JorgeVB/code_unlearning_dataset · Datasets at Hugging Face

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Calculates the expected lifecycle position the subscription in subscription_ids, and creates a BehindSubscription entry for them. Args: subscription_id (str): ID of subscription to calculate lifecycle for def calculate_subscription_lifecycle(subscription_id): """ Calculates the expected lifecy...
Finds any subscriptions that are behind according to where they should be, and creates a BehindSubscription entry for them. def find_behind_subscriptions(): """ Finds any subscriptions that are behind according to where they should be, and creates a BehindSubscription entry for them. """ subscr...
Sends all the subscriptions for the specified schedule def send(self, request, pk=None): """ Sends all the subscriptions for the specified schedule """ schedule = self.get_object() queue_subscription_send.delay(str(schedule.id)) return Response({}, status=status.HTTP_20...
Return the configured value for the given key name, or `default` if no value is available or key is invalid. def get(self, key: Any, default: Any=None) -> Any: '''Return the configured value for the given key name, or `default` if no value is available or key is invalid.''' return self...
Return the task-specific configuration. def task_config(self, task: Task) -> Any: '''Return the task-specific configuration.''' return self.get(task.__class__.__name__)
Load configuration in JSON format from either a file or a raw data string. async def init(self) -> None: '''Load configuration in JSON format from either a file or a raw data string.''' if self.data: return if self.json_data: try: self.d...
Execute the task inside the asyncio event loop after `DELAY` seconds. Track the time it takes to run, and log when it starts/stops. If/when `reset()` is called, reset the wait time to `DELAY` seconds. async def run_task(self) -> None: '''Execute the task inside the asyncio event loop after `DE...
Reset task execution to `DELAY` seconds from now. def reset(self) -> None: '''Reset task execution to `DELAY` seconds from now.''' Log.debug('resetting timer task %s') self.target = self.time() + self.DELAY
A view decorator which blocks access for requests coming through the load balancer. def internal_only(view_func): """ A view decorator which blocks access for requests coming through the load balancer. """ @functools.wraps(view_func) def wrapper(request, args, *kwargs): forwards = reques...
Validates subscription data before creating Outbound message def post(self, request, args, *kwargs): """ Validates subscription data before creating Outbound message """ schedule_disable.delay(kwargs["subscription_id"]) return Response({"accepted": True}, status=201)
Validates subscription data before creating Outbound message def post(self, request, args, *kwargs): """ Validates subscription data before creating Outbound message """ # Look up subscriber subscription_id = kwargs["subscription_id"] if Subscription.objects.filter(id=subscrip...
Validates subscription data before creating Subscription message def post(self, request, args, *kwargs): """ Validates subscription data before creating Subscription message """ # Ensure that we check for the 'data' key in the request object before # attempting to reference it ...
Starts a celery task that looks through active subscriptions to find and subscriptions that are behind where they should be, and adds a BehindSubscription for them. def find_behind_subscriptions(self, request): """ Starts a celery task that looks through active subscriptions to find ...
Read-Eval-Print-Loop for reading the query, printing it and its parse tree. Exit the loop either with an interrupt or "quit". def repl(): """Read-Eval-Print-Loop for reading the query, printing it and its parse tree. Exit the loop either with an interrupt or "quit". """ while True: try: ...
Initialize the queue and spawn extra worker tasks if this if the first task. Then wait for work items to enter the task queue, and execute the `run()` method with the current work item. async def run_task(self) -> None: '''Initialize the queue and spawn extra worker tasks if this if the ...
Fires off the celery task to ensure that this schedule is in the scheduler Arguments: sender {class} -- The model class, always Schedule instance {Schedule} -- The instance of the Schedule that we want to sync def schedule_saved(sender, instance, **kwargs): """ Fires off the ce...
Fires off the celery task to ensure that this schedule is deactivated Arguments: sender {class} -- The model class, always Schedule instance {Schedule} -- The instance of the schedule that we want to deactivate def schedule_deleted(sender, instance, **kwargs): """ Fires off the...
Execute the task inside the asyncio event loop. Track the time it takes to run, and log when it starts/stops. After `INTERVAL` seconds, if/once the task has finished running, run it again until `stop()` is called. async def run_task(self) -> None: '''Execute the task inside the asynci...
construct a grouping object on the given keys, optionally performing the given reduction on the given values Parameters ---------- keys : indexable object keys to group by values : array_like, optional sequence of values, of the same length as keys if a reduction function is pro...
Group iterable into iterables, in the order of the keys Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ iterable of items in values Notes ----- Memory consumption depends...
Group iterable into iterables, without regard for the ordering of self.index.unique key-group tuples are yielded as soon as they are complete Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ ...
Group sequence into iterables Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ iterable of items in values Notes ----- This is the preferred method if values has random ac...
Group ndarray into ndarray by means of reshaping Parameters ---------- values : ndarray_like, [index.size, ...] Returns ------- ndarray, [groups, group_size, ...] values grouped by key Raises ------ AssertionError This op...
Group values as a list of arrays, or a jagged-array Parameters ---------- values : ndarray, [keys, ...] Returns ------- list of length self.groups of ndarray, [key_count, ...] def split_array_as_list(self, values): """Group values as a list of arrays, or a jagg...
Reduce the values over identical key groups, using the given ufunc reduction is over the first axis, which should have elements corresponding to the keys all other axes are treated indepenently for the sake of this reduction Parameters ---------- values : ndarray, [keys, ...] ...
compute the sum over each group Parameters ---------- values : array_like, [keys, ...] values to sum per group axis : int, optional alternative reduction axis for values dtype : output dtype Returns ------- unique: ndarray, [group...
compute the product over each group Parameters ---------- values : array_like, [keys, ...] values to multiply per group axis : int, optional alternative reduction axis for values dtype : output dtype Returns ------- unique: ndarra...
compute the mean over each group Parameters ---------- values : array_like, [keys, ...] values to take average of per group axis : int, optional alternative reduction axis for values weights : ndarray, [keys, ...], optional weight to use for e...
compute the variance over each group Parameters ---------- values : array_like, [keys, ...] values to take variance of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...
standard deviation over each group Parameters ---------- values : array_like, [keys, ...] values to take standard deviation of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...
compute the median value over each group. Parameters ---------- values : array_like, [keys, ...] values to compute the median of per group axis : int, optional alternative reduction axis for values average : bool, optional when average is true...
compute the mode within each group. Parameters ---------- values : array_like, [keys, ...] values to compute the mode of per group weights : array_like, [keys], float, optional optional weight associated with each entry in values Returns ------- ...
return the minimum within each group Parameters ---------- values : array_like, [keys, ...] values to take minimum of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...
return the maximum within each group Parameters ---------- values : array_like, [keys, ...] values to take maximum of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...
return values at first occurance of its associated key Parameters ---------- values : array_like, [keys, ...] values to pick the first value of per group axis : int, optional alternative reduction axis for values Returns ------- unique: n...
return values at last occurance of its associated key Parameters ---------- values : array_like, [keys, ...] values to pick the last value of per group axis : int, optional alternative reduction axis for values Returns ------- unique: nda...
compute if any item evaluates to true in each group Parameters ---------- values : array_like, [keys, ...] values to take boolean predicate over per group axis : int, optional alternative reduction axis for values Returns ------- unique: ...
compute if all items evaluates to true in each group Parameters ---------- values : array_like, [keys, ...] values to take boolean predicate over per group axis : int, optional alternative reduction axis for values Returns ------- unique:...
return the index into values corresponding to the minimum value of the group Parameters ---------- values : array_like, [keys] values to pick the argmin of per group Returns ------- unique: ndarray, [groups] unique keys argmin : ndarray, ...
return the index into values corresponding to the maximum value of the group Parameters ---------- values : array_like, [keys] values to pick the argmax of per group Returns ------- unique: ndarray, [groups] unique keys argmax : ndarray, ...
casting rules for a keys object to an index object the preferred semantics is that keys is a sequence of key objects, except when keys is an instance of tuple, in which case the zipped elements of the tuple are the key objects the axis keyword specifies the axis which enumerates the keys if axis i...
return index array that maps unique values back to original space. unique[inverse]==keys def inverse(self): """return index array that maps unique values back to original space. unique[inverse]==keys""" inv = np.empty(self.size, np.int) inv[self.sorter] = self.sorted_group_rank_per_key ...
how high in sorted list each key is. inverse permutation of sorter, such that sorted[rank]==keys def rank(self): """how high in sorted list each key is. inverse permutation of sorter, such that sorted[rank]==keys""" r = np.empty(self.size, np.int) r[self.sorter] = np.arange(self.size) r...
returns a tuple of unique key columns def unique(self): """returns a tuple of unique key columns""" return tuple( (array_as_typed(s, k.dtype, k.shape) if k.ndim>1 else s)[self.start] for s, k in zip(self.sorted, self._keys))
pack a sequence of columns into a recarray Parameters ---------- columns : sequence of key objects Returns ------- data : recarray recarray containing the input columns as struct fields def as_struct_array(*columns): """pack a sequence of columns into a recarray Parameters ...
cast the given axis of an array to a void object if the axis to be cast is contiguous, a view is returned, otherwise a copy is made this is useful for efficiently sorting by the content of an axis, for instance Parameters ---------- arr : ndarray array to view as void object type axis :...
cast an array of void objects to a typed axis Parameters ---------- arr : ndarray, [ndim], void array of type np.void dtype : numpy dtype object the output dtype to cast the input array to axis : int position to insert the newly formed axis into Returns ------- ...
count the number of times each key occurs in the input set Arguments --------- keys : indexable object Returns ------- unique : ndarray, [groups, ...] unique keys count : ndarray, [groups], int the number of times each key occurs in the input set Notes ----- Ca...
count the number of times each key occurs in the input set Arguments --------- keys : tuple of indexable objects, each having the same number of items Returns ------- unique : tuple of ndarray, [groups, ...] unique keys for each input item they form the axes labels of the table...
Perform binning over the given axes of the keys Parameters ---------- keys : indexable or tuple of indexable Examples -------- binning(np.random.rand(100), 0, 1, 10) def binning(keys, start, end, count, axes=None): """Perform binning over the given axes of the keys Parameters ---...
return the multiplicity of each key, or how often it occurs in the set Parameters ---------- keys : indexable object Returns ------- ndarray, [keys.size], int the number of times each input item occurs in the set def multiplicity(keys, axis=semantics.axis_default): """return the m...
where each item is in the pecking order. Parameters ---------- keys : indexable object Returns ------- ndarray, [keys.size], int unique integers, ranking the sorting order Notes ----- we should have that index.sorted[index.rank] == keys def rank(keys, axis=semantics.axis_...
compute the mode, or most frequent occuring key in a set Parameters ---------- keys : ndarray, [n_keys, ...] input array. elements of 'keys' can have arbitrary shape or dtype weights : ndarray, [n_keys], optional if given, the contribution of each key to the mode is weighted by the give...
given an Nxm matrix containing boundary info between simplices, compute indidence info matrix not very reusable; should probably not be in this lib def incidence(boundary): """ given an Nxm matrix containing boundary info between simplices, compute indidence info matrix not very reusable; shoul...
Returns true if all keys are unique def all_unique(keys, axis=semantics.axis_default): """Returns true if all keys are unique""" index = as_index(keys, axis) return index.groups == index.size
returns true if any of the keys is unique def any_unique(keys, axis=semantics.axis_default): """returns true if any of the keys is unique""" index = as_index(keys, axis) return np.any(index.count == 1)
returns true of all keys are equal def all_equal(keys, axis=semantics.axis_default): """returns true of all keys are equal""" index = as_index(keys, axis) return index.groups == 1
returns true if all keys have equal multiplicity def is_uniform(keys, axis=semantics.axis_default): """returns true if all keys have equal multiplicity""" index = as_index(keys, axis) return index.uniform
Returns ------- Tuple of inverse indices def get_inverses(self, keys): """ Returns ------- Tuple of inverse indices """ return tuple([as_index(k, axis=0).inverse for k in keys])
Place each entry in a table, while asserting that each entry occurs once def unique(self, values): """Place each entry in a table, while asserting that each entry occurs once""" _, count = self.count() if not np.array_equiv(count, 1): raise ValueError("Not every entry in the table i...
compute the set of unique keys Parameters ---------- keys : indexable key object keys object to find unique keys within axis : int if keys is a multi-dimensional array, the axis to regard as the sequence of key objects return_index : bool if True, return indexes such that ke...
Returns bool for each element of `that`, indicating if it is contained in `this` Parameters ---------- this : indexable key sequence sequence of items to test against that : indexable key sequence sequence of items to test for Returns ------- ndarray, [that.size], bool ...
Returns bool for each element of `this`, indicating if it is present in `that` Parameters ---------- this : indexable key sequence sequence of items to test for that : indexable key sequence sequence of items to test against Returns ------- ndarray, [that.size], bool ...
Find indices such that this[indices] == that If multiple indices satisfy this condition, the first index found is returned Parameters ---------- this : indexable object items to search in that : indexable object items to search for axis : int, optional axis to operate on...
Given an input array, remap its entries corresponding to 'keys' to 'values' equivalent of output = [map.get(i, default=i) for i in input], if map were a dictionary of corresponding keys and values Parameters ---------- input : ndarray, [...] values to perform replacements in keys : ndar...
upcasts a sequence of indexable objects to Index objets according to the given kwargs Parameters ---------- sets : iterable of indexable objects axis : int, optional axis to view as item sequence assume_unique : bool, optional if we should assume the items sequence does not contain ...
concatenate indexable objects. Parameters ---------- sets : iterable of indexable objects Returns ------- indexable object handles both arrays and tuples of arrays def _set_concatenate(sets): """concatenate indexable objects. Parameters ---------- sets : iterable of inde...
return the elements which occur n times over the sequence of sets Parameters ---------- sets : iterable of indexable objects n : int number of sets the element should occur in Returns ------- indexable indexable with all elements that occured in n of the sets Notes ...
all unique items which occur in any one of the sets Parameters ---------- sets : tuple of indexable objects Returns ------- union of all items in all sets def union(sets, *kwargs): """all unique items which occur in any one of the sets Parameters ---------- sets : tuple of ...
subtracts all tail sets from the head set Parameters ---------- sets : tuple of indexable objects first set is the head, from which we subtract other items form the tail, which are subtracted from head Returns ------- items which are in the head but not in any of the tail sets ...
Generate a random id for div chart. def _generate_div_id_chart(prefix="chart_id", digits=8): """Generate a random id for div chart. """ choices = (random.randrange(0, 52) for _ in range(digits)) return prefix + "".join((string.ascii_letters[x] for x in choices))
Display you DataFrame with Highcharts. df: DataFrame chart_type: str 'default' or 'stock' render_to: str div id for plotting your data def display_charts(df, chart_type="default", render_to=None, **kwargs): """Display you DataFrame with Highcharts. df: DataFrame chart_type: st...
Replace each 'data' key in the list stored under 'series' by "[...]". Use to not store and display the series data when you just want display and modify the Highcharts parameters. data: dict Serialized DataFrame in a dict for Highcharts Returns: a dict with filtered values See also `core...
Pretty print your Highcharts params (into a JSON). data: dict Serialized DataFrame in a dict for Highcharts def pretty_params(data, indent=2): """Pretty print your Highcharts params (into a JSON). data: dict Serialized DataFrame in a dict for Highcharts """ data_to_print = _series...
Filter to get the additional params needed for polling def get_additional_params(self, **params): """ Filter to get the additional params needed for polling """ # TODO: Move these params to their own vertical if needed. polling_params = [ 'locationschema', ...
Get all results, no filtering, etc. by creating and polling the session. def get_result(self, errors=GRACEFUL, params): """ Get all results, no filtering, etc. by creating and polling the session. """ additional_params = self.get_additional_params(params) ret...
Reusable method for performing requests. :param service_url - URL to request :param method - request method, default is 'get' :param headers - request headers :param data - post data :param callback - callback to be applied to response, default callback...
Get the list of markets http://business.skyscanner.net/portal/en-GB/Documentation/Markets def get_markets(self, market): """ Get the list of markets http://business.skyscanner.net/portal/en-GB/Documentation/Markets """ url = "{url}/{market}".format(url=self.MARKET_SERVIC...
Location Autosuggest Services Doc URLs: http://business.skyscanner.net/portal/en-GB/ Documentation/Autosuggest http://business.skyscanner.net/portal/en-GB/ Documentation/CarHireAutoSuggest http://business.skyscanner.net/portal/en-GB/ Doc...
Poll the URL :param poll_url - URL to poll, should be returned by 'create_session' call :param initial_delay - specifies how many seconds to wait before the first poll :param delay - specifies how many seconds to wait between the polls ...
Construct params list in order of given keys. def _construct_params(params, required_keys, opt_keys=None): """ Construct params list in order of given keys. """ try: params_list = [params.pop(key) for key in required_keys] except KeyError as e: raise Miss...
Create the session date format: YYYY-mm-dd location: ISO code def create_session(self, **params): """ Create the session date format: YYYY-mm-dd location: ISO code """ return self.make_request(self.PRICING_SESSION_URL, met...
Request for booking details URL Format: {API_HOST}/apiservices/pricing/v1.0/{session key}/booking ?apiKey={apiKey} def request_booking_details(self, poll_url, **params): """ Request for booking details URL Format: {API_HOST}/apiservices/pricing/v1.0/{...
{API_HOST}/apiservices/browsedates/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_price_by_date(self, **params): """ {API_HOST}/apiservices/browsedates/v1.0/{market}/{currency}/{lo...
{API_HOST}/apiservices/browseroutes/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_price_by_route(self, **params): """ {API_HOST}/apiservices/browseroutes/v1.0/{market}/{currency}/...
{API_HOST}/apiservices/browsequotes/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_quotes(self, **params): """ {API_HOST}/apiservices/browsequotes/v1.0/{market}/{currency}/{locale}...
{API_HOST}/apiservices/browsegrid/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_grid_prices_by_date(self, **params): """ {API_HOST}/apiservices/browsegrid/v1.0/{market}/{currency}/{locale}...
Create the session date format: YYYY-MM-DDThh:mm location: ISO code def create_session(self, **params): """ Create the session date format: YYYY-MM-DDThh:mm location: ISO code """ required_keys = ('market', 'currency', 'locale', 'pickupplace', ...
Format keyboard /command field. def keyboard_field(value, args=None): """ Format keyboard /command field. """ qs = QueryDict(args) per_line = qs.get('per_line', 1) field = qs.get("field", "slug") command = qs.get("command") convert = lambda element: "/" + command + " " + str(getattr(el...
Return the `QuerySet` that will be used to look up the object. Note that this method is called by the default implementation of `get_object` and may not be called if `get_object` is overridden. def get_queryset(self): """ Return the `QuerySet` that will be used to look up the object. ...
Decorator for command views that checks that the chat is authenticated, sends message with link for authenticated if necessary. def login_required(view_func): """ Decorator for command views that checks that the chat is authenticated, sends message with link for authenticated if necessary. """ ...
Decorator that handles X objects and partial application for pipe-utils. def pipe_util(func): """ Decorator that handles X objects and partial application for pipe-utils. """ @wraps(func) def pipe_util_wrapper(function, args, *kwargs): if isinstance(function, XObject): functio...
Decorator that handles automatic string formatting. By converting a string argument to a function that does formatting on said string. def auto_string_formatter(func): """ Decorator that handles automatic string formatting. By converting a string argument to a function that does formatting on sai...
Decorator to handle automatic data structure creation for pipe-utils. def data_structure_builder(func): """ Decorator to handle automatic data structure creation for pipe-utils. """ @wraps(func) def ds_builder_wrapper(function, args, *kwargs): try: function = DSBuilder(functio...
If a condition is given as string instead of a function, it is turned into a regex-matching function. def regex_condition(func): """ If a condition is given as string instead of a function, it is turned into a regex-matching function. """ @wraps(func) def regex_condition_wrapper(condition, ...
Sorts an incoming sequence by using the given `function` as key. >>> range(10) > sort_by(-X) [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] Supports automatic data-structure creation:: users > sort_by([X.last_name, X.first_name]) There is also a shortcut for ``sort_by(X)`` called ``sort``: >>> [4, 5, 8...
Assumes an iterable on the input, returns an iterable with first `count` items from the input (or possibly less, if there isn't that many). >>> range(9000) > where(X % 100 == 0) \| take_first(5) \| tuple (0, 100, 200, 300, 400) def take_first(count): """ Assumes an iterable on the input, returns an ...
Assumes an iterable on the input, returns an iterable with identical items except for the first `count`. >>> range(10) > drop_first(5) \| tuple (5, 6, 7, 8, 9) def drop_first(count): """ Assumes an iterable on the input, returns an iterable with identical items except for the first `count`. ...
When `exception_class_or_tuple` occurs while executing `func`, it will be caught and ``None`` will be returned. >>> f = where(X > 10) \| list \| unless(IndexError, X[0]) >>> f([5, 8, 12, 4]) 12 >>> f([1, 2, 3]) None def unless(exception_class_or_tuple, func, args, *kwargs): """ When `e...
Groups input sequence by `function`. Returns an iterator over a sequence of tuples where the first item is a result of `function` and the second one a list of items matching this result. Ordering of the resulting iterator is undefined, but ordering of the items in the groups is preserved. >>>...

Calculates the expected lifecycle position the subscription in subscription_ids, and creates a BehindSubscription entry for them. Args: subscription_id (str): ID of subscription to calculate lifecycle for def calculate_subscription_lifecycle(subscription_id): """ Calculates the expected lifecy...

Finds any subscriptions that are behind according to where they should be, and creates a BehindSubscription entry for them. def find_behind_subscriptions(): """ Finds any subscriptions that are behind according to where they should be, and creates a BehindSubscription entry for them. """ subscr...

Sends all the subscriptions for the specified schedule def send(self, request, pk=None): """ Sends all the subscriptions for the specified schedule """ schedule = self.get_object() queue_subscription_send.delay(str(schedule.id)) return Response({}, status=status.HTTP_20...

Return the configured value for the given key name, or `default` if no value is available or key is invalid. def get(self, key: Any, default: Any=None) -> Any: '''Return the configured value for the given key name, or `default` if no value is available or key is invalid.''' return self...

Return the task-specific configuration. def task_config(self, task: Task) -> Any: '''Return the task-specific configuration.''' return self.get(task.__class__.__name__)

Load configuration in JSON format from either a file or a raw data string. async def init(self) -> None: '''Load configuration in JSON format from either a file or a raw data string.''' if self.data: return if self.json_data: try: self.d...

Execute the task inside the asyncio event loop after `DELAY` seconds. Track the time it takes to run, and log when it starts/stops. If/when `reset()` is called, reset the wait time to `DELAY` seconds. async def run_task(self) -> None: '''Execute the task inside the asyncio event loop after `DE...

Reset task execution to `DELAY` seconds from now. def reset(self) -> None: '''Reset task execution to `DELAY` seconds from now.''' Log.debug('resetting timer task %s') self.target = self.time() + self.DELAY

A view decorator which blocks access for requests coming through the load balancer. def internal_only(view_func): """ A view decorator which blocks access for requests coming through the load balancer. """ @functools.wraps(view_func) def wrapper(request, *args, **kwargs): forwards = reques...

Validates subscription data before creating Outbound message def post(self, request, *args, **kwargs): """ Validates subscription data before creating Outbound message """ schedule_disable.delay(kwargs["subscription_id"]) return Response({"accepted": True}, status=201)

Validates subscription data before creating Outbound message def post(self, request, *args, **kwargs): """ Validates subscription data before creating Outbound message """ # Look up subscriber subscription_id = kwargs["subscription_id"] if Subscription.objects.filter(id=subscrip...

Validates subscription data before creating Subscription message def post(self, request, *args, **kwargs): """ Validates subscription data before creating Subscription message """ # Ensure that we check for the 'data' key in the request object before # attempting to reference it ...

Starts a celery task that looks through active subscriptions to find and subscriptions that are behind where they should be, and adds a BehindSubscription for them. def find_behind_subscriptions(self, request): """ Starts a celery task that looks through active subscriptions to find ...

Read-Eval-Print-Loop for reading the query, printing it and its parse tree. Exit the loop either with an interrupt or "quit". def repl(): """Read-Eval-Print-Loop for reading the query, printing it and its parse tree. Exit the loop either with an interrupt or "quit". """ while True: try: ...

Initialize the queue and spawn extra worker tasks if this if the first task. Then wait for work items to enter the task queue, and execute the `run()` method with the current work item. async def run_task(self) -> None: '''Initialize the queue and spawn extra worker tasks if this if the ...

Fires off the celery task to ensure that this schedule is in the scheduler Arguments: sender {class} -- The model class, always Schedule instance {Schedule} -- The instance of the Schedule that we want to sync def schedule_saved(sender, instance, **kwargs): """ Fires off the ce...

Fires off the celery task to ensure that this schedule is deactivated Arguments: sender {class} -- The model class, always Schedule instance {Schedule} -- The instance of the schedule that we want to deactivate def schedule_deleted(sender, instance, **kwargs): """ Fires off the...

Execute the task inside the asyncio event loop. Track the time it takes to run, and log when it starts/stops. After `INTERVAL` seconds, if/once the task has finished running, run it again until `stop()` is called. async def run_task(self) -> None: '''Execute the task inside the asynci...

construct a grouping object on the given keys, optionally performing the given reduction on the given values Parameters ---------- keys : indexable object keys to group by values : array_like, optional sequence of values, of the same length as keys if a reduction function is pro...

Group iterable into iterables, in the order of the keys Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ iterable of items in values Notes ----- Memory consumption depends...

Group iterable into iterables, without regard for the ordering of self.index.unique key-group tuples are yielded as soon as they are complete Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ ...

Group sequence into iterables Parameters ---------- values : iterable of length equal to keys iterable of values to be grouped Yields ------ iterable of items in values Notes ----- This is the preferred method if values has random ac...

Group ndarray into ndarray by means of reshaping Parameters ---------- values : ndarray_like, [index.size, ...] Returns ------- ndarray, [groups, group_size, ...] values grouped by key Raises ------ AssertionError This op...

Group values as a list of arrays, or a jagged-array Parameters ---------- values : ndarray, [keys, ...] Returns ------- list of length self.groups of ndarray, [key_count, ...] def split_array_as_list(self, values): """Group values as a list of arrays, or a jagg...

Reduce the values over identical key groups, using the given ufunc reduction is over the first axis, which should have elements corresponding to the keys all other axes are treated indepenently for the sake of this reduction Parameters ---------- values : ndarray, [keys, ...] ...

compute the sum over each group Parameters ---------- values : array_like, [keys, ...] values to sum per group axis : int, optional alternative reduction axis for values dtype : output dtype Returns ------- unique: ndarray, [group...

compute the product over each group Parameters ---------- values : array_like, [keys, ...] values to multiply per group axis : int, optional alternative reduction axis for values dtype : output dtype Returns ------- unique: ndarra...

compute the mean over each group Parameters ---------- values : array_like, [keys, ...] values to take average of per group axis : int, optional alternative reduction axis for values weights : ndarray, [keys, ...], optional weight to use for e...

compute the variance over each group Parameters ---------- values : array_like, [keys, ...] values to take variance of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...

standard deviation over each group Parameters ---------- values : array_like, [keys, ...] values to take standard deviation of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...

compute the median value over each group. Parameters ---------- values : array_like, [keys, ...] values to compute the median of per group axis : int, optional alternative reduction axis for values average : bool, optional when average is true...

compute the mode within each group. Parameters ---------- values : array_like, [keys, ...] values to compute the mode of per group weights : array_like, [keys], float, optional optional weight associated with each entry in values Returns ------- ...

return the minimum within each group Parameters ---------- values : array_like, [keys, ...] values to take minimum of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...

return the maximum within each group Parameters ---------- values : array_like, [keys, ...] values to take maximum of per group axis : int, optional alternative reduction axis for values Returns ------- unique: ndarray, [groups] ...

return values at first occurance of its associated key Parameters ---------- values : array_like, [keys, ...] values to pick the first value of per group axis : int, optional alternative reduction axis for values Returns ------- unique: n...

return values at last occurance of its associated key Parameters ---------- values : array_like, [keys, ...] values to pick the last value of per group axis : int, optional alternative reduction axis for values Returns ------- unique: nda...

compute if any item evaluates to true in each group Parameters ---------- values : array_like, [keys, ...] values to take boolean predicate over per group axis : int, optional alternative reduction axis for values Returns ------- unique: ...

compute if all items evaluates to true in each group Parameters ---------- values : array_like, [keys, ...] values to take boolean predicate over per group axis : int, optional alternative reduction axis for values Returns ------- unique:...

return the index into values corresponding to the minimum value of the group Parameters ---------- values : array_like, [keys] values to pick the argmin of per group Returns ------- unique: ndarray, [groups] unique keys argmin : ndarray, ...

return the index into values corresponding to the maximum value of the group Parameters ---------- values : array_like, [keys] values to pick the argmax of per group Returns ------- unique: ndarray, [groups] unique keys argmax : ndarray, ...

casting rules for a keys object to an index object the preferred semantics is that keys is a sequence of key objects, except when keys is an instance of tuple, in which case the zipped elements of the tuple are the key objects the axis keyword specifies the axis which enumerates the keys if axis i...

return index array that maps unique values back to original space. unique[inverse]==keys def inverse(self): """return index array that maps unique values back to original space. unique[inverse]==keys""" inv = np.empty(self.size, np.int) inv[self.sorter] = self.sorted_group_rank_per_key ...

how high in sorted list each key is. inverse permutation of sorter, such that sorted[rank]==keys def rank(self): """how high in sorted list each key is. inverse permutation of sorter, such that sorted[rank]==keys""" r = np.empty(self.size, np.int) r[self.sorter] = np.arange(self.size) r...

returns a tuple of unique key columns def unique(self): """returns a tuple of unique key columns""" return tuple( (array_as_typed(s, k.dtype, k.shape) if k.ndim>1 else s)[self.start] for s, k in zip(self.sorted, self._keys))

pack a sequence of columns into a recarray Parameters ---------- columns : sequence of key objects Returns ------- data : recarray recarray containing the input columns as struct fields def as_struct_array(*columns): """pack a sequence of columns into a recarray Parameters ...

cast the given axis of an array to a void object if the axis to be cast is contiguous, a view is returned, otherwise a copy is made this is useful for efficiently sorting by the content of an axis, for instance Parameters ---------- arr : ndarray array to view as void object type axis :...

cast an array of void objects to a typed axis Parameters ---------- arr : ndarray, [ndim], void array of type np.void dtype : numpy dtype object the output dtype to cast the input array to axis : int position to insert the newly formed axis into Returns ------- ...

count the number of times each key occurs in the input set Arguments --------- keys : indexable object Returns ------- unique : ndarray, [groups, ...] unique keys count : ndarray, [groups], int the number of times each key occurs in the input set Notes ----- Ca...

count the number of times each key occurs in the input set Arguments --------- keys : tuple of indexable objects, each having the same number of items Returns ------- unique : tuple of ndarray, [groups, ...] unique keys for each input item they form the axes labels of the table...

Perform binning over the given axes of the keys Parameters ---------- keys : indexable or tuple of indexable Examples -------- binning(np.random.rand(100), 0, 1, 10) def binning(keys, start, end, count, axes=None): """Perform binning over the given axes of the keys Parameters ---...

return the multiplicity of each key, or how often it occurs in the set Parameters ---------- keys : indexable object Returns ------- ndarray, [keys.size], int the number of times each input item occurs in the set def multiplicity(keys, axis=semantics.axis_default): """return the m...

where each item is in the pecking order. Parameters ---------- keys : indexable object Returns ------- ndarray, [keys.size], int unique integers, ranking the sorting order Notes ----- we should have that index.sorted[index.rank] == keys def rank(keys, axis=semantics.axis_...

compute the mode, or most frequent occuring key in a set Parameters ---------- keys : ndarray, [n_keys, ...] input array. elements of 'keys' can have arbitrary shape or dtype weights : ndarray, [n_keys], optional if given, the contribution of each key to the mode is weighted by the give...

given an Nxm matrix containing boundary info between simplices, compute indidence info matrix not very reusable; should probably not be in this lib def incidence(boundary): """ given an Nxm matrix containing boundary info between simplices, compute indidence info matrix not very reusable; shoul...

Returns true if all keys are unique def all_unique(keys, axis=semantics.axis_default): """Returns true if all keys are unique""" index = as_index(keys, axis) return index.groups == index.size

returns true if any of the keys is unique def any_unique(keys, axis=semantics.axis_default): """returns true if any of the keys is unique""" index = as_index(keys, axis) return np.any(index.count == 1)

returns true of all keys are equal def all_equal(keys, axis=semantics.axis_default): """returns true of all keys are equal""" index = as_index(keys, axis) return index.groups == 1

returns true if all keys have equal multiplicity def is_uniform(keys, axis=semantics.axis_default): """returns true if all keys have equal multiplicity""" index = as_index(keys, axis) return index.uniform

Returns ------- Tuple of inverse indices def get_inverses(self, keys): """ Returns ------- Tuple of inverse indices """ return tuple([as_index(k, axis=0).inverse for k in keys])

Place each entry in a table, while asserting that each entry occurs once def unique(self, values): """Place each entry in a table, while asserting that each entry occurs once""" _, count = self.count() if not np.array_equiv(count, 1): raise ValueError("Not every entry in the table i...

compute the set of unique keys Parameters ---------- keys : indexable key object keys object to find unique keys within axis : int if keys is a multi-dimensional array, the axis to regard as the sequence of key objects return_index : bool if True, return indexes such that ke...

Returns bool for each element of `that`, indicating if it is contained in `this` Parameters ---------- this : indexable key sequence sequence of items to test against that : indexable key sequence sequence of items to test for Returns ------- ndarray, [that.size], bool ...

Returns bool for each element of `this`, indicating if it is present in `that` Parameters ---------- this : indexable key sequence sequence of items to test for that : indexable key sequence sequence of items to test against Returns ------- ndarray, [that.size], bool ...

Find indices such that this[indices] == that If multiple indices satisfy this condition, the first index found is returned Parameters ---------- this : indexable object items to search in that : indexable object items to search for axis : int, optional axis to operate on...

Given an input array, remap its entries corresponding to 'keys' to 'values' equivalent of output = [map.get(i, default=i) for i in input], if map were a dictionary of corresponding keys and values Parameters ---------- input : ndarray, [...] values to perform replacements in keys : ndar...

upcasts a sequence of indexable objects to Index objets according to the given kwargs Parameters ---------- sets : iterable of indexable objects axis : int, optional axis to view as item sequence assume_unique : bool, optional if we should assume the items sequence does not contain ...

concatenate indexable objects. Parameters ---------- sets : iterable of indexable objects Returns ------- indexable object handles both arrays and tuples of arrays def _set_concatenate(sets): """concatenate indexable objects. Parameters ---------- sets : iterable of inde...

return the elements which occur n times over the sequence of sets Parameters ---------- sets : iterable of indexable objects n : int number of sets the element should occur in Returns ------- indexable indexable with all elements that occured in n of the sets Notes ...

all unique items which occur in any one of the sets Parameters ---------- sets : tuple of indexable objects Returns ------- union of all items in all sets def union(*sets, **kwargs): """all unique items which occur in any one of the sets Parameters ---------- sets : tuple of ...

subtracts all tail sets from the head set Parameters ---------- sets : tuple of indexable objects first set is the head, from which we subtract other items form the tail, which are subtracted from head Returns ------- items which are in the head but not in any of the tail sets ...

Generate a random id for div chart. def _generate_div_id_chart(prefix="chart_id", digits=8): """Generate a random id for div chart. """ choices = (random.randrange(0, 52) for _ in range(digits)) return prefix + "".join((string.ascii_letters[x] for x in choices))

Display you DataFrame with Highcharts. df: DataFrame chart_type: str 'default' or 'stock' render_to: str div id for plotting your data def display_charts(df, chart_type="default", render_to=None, **kwargs): """Display you DataFrame with Highcharts. df: DataFrame chart_type: st...

Replace each 'data' key in the list stored under 'series' by "[...]". Use to not store and display the series data when you just want display and modify the Highcharts parameters. data: dict Serialized DataFrame in a dict for Highcharts Returns: a dict with filtered values See also `core...

Pretty print your Highcharts params (into a JSON). data: dict Serialized DataFrame in a dict for Highcharts def pretty_params(data, indent=2): """Pretty print your Highcharts params (into a JSON). data: dict Serialized DataFrame in a dict for Highcharts """ data_to_print = _series...

Filter to get the additional params needed for polling def get_additional_params(self, **params): """ Filter to get the additional params needed for polling """ # TODO: Move these params to their own vertical if needed. polling_params = [ 'locationschema', ...

Get all results, no filtering, etc. by creating and polling the session. def get_result(self, errors=GRACEFUL, **params): """ Get all results, no filtering, etc. by creating and polling the session. """ additional_params = self.get_additional_params(**params) ret...

Reusable method for performing requests. :param service_url - URL to request :param method - request method, default is 'get' :param headers - request headers :param data - post data :param callback - callback to be applied to response, default callback...

Get the list of markets http://business.skyscanner.net/portal/en-GB/Documentation/Markets def get_markets(self, market): """ Get the list of markets http://business.skyscanner.net/portal/en-GB/Documentation/Markets """ url = "{url}/{market}".format(url=self.MARKET_SERVIC...

Location Autosuggest Services Doc URLs: http://business.skyscanner.net/portal/en-GB/ Documentation/Autosuggest http://business.skyscanner.net/portal/en-GB/ Documentation/CarHireAutoSuggest http://business.skyscanner.net/portal/en-GB/ Doc...

Poll the URL :param poll_url - URL to poll, should be returned by 'create_session' call :param initial_delay - specifies how many seconds to wait before the first poll :param delay - specifies how many seconds to wait between the polls ...

Construct params list in order of given keys. def _construct_params(params, required_keys, opt_keys=None): """ Construct params list in order of given keys. """ try: params_list = [params.pop(key) for key in required_keys] except KeyError as e: raise Miss...

Create the session date format: YYYY-mm-dd location: ISO code def create_session(self, **params): """ Create the session date format: YYYY-mm-dd location: ISO code """ return self.make_request(self.PRICING_SESSION_URL, met...

Request for booking details URL Format: {API_HOST}/apiservices/pricing/v1.0/{session key}/booking ?apiKey={apiKey} def request_booking_details(self, poll_url, **params): """ Request for booking details URL Format: {API_HOST}/apiservices/pricing/v1.0/{...

{API_HOST}/apiservices/browsedates/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_price_by_date(self, **params): """ {API_HOST}/apiservices/browsedates/v1.0/{market}/{currency}/{lo...

{API_HOST}/apiservices/browseroutes/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_price_by_route(self, **params): """ {API_HOST}/apiservices/browseroutes/v1.0/{market}/{currency}/...

{API_HOST}/apiservices/browsequotes/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_cheapest_quotes(self, **params): """ {API_HOST}/apiservices/browsequotes/v1.0/{market}/{currency}/{locale}...

{API_HOST}/apiservices/browsegrid/v1.0/{market}/{currency}/{locale}/ {originPlace}/{destinationPlace}/ {outboundPartialDate}/{inboundPartialDate} ?apiKey={apiKey} def get_grid_prices_by_date(self, **params): """ {API_HOST}/apiservices/browsegrid/v1.0/{market}/{currency}/{locale}...

Create the session date format: YYYY-MM-DDThh:mm location: ISO code def create_session(self, **params): """ Create the session date format: YYYY-MM-DDThh:mm location: ISO code """ required_keys = ('market', 'currency', 'locale', 'pickupplace', ...

Format keyboard /command field. def keyboard_field(value, args=None): """ Format keyboard /command field. """ qs = QueryDict(args) per_line = qs.get('per_line', 1) field = qs.get("field", "slug") command = qs.get("command") convert = lambda element: "/" + command + " " + str(getattr(el...

Return the `QuerySet` that will be used to look up the object. Note that this method is called by the default implementation of `get_object` and may not be called if `get_object` is overridden. def get_queryset(self): """ Return the `QuerySet` that will be used to look up the object. ...

Decorator for command views that checks that the chat is authenticated, sends message with link for authenticated if necessary. def login_required(view_func): """ Decorator for command views that checks that the chat is authenticated, sends message with link for authenticated if necessary. """ ...

Decorator that handles X objects and partial application for pipe-utils. def pipe_util(func): """ Decorator that handles X objects and partial application for pipe-utils. """ @wraps(func) def pipe_util_wrapper(function, *args, **kwargs): if isinstance(function, XObject): functio...

Decorator that handles automatic string formatting. By converting a string argument to a function that does formatting on said string. def auto_string_formatter(func): """ Decorator that handles automatic string formatting. By converting a string argument to a function that does formatting on sai...

Decorator to handle automatic data structure creation for pipe-utils. def data_structure_builder(func): """ Decorator to handle automatic data structure creation for pipe-utils. """ @wraps(func) def ds_builder_wrapper(function, *args, **kwargs): try: function = DSBuilder(functio...

If a condition is given as string instead of a function, it is turned into a regex-matching function. def regex_condition(func): """ If a condition is given as string instead of a function, it is turned into a regex-matching function. """ @wraps(func) def regex_condition_wrapper(condition, ...

Sorts an incoming sequence by using the given `function` as key. >>> range(10) > sort_by(-X) [9, 8, 7, 6, 5, 4, 3, 2, 1, 0] Supports automatic data-structure creation:: users > sort_by([X.last_name, X.first_name]) There is also a shortcut for ``sort_by(X)`` called ``sort``: >>> [4, 5, 8...

Assumes an iterable on the input, returns an iterable with first `count` items from the input (or possibly less, if there isn't that many). >>> range(9000) > where(X % 100 == 0) | take_first(5) | tuple (0, 100, 200, 300, 400) def take_first(count): """ Assumes an iterable on the input, returns an ...

Assumes an iterable on the input, returns an iterable with identical items except for the first `count`. >>> range(10) > drop_first(5) | tuple (5, 6, 7, 8, 9) def drop_first(count): """ Assumes an iterable on the input, returns an iterable with identical items except for the first `count`. ...

When `exception_class_or_tuple` occurs while executing `func`, it will be caught and ``None`` will be returned. >>> f = where(X > 10) | list | unless(IndexError, X[0]) >>> f([5, 8, 12, 4]) 12 >>> f([1, 2, 3]) None def unless(exception_class_or_tuple, func, *args, **kwargs): """ When `e...

Groups input sequence by `function`. Returns an iterator over a sequence of tuples where the first item is a result of `function` and the second one a list of items matching this result. Ordering of the resulting iterator is undefined, but ordering of the items in the groups is preserved. >>>...