one.util

Decorators and small standalone functions for api module

Functions

Listable
autocomplete	Validate search term and return complete name, e.g.
datasets2records	Extract datasets DataFrame from one or more Alyx dataset records
ensure_list	Ensure input is a list
filter_datasets	Filter the datasets cache table by the relative path (dataset name, collection and revision).
filter_revision_last_before	Filter datasets by revision, returning previous revision in ordered list if revision doesn’t exactly match.
index_last_before	Returns the index of string that occurs directly before the provided revision string when lexicographic sorted.
parse_id	Ensures the input experiment identifier is an experiment UUID string
refresh	Refresh cache depending of query_type kwarg
ses2records	Extract session cache record and datasets cache from a remote session data record TODO Fix for new tables; use to update caches from remote queries
validate_date_range	Validates and arrange date range in a 2 elements list

Classes

LazyId

Using a paginated response object or list of session records, extracts eid string when required

Listable(t)

ses2records(ses: dict) → [<class ‘pandas.core.series.Series’>, <class ‘pandas.core.frame.DataFrame’>]

Extract session cache record and datasets cache from a remote session data record TODO Fix for new tables; use to update caches from remote queries

Parameters

ses – session dictionary from rest endpoint

Returns

session record, datasets frame

datasets2records(datasets) → pandas.core.frame.DataFrame

Extract datasets DataFrame from one or more Alyx dataset records

Parameters

datasets (dict, list) – One or more records from the Alyx ‘datasets’ endpoint

Returns

Return type

Datasets frame

Examples

datasets = one.alyx.rest(‘datasets’, ‘list’, subject=’foobar’) df = datasets2records(datasets)

parse_id(method)

Ensures the input experiment identifier is an experiment UUID string

Parameters

method (function) – An ONE method whose second arg is an experiment ID

Returns

Return type

A wrapper function that parses the ID to the expected string

refresh(method)

Refresh cache depending of query_type kwarg

validate_date_range(date_range)

Validates and arrange date range in a 2 elements list

Examples

_validate_date_range(‘2020-01-01’) # On this day _validate_date_range(datetime.date(2020, 1, 1)) _validate_date_range(np.array([‘2022-01-30’, ‘2022-01-30’], dtype=’datetime64[D]’)) _validate_date_range(pd.Timestamp(2020, 1, 1)) _validate_date_range(np.datetime64(2021, 3, 11)) _validate_date_range([‘2020-01-01’]) # from date _validate_date_range([‘2020-01-01’, None]) # from date _validate_date_range([None, ‘2020-01-01’]) # up to date

filter_datasets(all_datasets, filename=None, collection=None, revision=None, revision_last_before=True, assert_unique=True, wildcards=False)

Filter the datasets cache table by the relative path (dataset name, collection and revision). When None is passed, all values will match. To match on empty parts, use an empty string. When revision_last_before is true, None means return latest revision.

Parameters

• all_datasets (pandas.DataFrame) – A datasets cache table

• filename (str, dict, None) – A filename str or a dict of alf parts. Regular expressions permitted.

• collection (str, None) – A collection string. Regular expressions permitted.

• revision (str, None) – A revision string to match. If revision_last_before is true, regular expressions are not permitted.

• revision_last_before (bool) – When true and no exact match exists, the (lexicographically) previous revision is used instead. When false the revision string is matched like collection and filename, with regular expressions permitted.

• assert_unique (bool) – When true an error is raised if multiple collections or datasets are found

• wildcards (bool) – If true, use unix shell style matching instead of regular expressions

Returns

Return type

A slice of all_datasets that match the filters

Examples

# Filter by dataset name and collection datasets = filter_datasets(all_datasets, ‘.spikes.times.’, ‘alf/probe00’) # Filter datasets not in a collection datasets = filter_datasets(all_datasets, collection=’’) # Filter by matching revision datasets = filter_datasets(all_datasets, ‘spikes.times.npy’,

revision=’2020-01-12’, revision_last_before=False)

# Filter by filename parts datasets = filter_datasets(all_datasets, {object=’spikes’, attribute=’times’})

filter_revision_last_before(datasets, revision=None, assert_unique=True)

Filter datasets by revision, returning previous revision in ordered list if revision doesn’t exactly match.

Parameters

• datasets (pandas.DataFrame) – A datasets cache table

• revision (str) – A revision string to match (regular expressions not permitted)

• assert_unique (bool) – When true an alferr.ALFMultipleRevisionsFound exception is raised when multiple default revisions are found; an alferr.ALFError when no default revision is found

Returns

Return type

A datasets DataFrame with 0 or 1 row per unique dataset

index_last_before(revisions: List[str], revision: Optional[str]) → Optional[int]

Returns the index of string that occurs directly before the provided revision string when lexicographic sorted. If revision is None, the index of the most recent revision is returned.

Parameters

• revisions (list of strings) – A list of revision strings

• revision (None, str) – The revision string to match on

Returns

Return type

Index of revision before matching string in sorted list or None

Examples

idx = _index_last_before([], ‘2020-08-01’)

autocomplete(term, search_terms)

Validate search term and return complete name, e.g. autocomplete(‘subj’) == ‘subject’

ensure_list(value)

Ensure input is a list

class LazyId(pg)

Bases: collections.abc.Mapping

Using a paginated response object or list of session records, extracts eid string when required

static ses2eid(ses)