_style is not None:
params["outcome_group_style"] = outcome_group_style
self.logger.debug("GET /api/v1/accounts/{account_id}/outcome_group_links with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/accounts/{account_id}/outcome_group_links".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.get_all_outcome_links_for_context_courses | def get_all_outcome_links_for_context_courses(self, course_id, outcome_group_style=None, outcome_style=None):
"""
Get all outcome links for context.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - outcome_style
"""The detail level of the outcomes. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_style is not None:
params["outcome_style"] = outcome_style
# OPTIONAL - outcome_group_style
"""The detail level of the outcome groups. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_group_style is not None:
params["outcome_group_style"] = outcome_group_style
self.logger.debug("GET /api/v1/courses/{course_id}/outcome_group_links with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/outcome_group_links".format(**path), data=data, params=params, all_pages=True) | python | def get_all_outcome_links_for_context_courses(self, course_id, outcome_group_style=None, outcome_style=None):
"""
Get all outcome links for context.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - outcome_style
"""The detail level of the outcomes. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_style is not None:
params["outcome_style"] = outcome_style
# OPTIONAL - outcome_group_style
"""The detail level of the outcome groups. Defaults to "abbrev".
Specify "full" for more information."""
if outcome_group_style is not None:
params["outcome_group_style"] = outcome_group_style
self.logger.debug("GET /api/v1/courses/{course_id}/outcome_group_links with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/outcome_group_links".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.create_link_outcome_global_outcome_id | def create_link_outcome_global_outcome_id(self, id, outcome_id, calculation_int=None, calculation_method=None, description=None, display_name=None, mastery_points=None, ratings_description=None, ratings_points=None, title=None, vendor_guid=None):
"""
Create/link an outcome.
Link an outcome into the outcome group. The outcome to link can either be
specified by a PUT to the link URL for a specific outcome (the outcome_id
in the PUT URLs) or by supplying the information for a new outcome (title,
description, ratings, mastery_points) in a POST to the collection.
If linking an existing outcome, the outcome_id must identify an outcome
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an outcome owned by an associated account, or a global outcome. With
outcome_id present, any other parameters are ignored.
If defining a new outcome, the outcome is created in the outcome group's
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the title is required but all other fields are optional. The new outcome
is then linked into the outcome group.
If ratings are provided when creating a new outcome, an embedded rubric
criterion is included in the new outcome. This criterion's mastery_points
default to the maximum points in the highest rating if not specified in the
mastery_points parameter. Any ratings lacking a description are given a
default of "No description". Any ratings lacking a point value are given a
default of 0. If no ratings are provided, the mastery_points parameter is
ignored.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - PATH - outcome_id
"""The ID of the existing outcome to link."""
path["outcome_id"] = outcome_id
# OPTIONAL - title
"""The title of the new outcome. Required if outcome_id is absent."""
if title is not None:
data["title"] = title
# OPTIONAL - display_name
"""A friendly name shown in reports for outcomes with cryptic titles,
such as common core standards names."""
if display_name is not None:
data["display_name"] = display_name
# OPTIONAL - description
"""The description of the new outcome."""
if description is not None:
data["description"] = description
# OPTIONAL - vendor_guid
"""A custom GUID for the learning standard."""
if vendor_guid is not None:
data["vendor_guid"] = vendor_guid
# OPTIONAL - mastery_points
"""The mastery threshold for the embedded rubric criterion."""
if mastery_points is not None:
data["mastery_points"] = mastery_points
# OPTIONAL - ratings[description]
"""The description of a rating level for the embedded rubric criterion."""
if ratings_description is not None:
data["ratings[description]"] = ratings_description
# OPTIONAL - ratings[points]
"""The points corresponding to a rating level for the embedded rubric criterion."""
if ratings_points is not None:
data["ratings[points]"] = ratings_points
# OPTIONAL - calculation_method
"""The new calculation method. Defaults to "highest""""
if calculation_method is not None:
self._validate_enum(calculation_method, ["decaying_average", "n_mastery", "latest", "highest"])
data["calculation_method"] = calculation_method
# OPTIONAL - calculation_int
"""The new calculation int. Only applies if the calculation_method is "decaying_average" or "n_mastery""""
if calculation_int is not None:
data["calculation_int"] = calculation_int
self.logger.debug("PUT /api/v1/global/outcome_groups/{id}/outcomes/{outcome_id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("PUT", "/api/v1/global/outcome_groups/{id}/outcomes/{outcome_id}".format(**path), data=data, params=params, single_item=True) | python | def create_link_outcome_global_outcome_id(self, id, outcome_id, calculation_int=None, calculation_method=None, description=None, display_name=None, mastery_points=None, ratings_description=None, ratings_points=None, title=None, vendor_guid=None):
"""
Create/link an outcome.
Link an outcome into the outcome group. The outcome to link can either be
specified by a PUT to the link URL for a specific outcome (the outcome_id
in the PUT URLs) or by supplying the information for a new outcome (title,
description, ratings, mastery_points) in a POST to the collection.
If linking an existing outcome, the outcome_id must identify an outcome
available to this context; i.e. an outcome owned by this group's context,
an outcome owned by an associated account, or a global outcome. With
outcome_id present, any other parameters are ignored.
If defining a new outcome, the outcome is created in the outcome group's
context using the provided title, description, ratings, and mastery points;
the title is required but all other fields are optional. The new outcome
is then linked into the outcome group.
If ratings are provided when creating a new outcome, an embedded rubric
criterion is included in the new outcome. This criterion's mastery_points
default to the maximum points in the highest rating if not specified in the
mastery_points parameter. Any ratings lacking a description are given a
default of "No description". Any ratings lacking a point value are given a
default of 0. If no ratings are provided, the mastery_points parameter is
ignored.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - PATH - outcome_id
"""The ID of the existing outcome to link."""
path["outcome_id"] = outcome_id
# OPTIONAL - title
"""The title of the new outcome. Required if outcome_id is absent."""
if title is not None:
data["title"] = title
# OPTIONAL - display_name
"""A friendly name shown in reports for outcomes with cryptic titles,
such as common core standards names."""
if display_name is not None:
data["display_name"] = display_name
# OPTIONAL - description
"""The description of the new outcome."""
if description is not None:
data["description"] = description
# OPTIONAL - vendor_guid
"""A custom GUID for the learning standard."""
if vendor_guid is not None:
data["vendor_guid"] = vendor_guid
# OPTIONAL - mastery_points
"""The mastery threshold for the embedded rubric criterion."""
if mastery_points is not None:
data["mastery_points"] = mastery_points
# OPTIONAL - ratings[description]
"""The description of a rating level for the embedded rubric criterion."""
if ratings_description is not None:
data["ratings[description]"] = ratings_description
# OPTIONAL - ratings[points]
"""The points corresponding to a rating level for the embedded rubric criterion."""
if ratings_points is not None:
data["ratings[points]"] = ratings_points
# OPTIONAL - calculation_method
"""The new calculation method. Defaults to "highest""""
if calculation_method is not None:
self._validate_enum(calculation_method, ["decaying_average", "n_mastery", "latest", "highest"])
data["calculation_method"] = calculation_method
# OPTIONAL - calculation_int
"""The new calculation int. Only applies if the calculation_method is "decaying_average" or "n_mastery""""
if calculation_int is not None:
data["calculation_int"] = calculation_int
self.logger.debug("PUT /api/v1/global/outcome_groups/{id}/outcomes/{outcome_id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("PUT", "/api/v1/global/outcome_groups/{id}/outcomes/{outcome_id}".format(**path), data=data, params=params, single_item=True) | [
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.list_subgroups_global | def list_subgroups_global(self, id):
"""
List subgroups.
List the immediate OutcomeGroup children of the outcome group. Paginated.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
self.logger.debug("GET /api/v1/global/outcome_groups/{id}/subgroups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/global/outcome_groups/{id}/subgroups".format(**path), data=data, params=params, all_pages=True) | python | def list_subgroups_global(self, id):
"""
List subgroups.
List the immediate OutcomeGroup children of the outcome group. Paginated.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.list_subgroups_accounts | def list_subgroups_accounts(self, id, account_id):
"""
List subgroups.
List the immediate OutcomeGroup children of the outcome group. Paginated.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
self.logger.debug("GET /api/v1/accounts/{account_id}/outcome_groups/{id}/subgroups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/accounts/{account_id}/outcome_groups/{id}/subgroups".format(**path), data=data, params=params, all_pages=True) | python | def list_subgroups_accounts(self, id, account_id):
"""
List subgroups.
List the immediate OutcomeGroup children of the outcome group. Paginated.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
self.logger.debug("GET /api/v1/accounts/{account_id}/outcome_groups/{id}/subgroups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/accounts/{account_id}/outcome_groups/{id}/subgroups".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/outcome_groups.py | OutcomeGroupsAPI.create_subgroup_global | def create_subgroup_global(self, id, title, description=None, vendor_guid=None):
"""
Create a subgroup.
Creates a new empty subgroup under the outcome group with the given title
and description.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - title
"""The title of the new outcome group."""
data["title"] = title
# OPTIONAL - description
"""The description of the new outcome group."""
if description is not None:
data["description"] = description
# OPTIONAL - vendor_guid
"""A custom GUID for the learning standard"""
if vendor_guid is not None:
data["vendor_guid"] = vendor_guid
self.logger.debug("POST /api/v1/global/outcome_groups/{id}/subgroups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/global/outcome_groups/{id}/subgroups".format(**path), data=data, params=params, single_item=True) | python | def create_subgroup_global(self, id, title, description=None, vendor_guid=None):
"""
Create a subgroup.
Creates a new empty subgroup under the outcome group with the given title
and description.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - title
"""The title of the new outcome group."""
data["title"] = title
# OPTIONAL - description
"""The description of the new outcome group."""
if description is not None:
data["description"] = description
# OPTIONAL - vendor_guid
"""A custom GUID for the learning standard"""
if vendor_guid is not None:
data["vendor_guid"] = vendor_guid
self.logger.debug("POST /api/v1/global/outcome_groups/{id}/subgroups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/global/outcome_groups/{id}/subgroups".format(**path), data=data, params=params, single_item=True) | [
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PGower/PyCanvas | pycanvas/apis/grading_periods.py | GradingPeriodsAPI.update_single_grading_period | def update_single_grading_period(self, id, course_id, grading_periods_end_date, grading_periods_start_date, grading_periods_weight=None):
"""
Update a single grading period.
Update an existing grading period.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - grading_periods[start_date]
"""The date the grading period starts."""
data["grading_periods[start_date]"] = grading_periods_start_date
# REQUIRED - grading_periods[end_date]
"""no description"""
data["grading_periods[end_date]"] = grading_periods_end_date
# OPTIONAL - grading_periods[weight]
"""A weight value that contributes to the overall weight of a grading period set which is used to calculate how much assignments in this period contribute to the total grade"""
if grading_periods_weight is not None:
data["grading_periods[weight]"] = grading_periods_weight
self.logger.debug("PUT /api/v1/courses/{course_id}/grading_periods/{id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("PUT", "/api/v1/courses/{course_id}/grading_periods/{id}".format(**path), data=data, params=params, no_data=True) | python | def update_single_grading_period(self, id, course_id, grading_periods_end_date, grading_periods_start_date, grading_periods_weight=None):
"""
Update a single grading period.
Update an existing grading period.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# REQUIRED - grading_periods[start_date]
"""The date the grading period starts."""
data["grading_periods[start_date]"] = grading_periods_start_date
# REQUIRED - grading_periods[end_date]
"""no description"""
data["grading_periods[end_date]"] = grading_periods_end_date
# OPTIONAL - grading_periods[weight]
"""A weight value that contributes to the overall weight of a grading period set which is used to calculate how much assignments in this period contribute to the total grade"""
if grading_periods_weight is not None:
data["grading_periods[weight]"] = grading_periods_weight
self.logger.debug("PUT /api/v1/courses/{course_id}/grading_periods/{id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("PUT", "/api/v1/courses/{course_id}/grading_periods/{id}".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/grading_periods.py | GradingPeriodsAPI.delete_grading_period_accounts | def delete_grading_period_accounts(self, id, account_id):
"""
Delete a grading period.
<b>204 No Content</b> response code is returned if the deletion was
successful.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
self.logger.debug("DELETE /api/v1/accounts/{account_id}/grading_periods/{id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("DELETE", "/api/v1/accounts/{account_id}/grading_periods/{id}".format(**path), data=data, params=params, no_data=True) | python | def delete_grading_period_accounts(self, id, account_id):
"""
Delete a grading period.
<b>204 No Content</b> response code is returned if the deletion was
successful.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - account_id
"""ID"""
path["account_id"] = account_id
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
self.logger.debug("DELETE /api/v1/accounts/{account_id}/grading_periods/{id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("DELETE", "/api/v1/accounts/{account_id}/grading_periods/{id}".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/appointment_groups.py | AppointmentGroupsAPI.list_appointment_groups | def list_appointment_groups(self, context_codes=None, include=None, include_past_appointments=None, scope=None):
"""
List appointment groups.
Retrieve the list of appointment groups that can be reserved or managed by
the current user.
"""
path = {}
data = {}
params = {}
# OPTIONAL - scope
"""Defaults to "reservable""""
if scope is not None:
self._validate_enum(scope, ["reservable", "manageable"])
params["scope"] = scope
# OPTIONAL - context_codes
"""Array of context codes used to limit returned results."""
if context_codes is not None:
params["context_codes"] = context_codes
# OPTIONAL - include_past_appointments
"""Defaults to false. If true, includes past appointment groups"""
if include_past_appointments is not None:
params["include_past_appointments"] = include_past_appointments
# OPTIONAL - include
"""Array of additional information to include.
"appointments":: calendar event time slots for this appointment group
"child_events":: reservations of those time slots
"participant_count":: number of reservations
"reserved_times":: the event id, start time and end time of reservations
the current user has made)
"all_context_codes":: all context codes associated with this appointment group"""
if include is not None:
self._validate_enum(include, ["appointments", "child_events", "participant_count", "reserved_times", "all_context_codes"])
params["include"] = include
self.logger.debug("GET /api/v1/appointment_groups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups".format(**path), data=data, params=params, no_data=True) | python | def list_appointment_groups(self, context_codes=None, include=None, include_past_appointments=None, scope=None):
"""
List appointment groups.
Retrieve the list of appointment groups that can be reserved or managed by
the current user.
"""
path = {}
data = {}
params = {}
# OPTIONAL - scope
"""Defaults to "reservable""""
if scope is not None:
self._validate_enum(scope, ["reservable", "manageable"])
params["scope"] = scope
# OPTIONAL - context_codes
"""Array of context codes used to limit returned results."""
if context_codes is not None:
params["context_codes"] = context_codes
# OPTIONAL - include_past_appointments
"""Defaults to false. If true, includes past appointment groups"""
if include_past_appointments is not None:
params["include_past_appointments"] = include_past_appointments
# OPTIONAL - include
"""Array of additional information to include.
"appointments":: calendar event time slots for this appointment group
"child_events":: reservations of those time slots
"participant_count":: number of reservations
"reserved_times":: the event id, start time and end time of reservations
the current user has made)
"all_context_codes":: all context codes associated with this appointment group"""
if include is not None:
self._validate_enum(include, ["appointments", "child_events", "participant_count", "reserved_times", "all_context_codes"])
params["include"] = include
self.logger.debug("GET /api/v1/appointment_groups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/appointment_groups.py | AppointmentGroupsAPI.create_appointment_group | def create_appointment_group(self, appointment_group_title, appointment_group_context_codes, appointment_group_description=None, appointment_group_location_address=None, appointment_group_location_name=None, appointment_group_max_appointments_per_participant=None, appointment_group_min_appointments_per_participant=None, appointment_group_new_appointments_X=None, appointment_group_participant_visibility=None, appointment_group_participants_per_appointment=None, appointment_group_publish=None, appointment_group_sub_context_codes=None):
"""
Create an appointment group.
Create and return a new appointment group. If new_appointments are
specified, the response will return a new_appointments array (same format
as appointments array, see "List appointment groups" action)
"""
path = {}
data = {}
params = {}
# REQUIRED - appointment_group[context_codes]
"""Array of context codes (courses, e.g. course_1) this group should be
linked to (1 or more). Users in the course(s) with appropriate permissions
will be able to sign up for this appointment group."""
data["appointment_group[context_codes]"] = appointment_group_context_codes
# OPTIONAL - appointment_group[sub_context_codes]
"""Array of sub context codes (course sections or a single group category)
this group should be linked to. Used to limit the appointment group to
particular sections. If a group category is specified, students will sign
up in groups and the participant_type will be "Group" instead of "User"."""
if appointment_group_sub_context_codes is not None:
data["appointment_group[sub_context_codes]"] = appointment_group_sub_context_codes
# REQUIRED - appointment_group[title]
"""Short title for the appointment group."""
data["appointment_group[title]"] = appointment_group_title
# OPTIONAL - appointment_group[description]
"""Longer text description of the appointment group."""
if appointment_group_description is not None:
data["appointment_group[description]"] = appointment_group_description
# OPTIONAL - appointment_group[location_name]
"""Location name of the appointment group."""
if appointment_group_location_name is not None:
data["appointment_group[location_name]"] = appointment_group_location_name
# OPTIONAL - appointment_group[location_address]
"""Location address."""
if appointment_group_location_address is not None:
data["appointment_group[location_address]"] = appointment_group_location_address
# OPTIONAL - appointment_group[publish]
"""Indicates whether this appointment group should be published (i.e. made
available for signup). Once published, an appointment group cannot be
unpublished. Defaults to false."""
if appointment_group_publish is not None:
data["appointment_group[publish]"] = appointment_group_publish
# OPTIONAL - appointment_group[participants_per_appointment]
"""Maximum number of participants that may register for each time slot.
Defaults to null (no limit)."""
if appointment_group_participants_per_appointment is not None:
data["appointment_group[participants_per_appointment]"] = appointment_group_participants_per_appointment
# OPTIONAL - appointment_group[min_appointments_per_participant]
"""Minimum number of time slots a user must register for. If not set, users
do not need to sign up for any time slots."""
if appointment_group_min_appointments_per_participant is not None:
data["appointment_group[min_appointments_per_participant]"] = appointment_group_min_appointments_per_participant
# OPTIONAL - appointment_group[max_appointments_per_participant]
"""Maximum number of time slots a user may register for."""
if appointment_group_max_appointments_per_participant is not None:
data["appointment_group[max_appointments_per_participant]"] = appointment_group_max_appointments_per_participant
# OPTIONAL - appointment_group[new_appointments][X]
"""Nested array of start time/end time pairs indicating time slots for this
appointment group. Refer to the example request."""
if appointment_group_new_appointments_X is not None:
data["appointment_group[new_appointments][X]"] = appointment_group_new_appointments_X
# OPTIONAL - appointment_group[participant_visibility]
""""private":: participants cannot see who has signed up for a particular
time slot
"protected":: participants can see who has signed up. Defaults to
"private"."""
if appointment_group_participant_visibility is not None:
self._validate_enum(appointment_group_participant_visibility, ["private", "protected"])
data["appointment_group[participant_visibility]"] = appointment_group_participant_visibility
self.logger.debug("POST /api/v1/appointment_groups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/appointment_groups".format(**path), data=data, params=params, no_data=True) | python | def create_appointment_group(self, appointment_group_title, appointment_group_context_codes, appointment_group_description=None, appointment_group_location_address=None, appointment_group_location_name=None, appointment_group_max_appointments_per_participant=None, appointment_group_min_appointments_per_participant=None, appointment_group_new_appointments_X=None, appointment_group_participant_visibility=None, appointment_group_participants_per_appointment=None, appointment_group_publish=None, appointment_group_sub_context_codes=None):
"""
Create an appointment group.
Create and return a new appointment group. If new_appointments are
specified, the response will return a new_appointments array (same format
as appointments array, see "List appointment groups" action)
"""
path = {}
data = {}
params = {}
# REQUIRED - appointment_group[context_codes]
"""Array of context codes (courses, e.g. course_1) this group should be
linked to (1 or more). Users in the course(s) with appropriate permissions
will be able to sign up for this appointment group."""
data["appointment_group[context_codes]"] = appointment_group_context_codes
# OPTIONAL - appointment_group[sub_context_codes]
"""Array of sub context codes (course sections or a single group category)
this group should be linked to. Used to limit the appointment group to
particular sections. If a group category is specified, students will sign
up in groups and the participant_type will be "Group" instead of "User"."""
if appointment_group_sub_context_codes is not None:
data["appointment_group[sub_context_codes]"] = appointment_group_sub_context_codes
# REQUIRED - appointment_group[title]
"""Short title for the appointment group."""
data["appointment_group[title]"] = appointment_group_title
# OPTIONAL - appointment_group[description]
"""Longer text description of the appointment group."""
if appointment_group_description is not None:
data["appointment_group[description]"] = appointment_group_description
# OPTIONAL - appointment_group[location_name]
"""Location name of the appointment group."""
if appointment_group_location_name is not None:
data["appointment_group[location_name]"] = appointment_group_location_name
# OPTIONAL - appointment_group[location_address]
"""Location address."""
if appointment_group_location_address is not None:
data["appointment_group[location_address]"] = appointment_group_location_address
# OPTIONAL - appointment_group[publish]
"""Indicates whether this appointment group should be published (i.e. made
available for signup). Once published, an appointment group cannot be
unpublished. Defaults to false."""
if appointment_group_publish is not None:
data["appointment_group[publish]"] = appointment_group_publish
# OPTIONAL - appointment_group[participants_per_appointment]
"""Maximum number of participants that may register for each time slot.
Defaults to null (no limit)."""
if appointment_group_participants_per_appointment is not None:
data["appointment_group[participants_per_appointment]"] = appointment_group_participants_per_appointment
# OPTIONAL - appointment_group[min_appointments_per_participant]
"""Minimum number of time slots a user must register for. If not set, users
do not need to sign up for any time slots."""
if appointment_group_min_appointments_per_participant is not None:
data["appointment_group[min_appointments_per_participant]"] = appointment_group_min_appointments_per_participant
# OPTIONAL - appointment_group[max_appointments_per_participant]
"""Maximum number of time slots a user may register for."""
if appointment_group_max_appointments_per_participant is not None:
data["appointment_group[max_appointments_per_participant]"] = appointment_group_max_appointments_per_participant
# OPTIONAL - appointment_group[new_appointments][X]
"""Nested array of start time/end time pairs indicating time slots for this
appointment group. Refer to the example request."""
if appointment_group_new_appointments_X is not None:
data["appointment_group[new_appointments][X]"] = appointment_group_new_appointments_X
# OPTIONAL - appointment_group[participant_visibility]
""""private":: participants cannot see who has signed up for a particular
time slot
"protected":: participants can see who has signed up. Defaults to
"private"."""
if appointment_group_participant_visibility is not None:
self._validate_enum(appointment_group_participant_visibility, ["private", "protected"])
data["appointment_group[participant_visibility]"] = appointment_group_participant_visibility
self.logger.debug("POST /api/v1/appointment_groups with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/appointment_groups".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/appointment_groups.py | AppointmentGroupsAPI.list_user_participants | def list_user_participants(self, id, registration_status=None):
"""
List user participants.
List users that are (or may be) participating in this appointment group.
Refer to the Users API for the response fields. Returns no results for
appointment groups with the "Group" participant_type.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# OPTIONAL - registration_status
"""Limits results to the a given participation status, defaults to "all""""
if registration_status is not None:
self._validate_enum(registration_status, ["all", "registered", "registered"])
params["registration_status"] = registration_status
self.logger.debug("GET /api/v1/appointment_groups/{id}/users with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups/{id}/users".format(**path), data=data, params=params, no_data=True) | python | def list_user_participants(self, id, registration_status=None):
"""
List user participants.
List users that are (or may be) participating in this appointment group.
Refer to the Users API for the response fields. Returns no results for
appointment groups with the "Group" participant_type.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# OPTIONAL - registration_status
"""Limits results to the a given participation status, defaults to "all""""
if registration_status is not None:
self._validate_enum(registration_status, ["all", "registered", "registered"])
params["registration_status"] = registration_status
self.logger.debug("GET /api/v1/appointment_groups/{id}/users with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups/{id}/users".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/appointment_groups.py | AppointmentGroupsAPI.get_next_appointment | def get_next_appointment(self, appointment_group_ids=None):
"""
Get next appointment.
Return the next appointment available to sign up for. The appointment
is returned in a one-element array. If no future appointments are
available, an empty array is returned.
"""
path = {}
data = {}
params = {}
# OPTIONAL - appointment_group_ids
"""List of ids of appointment groups to search."""
if appointment_group_ids is not None:
params["appointment_group_ids"] = appointment_group_ids
self.logger.debug("GET /api/v1/appointment_groups/next_appointment with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups/next_appointment".format(**path), data=data, params=params, all_pages=True) | python | def get_next_appointment(self, appointment_group_ids=None):
"""
Get next appointment.
Return the next appointment available to sign up for. The appointment
is returned in a one-element array. If no future appointments are
available, an empty array is returned.
"""
path = {}
data = {}
params = {}
# OPTIONAL - appointment_group_ids
"""List of ids of appointment groups to search."""
if appointment_group_ids is not None:
params["appointment_group_ids"] = appointment_group_ids
self.logger.debug("GET /api/v1/appointment_groups/next_appointment with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/appointment_groups/next_appointment".format(**path), data=data, params=params, all_pages=True) | [
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bioasp/caspo | caspo/core/dataset.py | Dataset.to_funset | def to_funset(self, discrete):
"""
Converts the dataset to a set of `gringo.Fun`_ instances
Parameters
----------
discrete : callable
A discretization function
Returns
-------
set
Representation of the dataset as a set of `gringo.Fun`_ instances
.. _gringo.Fun: http://potassco.sourceforge.net/gringo.html#Fun
"""
fs = self.clampings.to_funset("exp")
fs = fs.union(self.setup.to_funset())
for i, row in self.readouts.iterrows():
for var, val in row.iteritems():
if not np.isnan(val):
fs.add(gringo.Fun('obs', [i, var, discrete(val)]))
return fs | python | def to_funset(self, discrete):
"""
Converts the dataset to a set of `gringo.Fun`_ instances
Parameters
----------
discrete : callable
A discretization function
Returns
-------
set
Representation of the dataset as a set of `gringo.Fun`_ instances
.. _gringo.Fun: http://potassco.sourceforge.net/gringo.html#Fun
"""
fs = self.clampings.to_funset("exp")
fs = fs.union(self.setup.to_funset())
for i, row in self.readouts.iterrows():
for var, val in row.iteritems():
if not np.isnan(val):
fs.add(gringo.Fun('obs', [i, var, discrete(val)]))
return fs | [
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bharadwaj-raju/libdesktop | libdesktop/dialog/files.py | open_file | def open_file(default_dir='~', extensions=None,
title='Choose a file', multiple_files=False, directory=False):
'''Start the native file dialog for opening file(s).
Starts the system native file dialog in order to open a file (or multiple files).
The toolkit used for each platform:
+-------------------------------------+------------------------------+
| Windows | Windows API (Win32) |
+-------------------------------------+------------------------------+
| Mac OS X | Cocoa |
+-------------------------------------+------------------------------+
| GNOME, Unity, Cinnamon, Pantheon | GTK+ 3 |
+-------------------------------------+------------------------------+
| KDE, LXQt | Qt 5 (fallback: Qt 4/GTK+ 3) |
+-------------------------------------+------------------------------+
| Other desktops (Xfce, WMs etc) | GTK+ 2 (fallback: GTK+ 3) |
+-------------------------------------+------------------------------+
**Note on Dependencies**
It depends on pywin32 for Windows (installed by default in Python for Windows)
It depends on `PyQt <https://riverbankcomputing.com/software/pyqt>`_ for KDE and LxQt (usually installed by default on these).
It depends on `PyGObject <https://wiki.gnome.org/Projects/PyGObject>`_ for GNOME etc. (virtually every Linux desktop has this).
It depends on `PyGTK <https://pygtk.org>`_ for other desktops (not usually installed, so has a GTK+ 3 fallback).
Args:
default_dir (str) : The directory to start the dialog in. Default: User home directory.
extensions (dict) : The extensions to filter by. Format:
.. code-block:: python
{
'Filter Name (example: Image Files)': ['*.png', '*.whatever', '*']
}
title (str) : The title of the dialog. Default: `Choose a file`
multiple_files (bool): Whether to choose multiple files or single files only. Default: `False`
directory (bool): Whether to choose directories. Default: `False`
Returns:
list: `list` of `str` s (each `str` being a selected file). If nothing is selected/dialog is cancelled, it is `None`.
'''
default_dir = os.path.expanduser(default_dir)
if not extensions:
extensions = {}
if system.get_name() == 'windows':
pass # TODO: Implement Win32 file dialog
elif system.get_name() == 'mac':
pass # TODO: Implement Cocoa file dialog
else:
def gtk3_dialog():
# GTK+ 3
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk
class FileChooserWindow(Gtk.Window):
def __init__(self):
self.path = ''
Gtk.Window.__init__(self, title='')
dialog = Gtk.FileChooserDialog(title, None,
Gtk.FileChooserAction.OPEN,
(Gtk.STOCK_CANCEL,
Gtk.ResponseType.CANCEL,
Gtk.STOCK_OPEN,
Gtk.ResponseType.OK)
)
if extensions:
for entry in extensions:
file_filter = Gtk.FileFilter()
file_filter.set_name(entry)
for pattern in extensions[entry]:
file_filter.add_pattern(pattern)
dialog.add_filter(file_filter)
dialog.set_select_multiple(multiple_files)
dialog.set_current_folder(default_dir)
response = dialog.run()
if response == Gtk.ResponseType.OK:
self.path = dialog.get_filenames()
dialog.destroy()
elif response == Gtk.ResponseType.CANCEL:
self.path = None
dialog.destroy()
win = FileChooserWindow()
win.connect('destroy', Gtk.main_quit)
win.connect('delete-event', Gtk.main_quit)
win.show_all()
win.destroy()
win.close()
return win.path
def qt5_dialog():
# Qt 5
try:
from PyQt5 import Qt
except ImportError:
# The API is the same for what this uses
from PyQt4 import Qt
class FileChooserWindow(Qt.QWidget):
def __init__(self):
super().__init__()
extensions_string = ''
if extensions:
for entry in extensions:
# entry → Filter name (i.e. 'Image Files' etc)
# value → Filter expression (i.e. '*.png, *.jpg'
# etc)
extensions_string += '%s (%s);;' % (entry,
' '.join(extensions[entry]))
else:
extensions_string = 'All Files (*)'
dialog = Qt.QFileDialog()
if multiple_files:
dialog.setFileMode(Qt.QFileDialog.ExistingFiles)
if directory:
dialog.setFileMode(Qt.QFileDialog.Directory)
dialog.setWindowTitle(title)
dialog.setDirectory(default_dir)
dialog.setNameFilter(extensions_string)
if dialog.exec_():
self.path = dialog.selectedFiles()
else:
self.path = None
app = Qt.QApplication(sys.argv)
win = FileChooserWindow()
win.close()
if win.path:
return win.path
else:
return None
app.exec_()
def gtk2_dialog():
# GTK+ 2
import pygtk
pygtk.require('2.0')
dialog = gtk.FileChooserDialog(title, None,
gtk.FILE_CHOOSER_ACTION_OPEN,
(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_OPEN, gtk.RESPONSE_OK))
dialog.set_default_response(gtk.RESPONSE_OK)
if extensions:
for entry in extensions:
file_filter = gtk.FileFilter()
file_filter.set_name(entry)
for pattern in extensions[entry]:
file_filter.add_pattern(pattern)
dialog.add_filter(file_filter)
dialog.set_select_multiple(multiple_files)
response = dialog.run()
if response == gtk.RESPONSE_OK:
return dialog.get_filenames()
elif response == gtk.RESPONSE_CANCEL:
return None
dialog.destroy()
if system.get_name() in ['gnome', 'unity', 'cinnamon', 'pantheon']:
return gtk3_dialog()
elif system.get_name() in ['kde', 'lxqt']:
try:
return qt5_dialog()
except ImportError:
return gtk3_dialog()
else:
try:
return gtk2_dialog()
except ImportError:
return gtk3_dialog() | python | def open_file(default_dir='~', extensions=None,
title='Choose a file', multiple_files=False, directory=False):
'''Start the native file dialog for opening file(s).
Starts the system native file dialog in order to open a file (or multiple files).
The toolkit used for each platform:
+-------------------------------------+------------------------------+
| Windows | Windows API (Win32) |
+-------------------------------------+------------------------------+
| Mac OS X | Cocoa |
+-------------------------------------+------------------------------+
| GNOME, Unity, Cinnamon, Pantheon | GTK+ 3 |
+-------------------------------------+------------------------------+
| KDE, LXQt | Qt 5 (fallback: Qt 4/GTK+ 3) |
+-------------------------------------+------------------------------+
| Other desktops (Xfce, WMs etc) | GTK+ 2 (fallback: GTK+ 3) |
+-------------------------------------+------------------------------+
**Note on Dependencies**
It depends on pywin32 for Windows (installed by default in Python for Windows)
It depends on `PyQt <https://riverbankcomputing.com/software/pyqt>`_ for KDE and LxQt (usually installed by default on these).
It depends on `PyGObject <https://wiki.gnome.org/Projects/PyGObject>`_ for GNOME etc. (virtually every Linux desktop has this).
It depends on `PyGTK <https://pygtk.org>`_ for other desktops (not usually installed, so has a GTK+ 3 fallback).
Args:
default_dir (str) : The directory to start the dialog in. Default: User home directory.
extensions (dict) : The extensions to filter by. Format:
.. code-block:: python
{
'Filter Name (example: Image Files)': ['*.png', '*.whatever', '*']
}
title (str) : The title of the dialog. Default: `Choose a file`
multiple_files (bool): Whether to choose multiple files or single files only. Default: `False`
directory (bool): Whether to choose directories. Default: `False`
Returns:
list: `list` of `str` s (each `str` being a selected file). If nothing is selected/dialog is cancelled, it is `None`.
'''
default_dir = os.path.expanduser(default_dir)
if not extensions:
extensions = {}
if system.get_name() == 'windows':
pass # TODO: Implement Win32 file dialog
elif system.get_name() == 'mac':
pass # TODO: Implement Cocoa file dialog
else:
def gtk3_dialog():
# GTK+ 3
import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk
class FileChooserWindow(Gtk.Window):
def __init__(self):
self.path = ''
Gtk.Window.__init__(self, title='')
dialog = Gtk.FileChooserDialog(title, None,
Gtk.FileChooserAction.OPEN,
(Gtk.STOCK_CANCEL,
Gtk.ResponseType.CANCEL,
Gtk.STOCK_OPEN,
Gtk.ResponseType.OK)
)
if extensions:
for entry in extensions:
file_filter = Gtk.FileFilter()
file_filter.set_name(entry)
for pattern in extensions[entry]:
file_filter.add_pattern(pattern)
dialog.add_filter(file_filter)
dialog.set_select_multiple(multiple_files)
dialog.set_current_folder(default_dir)
response = dialog.run()
if response == Gtk.ResponseType.OK:
self.path = dialog.get_filenames()
dialog.destroy()
elif response == Gtk.ResponseType.CANCEL:
self.path = None
dialog.destroy()
win = FileChooserWindow()
win.connect('destroy', Gtk.main_quit)
win.connect('delete-event', Gtk.main_quit)
win.show_all()
win.destroy()
win.close()
return win.path
def qt5_dialog():
# Qt 5
try:
from PyQt5 import Qt
except ImportError:
# The API is the same for what this uses
from PyQt4 import Qt
class FileChooserWindow(Qt.QWidget):
def __init__(self):
super().__init__()
extensions_string = ''
if extensions:
for entry in extensions:
# entry → Filter name (i.e. 'Image Files' etc)
# value → Filter expression (i.e. '*.png, *.jpg'
# etc)
extensions_string += '%s (%s);;' % (entry,
' '.join(extensions[entry]))
else:
extensions_string = 'All Files (*)'
dialog = Qt.QFileDialog()
if multiple_files:
dialog.setFileMode(Qt.QFileDialog.ExistingFiles)
if directory:
dialog.setFileMode(Qt.QFileDialog.Directory)
dialog.setWindowTitle(title)
dialog.setDirectory(default_dir)
dialog.setNameFilter(extensions_string)
if dialog.exec_():
self.path = dialog.selectedFiles()
else:
self.path = None
app = Qt.QApplication(sys.argv)
win = FileChooserWindow()
win.close()
if win.path:
return win.path
else:
return None
app.exec_()
def gtk2_dialog():
# GTK+ 2
import pygtk
pygtk.require('2.0')
dialog = gtk.FileChooserDialog(title, None,
gtk.FILE_CHOOSER_ACTION_OPEN,
(gtk.STOCK_CANCEL, gtk.RESPONSE_CANCEL,
gtk.STOCK_OPEN, gtk.RESPONSE_OK))
dialog.set_default_response(gtk.RESPONSE_OK)
if extensions:
for entry in extensions:
file_filter = gtk.FileFilter()
file_filter.set_name(entry)
for pattern in extensions[entry]:
file_filter.add_pattern(pattern)
dialog.add_filter(file_filter)
dialog.set_select_multiple(multiple_files)
response = dialog.run()
if response == gtk.RESPONSE_OK:
return dialog.get_filenames()
elif response == gtk.RESPONSE_CANCEL:
return None
dialog.destroy()
if system.get_name() in ['gnome', 'unity', 'cinnamon', 'pantheon']:
return gtk3_dialog()
elif system.get_name() in ['kde', 'lxqt']:
try:
return qt5_dialog()
except ImportError:
return gtk3_dialog()
else:
try:
return gtk2_dialog()
except ImportError:
return gtk3_dialog() | [
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"expanduser... | Start the native file dialog for opening file(s).
Starts the system native file dialog in order to open a file (or multiple files).
The toolkit used for each platform:
+-------------------------------------+------------------------------+
| Windows | Windows API (Win32) |
+-------------------------------------+------------------------------+
| Mac OS X | Cocoa |
+-------------------------------------+------------------------------+
| GNOME, Unity, Cinnamon, Pantheon | GTK+ 3 |
+-------------------------------------+------------------------------+
| KDE, LXQt | Qt 5 (fallback: Qt 4/GTK+ 3) |
+-------------------------------------+------------------------------+
| Other desktops (Xfce, WMs etc) | GTK+ 2 (fallback: GTK+ 3) |
+-------------------------------------+------------------------------+
**Note on Dependencies**
It depends on pywin32 for Windows (installed by default in Python for Windows)
It depends on `PyQt <https://riverbankcomputing.com/software/pyqt>`_ for KDE and LxQt (usually installed by default on these).
It depends on `PyGObject <https://wiki.gnome.org/Projects/PyGObject>`_ for GNOME etc. (virtually every Linux desktop has this).
It depends on `PyGTK <https://pygtk.org>`_ for other desktops (not usually installed, so has a GTK+ 3 fallback).
Args:
default_dir (str) : The directory to start the dialog in. Default: User home directory.
extensions (dict) : The extensions to filter by. Format:
.. code-block:: python
{
'Filter Name (example: Image Files)': ['*.png', '*.whatever', '*']
}
title (str) : The title of the dialog. Default: `Choose a file`
multiple_files (bool): Whether to choose multiple files or single files only. Default: `False`
directory (bool): Whether to choose directories. Default: `False`
Returns:
list: `list` of `str` s (each `str` being a selected file). If nothing is selected/dialog is cancelled, it is `None`. | [
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mrstephenneal/mysql-toolkit | mysql/toolkit/commands/dump.py | set_dump_directory | def set_dump_directory(base=None, sub_dir=None):
"""Create directory for dumping SQL commands."""
# Set current timestamp
timestamp = datetime.fromtimestamp(time()).strftime('%Y-%m-%d %H-%M-%S')
# Clean sub_dir
if sub_dir and '.' in sub_dir:
sub_dir = sub_dir.rsplit('.', 1)[0]
# Create a directory to save fail SQL scripts
# TODO: Replace with function that recursively creates directories until path exists
if not os.path.exists(base):
os.mkdir(base)
dump_dir = os.path.join(base, sub_dir) if sub_dir else base
if not os.path.exists(dump_dir):
os.mkdir(dump_dir)
dump_dir = os.path.join(dump_dir, timestamp)
if not os.path.exists(dump_dir):
os.mkdir(dump_dir)
return dump_dir | python | def set_dump_directory(base=None, sub_dir=None):
"""Create directory for dumping SQL commands."""
# Set current timestamp
timestamp = datetime.fromtimestamp(time()).strftime('%Y-%m-%d %H-%M-%S')
# Clean sub_dir
if sub_dir and '.' in sub_dir:
sub_dir = sub_dir.rsplit('.', 1)[0]
# Create a directory to save fail SQL scripts
# TODO: Replace with function that recursively creates directories until path exists
if not os.path.exists(base):
os.mkdir(base)
dump_dir = os.path.join(base, sub_dir) if sub_dir else base
if not os.path.exists(dump_dir):
os.mkdir(dump_dir)
dump_dir = os.path.join(dump_dir, timestamp)
if not os.path.exists(dump_dir):
os.mkdir(dump_dir)
return dump_dir | [
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mrstephenneal/mysql-toolkit | mysql/toolkit/commands/dump.py | dump_commands | def dump_commands(commands, directory=None, sub_dir=None):
"""
Dump SQL commands to .sql files.
:param commands: List of SQL commands
:param directory: Directory to dump commands to
:param sub_dir: Sub directory
:return: Directory failed commands were dumped to
"""
print('\t' + str(len(commands)), 'failed commands')
# Create dump_dir directory
if directory and os.path.isfile(directory):
dump_dir = set_dump_directory(os.path.dirname(directory), sub_dir)
return_dir = dump_dir
elif directory:
dump_dir = set_dump_directory(directory, sub_dir)
return_dir = dump_dir
else:
dump_dir = TemporaryDirectory().name
return_dir = TemporaryDirectory()
# Create list of (path, content) tuples
command_filepath = [(fail, os.path.join(dump_dir, str(count) + '.sql')) for count, fail in enumerate(commands)]
# Dump failed commands to text file in the same directory as the commands
# Utilize's multiprocessing module if it is available
timer = Timer()
if MULTIPROCESS:
pool = Pool(cpu_count())
pool.map(write_text_tup, command_filepath)
pool.close()
print('\tDumped ', len(command_filepath), 'commands\n\t\tTime : {0}'.format(timer.end),
'\n\t\tMethod : (multiprocessing)\n\t\tDirectory : {0}'.format(dump_dir))
else:
for tup in command_filepath:
write_text_tup(tup)
print('\tDumped ', len(command_filepath), 'commands\n\t\tTime : {0}'.format(timer.end),
'\n\t\tMethod : (sequential)\n\t\tDirectory : {0}'.format(dump_dir))
# Return base directory of dumped commands
return return_dir | python | def dump_commands(commands, directory=None, sub_dir=None):
"""
Dump SQL commands to .sql files.
:param commands: List of SQL commands
:param directory: Directory to dump commands to
:param sub_dir: Sub directory
:return: Directory failed commands were dumped to
"""
print('\t' + str(len(commands)), 'failed commands')
# Create dump_dir directory
if directory and os.path.isfile(directory):
dump_dir = set_dump_directory(os.path.dirname(directory), sub_dir)
return_dir = dump_dir
elif directory:
dump_dir = set_dump_directory(directory, sub_dir)
return_dir = dump_dir
else:
dump_dir = TemporaryDirectory().name
return_dir = TemporaryDirectory()
# Create list of (path, content) tuples
command_filepath = [(fail, os.path.join(dump_dir, str(count) + '.sql')) for count, fail in enumerate(commands)]
# Dump failed commands to text file in the same directory as the commands
# Utilize's multiprocessing module if it is available
timer = Timer()
if MULTIPROCESS:
pool = Pool(cpu_count())
pool.map(write_text_tup, command_filepath)
pool.close()
print('\tDumped ', len(command_filepath), 'commands\n\t\tTime : {0}'.format(timer.end),
'\n\t\tMethod : (multiprocessing)\n\t\tDirectory : {0}'.format(dump_dir))
else:
for tup in command_filepath:
write_text_tup(tup)
print('\tDumped ', len(command_filepath), 'commands\n\t\tTime : {0}'.format(timer.end),
'\n\t\tMethod : (sequential)\n\t\tDirectory : {0}'.format(dump_dir))
# Return base directory of dumped commands
return return_dir | [
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mrstephenneal/mysql-toolkit | mysql/toolkit/commands/dump.py | write_text | def write_text(_command, txt_file):
"""Dump SQL command to a text file."""
command = _command.strip()
with open(txt_file, 'w') as txt:
txt.writelines(command) | python | def write_text(_command, txt_file):
"""Dump SQL command to a text file."""
command = _command.strip()
with open(txt_file, 'w') as txt:
txt.writelines(command) | [
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mrstephenneal/mysql-toolkit | mysql/toolkit/commands/dump.py | get_commands_from_dir | def get_commands_from_dir(directory, zip_backup=True, remove_dir=True):
"""Traverse a directory and read contained SQL files."""
# Get SQL commands file paths
failed_scripts = sorted([os.path.join(directory, fn) for fn in os.listdir(directory) if fn.endswith('.sql')])
# Read each failed SQL file and append contents to a list
print('\tReading SQL scripts from files')
commands = []
for sql_file in failed_scripts:
with open(sql_file, 'r') as txt:
sql_command = txt.read()
commands.append(sql_command)
# Remove most recent failures folder after reading
if zip_backup:
ZipBackup(directory).backup()
if remove_dir:
shutil.rmtree(directory)
return commands | python | def get_commands_from_dir(directory, zip_backup=True, remove_dir=True):
"""Traverse a directory and read contained SQL files."""
# Get SQL commands file paths
failed_scripts = sorted([os.path.join(directory, fn) for fn in os.listdir(directory) if fn.endswith('.sql')])
# Read each failed SQL file and append contents to a list
print('\tReading SQL scripts from files')
commands = []
for sql_file in failed_scripts:
with open(sql_file, 'r') as txt:
sql_command = txt.read()
commands.append(sql_command)
# Remove most recent failures folder after reading
if zip_backup:
ZipBackup(directory).backup()
if remove_dir:
shutil.rmtree(directory)
return commands | [
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anomaly/prestans | prestans/parser/parameter_set.py | ParameterSet.blueprint | def blueprint(self):
"""
blueprint support, returns a partial dictionary
"""
blueprint = dict()
blueprint['type'] = "%s.%s" % (self.__module__, self.__class__.__name__)
# Fields
fields = dict()
# inspects the attributes of a parameter set and tries to validate the input
for attribute_name, type_instance in self.getmembers():
# must be one of the following types
if not isinstance(type_instance, String) and \
not isinstance(type_instance, Float) and \
not isinstance(type_instance, Integer) and \
not isinstance(type_instance, Date) and \
not isinstance(type_instance, DateTime) and \
not isinstance(type_instance, Array):
raise TypeError("%s should be instance of\
prestans.types.String/Integer/Float/Date/DateTime/Array" % attribute_name)
if isinstance(type_instance, Array):
if not isinstance(type_instance.element_template, String) and \
not isinstance(type_instance.element_template, Float) and \
not isinstance(type_instance.element_template, Integer):
raise TypeError("%s should be instance of \
prestans.types.String/Integer/Float/Array" % attribute_name)
fields[attribute_name] = type_instance.blueprint()
blueprint['fields'] = fields
return blueprint | python | def blueprint(self):
"""
blueprint support, returns a partial dictionary
"""
blueprint = dict()
blueprint['type'] = "%s.%s" % (self.__module__, self.__class__.__name__)
# Fields
fields = dict()
# inspects the attributes of a parameter set and tries to validate the input
for attribute_name, type_instance in self.getmembers():
# must be one of the following types
if not isinstance(type_instance, String) and \
not isinstance(type_instance, Float) and \
not isinstance(type_instance, Integer) and \
not isinstance(type_instance, Date) and \
not isinstance(type_instance, DateTime) and \
not isinstance(type_instance, Array):
raise TypeError("%s should be instance of\
prestans.types.String/Integer/Float/Date/DateTime/Array" % attribute_name)
if isinstance(type_instance, Array):
if not isinstance(type_instance.element_template, String) and \
not isinstance(type_instance.element_template, Float) and \
not isinstance(type_instance.element_template, Integer):
raise TypeError("%s should be instance of \
prestans.types.String/Integer/Float/Array" % attribute_name)
fields[attribute_name] = type_instance.blueprint()
blueprint['fields'] = fields
return blueprint | [
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anomaly/prestans | prestans/parser/parameter_set.py | ParameterSet.validate | def validate(self, request):
"""
validate method for %ParameterSet
Since the introduction of ResponseFieldListParser, the parameter _response_field_list
will be ignored, this is a prestans reserved parameter, and cannot be used by apps.
:param request: The request object to be validated
:type request: webob.request.Request
:return The validated parameter set
:rtype: ParameterSet
"""
validated_parameter_set = self.__class__()
# Inspects the attributes of a parameter set and tries to validate the input
for attribute_name, type_instance in self.getmembers():
#: Must be one of the following types
if not isinstance(type_instance, String) and \
not isinstance(type_instance, Float) and \
not isinstance(type_instance, Integer) and \
not isinstance(type_instance, Date) and \
not isinstance(type_instance, DateTime) and \
not isinstance(type_instance, Array):
raise TypeError("%s should be of type \
prestans.types.String/Integer/Float/Date/DateTime/Array" % attribute_name)
if issubclass(type_instance.__class__, Array):
if not isinstance(type_instance.element_template, String) and \
not isinstance(type_instance.element_template, Float) and \
not isinstance(type_instance.element_template, Integer):
raise TypeError("%s elements should be of \
type prestans.types.String/Integer/Float" % attribute_name)
try:
#: Get input from parameters
#: Empty list returned if key is missing for getall
if issubclass(type_instance.__class__, Array):
validation_input = request.params.getall(attribute_name)
#: Key error thrown if key is missing for getone
else:
try:
validation_input = request.params.getone(attribute_name)
except KeyError:
validation_input = None
#: Validate input based on data type rules,
#: raises DataTypeValidationException if validation fails
validation_result = type_instance.validate(validation_input)
setattr(validated_parameter_set, attribute_name, validation_result)
except exception.DataValidationException as exp:
raise exception.ValidationError(
message=str(exp),
attribute_name=attribute_name,
value=validation_input,
blueprint=type_instance.blueprint())
return validated_parameter_set | python | def validate(self, request):
"""
validate method for %ParameterSet
Since the introduction of ResponseFieldListParser, the parameter _response_field_list
will be ignored, this is a prestans reserved parameter, and cannot be used by apps.
:param request: The request object to be validated
:type request: webob.request.Request
:return The validated parameter set
:rtype: ParameterSet
"""
validated_parameter_set = self.__class__()
# Inspects the attributes of a parameter set and tries to validate the input
for attribute_name, type_instance in self.getmembers():
#: Must be one of the following types
if not isinstance(type_instance, String) and \
not isinstance(type_instance, Float) and \
not isinstance(type_instance, Integer) and \
not isinstance(type_instance, Date) and \
not isinstance(type_instance, DateTime) and \
not isinstance(type_instance, Array):
raise TypeError("%s should be of type \
prestans.types.String/Integer/Float/Date/DateTime/Array" % attribute_name)
if issubclass(type_instance.__class__, Array):
if not isinstance(type_instance.element_template, String) and \
not isinstance(type_instance.element_template, Float) and \
not isinstance(type_instance.element_template, Integer):
raise TypeError("%s elements should be of \
type prestans.types.String/Integer/Float" % attribute_name)
try:
#: Get input from parameters
#: Empty list returned if key is missing for getall
if issubclass(type_instance.__class__, Array):
validation_input = request.params.getall(attribute_name)
#: Key error thrown if key is missing for getone
else:
try:
validation_input = request.params.getone(attribute_name)
except KeyError:
validation_input = None
#: Validate input based on data type rules,
#: raises DataTypeValidationException if validation fails
validation_result = type_instance.validate(validation_input)
setattr(validated_parameter_set, attribute_name, validation_result)
except exception.DataValidationException as exp:
raise exception.ValidationError(
message=str(exp),
attribute_name=attribute_name,
value=validation_input,
blueprint=type_instance.blueprint())
return validated_parameter_set | [
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Since the introduction of ResponseFieldListParser, the parameter _response_field_list
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:param request: The request object to be validated
:type request: webob.request.Request
:return The validated parameter set
:rtype: ParameterSet | [
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Rockhopper-Technologies/pluginlib | pluginlib/_parent.py | _check_methods | def _check_methods(cls, subclass): # pylint: disable=too-many-branches
"""
Args:
cls(:py:class:`Plugin`): Parent class
subclass(:py:class:`Plugin`): Subclass to evaluate
Returns:
Result: Named tuple
Validate abstract methods are defined in subclass
For error codes see _inspect_class
"""
for meth, methobj in cls.__abstractmethods__.items():
# Need to get attribute from dictionary for instance tests to work
for base in subclass.__mro__: # pragma: no branch
if meth in base.__dict__:
submethobj = base.__dict__[meth]
break
# If we found our abstract method, we didn't find anything
if submethobj is methobj:
submethobj = UNDEFINED
# Determine if we have the right method type
result = None
bad_arg_spec = 'Argument spec does not match parent for method %s'
# pylint: disable=deprecated-method
if isinstance(methobj, property):
if submethobj is UNDEFINED or not isinstance(submethobj, property):
result = Result(False, 'Does not contain required property (%s)' % meth, 210)
elif isinstance(methobj, staticmethod):
if submethobj is UNDEFINED or not isinstance(submethobj, staticmethod):
result = Result(False, 'Does not contain required static method (%s)' % meth, 211)
elif PY26: # pragma: no cover
if getfullargspec(methobj.__get__(True)) != \
getfullargspec(submethobj.__get__(True)):
result = Result(False, bad_arg_spec % meth, 220)
elif getfullargspec(methobj.__func__) != getfullargspec(submethobj.__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif isinstance(methobj, classmethod):
if submethobj is UNDEFINED or not isinstance(submethobj, classmethod):
result = Result(False, 'Does not contain required class method (%s)' % meth, 212)
elif PY26: # pragma: no cover
if getfullargspec(methobj.__get__(True).__func__) != \
getfullargspec(submethobj.__get__(True).__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif getfullargspec(methobj.__func__) != getfullargspec(submethobj.__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif isfunction(methobj):
if submethobj is UNDEFINED or not isfunction(submethobj):
result = Result(False, 'Does not contain required method (%s)' % meth, 213)
elif getfullargspec(methobj) != getfullargspec(submethobj):
result = Result(False, bad_arg_spec % meth, 220)
# If it's not a type we're specifically checking, just check for existence
elif submethobj is UNDEFINED:
result = Result(False, 'Does not contain required attribute (%s)' % meth, 214)
if result:
return result
return Result(True, None, 0) | python | def _check_methods(cls, subclass): # pylint: disable=too-many-branches
"""
Args:
cls(:py:class:`Plugin`): Parent class
subclass(:py:class:`Plugin`): Subclass to evaluate
Returns:
Result: Named tuple
Validate abstract methods are defined in subclass
For error codes see _inspect_class
"""
for meth, methobj in cls.__abstractmethods__.items():
# Need to get attribute from dictionary for instance tests to work
for base in subclass.__mro__: # pragma: no branch
if meth in base.__dict__:
submethobj = base.__dict__[meth]
break
# If we found our abstract method, we didn't find anything
if submethobj is methobj:
submethobj = UNDEFINED
# Determine if we have the right method type
result = None
bad_arg_spec = 'Argument spec does not match parent for method %s'
# pylint: disable=deprecated-method
if isinstance(methobj, property):
if submethobj is UNDEFINED or not isinstance(submethobj, property):
result = Result(False, 'Does not contain required property (%s)' % meth, 210)
elif isinstance(methobj, staticmethod):
if submethobj is UNDEFINED or not isinstance(submethobj, staticmethod):
result = Result(False, 'Does not contain required static method (%s)' % meth, 211)
elif PY26: # pragma: no cover
if getfullargspec(methobj.__get__(True)) != \
getfullargspec(submethobj.__get__(True)):
result = Result(False, bad_arg_spec % meth, 220)
elif getfullargspec(methobj.__func__) != getfullargspec(submethobj.__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif isinstance(methobj, classmethod):
if submethobj is UNDEFINED or not isinstance(submethobj, classmethod):
result = Result(False, 'Does not contain required class method (%s)' % meth, 212)
elif PY26: # pragma: no cover
if getfullargspec(methobj.__get__(True).__func__) != \
getfullargspec(submethobj.__get__(True).__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif getfullargspec(methobj.__func__) != getfullargspec(submethobj.__func__):
result = Result(False, bad_arg_spec % meth, 220)
elif isfunction(methobj):
if submethobj is UNDEFINED or not isfunction(submethobj):
result = Result(False, 'Does not contain required method (%s)' % meth, 213)
elif getfullargspec(methobj) != getfullargspec(submethobj):
result = Result(False, bad_arg_spec % meth, 220)
# If it's not a type we're specifically checking, just check for existence
elif submethobj is UNDEFINED:
result = Result(False, 'Does not contain required attribute (%s)' % meth, 214)
if result:
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Rockhopper-Technologies/pluginlib | pluginlib/_parent.py | _inspect_class | def _inspect_class(cls, subclass):
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"""
Args:
cls(:py:class:`Plugin`): Parent class
subclass(:py:class:`Plugin`): Subclass to evaluate
Returns:
Result: Named tuple
Inspect subclass for inclusion
Values for errorcode:
* 0: No error
Error codes between 0 and 100 are not intended for import
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Error codes between 99 and 200 are excluded from import
* 156: Skipload call returned True
Error codes 200 and above are malformed classes
* 210: Missing abstract property
* 211: Missing abstract static method
* 212: Missing abstract class method
* 213: Missing abstract method
* 214: Missing abstract attribute
* 220: Argument spec does not match
"""
if callable(subclass._skipload_):
result = subclass._skipload_()
if isinstance(result, tuple):
skip, msg = result
else:
skip, msg = result, None
if skip:
return Result(False, msg, 156)
elif subclass._skipload_:
return Result(False, 'Skipload flag is True', 50)
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Rockhopper-Technologies/pluginlib | pluginlib/_parent.py | Plugin.version | def version(cls): # noqa: N805 # pylint: disable=no-self-argument
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:py:class:Returns `str` -- Returns :attr:`_version_` if set,
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"""
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"""
:py:class:Returns `str` -- Returns :attr:`_version_` if set,
otherwise falls back to module `__version__` or None
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inveniosoftware/invenio-pages | invenio_pages/views.py | preload_pages | def preload_pages():
"""Register all pages before the first application request."""
try:
_add_url_rule([page.url for page in Page.query.all()])
except Exception: # pragma: no cover
current_app.logger.warn('Pages were not loaded.')
raise | python | def preload_pages():
"""Register all pages before the first application request."""
try:
_add_url_rule([page.url for page in Page.query.all()])
except Exception: # pragma: no cover
current_app.logger.warn('Pages were not loaded.')
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inveniosoftware/invenio-pages | invenio_pages/views.py | render_page | def render_page(path):
"""Internal interface to the page view.
:param path: Page path.
:returns: The rendered template.
"""
try:
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except NoResultFound:
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"""Internal interface to the page view.
:param path: Page path.
:returns: The rendered template.
"""
try:
page = Page.get_by_url(request.path)
except NoResultFound:
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return render_template(
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inveniosoftware/invenio-pages | invenio_pages/views.py | handle_not_found | def handle_not_found(exception, **extra):
"""Custom blueprint exception handler."""
assert isinstance(exception, NotFound)
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"""Custom blueprint exception handler."""
assert isinstance(exception, NotFound)
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inveniosoftware/invenio-pages | invenio_pages/views.py | _add_url_rule | def _add_url_rule(url_or_urls):
"""Register URL rule to application URL map."""
old = current_app._got_first_request
# This is bit of cheating to overcome @flask.app.setupmethod decorator.
current_app._got_first_request = False
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current_app._got_first_request = old | python | def _add_url_rule(url_or_urls):
"""Register URL rule to application URL map."""
old = current_app._got_first_request
# This is bit of cheating to overcome @flask.app.setupmethod decorator.
current_app._got_first_request = False
if isinstance(url_or_urls, six.string_types):
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PGower/PyCanvas | pycanvas/apis/collaborations.py | CollaborationsAPI.list_members_of_collaboration | def list_members_of_collaboration(self, id, include=None):
"""
List members of a collaboration.
List the collaborators of a given collaboration
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# OPTIONAL - include
"""- "collaborator_lti_id": Optional information to include with each member.
Represents an identifier to be used for the member in an LTI context.
- "avatar_image_url": Optional information to include with each member.
The url for the avatar of a collaborator with type 'user'."""
if include is not None:
self._validate_enum(include, ["collaborator_lti_id", "avatar_image_url"])
params["include"] = include
self.logger.debug("GET /api/v1/collaborations/{id}/members with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/collaborations/{id}/members".format(**path), data=data, params=params, all_pages=True) | python | def list_members_of_collaboration(self, id, include=None):
"""
List members of a collaboration.
List the collaborators of a given collaboration
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - id
"""ID"""
path["id"] = id
# OPTIONAL - include
"""- "collaborator_lti_id": Optional information to include with each member.
Represents an identifier to be used for the member in an LTI context.
- "avatar_image_url": Optional information to include with each member.
The url for the avatar of a collaborator with type 'user'."""
if include is not None:
self._validate_enum(include, ["collaborator_lti_id", "avatar_image_url"])
params["include"] = include
self.logger.debug("GET /api/v1/collaborations/{id}/members with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/collaborations/{id}/members".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.list_discussion_topics_courses | def list_discussion_topics_courses(self, course_id, exclude_context_module_locked_topics=None, include=None, only_announcements=None, order_by=None, scope=None, search_term=None):
"""
List discussion topics.
Returns the paginated list of discussion topics for this course or group.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - include
"""If "all_dates" is passed, all dates associated with graded discussions'
assignments will be included."""
if include is not None:
self._validate_enum(include, ["all_dates"])
params["include"] = include
# OPTIONAL - order_by
"""Determines the order of the discussion topic list. Defaults to "position"."""
if order_by is not None:
self._validate_enum(order_by, ["position", "recent_activity"])
params["order_by"] = order_by
# OPTIONAL - scope
"""Only return discussion topics in the given state(s). Defaults to including
all topics. Filtering is done after pagination, so pages
may be smaller than requested if topics are filtered.
Can pass multiple states as comma separated string."""
if scope is not None:
self._validate_enum(scope, ["locked", "unlocked", "pinned", "unpinned"])
params["scope"] = scope
# OPTIONAL - only_announcements
"""Return announcements instead of discussion topics. Defaults to false"""
if only_announcements is not None:
params["only_announcements"] = only_announcements
# OPTIONAL - search_term
"""The partial title of the discussion topics to match and return."""
if search_term is not None:
params["search_term"] = search_term
# OPTIONAL - exclude_context_module_locked_topics
"""For students, exclude topics that are locked by module progression.
Defaults to false."""
if exclude_context_module_locked_topics is not None:
params["exclude_context_module_locked_topics"] = exclude_context_module_locked_topics
self.logger.debug("GET /api/v1/courses/{course_id}/discussion_topics with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/discussion_topics".format(**path), data=data, params=params, all_pages=True) | python | def list_discussion_topics_courses(self, course_id, exclude_context_module_locked_topics=None, include=None, only_announcements=None, order_by=None, scope=None, search_term=None):
"""
List discussion topics.
Returns the paginated list of discussion topics for this course or group.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - include
"""If "all_dates" is passed, all dates associated with graded discussions'
assignments will be included."""
if include is not None:
self._validate_enum(include, ["all_dates"])
params["include"] = include
# OPTIONAL - order_by
"""Determines the order of the discussion topic list. Defaults to "position"."""
if order_by is not None:
self._validate_enum(order_by, ["position", "recent_activity"])
params["order_by"] = order_by
# OPTIONAL - scope
"""Only return discussion topics in the given state(s). Defaults to including
all topics. Filtering is done after pagination, so pages
may be smaller than requested if topics are filtered.
Can pass multiple states as comma separated string."""
if scope is not None:
self._validate_enum(scope, ["locked", "unlocked", "pinned", "unpinned"])
params["scope"] = scope
# OPTIONAL - only_announcements
"""Return announcements instead of discussion topics. Defaults to false"""
if only_announcements is not None:
params["only_announcements"] = only_announcements
# OPTIONAL - search_term
"""The partial title of the discussion topics to match and return."""
if search_term is not None:
params["search_term"] = search_term
# OPTIONAL - exclude_context_module_locked_topics
"""For students, exclude topics that are locked by module progression.
Defaults to false."""
if exclude_context_module_locked_topics is not None:
params["exclude_context_module_locked_topics"] = exclude_context_module_locked_topics
self.logger.debug("GET /api/v1/courses/{course_id}/discussion_topics with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/discussion_topics".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.create_new_discussion_topic_courses | def create_new_discussion_topic_courses(self, course_id, allow_rating=None, assignment=None, attachment=None, delayed_post_at=None, discussion_type=None, group_category_id=None, is_announcement=None, lock_at=None, message=None, only_graders_can_rate=None, pinned=None, podcast_enabled=None, podcast_has_student_posts=None, position_after=None, published=None, require_initial_post=None, sort_by_rating=None, title=None):
"""
Create a new discussion topic.
Create an new discussion topic for the course or group.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - title
"""no description"""
if title is not None:
data["title"] = title
# OPTIONAL - message
"""no description"""
if message is not None:
data["message"] = message
# OPTIONAL - discussion_type
"""The type of discussion. Defaults to side_comment if not value is given. Accepted values are 'side_comment', for discussions that only allow one level of nested comments, and 'threaded' for fully threaded discussions."""
if discussion_type is not None:
self._validate_enum(discussion_type, ["side_comment", "threaded"])
data["discussion_type"] = discussion_type
# OPTIONAL - published
"""Whether this topic is published (true) or draft state (false). Only
teachers and TAs have the ability to create draft state topics."""
if published is not None:
data["published"] = published
# OPTIONAL - delayed_post_at
"""If a timestamp is given, the topic will not be published until that time."""
if delayed_post_at is not None:
data["delayed_post_at"] = delayed_post_at
# OPTIONAL - lock_at
"""If a timestamp is given, the topic will be scheduled to lock at the
provided timestamp. If the timestamp is in the past, the topic will be
locked."""
if lock_at is not None:
data["lock_at"] = lock_at
# OPTIONAL - podcast_enabled
"""If true, the topic will have an associated podcast feed."""
if podcast_enabled is not None:
data["podcast_enabled"] = podcast_enabled
# OPTIONAL - podcast_has_student_posts
"""If true, the podcast will include posts from students as well. Implies
podcast_enabled."""
if podcast_has_student_posts is not None:
data["podcast_has_student_posts"] = podcast_has_student_posts
# OPTIONAL - require_initial_post
"""If true then a user may not respond to other replies until that user has
made an initial reply. Defaults to false."""
if require_initial_post is not None:
data["require_initial_post"] = require_initial_post
# OPTIONAL - assignment
"""To create an assignment discussion, pass the assignment parameters as a
sub-object. See the {api:AssignmentsApiController#create Create an Assignment API}
for the available parameters. The name parameter will be ignored, as it's
taken from the discussion title. If you want to make a discussion that was
an assignment NOT an assignment, pass set_assignment = false as part of
the assignment object"""
if assignment is not None:
data["assignment"] = assignment
# OPTIONAL - is_announcement
"""If true, this topic is an announcement. It will appear in the
announcement's section rather than the discussions section. This requires
announcment-posting permissions."""
if is_announcement is not None:
data["is_announcement"] = is_announcement
# OPTIONAL - pinned
"""If true, this topic will be listed in the "Pinned Discussion" section"""
if pinned is not None:
data["pinned"] = pinned
# OPTIONAL - position_after
"""By default, discussions are sorted chronologically by creation date, you
can pass the id of another topic to have this one show up after the other
when they are listed."""
if position_after is not None:
data["position_after"] = position_after
# OPTIONAL - group_category_id
"""If present, the topic will become a group discussion assigned
to the group."""
if group_category_id is not None:
data["group_category_id"] = group_category_id
# OPTIONAL - allow_rating
"""If true, users will be allowed to rate entries."""
if allow_rating is not None:
data["allow_rating"] = allow_rating
# OPTIONAL - only_graders_can_rate
"""If true, only graders will be allowed to rate entries."""
if only_graders_can_rate is not None:
data["only_graders_can_rate"] = only_graders_can_rate
# OPTIONAL - sort_by_rating
"""If true, entries will be sorted by rating."""
if sort_by_rating is not None:
data["sort_by_rating"] = sort_by_rating
# OPTIONAL - attachment
"""A multipart/form-data form-field-style attachment.
Attachments larger than 1 kilobyte are subject to quota restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics".format(**path), data=data, params=params, no_data=True) | python | def create_new_discussion_topic_courses(self, course_id, allow_rating=None, assignment=None, attachment=None, delayed_post_at=None, discussion_type=None, group_category_id=None, is_announcement=None, lock_at=None, message=None, only_graders_can_rate=None, pinned=None, podcast_enabled=None, podcast_has_student_posts=None, position_after=None, published=None, require_initial_post=None, sort_by_rating=None, title=None):
"""
Create a new discussion topic.
Create an new discussion topic for the course or group.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - title
"""no description"""
if title is not None:
data["title"] = title
# OPTIONAL - message
"""no description"""
if message is not None:
data["message"] = message
# OPTIONAL - discussion_type
"""The type of discussion. Defaults to side_comment if not value is given. Accepted values are 'side_comment', for discussions that only allow one level of nested comments, and 'threaded' for fully threaded discussions."""
if discussion_type is not None:
self._validate_enum(discussion_type, ["side_comment", "threaded"])
data["discussion_type"] = discussion_type
# OPTIONAL - published
"""Whether this topic is published (true) or draft state (false). Only
teachers and TAs have the ability to create draft state topics."""
if published is not None:
data["published"] = published
# OPTIONAL - delayed_post_at
"""If a timestamp is given, the topic will not be published until that time."""
if delayed_post_at is not None:
data["delayed_post_at"] = delayed_post_at
# OPTIONAL - lock_at
"""If a timestamp is given, the topic will be scheduled to lock at the
provided timestamp. If the timestamp is in the past, the topic will be
locked."""
if lock_at is not None:
data["lock_at"] = lock_at
# OPTIONAL - podcast_enabled
"""If true, the topic will have an associated podcast feed."""
if podcast_enabled is not None:
data["podcast_enabled"] = podcast_enabled
# OPTIONAL - podcast_has_student_posts
"""If true, the podcast will include posts from students as well. Implies
podcast_enabled."""
if podcast_has_student_posts is not None:
data["podcast_has_student_posts"] = podcast_has_student_posts
# OPTIONAL - require_initial_post
"""If true then a user may not respond to other replies until that user has
made an initial reply. Defaults to false."""
if require_initial_post is not None:
data["require_initial_post"] = require_initial_post
# OPTIONAL - assignment
"""To create an assignment discussion, pass the assignment parameters as a
sub-object. See the {api:AssignmentsApiController#create Create an Assignment API}
for the available parameters. The name parameter will be ignored, as it's
taken from the discussion title. If you want to make a discussion that was
an assignment NOT an assignment, pass set_assignment = false as part of
the assignment object"""
if assignment is not None:
data["assignment"] = assignment
# OPTIONAL - is_announcement
"""If true, this topic is an announcement. It will appear in the
announcement's section rather than the discussions section. This requires
announcment-posting permissions."""
if is_announcement is not None:
data["is_announcement"] = is_announcement
# OPTIONAL - pinned
"""If true, this topic will be listed in the "Pinned Discussion" section"""
if pinned is not None:
data["pinned"] = pinned
# OPTIONAL - position_after
"""By default, discussions are sorted chronologically by creation date, you
can pass the id of another topic to have this one show up after the other
when they are listed."""
if position_after is not None:
data["position_after"] = position_after
# OPTIONAL - group_category_id
"""If present, the topic will become a group discussion assigned
to the group."""
if group_category_id is not None:
data["group_category_id"] = group_category_id
# OPTIONAL - allow_rating
"""If true, users will be allowed to rate entries."""
if allow_rating is not None:
data["allow_rating"] = allow_rating
# OPTIONAL - only_graders_can_rate
"""If true, only graders will be allowed to rate entries."""
if only_graders_can_rate is not None:
data["only_graders_can_rate"] = only_graders_can_rate
# OPTIONAL - sort_by_rating
"""If true, entries will be sorted by rating."""
if sort_by_rating is not None:
data["sort_by_rating"] = sort_by_rating
# OPTIONAL - attachment
"""A multipart/form-data form-field-style attachment.
Attachments larger than 1 kilobyte are subject to quota restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.delete_topic_groups | def delete_topic_groups(self, group_id, topic_id):
"""
Delete a topic.
Deletes the discussion topic. This will also delete the assignment, if it's
an assignment discussion.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
self.logger.debug("DELETE /api/v1/groups/{group_id}/discussion_topics/{topic_id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("DELETE", "/api/v1/groups/{group_id}/discussion_topics/{topic_id}".format(**path), data=data, params=params, no_data=True) | python | def delete_topic_groups(self, group_id, topic_id):
"""
Delete a topic.
Deletes the discussion topic. This will also delete the assignment, if it's
an assignment discussion.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
self.logger.debug("DELETE /api/v1/groups/{group_id}/discussion_topics/{topic_id} with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("DELETE", "/api/v1/groups/{group_id}/discussion_topics/{topic_id}".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.reorder_pinned_topics_courses | def reorder_pinned_topics_courses(self, order, course_id):
"""
Reorder pinned topics.
Puts the pinned discussion topics in the specified order.
All pinned topics should be included.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - order
"""The ids of the pinned discussion topics in the desired order.
(For example, "order=104,102,103".)"""
data["order"] = order
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/reorder with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/reorder".format(**path), data=data, params=params, no_data=True) | python | def reorder_pinned_topics_courses(self, order, course_id):
"""
Reorder pinned topics.
Puts the pinned discussion topics in the specified order.
All pinned topics should be included.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - order
"""The ids of the pinned discussion topics in the desired order.
(For example, "order=104,102,103".)"""
data["order"] = order
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/reorder with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/reorder".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.reorder_pinned_topics_groups | def reorder_pinned_topics_groups(self, order, group_id):
"""
Reorder pinned topics.
Puts the pinned discussion topics in the specified order.
All pinned topics should be included.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - order
"""The ids of the pinned discussion topics in the desired order.
(For example, "order=104,102,103".)"""
data["order"] = order
self.logger.debug("POST /api/v1/groups/{group_id}/discussion_topics/reorder with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/groups/{group_id}/discussion_topics/reorder".format(**path), data=data, params=params, no_data=True) | python | def reorder_pinned_topics_groups(self, order, group_id):
"""
Reorder pinned topics.
Puts the pinned discussion topics in the specified order.
All pinned topics should be included.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - order
"""The ids of the pinned discussion topics in the desired order.
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data["order"] = order
self.logger.debug("POST /api/v1/groups/{group_id}/discussion_topics/reorder with query params: {params} and form data: {data}".format(params=params, data=data, **path))
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.post_entry_courses | def post_entry_courses(self, topic_id, course_id, attachment=None, message=None):
"""
Post an entry.
Create a new entry in a discussion topic. Returns a json representation of
the created entry (see documentation for 'entries' method) on success.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# OPTIONAL - message
"""The body of the entry."""
if message is not None:
data["message"] = message
# OPTIONAL - attachment
"""a multipart/form-data form-field-style
attachment. Attachments larger than 1 kilobyte are subject to quota
restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries".format(**path), data=data, params=params, no_data=True) | python | def post_entry_courses(self, topic_id, course_id, attachment=None, message=None):
"""
Post an entry.
Create a new entry in a discussion topic. Returns a json representation of
the created entry (see documentation for 'entries' method) on success.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# OPTIONAL - message
"""The body of the entry."""
if message is not None:
data["message"] = message
# OPTIONAL - attachment
"""a multipart/form-data form-field-style
attachment. Attachments larger than 1 kilobyte are subject to quota
restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.post_reply_groups | def post_reply_groups(self, group_id, topic_id, entry_id, attachment=None, message=None):
"""
Post a reply.
Add a reply to an entry in a discussion topic. Returns a json
representation of the created reply (see documentation for 'replies'
method) on success.
May require (depending on the topic) that the user has posted in the topic.
If it is required, and the user has not posted, will respond with a 403
Forbidden status and the body 'require_initial_post'.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# REQUIRED - PATH - entry_id
"""ID"""
path["entry_id"] = entry_id
# OPTIONAL - message
"""The body of the entry."""
if message is not None:
data["message"] = message
# OPTIONAL - attachment
"""a multipart/form-data form-field-style
attachment. Attachments larger than 1 kilobyte are subject to quota
restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/groups/{group_id}/discussion_topics/{topic_id}/entries/{entry_id}/replies with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/groups/{group_id}/discussion_topics/{topic_id}/entries/{entry_id}/replies".format(**path), data=data, params=params, no_data=True) | python | def post_reply_groups(self, group_id, topic_id, entry_id, attachment=None, message=None):
"""
Post a reply.
Add a reply to an entry in a discussion topic. Returns a json
representation of the created reply (see documentation for 'replies'
method) on success.
May require (depending on the topic) that the user has posted in the topic.
If it is required, and the user has not posted, will respond with a 403
Forbidden status and the body 'require_initial_post'.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# REQUIRED - PATH - entry_id
"""ID"""
path["entry_id"] = entry_id
# OPTIONAL - message
"""The body of the entry."""
if message is not None:
data["message"] = message
# OPTIONAL - attachment
"""a multipart/form-data form-field-style
attachment. Attachments larger than 1 kilobyte are subject to quota
restrictions."""
if attachment is not None:
data["attachment"] = attachment
self.logger.debug("POST /api/v1/groups/{group_id}/discussion_topics/{topic_id}/entries/{entry_id}/replies with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/groups/{group_id}/discussion_topics/{topic_id}/entries/{entry_id}/replies".format(**path), data=data, params=params, no_data=True) | [
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PGower/PyCanvas | pycanvas/apis/discussion_topics.py | DiscussionTopicsAPI.rate_entry_courses | def rate_entry_courses(self, topic_id, entry_id, course_id, rating=None):
"""
Rate entry.
Rate a discussion entry.
On success, the response will be 204 No Content with an empty body.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# REQUIRED - PATH - entry_id
"""ID"""
path["entry_id"] = entry_id
# OPTIONAL - rating
"""A rating to set on this entry. Only 0 and 1 are accepted."""
if rating is not None:
data["rating"] = rating
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries/{entry_id}/rating with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries/{entry_id}/rating".format(**path), data=data, params=params, no_data=True) | python | def rate_entry_courses(self, topic_id, entry_id, course_id, rating=None):
"""
Rate entry.
Rate a discussion entry.
On success, the response will be 204 No Content with an empty body.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# REQUIRED - PATH - topic_id
"""ID"""
path["topic_id"] = topic_id
# REQUIRED - PATH - entry_id
"""ID"""
path["entry_id"] = entry_id
# OPTIONAL - rating
"""A rating to set on this entry. Only 0 and 1 are accepted."""
if rating is not None:
data["rating"] = rating
self.logger.debug("POST /api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries/{entry_id}/rating with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("POST", "/api/v1/courses/{course_id}/discussion_topics/{topic_id}/entries/{entry_id}/rating".format(**path), data=data, params=params, no_data=True) | [
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coagulant/critics | critics/commands.py | cli | def cli(**settings):
"""Notify about new reviews in AppStore and Google Play in slack.
Launch command using supervisor or using screen/tmux/etc.
Reviews are fetched for multiple apps and languages in --beat=300 interval.
"""
setup_logging(settings)
settings = setup_languages(settings)
channels = setup_channel_map(settings)
app = CriticApp(**dict(settings, channels=channels))
if settings['sentry_dsn']:
app.sentry_client = Client(settings['sentry_dsn'])
logger.debug('Errors are reported to %s' % settings['sentry_dsn'])
else:
app.sentry_client = None
if settings['version']:
click.echo('Version %s' % critics.__version__)
return
if not (settings['ios'] or settings['android']):
click.echo('Please choose either --ios or --android')
return
loop = tornado.ioloop.IOLoop.instance()
if app.load_model():
logger.debug('Model loaded OK, not skipping notify on first run')
notify = True
else:
notify = False
if settings['ios']:
logger.info('Tracking IOS apps: %s', ', '.join(settings['ios']))
itunes = tornado.ioloop.PeriodicCallback(partial(app.poll_store, 'ios'),
1000 * settings['beat'], loop)
itunes.start()
if settings['android']:
logger.info('Tracking Android apps: %s', ', '.join(settings['android']))
google_play = tornado.ioloop.PeriodicCallback(partial(app.poll_store, 'android'),
1000 * settings['beat'], loop)
google_play.start()
echo_channel_map(channels)
if settings['ios']:
app.poll_store('ios', notify=notify)
if settings['android']:
app.poll_store('android', notify=notify)
if settings['stats']:
port = int(settings['stats'])
logger.debug('Serving metrics server on port %s' % port)
start_http_server(port)
if settings['daemonize']:
loop.start() | python | def cli(**settings):
"""Notify about new reviews in AppStore and Google Play in slack.
Launch command using supervisor or using screen/tmux/etc.
Reviews are fetched for multiple apps and languages in --beat=300 interval.
"""
setup_logging(settings)
settings = setup_languages(settings)
channels = setup_channel_map(settings)
app = CriticApp(**dict(settings, channels=channels))
if settings['sentry_dsn']:
app.sentry_client = Client(settings['sentry_dsn'])
logger.debug('Errors are reported to %s' % settings['sentry_dsn'])
else:
app.sentry_client = None
if settings['version']:
click.echo('Version %s' % critics.__version__)
return
if not (settings['ios'] or settings['android']):
click.echo('Please choose either --ios or --android')
return
loop = tornado.ioloop.IOLoop.instance()
if app.load_model():
logger.debug('Model loaded OK, not skipping notify on first run')
notify = True
else:
notify = False
if settings['ios']:
logger.info('Tracking IOS apps: %s', ', '.join(settings['ios']))
itunes = tornado.ioloop.PeriodicCallback(partial(app.poll_store, 'ios'),
1000 * settings['beat'], loop)
itunes.start()
if settings['android']:
logger.info('Tracking Android apps: %s', ', '.join(settings['android']))
google_play = tornado.ioloop.PeriodicCallback(partial(app.poll_store, 'android'),
1000 * settings['beat'], loop)
google_play.start()
echo_channel_map(channels)
if settings['ios']:
app.poll_store('ios', notify=notify)
if settings['android']:
app.poll_store('android', notify=notify)
if settings['stats']:
port = int(settings['stats'])
logger.debug('Serving metrics server on port %s' % port)
start_http_server(port)
if settings['daemonize']:
loop.start() | [
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karel-brinda/rnftools | rnftools/mishmash/Source.py | Source.create_fa | def create_fa(self):
"""Create a FASTA file with extracted sequences.
"""
if self._seqs is None:
os.symlink(self._fa0_fn, self._fa_fn)
else:
in_seqs = pyfaidx.Fasta(self._fa0_fn)
with open(self._fa_fn, "w+") as g:
for seq_desc in self._seqs:
x = in_seqs[seq_desc]
name, seq = x.name, str(x)
g.write(">" + name + "\n")
n = 80
seq_split = "\n".join([seq[i:i + n] for i in range(0, len(seq), n)])
g.write(seq_split + "\n") | python | def create_fa(self):
"""Create a FASTA file with extracted sequences.
"""
if self._seqs is None:
os.symlink(self._fa0_fn, self._fa_fn)
else:
in_seqs = pyfaidx.Fasta(self._fa0_fn)
with open(self._fa_fn, "w+") as g:
for seq_desc in self._seqs:
x = in_seqs[seq_desc]
name, seq = x.name, str(x)
g.write(">" + name + "\n")
n = 80
seq_split = "\n".join([seq[i:i + n] for i in range(0, len(seq), n)])
g.write(seq_split + "\n") | [
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karel-brinda/rnftools | rnftools/mishmash/Source.py | Source.recode_sam_reads | def recode_sam_reads(
sam_fn,
fastq_rnf_fo,
fai_fo,
genome_id,
number_of_read_tuples=10**9,
simulator_name=None,
allow_unmapped=False,
):
"""Transform a SAM file to RNF-compatible FASTQ.
Args:
sam_fn (str): SAM/BAM file - file name.
fastq_rnf_fo (str): Output FASTQ file - file object.
fai_fo (str): FAI index of the reference genome - file object.
genome_id (int): Genome ID for RNF.
number_of_read_tuples (int): Expected number of read tuples (to set width of read tuple id).
simulator_name (str): Name of the simulator. Used for comment in read tuple name.
allow_unmapped (bool): Allow unmapped reads.
Raises:
NotImplementedError
"""
fai_index = rnftools.utils.FaIdx(fai_fo)
# last_read_tuple_name=[]
read_tuple_id_width = len(format(number_of_read_tuples, 'x'))
fq_creator = rnftools.rnfformat.FqCreator(
fastq_fo=fastq_rnf_fo,
read_tuple_id_width=read_tuple_id_width,
genome_id_width=2,
chr_id_width=fai_index.chr_id_width,
coor_width=fai_index.coor_width,
info_reads_in_tuple=True,
info_simulator=simulator_name,
)
# todo: check if clipping corrections is well implemented
cigar_reg_shift = re.compile("([0-9]+)([MDNP=X])")
# todo: other upac codes
reverse_complement_dict = {
"A": "T",
"T": "A",
"C": "G",
"G": "C",
"N": "N",
}
read_tuple_id = 0
last_read_tuple_name = None
with pysam.AlignmentFile(
sam_fn,
check_header=False,
) as samfile:
for alignment in samfile:
if alignment.query_name != last_read_tuple_name and last_read_tuple_name is not None:
read_tuple_id += 1
last_read_tuple_name = alignment.query_name
if alignment.is_unmapped:
rnftools.utils.error(
"SAM files used for conversion should not contain unaligned segments. "
"This condition is broken by read tuple "
"'{}' in file '{}'.".format(alignment.query_name, sam_fn),
program="RNFtools",
subprogram="MIShmash",
exception=NotImplementedError,
)
if alignment.is_reverse:
direction = "R"
bases = "".join([reverse_complement_dict[nucl] for nucl in alignment.seq[::-1]])
qualities = str(alignment.qual[::-1])
else:
direction = "F"
bases = alignment.seq[:]
qualities = str(alignment.qual[:])
# todo: are chromosomes in bam sorted correctly (the same order as in FASTA)?
if fai_index.dict_chr_ids != {}:
chr_id = fai_index.dict_chr_ids[samfile.getrname(alignment.reference_id)]
else:
chr_id = "0"
left = int(alignment.reference_start) + 1
right = left - 1
for (steps, operation) in cigar_reg_shift.findall(alignment.cigarstring):
right += int(steps)
segment = rnftools.rnfformat.Segment(
genome_id=genome_id,
chr_id=chr_id,
direction=direction,
left=left,
right=right,
)
fq_creator.add_read(
read_tuple_id=read_tuple_id,
bases=bases,
qualities=qualities,
segments=[segment],
)
fq_creator.flush_read_tuple() | python | def recode_sam_reads(
sam_fn,
fastq_rnf_fo,
fai_fo,
genome_id,
number_of_read_tuples=10**9,
simulator_name=None,
allow_unmapped=False,
):
"""Transform a SAM file to RNF-compatible FASTQ.
Args:
sam_fn (str): SAM/BAM file - file name.
fastq_rnf_fo (str): Output FASTQ file - file object.
fai_fo (str): FAI index of the reference genome - file object.
genome_id (int): Genome ID for RNF.
number_of_read_tuples (int): Expected number of read tuples (to set width of read tuple id).
simulator_name (str): Name of the simulator. Used for comment in read tuple name.
allow_unmapped (bool): Allow unmapped reads.
Raises:
NotImplementedError
"""
fai_index = rnftools.utils.FaIdx(fai_fo)
# last_read_tuple_name=[]
read_tuple_id_width = len(format(number_of_read_tuples, 'x'))
fq_creator = rnftools.rnfformat.FqCreator(
fastq_fo=fastq_rnf_fo,
read_tuple_id_width=read_tuple_id_width,
genome_id_width=2,
chr_id_width=fai_index.chr_id_width,
coor_width=fai_index.coor_width,
info_reads_in_tuple=True,
info_simulator=simulator_name,
)
# todo: check if clipping corrections is well implemented
cigar_reg_shift = re.compile("([0-9]+)([MDNP=X])")
# todo: other upac codes
reverse_complement_dict = {
"A": "T",
"T": "A",
"C": "G",
"G": "C",
"N": "N",
}
read_tuple_id = 0
last_read_tuple_name = None
with pysam.AlignmentFile(
sam_fn,
check_header=False,
) as samfile:
for alignment in samfile:
if alignment.query_name != last_read_tuple_name and last_read_tuple_name is not None:
read_tuple_id += 1
last_read_tuple_name = alignment.query_name
if alignment.is_unmapped:
rnftools.utils.error(
"SAM files used for conversion should not contain unaligned segments. "
"This condition is broken by read tuple "
"'{}' in file '{}'.".format(alignment.query_name, sam_fn),
program="RNFtools",
subprogram="MIShmash",
exception=NotImplementedError,
)
if alignment.is_reverse:
direction = "R"
bases = "".join([reverse_complement_dict[nucl] for nucl in alignment.seq[::-1]])
qualities = str(alignment.qual[::-1])
else:
direction = "F"
bases = alignment.seq[:]
qualities = str(alignment.qual[:])
# todo: are chromosomes in bam sorted correctly (the same order as in FASTA)?
if fai_index.dict_chr_ids != {}:
chr_id = fai_index.dict_chr_ids[samfile.getrname(alignment.reference_id)]
else:
chr_id = "0"
left = int(alignment.reference_start) + 1
right = left - 1
for (steps, operation) in cigar_reg_shift.findall(alignment.cigarstring):
right += int(steps)
segment = rnftools.rnfformat.Segment(
genome_id=genome_id,
chr_id=chr_id,
direction=direction,
left=left,
right=right,
)
fq_creator.add_read(
read_tuple_id=read_tuple_id,
bases=bases,
qualities=qualities,
segments=[segment],
)
fq_creator.flush_read_tuple() | [
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20c/vodka | vodka/instance.py | instantiate | def instantiate(config):
"""
instantiate all registered vodka applications
Args:
config (dict or MungeConfig): configuration object
"""
for handle, cfg in list(config["apps"].items()):
if not cfg.get("enabled", True):
continue
app = get_application(handle)
instances[app.handle] = app(cfg) | python | def instantiate(config):
"""
instantiate all registered vodka applications
Args:
config (dict or MungeConfig): configuration object
"""
for handle, cfg in list(config["apps"].items()):
if not cfg.get("enabled", True):
continue
app = get_application(handle)
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Sanji-IO/sanji | sanji/router.py | compile_resource | def compile_resource(resource):
"""
Return compiled regex for resource matching
"""
return re.compile("^" + trim_resource(re.sub(r":(\w+)", r"(?P<\1>[\w-]+?)",
resource)) + r"(\?(?P<querystring>.*))?$") | python | def compile_resource(resource):
"""
Return compiled regex for resource matching
"""
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Sanji-IO/sanji | sanji/router.py | Route.create_handler_func | def create_handler_func(self, method):
"""
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def _handler(callback, schema=None):
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_handler
"""
# reentrant default is False [POST, DELETE, PUT]
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self.handlers.append({
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"schema": schema,
"reentrant": reentrant
})
return self
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"""
create_handler_func
"""
def _handler(callback, schema=None):
"""
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"""
# reentrant default is False [POST, DELETE, PUT]
reentrant = False
if method == "get":
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self.handlers.append({
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"""
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handlers = []
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handlers.append(handler)
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"""
dispatch
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handlers = []
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"""
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Sanji-IO/sanji | sanji/router.py | Router.create_route_func | def create_route_func(self, method):
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"""
create_route_func
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_route
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route = self.routes.get(resource, Route(resource))
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Sanji-IO/sanji | sanji/router.py | Router.dispatch | def dispatch(self, message):
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return results | python | def dispatch(self, message):
"""
dispatch
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results = []
# match routes
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__message = message.match(route)
if __message is None:
continue
route_result = route.dispatch(__message)
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20c/vodka | vodka/data/__init__.py | handle | def handle(data_type, data, data_id=None, caller=None):
"""
execute all data handlers on the specified data according to data type
Args:
data_type (str): data type handle
data (dict or list): data
Kwargs:
data_id (str): can be used to differentiate between different data
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caller (object): if specified, holds the object or function that
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dict or list - data after handlers have been executed on it
"""
if not data_id:
data_id = data_type
# instantiate handlers for data type if they havent been yet
if data_id not in _handlers:
_handlers[data_id] = dict(
[(h.handle, h) for h in handlers.instantiate_for_data_type(data_type, data_id=data_id)])
for handler in list(_handlers[data_id].values()):
try:
data = handler(data, caller=caller)
except Exception as inst:
vodka.log.error("Data handler '%s' failed with error" % handler)
vodka.log.error(traceback.format_exc())
return data | python | def handle(data_type, data, data_id=None, caller=None):
"""
execute all data handlers on the specified data according to data type
Args:
data_type (str): data type handle
data (dict or list): data
Kwargs:
data_id (str): can be used to differentiate between different data
sets of the same data type. If not specified will default to
the data type
caller (object): if specified, holds the object or function that
is trying to handle data
Returns:
dict or list - data after handlers have been executed on it
"""
if not data_id:
data_id = data_type
# instantiate handlers for data type if they havent been yet
if data_id not in _handlers:
_handlers[data_id] = dict(
[(h.handle, h) for h in handlers.instantiate_for_data_type(data_type, data_id=data_id)])
for handler in list(_handlers[data_id].values()):
try:
data = handler(data, caller=caller)
except Exception as inst:
vodka.log.error("Data handler '%s' failed with error" % handler)
vodka.log.error(traceback.format_exc())
return data | [
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theonion/django-bulbs | bulbs/reading_list/mixins.py | ReadingListMixin.validate_query | def validate_query(self, query):
"""Confirm query exists given common filters."""
if query is None:
return query
query = self.update_reading_list(query)
return query | python | def validate_query(self, query):
"""Confirm query exists given common filters."""
if query is None:
return query
query = self.update_reading_list(query)
return query | [
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theonion/django-bulbs | bulbs/reading_list/mixins.py | ReadingListMixin.get_validated_augment_query | def get_validated_augment_query(self, augment_query=None):
"""
Common rules for reading list augmentation hierarchy.
1. Sponsored Content.
2. Video Content.
"""
augment_query = self.validate_query(augment_query)
# Given an invalid query, reach for a Sponsored query.
if not augment_query:
augment_query = self.validate_query(Content.search_objects.sponsored())
# Given an invalid Sponsored query, reach for a Video query.
if not augment_query:
reading_list_config = getattr(settings, "READING_LIST_CONFIG", {})
excluded_channel_ids = reading_list_config.get("excluded_channel_ids", [])
augment_query = self.validate_query(Content.search_objects.evergreen_video(
excluded_channel_ids=excluded_channel_ids
))
return augment_query | python | def get_validated_augment_query(self, augment_query=None):
"""
Common rules for reading list augmentation hierarchy.
1. Sponsored Content.
2. Video Content.
"""
augment_query = self.validate_query(augment_query)
# Given an invalid query, reach for a Sponsored query.
if not augment_query:
augment_query = self.validate_query(Content.search_objects.sponsored())
# Given an invalid Sponsored query, reach for a Video query.
if not augment_query:
reading_list_config = getattr(settings, "READING_LIST_CONFIG", {})
excluded_channel_ids = reading_list_config.get("excluded_channel_ids", [])
augment_query = self.validate_query(Content.search_objects.evergreen_video(
excluded_channel_ids=excluded_channel_ids
))
return augment_query | [
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theonion/django-bulbs | bulbs/reading_list/mixins.py | ReadingListMixin.augment_reading_list | def augment_reading_list(self, primary_query, augment_query=None, reverse_negate=False):
"""Apply injected logic for slicing reading lists with additional content."""
primary_query = self.validate_query(primary_query)
augment_query = self.get_validated_augment_query(augment_query=augment_query)
try:
# We use this for cases like recent where queries are vague.
if reverse_negate:
primary_query = primary_query.filter(NegateQueryFilter(augment_query))
else:
augment_query = augment_query.filter(NegateQueryFilter(primary_query))
augment_query = randomize_es(augment_query)
return FirstSlotSlicer(primary_query, augment_query)
except TransportError:
return primary_query | python | def augment_reading_list(self, primary_query, augment_query=None, reverse_negate=False):
"""Apply injected logic for slicing reading lists with additional content."""
primary_query = self.validate_query(primary_query)
augment_query = self.get_validated_augment_query(augment_query=augment_query)
try:
# We use this for cases like recent where queries are vague.
if reverse_negate:
primary_query = primary_query.filter(NegateQueryFilter(augment_query))
else:
augment_query = augment_query.filter(NegateQueryFilter(primary_query))
augment_query = randomize_es(augment_query)
return FirstSlotSlicer(primary_query, augment_query)
except TransportError:
return primary_query | [
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theonion/django-bulbs | bulbs/reading_list/mixins.py | ReadingListMixin.update_reading_list | def update_reading_list(self, reading_list):
"""Generic behaviors for reading lists before being rendered."""
# remove the current piece of content from the query.
reading_list = reading_list.filter(
~es_filter.Ids(values=[self.id])
)
# remove excluded document types from the query.
reading_list_config = getattr(settings, "READING_LIST_CONFIG", {})
excluded_doc_types = reading_list_config.get("excluded_doc_types", [])
for obj in excluded_doc_types:
reading_list = reading_list.filter(~es_filter.Type(value=obj))
return reading_list | python | def update_reading_list(self, reading_list):
"""Generic behaviors for reading lists before being rendered."""
# remove the current piece of content from the query.
reading_list = reading_list.filter(
~es_filter.Ids(values=[self.id])
)
# remove excluded document types from the query.
reading_list_config = getattr(settings, "READING_LIST_CONFIG", {})
excluded_doc_types = reading_list_config.get("excluded_doc_types", [])
for obj in excluded_doc_types:
reading_list = reading_list.filter(~es_filter.Type(value=obj))
return reading_list | [
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theonion/django-bulbs | bulbs/reading_list/mixins.py | ReadingListMixin.get_reading_list_context | def get_reading_list_context(self, **kwargs):
"""Returns the context dictionary for a given reading list."""
reading_list = None
context = {
"name": "",
"content": reading_list,
"targeting": {},
"videos": []
}
if self.reading_list_identifier == "popular":
reading_list = popular_content()
context.update({"name": self.reading_list_identifier})
# Popular is augmented.
reading_list = self.augment_reading_list(reading_list)
context.update({"content": reading_list})
return context
if self.reading_list_identifier.startswith("specialcoverage"):
special_coverage = SpecialCoverage.objects.get_by_identifier(
self.reading_list_identifier
)
reading_list = special_coverage.get_content().query(
SponsoredBoost(field_name="tunic_campaign_id")
).sort("_score", "-published")
context["targeting"]["dfp_specialcoverage"] = special_coverage.slug
if special_coverage.tunic_campaign_id:
context["tunic_campaign_id"] = special_coverage.tunic_campaign_id
context["targeting"].update({
"dfp_campaign_id": special_coverage.tunic_campaign_id
})
# We do not augment sponsored special coverage lists.
reading_list = self.update_reading_list(reading_list)
else:
reading_list = self.augment_reading_list(reading_list)
context.update({
"name": special_coverage.name,
"videos": special_coverage.videos,
"content": reading_list
})
return context
if self.reading_list_identifier.startswith("section"):
section = Section.objects.get_by_identifier(self.reading_list_identifier)
reading_list = section.get_content()
reading_list = self.augment_reading_list(reading_list)
context.update({
"name": section.name,
"content": reading_list
})
return context
reading_list = Content.search_objects.search()
reading_list = self.augment_reading_list(reading_list, reverse_negate=True)
context.update({
"name": "Recent News",
"content": reading_list
})
return context | python | def get_reading_list_context(self, **kwargs):
"""Returns the context dictionary for a given reading list."""
reading_list = None
context = {
"name": "",
"content": reading_list,
"targeting": {},
"videos": []
}
if self.reading_list_identifier == "popular":
reading_list = popular_content()
context.update({"name": self.reading_list_identifier})
# Popular is augmented.
reading_list = self.augment_reading_list(reading_list)
context.update({"content": reading_list})
return context
if self.reading_list_identifier.startswith("specialcoverage"):
special_coverage = SpecialCoverage.objects.get_by_identifier(
self.reading_list_identifier
)
reading_list = special_coverage.get_content().query(
SponsoredBoost(field_name="tunic_campaign_id")
).sort("_score", "-published")
context["targeting"]["dfp_specialcoverage"] = special_coverage.slug
if special_coverage.tunic_campaign_id:
context["tunic_campaign_id"] = special_coverage.tunic_campaign_id
context["targeting"].update({
"dfp_campaign_id": special_coverage.tunic_campaign_id
})
# We do not augment sponsored special coverage lists.
reading_list = self.update_reading_list(reading_list)
else:
reading_list = self.augment_reading_list(reading_list)
context.update({
"name": special_coverage.name,
"videos": special_coverage.videos,
"content": reading_list
})
return context
if self.reading_list_identifier.startswith("section"):
section = Section.objects.get_by_identifier(self.reading_list_identifier)
reading_list = section.get_content()
reading_list = self.augment_reading_list(reading_list)
context.update({
"name": section.name,
"content": reading_list
})
return context
reading_list = Content.search_objects.search()
reading_list = self.augment_reading_list(reading_list, reverse_negate=True)
context.update({
"name": "Recent News",
"content": reading_list
})
return context | [
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jonbeebe/frontmatter | frontmatter/__init__.py | Frontmatter.read_file | def read_file(cls, path):
"""Reads file at path and returns dict with separated frontmatter.
See read() for more info on dict return value.
"""
with open(path, encoding="utf-8") as file:
file_contents = file.read()
return cls.read(file_contents) | python | def read_file(cls, path):
"""Reads file at path and returns dict with separated frontmatter.
See read() for more info on dict return value.
"""
with open(path, encoding="utf-8") as file:
file_contents = file.read()
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jonbeebe/frontmatter | frontmatter/__init__.py | Frontmatter.read | def read(cls, string):
"""Returns dict with separated frontmatter from string.
Returned dict keys:
attributes -- extracted YAML attributes in dict form.
body -- string contents below the YAML separators
frontmatter -- string representation of YAML
"""
fmatter = ""
body = ""
result = cls._regex.search(string)
if result:
fmatter = result.group(1)
body = result.group(2)
return {
"attributes": yaml.load(fmatter),
"body": body,
"frontmatter": fmatter,
} | python | def read(cls, string):
"""Returns dict with separated frontmatter from string.
Returned dict keys:
attributes -- extracted YAML attributes in dict form.
body -- string contents below the YAML separators
frontmatter -- string representation of YAML
"""
fmatter = ""
body = ""
result = cls._regex.search(string)
if result:
fmatter = result.group(1)
body = result.group(2)
return {
"attributes": yaml.load(fmatter),
"body": body,
"frontmatter": fmatter,
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LIVVkit/LIVVkit | livvkit/components/performance.py | run_suite | def run_suite(case, config, summary):
""" Run the full suite of performance tests """
config["name"] = case
timing_data = dict()
model_dir = os.path.join(livvkit.model_dir, config['data_dir'], case)
bench_dir = os.path.join(livvkit.bench_dir, config['data_dir'], case)
plot_dir = os.path.join(livvkit.output_dir, "performance", "imgs")
model_cases = functions.collect_cases(model_dir)
bench_cases = functions.collect_cases(bench_dir)
functions.mkdir_p(plot_dir)
# Generate all of the timing data
for subcase in sorted(model_cases):
bench_subcases = bench_cases[subcase] if subcase in bench_cases else []
timing_data[subcase] = dict()
for mcase in model_cases[subcase]:
config["case"] = "-".join([subcase, mcase])
bpath = (os.path.join(bench_dir, subcase, mcase.replace("-", os.path.sep))
if mcase in bench_subcases else None)
mpath = os.path.join(model_dir, subcase, mcase.replace("-", os.path.sep))
timing_data[subcase][mcase] = _analyze_case(mpath, bpath, config)
# Create scaling and timing breakdown plots
weak_data = weak_scaling(timing_data, config['scaling_var'],
config['weak_scaling_points'])
strong_data = strong_scaling(timing_data, config['scaling_var'],
config['strong_scaling_points'])
timing_plots = [
generate_scaling_plot(weak_data,
"Weak scaling for " + case.capitalize(),
"runtime (s)", "",
os.path.join(plot_dir, case + "_weak_scaling.png")
),
weak_scaling_efficiency_plot(weak_data,
"Weak scaling efficiency for " + case.capitalize(),
"Parallel efficiency (% of linear)", "",
os.path.join(plot_dir, case + "_weak_scaling_efficiency.png")
),
generate_scaling_plot(strong_data,
"Strong scaling for " + case.capitalize(),
"Runtime (s)", "",
os.path.join(plot_dir, case + "_strong_scaling.png")
),
strong_scaling_efficiency_plot(strong_data,
"Strong scaling efficiency for " + case.capitalize(),
"Parallel efficiency (% of linear)", "",
os.path.join(plot_dir,
case + "_strong_scaling_efficiency.png")
),
]
timing_plots = timing_plots + \
[generate_timing_breakdown_plot(timing_data[s],
config['scaling_var'],
"Timing breakdown for " + case.capitalize()+" "+s,
"",
os.path.join(plot_dir, case+"_"+s+"_timing_breakdown.png")
)
for s in sorted(six.iterkeys(timing_data), key=functions.sort_scale)]
# Build an image gallery and write the results
el = [
elements.gallery("Performance Plots", timing_plots)
]
result = elements.page(case, config["description"], element_list=el)
summary[case] = _summarize_result(timing_data, config)
_print_result(case, summary)
functions.create_page_from_template("performance.html",
os.path.join(livvkit.index_dir, "performance",
case + ".html"))
functions.write_json(result, os.path.join(livvkit.output_dir, "performance"),
case + ".json") | python | def run_suite(case, config, summary):
""" Run the full suite of performance tests """
config["name"] = case
timing_data = dict()
model_dir = os.path.join(livvkit.model_dir, config['data_dir'], case)
bench_dir = os.path.join(livvkit.bench_dir, config['data_dir'], case)
plot_dir = os.path.join(livvkit.output_dir, "performance", "imgs")
model_cases = functions.collect_cases(model_dir)
bench_cases = functions.collect_cases(bench_dir)
functions.mkdir_p(plot_dir)
# Generate all of the timing data
for subcase in sorted(model_cases):
bench_subcases = bench_cases[subcase] if subcase in bench_cases else []
timing_data[subcase] = dict()
for mcase in model_cases[subcase]:
config["case"] = "-".join([subcase, mcase])
bpath = (os.path.join(bench_dir, subcase, mcase.replace("-", os.path.sep))
if mcase in bench_subcases else None)
mpath = os.path.join(model_dir, subcase, mcase.replace("-", os.path.sep))
timing_data[subcase][mcase] = _analyze_case(mpath, bpath, config)
# Create scaling and timing breakdown plots
weak_data = weak_scaling(timing_data, config['scaling_var'],
config['weak_scaling_points'])
strong_data = strong_scaling(timing_data, config['scaling_var'],
config['strong_scaling_points'])
timing_plots = [
generate_scaling_plot(weak_data,
"Weak scaling for " + case.capitalize(),
"runtime (s)", "",
os.path.join(plot_dir, case + "_weak_scaling.png")
),
weak_scaling_efficiency_plot(weak_data,
"Weak scaling efficiency for " + case.capitalize(),
"Parallel efficiency (% of linear)", "",
os.path.join(plot_dir, case + "_weak_scaling_efficiency.png")
),
generate_scaling_plot(strong_data,
"Strong scaling for " + case.capitalize(),
"Runtime (s)", "",
os.path.join(plot_dir, case + "_strong_scaling.png")
),
strong_scaling_efficiency_plot(strong_data,
"Strong scaling efficiency for " + case.capitalize(),
"Parallel efficiency (% of linear)", "",
os.path.join(plot_dir,
case + "_strong_scaling_efficiency.png")
),
]
timing_plots = timing_plots + \
[generate_timing_breakdown_plot(timing_data[s],
config['scaling_var'],
"Timing breakdown for " + case.capitalize()+" "+s,
"",
os.path.join(plot_dir, case+"_"+s+"_timing_breakdown.png")
)
for s in sorted(six.iterkeys(timing_data), key=functions.sort_scale)]
# Build an image gallery and write the results
el = [
elements.gallery("Performance Plots", timing_plots)
]
result = elements.page(case, config["description"], element_list=el)
summary[case] = _summarize_result(timing_data, config)
_print_result(case, summary)
functions.create_page_from_template("performance.html",
os.path.join(livvkit.index_dir, "performance",
case + ".html"))
functions.write_json(result, os.path.join(livvkit.output_dir, "performance"),
case + ".json") | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | _analyze_case | def _analyze_case(model_dir, bench_dir, config):
""" Generates statistics from the timing summaries """
model_timings = set(glob.glob(os.path.join(model_dir, "*" + config["timing_ext"])))
if bench_dir is not None:
bench_timings = set(glob.glob(os.path.join(bench_dir, "*" + config["timing_ext"])))
else:
bench_timings = set()
if not len(model_timings):
return dict()
model_stats = generate_timing_stats(model_timings, config['timing_vars'])
bench_stats = generate_timing_stats(bench_timings, config['timing_vars'])
return dict(model=model_stats, bench=bench_stats) | python | def _analyze_case(model_dir, bench_dir, config):
""" Generates statistics from the timing summaries """
model_timings = set(glob.glob(os.path.join(model_dir, "*" + config["timing_ext"])))
if bench_dir is not None:
bench_timings = set(glob.glob(os.path.join(bench_dir, "*" + config["timing_ext"])))
else:
bench_timings = set()
if not len(model_timings):
return dict()
model_stats = generate_timing_stats(model_timings, config['timing_vars'])
bench_stats = generate_timing_stats(bench_timings, config['timing_vars'])
return dict(model=model_stats, bench=bench_stats) | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | _print_result | def _print_result(case, summary):
""" Show some statistics from the run """
for case, case_data in summary.items():
for dof, data in case_data.items():
print(" " + case + " " + dof)
print(" -------------------")
for header, val in data.items():
print(" " + header + " : " + str(val))
print("") | python | def _print_result(case, summary):
""" Show some statistics from the run """
for case, case_data in summary.items():
for dof, data in case_data.items():
print(" " + case + " " + dof)
print(" -------------------")
for header, val in data.items():
print(" " + header + " : " + str(val))
print("") | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | _summarize_result | def _summarize_result(result, config):
""" Trim out some data to return for the index page """
timing_var = config['scaling_var']
summary = LIVVDict()
for size, res in result.items():
proc_counts = []
bench_times = []
model_times = []
for proc, data in res.items():
proc_counts.append(int(proc[1:]))
try:
bench_times.append(data['bench'][timing_var]['mean'])
except KeyError:
pass
try:
model_times.append(data['model'][timing_var]['mean'])
except KeyError:
pass
if model_times != [] and bench_times != []:
time_diff = np.mean(model_times)/np.mean(bench_times)
else:
time_diff = 'NA'
summary[size]['Proc. Counts'] = ", ".join([str(x) for x in sorted(proc_counts)])
summary[size]['Mean Time Diff (% of benchmark)'] = time_diff
return summary | python | def _summarize_result(result, config):
""" Trim out some data to return for the index page """
timing_var = config['scaling_var']
summary = LIVVDict()
for size, res in result.items():
proc_counts = []
bench_times = []
model_times = []
for proc, data in res.items():
proc_counts.append(int(proc[1:]))
try:
bench_times.append(data['bench'][timing_var]['mean'])
except KeyError:
pass
try:
model_times.append(data['model'][timing_var]['mean'])
except KeyError:
pass
if model_times != [] and bench_times != []:
time_diff = np.mean(model_times)/np.mean(bench_times)
else:
time_diff = 'NA'
summary[size]['Proc. Counts'] = ", ".join([str(x) for x in sorted(proc_counts)])
summary[size]['Mean Time Diff (% of benchmark)'] = time_diff
return summary | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | generate_timing_stats | def generate_timing_stats(file_list, var_list):
"""
Parse all of the timing files, and generate some statistics
about the run.
Args:
file_list: A list of timing files to parse
var_list: A list of variables to look for in the timing file
Returns:
A dict containing values that have the form:
[mean, min, max, mean, standard deviation]
"""
timing_result = dict()
timing_summary = dict()
for file in file_list:
timing_result[file] = functions.parse_gptl(file, var_list)
for var in var_list:
var_time = []
for f, data in timing_result.items():
try:
var_time.append(data[var])
except:
continue
if len(var_time):
timing_summary[var] = {'mean': np.mean(var_time),
'max': np.max(var_time),
'min': np.min(var_time),
'std': np.std(var_time)}
return timing_summary | python | def generate_timing_stats(file_list, var_list):
"""
Parse all of the timing files, and generate some statistics
about the run.
Args:
file_list: A list of timing files to parse
var_list: A list of variables to look for in the timing file
Returns:
A dict containing values that have the form:
[mean, min, max, mean, standard deviation]
"""
timing_result = dict()
timing_summary = dict()
for file in file_list:
timing_result[file] = functions.parse_gptl(file, var_list)
for var in var_list:
var_time = []
for f, data in timing_result.items():
try:
var_time.append(data[var])
except:
continue
if len(var_time):
timing_summary[var] = {'mean': np.mean(var_time),
'max': np.max(var_time),
'min': np.min(var_time),
'std': np.std(var_time)}
return timing_summary | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | weak_scaling | def weak_scaling(timing_stats, scaling_var, data_points):
"""
Generate data for plotting weak scaling. The data points keep
a constant amount of work per processor for each data point.
Args:
timing_stats: the result of the generate_timing_stats function
scaling_var: the variable to select from the timing_stats dictionary
(can be provided in configurations via the 'scaling_var' key)
data_points: the list of size and processor counts to use as data
(can be provided in configurations via the 'weak_scaling_points' key)
Returns:
A dict of the form:
{'bench' : {'mins' : [], 'means' : [], 'maxs' : []},
'model' : {'mins' : [], 'means' : [], 'maxs' : []},
'proc_counts' : []}
"""
timing_data = dict()
proc_counts = []
bench_means = []
bench_mins = []
bench_maxs = []
model_means = []
model_mins = []
model_maxs = []
for point in data_points:
size = point[0]
proc = point[1]
try:
model_data = timing_stats[size][proc]['model'][scaling_var]
bench_data = timing_stats[size][proc]['bench'][scaling_var]
except KeyError:
continue
proc_counts.append(proc)
model_means.append(model_data['mean'])
model_mins.append(model_data['min'])
model_maxs.append(model_data['max'])
bench_means.append(bench_data['mean'])
bench_mins.append(bench_data['min'])
bench_maxs.append(bench_data['max'])
timing_data['bench'] = dict(mins=bench_mins, means=bench_means, maxs=bench_maxs)
timing_data['model'] = dict(mins=model_mins, means=model_means, maxs=model_maxs)
timing_data['proc_counts'] = [int(pc[1:]) for pc in proc_counts]
return timing_data | python | def weak_scaling(timing_stats, scaling_var, data_points):
"""
Generate data for plotting weak scaling. The data points keep
a constant amount of work per processor for each data point.
Args:
timing_stats: the result of the generate_timing_stats function
scaling_var: the variable to select from the timing_stats dictionary
(can be provided in configurations via the 'scaling_var' key)
data_points: the list of size and processor counts to use as data
(can be provided in configurations via the 'weak_scaling_points' key)
Returns:
A dict of the form:
{'bench' : {'mins' : [], 'means' : [], 'maxs' : []},
'model' : {'mins' : [], 'means' : [], 'maxs' : []},
'proc_counts' : []}
"""
timing_data = dict()
proc_counts = []
bench_means = []
bench_mins = []
bench_maxs = []
model_means = []
model_mins = []
model_maxs = []
for point in data_points:
size = point[0]
proc = point[1]
try:
model_data = timing_stats[size][proc]['model'][scaling_var]
bench_data = timing_stats[size][proc]['bench'][scaling_var]
except KeyError:
continue
proc_counts.append(proc)
model_means.append(model_data['mean'])
model_mins.append(model_data['min'])
model_maxs.append(model_data['max'])
bench_means.append(bench_data['mean'])
bench_mins.append(bench_data['min'])
bench_maxs.append(bench_data['max'])
timing_data['bench'] = dict(mins=bench_mins, means=bench_means, maxs=bench_maxs)
timing_data['model'] = dict(mins=model_mins, means=model_means, maxs=model_maxs)
timing_data['proc_counts'] = [int(pc[1:]) for pc in proc_counts]
return timing_data | [
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data_points: the list of size and processor counts to use as data
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LIVVkit/LIVVkit | livvkit/components/performance.py | generate_scaling_plot | def generate_scaling_plot(timing_data, title, ylabel, description, plot_file):
"""
Generate a scaling plot.
Args:
timing_data: data returned from a `*_scaling` method
title: the title of the plot
ylabel: the y-axis label of the plot
description: a description of the plot
plot_file: the file to write out to
Returns:
an image element containing the plot file and metadata
"""
proc_counts = timing_data['proc_counts']
if len(proc_counts) > 2:
plt.figure(figsize=(10, 8), dpi=150)
plt.title(title)
plt.xlabel("Number of processors")
plt.ylabel(ylabel)
for case, case_color in zip(['bench', 'model'], ['#91bfdb', '#fc8d59']):
case_data = timing_data[case]
means = case_data['means']
mins = case_data['mins']
maxs = case_data['maxs']
plt.fill_between(proc_counts, mins, maxs, facecolor=case_color, alpha=0.5)
plt.plot(proc_counts, means, 'o-', color=case_color, label=case)
plt.legend(loc='best')
else:
plt.figure(figsize=(5, 3))
plt.axis('off')
plt.text(0.4, 0.8, "ERROR:")
plt.text(0.0, 0.6, "Not enough data points to draw scaling plot")
plt.text(0.0, 0.44, "To generate this data rerun BATS with the")
plt.text(0.0, 0.36, "performance option enabled.")
if livvkit.publish:
plt.savefig(os.path.splitext(plot_file)[0]+'.eps', dpi=600)
plt.savefig(plot_file)
plt.close()
return elements.image(title, description, os.path.basename(plot_file)) | python | def generate_scaling_plot(timing_data, title, ylabel, description, plot_file):
"""
Generate a scaling plot.
Args:
timing_data: data returned from a `*_scaling` method
title: the title of the plot
ylabel: the y-axis label of the plot
description: a description of the plot
plot_file: the file to write out to
Returns:
an image element containing the plot file and metadata
"""
proc_counts = timing_data['proc_counts']
if len(proc_counts) > 2:
plt.figure(figsize=(10, 8), dpi=150)
plt.title(title)
plt.xlabel("Number of processors")
plt.ylabel(ylabel)
for case, case_color in zip(['bench', 'model'], ['#91bfdb', '#fc8d59']):
case_data = timing_data[case]
means = case_data['means']
mins = case_data['mins']
maxs = case_data['maxs']
plt.fill_between(proc_counts, mins, maxs, facecolor=case_color, alpha=0.5)
plt.plot(proc_counts, means, 'o-', color=case_color, label=case)
plt.legend(loc='best')
else:
plt.figure(figsize=(5, 3))
plt.axis('off')
plt.text(0.4, 0.8, "ERROR:")
plt.text(0.0, 0.6, "Not enough data points to draw scaling plot")
plt.text(0.0, 0.44, "To generate this data rerun BATS with the")
plt.text(0.0, 0.36, "performance option enabled.")
if livvkit.publish:
plt.savefig(os.path.splitext(plot_file)[0]+'.eps', dpi=600)
plt.savefig(plot_file)
plt.close()
return elements.image(title, description, os.path.basename(plot_file)) | [
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LIVVkit/LIVVkit | livvkit/components/performance.py | generate_timing_breakdown_plot | def generate_timing_breakdown_plot(timing_stats, scaling_var, title, description, plot_file):
"""
Description
Args:
timing_stats: a dictionary of the form
{proc_count : {model||bench : { var : { stat : val }}}}
scaling_var: the variable that accounts for the total runtime
title: the title of the plot
description: the description of the plot
plot_file: the file to write the plot out to
Returns:
an image element containing the plot file and metadata
"""
# noinspection PyProtectedMember
cmap_data = colormaps._viridis_data
n_subplots = len(six.viewkeys(timing_stats))
fig, ax = plt.subplots(1, n_subplots+1, figsize=(3*(n_subplots+2), 5))
for plot_num, p_count in enumerate(
sorted(six.iterkeys(timing_stats), key=functions.sort_processor_counts)):
case_data = timing_stats[p_count]
all_timers = set(six.iterkeys(case_data['model'])) | set(six.iterkeys(case_data['bench']))
all_timers = sorted(list(all_timers), reverse=True)
cmap_stride = int(len(cmap_data)/(len(all_timers)+1))
colors = {all_timers[i]: cmap_data[i*cmap_stride] for i in range(len(all_timers))}
sub_ax = plt.subplot(1, n_subplots+1, plot_num+1)
sub_ax.set_title(p_count)
sub_ax.set_ylabel('Runtime (s)')
for case, var_data in case_data.items():
if case == 'bench':
bar_num = 2
else:
bar_num = 1
offset = 0
if var_data != {}:
for var in sorted(six.iterkeys(var_data), reverse=True):
if var != scaling_var:
plt.bar(bar_num, var_data[var]['mean'], 0.8, bottom=offset,
color=colors[var], label=(var if bar_num == 1 else '_none'))
offset += var_data[var]['mean']
plt.bar(bar_num, var_data[scaling_var]['mean']-offset, 0.8, bottom=offset,
color=colors[scaling_var], label=(scaling_var if bar_num == 1 else '_none'))
sub_ax.set_xticks([1.4, 2.4])
sub_ax.set_xticklabels(('test', 'bench'))
plt.legend(loc=6, bbox_to_anchor=(1.05, 0.5))
plt.tight_layout()
sub_ax = plt.subplot(1, n_subplots+1, n_subplots+1)
hid_bar = plt.bar(1, 100)
for group in hid_bar:
group.set_visible(False)
sub_ax.set_visible(False)
if livvkit.publish:
plt.savefig(os.path.splitext(plot_file)[0]+'.eps', dpi=600)
plt.savefig(plot_file)
plt.close()
return elements.image(title, description, os.path.basename(plot_file)) | python | def generate_timing_breakdown_plot(timing_stats, scaling_var, title, description, plot_file):
"""
Description
Args:
timing_stats: a dictionary of the form
{proc_count : {model||bench : { var : { stat : val }}}}
scaling_var: the variable that accounts for the total runtime
title: the title of the plot
description: the description of the plot
plot_file: the file to write the plot out to
Returns:
an image element containing the plot file and metadata
"""
# noinspection PyProtectedMember
cmap_data = colormaps._viridis_data
n_subplots = len(six.viewkeys(timing_stats))
fig, ax = plt.subplots(1, n_subplots+1, figsize=(3*(n_subplots+2), 5))
for plot_num, p_count in enumerate(
sorted(six.iterkeys(timing_stats), key=functions.sort_processor_counts)):
case_data = timing_stats[p_count]
all_timers = set(six.iterkeys(case_data['model'])) | set(six.iterkeys(case_data['bench']))
all_timers = sorted(list(all_timers), reverse=True)
cmap_stride = int(len(cmap_data)/(len(all_timers)+1))
colors = {all_timers[i]: cmap_data[i*cmap_stride] for i in range(len(all_timers))}
sub_ax = plt.subplot(1, n_subplots+1, plot_num+1)
sub_ax.set_title(p_count)
sub_ax.set_ylabel('Runtime (s)')
for case, var_data in case_data.items():
if case == 'bench':
bar_num = 2
else:
bar_num = 1
offset = 0
if var_data != {}:
for var in sorted(six.iterkeys(var_data), reverse=True):
if var != scaling_var:
plt.bar(bar_num, var_data[var]['mean'], 0.8, bottom=offset,
color=colors[var], label=(var if bar_num == 1 else '_none'))
offset += var_data[var]['mean']
plt.bar(bar_num, var_data[scaling_var]['mean']-offset, 0.8, bottom=offset,
color=colors[scaling_var], label=(scaling_var if bar_num == 1 else '_none'))
sub_ax.set_xticks([1.4, 2.4])
sub_ax.set_xticklabels(('test', 'bench'))
plt.legend(loc=6, bbox_to_anchor=(1.05, 0.5))
plt.tight_layout()
sub_ax = plt.subplot(1, n_subplots+1, n_subplots+1)
hid_bar = plt.bar(1, 100)
for group in hid_bar:
group.set_visible(False)
sub_ax.set_visible(False)
if livvkit.publish:
plt.savefig(os.path.splitext(plot_file)[0]+'.eps', dpi=600)
plt.savefig(plot_file)
plt.close()
return elements.image(title, description, os.path.basename(plot_file)) | [
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Args:
timing_stats: a dictionary of the form
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scaling_var: the variable that accounts for the total runtime
title: the title of the plot
description: the description of the plot
plot_file: the file to write the plot out to
Returns:
an image element containing the plot file and metadata | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.add_source | def add_source(self, ra, dec, flag='', radius=10*q.arcsec):
"""
Add a source to the catalog manually and find data in existing catalogs
Parameters
----------
ra: astropy.units.quantity.Quantity
The RA of the source
dec: astropy.units.quantity.Quantity
The Dec of the source
flag: str
A flag for the source
radius: float
The cross match radius for the list of catalogs
"""
# Get the id
id = int(len(self.catalog)+1)
# Check the coordinates
ra = ra.to(q.deg)
dec = dec.to(q.deg)
datasets = 0
# Search the catalogs for this source
for cat_name,params in self.catalogs.items():
self.Vizier_query(params['cat_loc'], cat_name, ra, dec, radius, ra_col=params['ra_col'], dec_col=params['dec_col'], append=True, group=False)
# Add the source to the catalog
self.catalog = self.catalog.append([id, ra.value, dec.value, flag, datasets], ignore_index=True) | python | def add_source(self, ra, dec, flag='', radius=10*q.arcsec):
"""
Add a source to the catalog manually and find data in existing catalogs
Parameters
----------
ra: astropy.units.quantity.Quantity
The RA of the source
dec: astropy.units.quantity.Quantity
The Dec of the source
flag: str
A flag for the source
radius: float
The cross match radius for the list of catalogs
"""
# Get the id
id = int(len(self.catalog)+1)
# Check the coordinates
ra = ra.to(q.deg)
dec = dec.to(q.deg)
datasets = 0
# Search the catalogs for this source
for cat_name,params in self.catalogs.items():
self.Vizier_query(params['cat_loc'], cat_name, ra, dec, radius, ra_col=params['ra_col'], dec_col=params['dec_col'], append=True, group=False)
# Add the source to the catalog
self.catalog = self.catalog.append([id, ra.value, dec.value, flag, datasets], ignore_index=True) | [
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A flag for the source
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.delete_source | def delete_source(self, id):
"""
Delete a source from the catalog
Parameters
----------
id: int
The id of the source in the catalog
"""
# Set the index
self.catalog.set_index('id')
# Exclude the unwanted source
self.catalog = self.catalog[self.catalog.id!=id]
# Remove the records from the catalogs
for cat_name in self.catalogs:
new_cat = getattr(self, cat_name)[getattr(self, cat_name).source_id!=id]
print('{} records removed from {} catalog'.format(int(len(getattr(self, cat_name))-len(new_cat)), cat_name))
setattr(self, cat_name, new_cat) | python | def delete_source(self, id):
"""
Delete a source from the catalog
Parameters
----------
id: int
The id of the source in the catalog
"""
# Set the index
self.catalog.set_index('id')
# Exclude the unwanted source
self.catalog = self.catalog[self.catalog.id!=id]
# Remove the records from the catalogs
for cat_name in self.catalogs:
new_cat = getattr(self, cat_name)[getattr(self, cat_name).source_id!=id]
print('{} records removed from {} catalog'.format(int(len(getattr(self, cat_name))-len(new_cat)), cat_name))
setattr(self, cat_name, new_cat) | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.ingest_data | def ingest_data(self, data, cat_name, id_col, ra_col='_RAJ2000', dec_col='_DEJ2000', cat_loc='', append=False, count=-1):
"""
Ingest a data file and regroup sources
Parameters
----------
data: str, pandas.DataFrame, astropy.table.Table
The path to the exported VizieR data or the data table
cat_name: str
The name of the added catalog
id_col: str
The name of the column containing the unique ids
ra_col: str
The name of the RA column
dec_col: str
The name of the DEC column
cat_loc: str
The location of the original catalog data
append: bool
Append the catalog rather than replace
count: int
The number of table rows to add
(This is mainly for testing purposes)
"""
# Check if the catalog is already ingested
if not append and cat_name in self.catalogs:
print('Catalog {} already ingested.'.format(cat_name))
else:
if isinstance(data, str):
cat_loc = cat_loc or data
data = pd.read_csv(data, sep='\t', comment='#', engine='python')[:count]
elif isinstance(data, pd.core.frame.DataFrame):
cat_loc = cat_loc or type(data)
elif isinstance(data, (at.QTable, at.Table)):
cat_loc = cat_loc or type(data)
data = pd.DataFrame(list(data), columns=data.colnames)
else:
print("Sorry, but I cannot read that data. Try an ascii file cat_loc, astropy table, or pandas data frame.")
return
# Make sure ra and dec are decimal degrees
if isinstance(data[ra_col][0], str):
crds = coord.SkyCoord(ra=data[ra_col], dec=data[dec_col], unit=(q.hour, q.deg), frame='icrs')
data.insert(0,'dec', crds.dec)
data.insert(0,'ra', crds.ra)
elif isinstance(data[ra_col][0], float):
data.rename(columns={ra_col:'ra', dec_col:'dec'}, inplace=True)
else:
print("I can't read the RA and DEC of the input data. Please try again.")
return
# Change some names
try:
last = len(getattr(self, cat_name)) if append else 0
data.insert(0,'catID', ['{}_{}'.format(cat_name,n+1) for n in range(last,last+len(data))])
data.insert(0,'dec_corr', data['dec'])
data.insert(0,'ra_corr', data['ra'])
data.insert(0,'source_id', np.nan)
print('Ingesting {} rows from {} catalog...'.format(len(data),cat_name))
# Save the raw data as an attribute
if append:
setattr(self, cat_name, getattr(self, cat_name).append(data, ignore_index=True))
else:
setattr(self, cat_name, data)
# Update the history
self.history += "\n{}: Catalog {} ingested.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),cat_name)
self.catalogs.update({cat_name:{'cat_loc':cat_loc, 'id_col':id_col, 'ra_col':ra_col, 'dec_col':dec_col}})
except AttributeError:
print("No catalog named '{}'. Set 'append=False' to create it.".format(cat_name)) | python | def ingest_data(self, data, cat_name, id_col, ra_col='_RAJ2000', dec_col='_DEJ2000', cat_loc='', append=False, count=-1):
"""
Ingest a data file and regroup sources
Parameters
----------
data: str, pandas.DataFrame, astropy.table.Table
The path to the exported VizieR data or the data table
cat_name: str
The name of the added catalog
id_col: str
The name of the column containing the unique ids
ra_col: str
The name of the RA column
dec_col: str
The name of the DEC column
cat_loc: str
The location of the original catalog data
append: bool
Append the catalog rather than replace
count: int
The number of table rows to add
(This is mainly for testing purposes)
"""
# Check if the catalog is already ingested
if not append and cat_name in self.catalogs:
print('Catalog {} already ingested.'.format(cat_name))
else:
if isinstance(data, str):
cat_loc = cat_loc or data
data = pd.read_csv(data, sep='\t', comment='#', engine='python')[:count]
elif isinstance(data, pd.core.frame.DataFrame):
cat_loc = cat_loc or type(data)
elif isinstance(data, (at.QTable, at.Table)):
cat_loc = cat_loc or type(data)
data = pd.DataFrame(list(data), columns=data.colnames)
else:
print("Sorry, but I cannot read that data. Try an ascii file cat_loc, astropy table, or pandas data frame.")
return
# Make sure ra and dec are decimal degrees
if isinstance(data[ra_col][0], str):
crds = coord.SkyCoord(ra=data[ra_col], dec=data[dec_col], unit=(q.hour, q.deg), frame='icrs')
data.insert(0,'dec', crds.dec)
data.insert(0,'ra', crds.ra)
elif isinstance(data[ra_col][0], float):
data.rename(columns={ra_col:'ra', dec_col:'dec'}, inplace=True)
else:
print("I can't read the RA and DEC of the input data. Please try again.")
return
# Change some names
try:
last = len(getattr(self, cat_name)) if append else 0
data.insert(0,'catID', ['{}_{}'.format(cat_name,n+1) for n in range(last,last+len(data))])
data.insert(0,'dec_corr', data['dec'])
data.insert(0,'ra_corr', data['ra'])
data.insert(0,'source_id', np.nan)
print('Ingesting {} rows from {} catalog...'.format(len(data),cat_name))
# Save the raw data as an attribute
if append:
setattr(self, cat_name, getattr(self, cat_name).append(data, ignore_index=True))
else:
setattr(self, cat_name, data)
# Update the history
self.history += "\n{}: Catalog {} ingested.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"),cat_name)
self.catalogs.update({cat_name:{'cat_loc':cat_loc, 'id_col':id_col, 'ra_col':ra_col, 'dec_col':dec_col}})
except AttributeError:
print("No catalog named '{}'. Set 'append=False' to create it.".format(cat_name)) | [
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cat_name: str
The name of the added catalog
id_col: str
The name of the column containing the unique ids
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The name of the RA column
dec_col: str
The name of the DEC column
cat_loc: str
The location of the original catalog data
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Append the catalog rather than replace
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The number of table rows to add
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.inventory | def inventory(self, source_id):
"""
Look at the inventory for a given source
Parameters
----------
source_id: int
The id of the source to inspect
"""
if self.n_sources==0:
print('Please run group_sources() to create the catalog first.')
else:
if source_id>self.n_sources or source_id<1 or not isinstance(source_id, int):
print('Please enter an integer between 1 and',self.n_sources)
else:
print('Source:')
print(at.Table.from_pandas(self.catalog[self.catalog['id']==source_id]).pprint())
for cat_name in self.catalogs:
cat = getattr(self, cat_name)
rows = cat[cat['source_id']==source_id]
if not rows.empty:
print('\n{}:'.format(cat_name))
at.Table.from_pandas(rows).pprint() | python | def inventory(self, source_id):
"""
Look at the inventory for a given source
Parameters
----------
source_id: int
The id of the source to inspect
"""
if self.n_sources==0:
print('Please run group_sources() to create the catalog first.')
else:
if source_id>self.n_sources or source_id<1 or not isinstance(source_id, int):
print('Please enter an integer between 1 and',self.n_sources)
else:
print('Source:')
print(at.Table.from_pandas(self.catalog[self.catalog['id']==source_id]).pprint())
for cat_name in self.catalogs:
cat = getattr(self, cat_name)
rows = cat[cat['source_id']==source_id]
if not rows.empty:
print('\n{}:'.format(cat_name))
at.Table.from_pandas(rows).pprint() | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog._catalog_check | def _catalog_check(self, cat_name, append=False):
"""
Check to see if the name of the ingested catalog is valid
Parameters
----------
cat_name: str
The name of the catalog in the Catalog object
append: bool
Append the catalog rather than replace
Returns
-------
bool
True if good catalog name else False
"""
good = True
# Make sure the attribute name is good
if cat_name[0].isdigit():
print("No names beginning with numbers please!")
good = False
# Make sure catalog is unique
if not append and cat_name in self.catalogs:
print("Catalog {} already ingested. Set 'append=True' to add more records.".format(cat_name))
good = False
return good | python | def _catalog_check(self, cat_name, append=False):
"""
Check to see if the name of the ingested catalog is valid
Parameters
----------
cat_name: str
The name of the catalog in the Catalog object
append: bool
Append the catalog rather than replace
Returns
-------
bool
True if good catalog name else False
"""
good = True
# Make sure the attribute name is good
if cat_name[0].isdigit():
print("No names beginning with numbers please!")
good = False
# Make sure catalog is unique
if not append and cat_name in self.catalogs:
print("Catalog {} already ingested. Set 'append=True' to add more records.".format(cat_name))
good = False
return good | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.SDSS_spectra_query | def SDSS_spectra_query(self, cat_name, ra, dec, radius, group=True, **kwargs):
"""
Use astroquery to search SDSS for sources within a search cone
Parameters
----------
cat_name: str
A name for the imported catalog (e.g. '2MASS')
ra: astropy.units.quantity.Quantity
The RA of the center of the cone search
dec: astropy.units.quantity.Quantity
The Dec of the center of the cone search
radius: astropy.units.quantity.Quantity
The radius of the cone search
"""
# Verify the cat_name
if self._catalog_check(cat_name):
# Prep the current catalog as an astropy.QTable
tab = at.Table.from_pandas(self.catalog)
# Cone search Vizier
print("Searching SDSS for sources within {} of ({}, {}). Please be patient...".format(viz_cat, radius, ra, dec))
crds = coord.SkyCoord(ra=ra, dec=dec, frame='icrs')
try:
data = SDSS.query_region(crds, spectro=True, radius=radius)
except:
print("No data found in SDSS within {} of ({}, {}).".format(viz_cat, radius, ra, dec))
return
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col)
# Regroup
if len(self.catalogs)>1 and group:
self.group_sources(self.xmatch_radius) | python | def SDSS_spectra_query(self, cat_name, ra, dec, radius, group=True, **kwargs):
"""
Use astroquery to search SDSS for sources within a search cone
Parameters
----------
cat_name: str
A name for the imported catalog (e.g. '2MASS')
ra: astropy.units.quantity.Quantity
The RA of the center of the cone search
dec: astropy.units.quantity.Quantity
The Dec of the center of the cone search
radius: astropy.units.quantity.Quantity
The radius of the cone search
"""
# Verify the cat_name
if self._catalog_check(cat_name):
# Prep the current catalog as an astropy.QTable
tab = at.Table.from_pandas(self.catalog)
# Cone search Vizier
print("Searching SDSS for sources within {} of ({}, {}). Please be patient...".format(viz_cat, radius, ra, dec))
crds = coord.SkyCoord(ra=ra, dec=dec, frame='icrs')
try:
data = SDSS.query_region(crds, spectro=True, radius=radius)
except:
print("No data found in SDSS within {} of ({}, {}).".format(viz_cat, radius, ra, dec))
return
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col)
# Regroup
if len(self.catalogs)>1 and group:
self.group_sources(self.xmatch_radius) | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.Vizier_query | def Vizier_query(self, viz_cat, cat_name, ra, dec, radius, ra_col='RAJ2000', dec_col='DEJ2000', columns=["**"], append=False, group=True, **kwargs):
"""
Use astroquery to search a catalog for sources within a search cone
Parameters
----------
viz_cat: str
The catalog string from Vizier (e.g. 'II/246' for 2MASS PSC)
cat_name: str
A name for the imported catalog (e.g. '2MASS')
ra: astropy.units.quantity.Quantity
The RA of the center of the cone search
dec: astropy.units.quantity.Quantity
The Dec of the center of the cone search
radius: astropy.units.quantity.Quantity
The radius of the cone search
ra_col: str
The name of the RA column in the raw catalog
dec_col: str
The name of the Dec column in the raw catalog
columns: sequence
The list of columns to pass to astroquery
append: bool
Append the catalog rather than replace
"""
# Verify the cat_name
if self._catalog_check(cat_name, append=append):
# Cone search Vizier
print("Searching {} for sources within {} of ({}, {}). Please be patient...".format(viz_cat, radius, ra, dec))
crds = coord.SkyCoord(ra=ra, dec=dec, frame='icrs')
V = Vizier(columns=columns, **kwargs)
V.ROW_LIMIT = -1
try:
data = V.query_region(crds, radius=radius, catalog=viz_cat)[0]
except:
print("No data found in {} within {} of ({}, {}).".format(viz_cat, radius, ra, dec))
return
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col, cat_loc=viz_cat, append=append)
# Regroup
if len(self.catalogs)>1 and group:
self.group_sources(self.xmatch_radius) | python | def Vizier_query(self, viz_cat, cat_name, ra, dec, radius, ra_col='RAJ2000', dec_col='DEJ2000', columns=["**"], append=False, group=True, **kwargs):
"""
Use astroquery to search a catalog for sources within a search cone
Parameters
----------
viz_cat: str
The catalog string from Vizier (e.g. 'II/246' for 2MASS PSC)
cat_name: str
A name for the imported catalog (e.g. '2MASS')
ra: astropy.units.quantity.Quantity
The RA of the center of the cone search
dec: astropy.units.quantity.Quantity
The Dec of the center of the cone search
radius: astropy.units.quantity.Quantity
The radius of the cone search
ra_col: str
The name of the RA column in the raw catalog
dec_col: str
The name of the Dec column in the raw catalog
columns: sequence
The list of columns to pass to astroquery
append: bool
Append the catalog rather than replace
"""
# Verify the cat_name
if self._catalog_check(cat_name, append=append):
# Cone search Vizier
print("Searching {} for sources within {} of ({}, {}). Please be patient...".format(viz_cat, radius, ra, dec))
crds = coord.SkyCoord(ra=ra, dec=dec, frame='icrs')
V = Vizier(columns=columns, **kwargs)
V.ROW_LIMIT = -1
try:
data = V.query_region(crds, radius=radius, catalog=viz_cat)[0]
except:
print("No data found in {} within {} of ({}, {}).".format(viz_cat, radius, ra, dec))
return
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col, cat_loc=viz_cat, append=append)
# Regroup
if len(self.catalogs)>1 and group:
self.group_sources(self.xmatch_radius) | [
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The RA of the center of the cone search
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The radius of the cone search
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The name of the RA column in the raw catalog
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The list of columns to pass to astroquery
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.Vizier_xmatch | def Vizier_xmatch(self, viz_cat, cat_name, ra_col='_RAJ2000', dec_col='_DEJ2000', radius='', group=True):
"""
Use astroquery to pull in and cross match a catalog with sources in self.catalog
Parameters
----------
viz_cat: str
The catalog string from Vizier (e.g. 'II/246' for 2MASS PSC)
cat_name: str
A name for the imported catalog (e.g. '2MASS')
radius: astropy.units.quantity.Quantity
The matching radius
"""
# Make sure sources have been grouped
if self.catalog.empty:
print('Please run group_sources() before cross matching.')
return
if self._catalog_check(cat_name):
# Verify the cat_name
viz_cat = "vizier:{}".format(viz_cat)
# Prep the current catalog as an astropy.QTable
tab = at.Table.from_pandas(self.catalog)
# Crossmatch with Vizier
print("Cross matching {} sources with {} catalog. Please be patient...".format(len(tab), viz_cat))
data = XMatch.query(cat1=tab, cat2=viz_cat, max_distance=radius or self.xmatch_radius*q.deg, colRA1='ra', colDec1='dec', colRA2=ra_col, colDec2=dec_col)
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col)
# Regroup
if group:
self.group_sources(self.xmatch_radius) | python | def Vizier_xmatch(self, viz_cat, cat_name, ra_col='_RAJ2000', dec_col='_DEJ2000', radius='', group=True):
"""
Use astroquery to pull in and cross match a catalog with sources in self.catalog
Parameters
----------
viz_cat: str
The catalog string from Vizier (e.g. 'II/246' for 2MASS PSC)
cat_name: str
A name for the imported catalog (e.g. '2MASS')
radius: astropy.units.quantity.Quantity
The matching radius
"""
# Make sure sources have been grouped
if self.catalog.empty:
print('Please run group_sources() before cross matching.')
return
if self._catalog_check(cat_name):
# Verify the cat_name
viz_cat = "vizier:{}".format(viz_cat)
# Prep the current catalog as an astropy.QTable
tab = at.Table.from_pandas(self.catalog)
# Crossmatch with Vizier
print("Cross matching {} sources with {} catalog. Please be patient...".format(len(tab), viz_cat))
data = XMatch.query(cat1=tab, cat2=viz_cat, max_distance=radius or self.xmatch_radius*q.deg, colRA1='ra', colDec1='dec', colRA2=ra_col, colDec2=dec_col)
# Ingest the data
self.ingest_data(data, cat_name, 'id', ra_col=ra_col, dec_col=dec_col)
# Regroup
if group:
self.group_sources(self.xmatch_radius) | [
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A name for the imported catalog (e.g. '2MASS')
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.group_sources | def group_sources(self, radius='', plot=False):
"""
Calculate the centers of the point clusters given the
radius and minimum number of points
Parameters
----------
coords: array-like
The list of (x,y) coordinates of all clicks
radius: int
The distance threshold in degrees for cluster membership
[default of 0.36 arcseconds]
Returns
-------
np.ndarray
An array of the cluster centers
"""
if len(self.catalogs)==0:
print("No catalogs to start grouping! Add one with the ingest_data() method first.")
else:
# Gather the catalogs
print('Grouping sources from the following catalogs:',list(self.catalogs.keys()))
cats = pd.concat([getattr(self, cat_name) for cat_name in self.catalogs])
# Clear the source grouping
cats['oncID'] = np.nan
cats['oncflag'] = ''
self.xmatch_radius = radius if isinstance(radius,(float,int)) else self.xmatch_radius
# Make a list of the coordinates of each catalog row
coords = cats[['ra_corr','dec_corr']].values
# Perform DBSCAN to find clusters
db = DBSCAN(eps=self.xmatch_radius, min_samples=1, n_jobs=-1).fit(coords)
# Group the sources
core_samples_mask = np.zeros_like(db.labels_, dtype=bool)
core_samples_mask[db.core_sample_indices_] = True
source_ids = db.labels_+1
unique_source_ids = list(set(source_ids))
self.n_sources = len(unique_source_ids)
# Get the average coordinates of all clusters
unique_coords = np.asarray([np.mean(coords[source_ids==id], axis=0) for id in list(set(source_ids))])
# Generate a source catalog
self.catalog = pd.DataFrame(columns=('id','ra','dec','flag','datasets'))
self.catalog['id'] = unique_source_ids
self.catalog[['ra','dec']] = unique_coords
self.catalog['flag'] = [None]*len(unique_source_ids)
# self.catalog['flag'] = ['d{}'.format(i) if i>1 else '' for i in Counter(source_ids).values()]
self.catalog['datasets'] = Counter(source_ids).values()
# Update history
self.history += "\n{}: Catalog grouped with radius {} arcsec.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), self.xmatch_radius)
# Update the source_ids in each catalog
cats['source_id'] = source_ids
for cat_name in self.catalogs:
# Get the source_ids for the catalog
cat_source_ids = cats.loc[cats['catID'].str.startswith(cat_name)]['source_id']
# Get the catalog
cat = getattr(self, cat_name)
# Update the source_ids and put it back
cat['source_id'] = cat_source_ids
setattr(self, cat_name, cat)
del cat, cat_source_ids
del cats
# Plot it
if plot:
plt.figure()
plt.title('{} clusters for {} sources'.format(self.n_sources,len(coords)))
colors = [plt.cm.Spectral(each) for each in np.linspace(0, 1, self.n_sources)]
for k, col in zip(unique_source_ids, colors):
class_member_mask = (source_ids == k)
xy = coords[class_member_mask & core_samples_mask]
marker = 'o'
if len(xy)==1:
col = [0,0,0,1]
marker = '+'
plt.plot(xy[:, 0], xy[:, 1], color=tuple(col), marker=marker, markerfacecolor=tuple(col)) | python | def group_sources(self, radius='', plot=False):
"""
Calculate the centers of the point clusters given the
radius and minimum number of points
Parameters
----------
coords: array-like
The list of (x,y) coordinates of all clicks
radius: int
The distance threshold in degrees for cluster membership
[default of 0.36 arcseconds]
Returns
-------
np.ndarray
An array of the cluster centers
"""
if len(self.catalogs)==0:
print("No catalogs to start grouping! Add one with the ingest_data() method first.")
else:
# Gather the catalogs
print('Grouping sources from the following catalogs:',list(self.catalogs.keys()))
cats = pd.concat([getattr(self, cat_name) for cat_name in self.catalogs])
# Clear the source grouping
cats['oncID'] = np.nan
cats['oncflag'] = ''
self.xmatch_radius = radius if isinstance(radius,(float,int)) else self.xmatch_radius
# Make a list of the coordinates of each catalog row
coords = cats[['ra_corr','dec_corr']].values
# Perform DBSCAN to find clusters
db = DBSCAN(eps=self.xmatch_radius, min_samples=1, n_jobs=-1).fit(coords)
# Group the sources
core_samples_mask = np.zeros_like(db.labels_, dtype=bool)
core_samples_mask[db.core_sample_indices_] = True
source_ids = db.labels_+1
unique_source_ids = list(set(source_ids))
self.n_sources = len(unique_source_ids)
# Get the average coordinates of all clusters
unique_coords = np.asarray([np.mean(coords[source_ids==id], axis=0) for id in list(set(source_ids))])
# Generate a source catalog
self.catalog = pd.DataFrame(columns=('id','ra','dec','flag','datasets'))
self.catalog['id'] = unique_source_ids
self.catalog[['ra','dec']] = unique_coords
self.catalog['flag'] = [None]*len(unique_source_ids)
# self.catalog['flag'] = ['d{}'.format(i) if i>1 else '' for i in Counter(source_ids).values()]
self.catalog['datasets'] = Counter(source_ids).values()
# Update history
self.history += "\n{}: Catalog grouped with radius {} arcsec.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), self.xmatch_radius)
# Update the source_ids in each catalog
cats['source_id'] = source_ids
for cat_name in self.catalogs:
# Get the source_ids for the catalog
cat_source_ids = cats.loc[cats['catID'].str.startswith(cat_name)]['source_id']
# Get the catalog
cat = getattr(self, cat_name)
# Update the source_ids and put it back
cat['source_id'] = cat_source_ids
setattr(self, cat_name, cat)
del cat, cat_source_ids
del cats
# Plot it
if plot:
plt.figure()
plt.title('{} clusters for {} sources'.format(self.n_sources,len(coords)))
colors = [plt.cm.Spectral(each) for each in np.linspace(0, 1, self.n_sources)]
for k, col in zip(unique_source_ids, colors):
class_member_mask = (source_ids == k)
xy = coords[class_member_mask & core_samples_mask]
marker = 'o'
if len(xy)==1:
col = [0,0,0,1]
marker = '+'
plt.plot(xy[:, 0], xy[:, 1], color=tuple(col), marker=marker, markerfacecolor=tuple(col)) | [
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The distance threshold in degrees for cluster membership
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np.ndarray
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.drop_catalog | def drop_catalog(self, cat_name):
"""
Remove an imported catalog from the Dataset object
Parameters
----------
cat_name: str
The name given to the catalog
"""
# Delete the name and data
self.catalogs.pop(cat_name)
delattr(self, cat_name)
# Update history
print("Deleted {} catalog.".format(cat_name))
self.history += "\n{}: Deleted {} catalog.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), cat_name) | python | def drop_catalog(self, cat_name):
"""
Remove an imported catalog from the Dataset object
Parameters
----------
cat_name: str
The name given to the catalog
"""
# Delete the name and data
self.catalogs.pop(cat_name)
delattr(self, cat_name)
# Update history
print("Deleted {} catalog.".format(cat_name))
self.history += "\n{}: Deleted {} catalog.".format(datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S"), cat_name) | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.load | def load(self, path):
"""
Load the catalog from file
Parameters
----------
path: str
The path to the file
"""
# Get the object
DB = joblib.load(path)
# Load the attributes
self.catalog = DB.catalog
self.n_sources = DB.n_sources
self.name = DB.name
self.history = DB.history
del DB | python | def load(self, path):
"""
Load the catalog from file
Parameters
----------
path: str
The path to the file
"""
# Get the object
DB = joblib.load(path)
# Load the attributes
self.catalog = DB.catalog
self.n_sources = DB.n_sources
self.name = DB.name
self.history = DB.history
del DB | [
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BDNYC/astrodbkit | astrodbkit/astrocat.py | Catalog.correct_offsets | def correct_offsets(self, cat_name, truth='ACS'):
"""
Function to determine systematic, linear offsets between catalogs
FUTURE -- do this with TweakReg, which also accounts for rotation/scaling
See thread at https://github.com/spacetelescope/drizzlepac/issues/77
Parameters
----------
cat_name: str
Name of catalog to correct
truth: str
The catalog to measure against
"""
# Must be grouped!
if not self.xmatch_radius:
print("Please run group_sources() before running correct_offsets().")
else:
# First, remove any previous catalog correction
self.catalog.loc[self.catalog['cat_name']==cat_name, 'ra_corr'] = self.catalog.loc[self.catalog['cat_name']==cat_name, '_RAJ2000']
self.catalog.loc[self.catalog['cat_name']==cat_name, 'dec_corr'] = self.catalog.loc[self.catalog['cat_name']==cat_name, '_DEJ2000']
# Copy the catalog
onc_gr = self.catalog.copy()
# restrict to one-to-one matches, sort by oncID so that matches are paired
o2o_new = onc_gr.loc[(onc_gr['oncflag'].str.contains('o')) & (onc_gr['cat_name'] == cat_name) ,:].sort_values('oncID')
o2o_old = onc_gr.loc[(onc_gr['oncID'].isin(o2o_new['oncID']) & (onc_gr['cat_name'] == truth)), :].sort_values('oncID')
# get coords
c_o2o_new = SkyCoord(o2o_new.loc[o2o_new['cat_name'] == cat_name, 'ra_corr'],\
o2o_new.loc[o2o_new['cat_name'] == cat_name, 'dec_corr'], unit='degree')
c_o2o_old = SkyCoord(o2o_old.loc[o2o_old['cat_name'] == truth, 'ra_corr'],\
o2o_old.loc[o2o_old['cat_name'] == truth, 'dec_corr'], unit='degree')
print(len(c_o2o_old), 'one-to-one matches found!')
if len(c_o2o_old)>0:
delta_ra = []
delta_dec = []
for i in range(len(c_o2o_old)):
# offsets FROM ACS TO new catalog
ri, di = c_o2o_old[i].spherical_offsets_to(c_o2o_new[i])
delta_ra.append(ri.arcsecond)
delta_dec.append(di.arcsecond)
progress_meter((i+1)*100./len(c_o2o_old))
delta_ra = np.array(delta_ra)
delta_dec = np.array(delta_dec)
print('\n')
# fit a gaussian
mu_ra, std_ra = norm.fit(delta_ra)
mu_dec, std_dec = norm.fit(delta_dec)
# Fix precision
mu_ra = round(mu_ra, 6)
mu_dec = round(mu_dec, 6)
# Update the coordinates of the appropriate sources
print('Shifting {} sources by {}" in RA and {}" in Dec...'.format(cat_name,mu_ra,mu_dec))
self.catalog.loc[self.catalog['cat_name']==cat_name, 'ra_corr'] += mu_ra
self.catalog.loc[self.catalog['cat_name']==cat_name, 'dec_corr'] += mu_dec
# Update history
now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
self.history += "\n{}: {} sources shifted by {} deg in RA and {} deg in Declination.".format(now, cat_name, mu_ra, mu_dec)
# Regroup the sources since many have moved
self.group_sources(self.xmatch_radius)
else:
print('Cannot correct offsets in {} sources.'.format(cat_name)) | python | def correct_offsets(self, cat_name, truth='ACS'):
"""
Function to determine systematic, linear offsets between catalogs
FUTURE -- do this with TweakReg, which also accounts for rotation/scaling
See thread at https://github.com/spacetelescope/drizzlepac/issues/77
Parameters
----------
cat_name: str
Name of catalog to correct
truth: str
The catalog to measure against
"""
# Must be grouped!
if not self.xmatch_radius:
print("Please run group_sources() before running correct_offsets().")
else:
# First, remove any previous catalog correction
self.catalog.loc[self.catalog['cat_name']==cat_name, 'ra_corr'] = self.catalog.loc[self.catalog['cat_name']==cat_name, '_RAJ2000']
self.catalog.loc[self.catalog['cat_name']==cat_name, 'dec_corr'] = self.catalog.loc[self.catalog['cat_name']==cat_name, '_DEJ2000']
# Copy the catalog
onc_gr = self.catalog.copy()
# restrict to one-to-one matches, sort by oncID so that matches are paired
o2o_new = onc_gr.loc[(onc_gr['oncflag'].str.contains('o')) & (onc_gr['cat_name'] == cat_name) ,:].sort_values('oncID')
o2o_old = onc_gr.loc[(onc_gr['oncID'].isin(o2o_new['oncID']) & (onc_gr['cat_name'] == truth)), :].sort_values('oncID')
# get coords
c_o2o_new = SkyCoord(o2o_new.loc[o2o_new['cat_name'] == cat_name, 'ra_corr'],\
o2o_new.loc[o2o_new['cat_name'] == cat_name, 'dec_corr'], unit='degree')
c_o2o_old = SkyCoord(o2o_old.loc[o2o_old['cat_name'] == truth, 'ra_corr'],\
o2o_old.loc[o2o_old['cat_name'] == truth, 'dec_corr'], unit='degree')
print(len(c_o2o_old), 'one-to-one matches found!')
if len(c_o2o_old)>0:
delta_ra = []
delta_dec = []
for i in range(len(c_o2o_old)):
# offsets FROM ACS TO new catalog
ri, di = c_o2o_old[i].spherical_offsets_to(c_o2o_new[i])
delta_ra.append(ri.arcsecond)
delta_dec.append(di.arcsecond)
progress_meter((i+1)*100./len(c_o2o_old))
delta_ra = np.array(delta_ra)
delta_dec = np.array(delta_dec)
print('\n')
# fit a gaussian
mu_ra, std_ra = norm.fit(delta_ra)
mu_dec, std_dec = norm.fit(delta_dec)
# Fix precision
mu_ra = round(mu_ra, 6)
mu_dec = round(mu_dec, 6)
# Update the coordinates of the appropriate sources
print('Shifting {} sources by {}" in RA and {}" in Dec...'.format(cat_name,mu_ra,mu_dec))
self.catalog.loc[self.catalog['cat_name']==cat_name, 'ra_corr'] += mu_ra
self.catalog.loc[self.catalog['cat_name']==cat_name, 'dec_corr'] += mu_dec
# Update history
now = datetime.datetime.now().strftime("%Y-%m-%d %H:%M:%S")
self.history += "\n{}: {} sources shifted by {} deg in RA and {} deg in Declination.".format(now, cat_name, mu_ra, mu_dec)
# Regroup the sources since many have moved
self.group_sources(self.xmatch_radius)
else:
print('Cannot correct offsets in {} sources.'.format(cat_name)) | [
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inveniosoftware/invenio-pages | invenio_pages/ext.py | _InvenioPagesState.jinja_env | def jinja_env(self):
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if self._jinja_env is None:
self._jinja_env = SandboxedEnvironment(
extensions=[
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for var in self.app.config['PAGES_WHITELIST_CONFIG_KEYS']:
self._jinja_env.globals[var] = self.app.config.get(var)
return self._jinja_env | python | def jinja_env(self):
"""Create a sandboxed Jinja environment."""
if self._jinja_env is None:
self._jinja_env = SandboxedEnvironment(
extensions=[
'jinja2.ext.autoescape', 'jinja2.ext.with_', ],
autoescape=True,
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self._jinja_env.globals['url_for'] = url_for
# Load whitelisted configuration variables.
for var in self.app.config['PAGES_WHITELIST_CONFIG_KEYS']:
self._jinja_env.globals[var] = self.app.config.get(var)
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inveniosoftware/invenio-pages | invenio_pages/ext.py | _InvenioPagesState.render_template | def render_template(self, source, **kwargs_context):
r"""Render a template string using sandboxed environment.
:param source: A string containing the page source.
:param \*\*kwargs_context: The context associated with the page.
:returns: The rendered template.
"""
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r"""Render a template string using sandboxed environment.
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inveniosoftware/invenio-pages | invenio_pages/ext.py | InvenioPages.wrap_errorhandler | def wrap_errorhandler(app):
"""Wrap error handler.
:param app: The Flask application.
"""
try:
existing_handler = app.error_handler_spec[None][404][NotFound]
except (KeyError, TypeError):
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app.error_handler_spec[None][404][NotFound] = \
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else:
app.error_handler_spec.setdefault(None, {}).setdefault(404, {})
app.error_handler_spec[None][404][NotFound] = handle_not_found | python | def wrap_errorhandler(app):
"""Wrap error handler.
:param app: The Flask application.
"""
try:
existing_handler = app.error_handler_spec[None][404][NotFound]
except (KeyError, TypeError):
existing_handler = None
if existing_handler:
app.error_handler_spec[None][404][NotFound] = \
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app.error_handler_spec.setdefault(None, {}).setdefault(404, {})
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inveniosoftware/invenio-pages | invenio_pages/ext.py | InvenioPages.init_app | def init_app(self, app):
"""Flask application initialization.
:param app: The Flask application.
:returns: The :class:`invenio_pages.ext.InvenioPages` instance
initialized.
"""
self.init_config(app)
self.wrap_errorhandler(app)
app.extensions['invenio-pages'] = _InvenioPagesState(app)
return app.extensions['invenio-pages'] | python | def init_app(self, app):
"""Flask application initialization.
:param app: The Flask application.
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self.init_config(app)
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PGower/PyCanvas | pycanvas/apis/conferences.py | ConferencesAPI.list_conferences_groups | def list_conferences_groups(self, group_id):
"""
List conferences.
Retrieve the list of conferences for this context
This API returns a JSON object containing the list of conferences,
the key for the list of conferences is "conferences"
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
self.logger.debug("GET /api/v1/groups/{group_id}/conferences with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/groups/{group_id}/conferences".format(**path), data=data, params=params, all_pages=True) | python | def list_conferences_groups(self, group_id):
"""
List conferences.
Retrieve the list of conferences for this context
This API returns a JSON object containing the list of conferences,
the key for the list of conferences is "conferences"
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - group_id
"""ID"""
path["group_id"] = group_id
self.logger.debug("GET /api/v1/groups/{group_id}/conferences with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/groups/{group_id}/conferences".format(**path), data=data, params=params, all_pages=True) | [
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PGower/PyCanvas | pycanvas/apis/quiz_assignment_overrides.py | QuizAssignmentOverridesAPI.retrieve_assignment_overridden_dates_for_quizzes | def retrieve_assignment_overridden_dates_for_quizzes(self, course_id, quiz_assignment_overrides_0_quiz_ids=None):
"""
Retrieve assignment-overridden dates for quizzes.
Retrieve the actual due-at, unlock-at, and available-at dates for quizzes
based on the assignment overrides active for the current API user.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - quiz_assignment_overrides[0][quiz_ids]
"""An array of quiz IDs. If omitted, overrides for all quizzes available to
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if quiz_assignment_overrides_0_quiz_ids is not None:
params["quiz_assignment_overrides[0][quiz_ids]"] = quiz_assignment_overrides_0_quiz_ids
self.logger.debug("GET /api/v1/courses/{course_id}/quizzes/assignment_overrides with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/quizzes/assignment_overrides".format(**path), data=data, params=params, single_item=True) | python | def retrieve_assignment_overridden_dates_for_quizzes(self, course_id, quiz_assignment_overrides_0_quiz_ids=None):
"""
Retrieve assignment-overridden dates for quizzes.
Retrieve the actual due-at, unlock-at, and available-at dates for quizzes
based on the assignment overrides active for the current API user.
"""
path = {}
data = {}
params = {}
# REQUIRED - PATH - course_id
"""ID"""
path["course_id"] = course_id
# OPTIONAL - quiz_assignment_overrides[0][quiz_ids]
"""An array of quiz IDs. If omitted, overrides for all quizzes available to
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if quiz_assignment_overrides_0_quiz_ids is not None:
params["quiz_assignment_overrides[0][quiz_ids]"] = quiz_assignment_overrides_0_quiz_ids
self.logger.debug("GET /api/v1/courses/{course_id}/quizzes/assignment_overrides with query params: {params} and form data: {data}".format(params=params, data=data, **path))
return self.generic_request("GET", "/api/v1/courses/{course_id}/quizzes/assignment_overrides".format(**path), data=data, params=params, single_item=True) | [
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hbldh/sudokuextract | sudokuextract/ml/knn.py | KNeighborsClassifier.fit | def fit(self, X, y):
"""Fit the model using X as training data and y as target values"""
self._data = X
self._classes = np.unique(y)
self._labels = y
self._is_fitted = True | python | def fit(self, X, y):
"""Fit the model using X as training data and y as target values"""
self._data = X
self._classes = np.unique(y)
self._labels = y
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hbldh/sudokuextract | sudokuextract/ml/knn.py | KNeighborsClassifier.predict | def predict(self, X):
"""Predict the class labels for the provided data
Parameters
----------
X : array-like, shape (n_query, n_features).
Test samples.
Returns
-------
y : array of shape [n_samples]
Class labels for each data sample.
"""
# TODO: Make classification of multiple samples a bit more effective...
if X.ndim > 1 and X.shape[1] != 1:
out = []
for x in X:
out += self.predict(x)
return out
X = X.flatten()
if self.metric == 'minkowski':
dists = np.sum(np.abs(self._data - X) ** self.p, axis=1)
else:
# TODO: Implement other metrics.
raise ValueError("Only Minkowski distance metric implemented...")
argument = np.argsort(dists)
labels = self._labels[argument[:self.n_neighbors]]
if self.weights == 'distance':
weights = 1 / dists[argument[:self.n_neighbors]]
out = np.zeros((len(self._classes), ), 'float')
for i, c in enumerate(self._classes):
out[i] = np.sum(weights[labels == c])
out /= np.sum(out)
y_pred = self._labels[np.argmax(out)]
else:
y_pred, _ = mode(labels)
return y_pred.tolist() | python | def predict(self, X):
"""Predict the class labels for the provided data
Parameters
----------
X : array-like, shape (n_query, n_features).
Test samples.
Returns
-------
y : array of shape [n_samples]
Class labels for each data sample.
"""
# TODO: Make classification of multiple samples a bit more effective...
if X.ndim > 1 and X.shape[1] != 1:
out = []
for x in X:
out += self.predict(x)
return out
X = X.flatten()
if self.metric == 'minkowski':
dists = np.sum(np.abs(self._data - X) ** self.p, axis=1)
else:
# TODO: Implement other metrics.
raise ValueError("Only Minkowski distance metric implemented...")
argument = np.argsort(dists)
labels = self._labels[argument[:self.n_neighbors]]
if self.weights == 'distance':
weights = 1 / dists[argument[:self.n_neighbors]]
out = np.zeros((len(self._classes), ), 'float')
for i, c in enumerate(self._classes):
out[i] = np.sum(weights[labels == c])
out /= np.sum(out)
y_pred = self._labels[np.argmax(out)]
else:
y_pred, _ = mode(labels)
return y_pred.tolist() | [
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Test samples.
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lobeck/flask-bower | flask_bower/__init__.py | replaced_url_for | def replaced_url_for(endpoint, filename=None, **values):
"""
This function acts as "replacement" for the default url_for() and intercepts if it is a request for bower assets
If the file is not available in bower, the result is passed to flasks url_for().
This is useful - but not recommended - for "overlaying" the static directory (see README.rst).
"""
lookup_result = overlay_url_for(endpoint, filename, **values)
if lookup_result is not None:
return lookup_result
return url_for(endpoint, filename=filename, **values) | python | def replaced_url_for(endpoint, filename=None, **values):
"""
This function acts as "replacement" for the default url_for() and intercepts if it is a request for bower assets
If the file is not available in bower, the result is passed to flasks url_for().
This is useful - but not recommended - for "overlaying" the static directory (see README.rst).
"""
lookup_result = overlay_url_for(endpoint, filename, **values)
if lookup_result is not None:
return lookup_result
return url_for(endpoint, filename=filename, **values) | [
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This is useful - but not recommended - for "overlaying" the static directory (see README.rst). | [
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lobeck/flask-bower | flask_bower/__init__.py | handle_url_error | def handle_url_error(error, endpoint, values):
"""
Intercept BuildErrors of url_for() using flasks build_error_handler API
"""
url = overlay_url_for(endpoint, **values)
if url is None:
exc_type, exc_value, tb = sys.exc_info()
if exc_value is error:
reraise(exc_type, exc_value, tb)
else:
raise error
# url_for will use this result, instead of raising BuildError.
return url | python | def handle_url_error(error, endpoint, values):
"""
Intercept BuildErrors of url_for() using flasks build_error_handler API
"""
url = overlay_url_for(endpoint, **values)
if url is None:
exc_type, exc_value, tb = sys.exc_info()
if exc_value is error:
reraise(exc_type, exc_value, tb)
else:
raise error
# url_for will use this result, instead of raising BuildError.
return url | [
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lobeck/flask-bower | flask_bower/__init__.py | overlay_url_for | def overlay_url_for(endpoint, filename=None, **values):
"""
Replace flasks url_for() function to allow usage without template changes
If the requested endpoint is static or ending in .static, it tries to serve a bower asset, otherwise it will pass
the arguments to flask.url_for()
See http://flask.pocoo.org/docs/0.10/api/#flask.url_for
"""
default_url_for_args = values.copy()
if filename:
default_url_for_args['filename'] = filename
if endpoint == 'static' or endpoint.endswith('.static'):
if os.path.sep in filename:
filename_parts = filename.split(os.path.sep)
component = filename_parts[0]
# Using * magic here to expand list
filename = os.path.join(*filename_parts[1:])
returned_url = build_url(component, filename, **values)
if returned_url is not None:
return returned_url
return None | python | def overlay_url_for(endpoint, filename=None, **values):
"""
Replace flasks url_for() function to allow usage without template changes
If the requested endpoint is static or ending in .static, it tries to serve a bower asset, otherwise it will pass
the arguments to flask.url_for()
See http://flask.pocoo.org/docs/0.10/api/#flask.url_for
"""
default_url_for_args = values.copy()
if filename:
default_url_for_args['filename'] = filename
if endpoint == 'static' or endpoint.endswith('.static'):
if os.path.sep in filename:
filename_parts = filename.split(os.path.sep)
component = filename_parts[0]
# Using * magic here to expand list
filename = os.path.join(*filename_parts[1:])
returned_url = build_url(component, filename, **values)
if returned_url is not None:
return returned_url
return None | [
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See http://flask.pocoo.org/docs/0.10/api/#flask.url_for | [
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