atoti.query package¶

Submodules¶

atoti.query.auth module¶

atoti.query.auth.Auth¶

Called with the URL of the request and returning the HTTP headers necessary to authenticate it.

alias of Callable[[str], Optional[Mapping[str, str]]]

atoti.query.cube module¶

class atoti.query.cube.QueryCube(name, hierarchies, measures, _session)¶

Bases: object

Query cube.

hierarchies: QueryHierarchies¶: Hierarchies of the cube.

property levels¶

Levels of the cube.

Return type: QueryLevels

measures: QueryMeasures¶: Measures of the cube.

name: str¶: Name of the cube.

query(*measures, levels=None, condition=None, scenario='Base', timeout=30, **kwargs)¶

Query the cube to get the value of some measures.

The value of the measures is given on all the members of the given levels.

Parameters

measures (QueryMeasure) – The measures to query. If None, all the measures are queried.
levels (Union[QueryLevel, Sequence[QueryLevel], None]) – The levels to split on. If None, the value of the measures at the top of the cube is returned.
condition (Union[LevelCondition, MultiCondition, None]) –
The filtering condition. Only conditions on level equality with a string are supported. For instance:
- lvl["Country"] == "France"
- (lvl["Country"] == "USA") & (lvl["Currency"] == "USD")
scenario (str) – The scenario to query.
timeout (int) – The query timeout in seconds.

Return type

QueryResult

Returns

The resulting DataFrame.

atoti.query.cubes module¶

class atoti.query.cubes.QueryCubes(_data)¶

Bases: atoti._mappings.ImmutableMapping

Manage the query cubes.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

values() → an object providing a view on D’s values¶

atoti.query.hierarchies module¶

class atoti.query.hierarchies.QueryHierarchies(_data)¶

Bases: atoti._mappings.ImmutableMapping

Manage the query hierarchies.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

values() → an object providing a view on D’s values¶

atoti.query.hierarchy module¶

class atoti.query.hierarchy.QueryHierarchy(name, dimension, levels, slicing)¶

Bases: object

Hierarchy of a query cube.

dimension: str¶: Dimension of the hierarchy.

isin(*member_paths)¶

Return a condition to check that the hierarchy is on one of the given members.

Considering hierarchy_1 containing level_1 and level_2, hierarchy_1.isin((a, x), (b,)) is equivalent to ((level_1 == a) & (level_2 == x)) | (level_1 == b).

Example

Considering a “Geography” hierarchy containing two levels “Country” and “City”, and this measure:

measures["Price in USA/Paris and Germany"] = atoti.filter(
    measures["Price"],
    hierarchies["Geography"].isin(("USA", "Paris"), ("Germany", ))
)

The behavior is the following one:

Country	City	Price	measures[“Price in USA/Paris and Germany”]
France	Paris	200.0
Germany	Berlin	150.0	150.0
UK	London	240.0
USA	New York	270.0
USA	Paris	500.0	500.0

Parameters: members – One or more members expressed as tuples on which the hierarchy should be. Each element in a tuple corresponds to a level of the hierarchy, from the shallowest to the deepest.
Return type: HierarchyIsInCondition

levels: atoti._mappings.ImmutableMapping[str, atoti.query.level.QueryLevel]¶: Levels of the hierarchy.

name: str¶: Name of the hierarchy.

slicing: bool¶: Whether the hierarchy is slicing or not.

atoti.query.level module¶

class atoti.query.level.QueryLevel(name, dimension, hierarchy)¶

Bases: object

Level of a query cube.

dimension: str¶: Dimension of the level.

hierarchy: str¶: Hierarchy of the level.

isin(*members)¶

Return a condition to check that the level is on one of the given members.

levels["x"].isin("a", "b") is equivalent to levels["x"] == "a" OR levels["x"] == "b".

Example

Considering this measure:

measures["Price in Paris and London"] = atoti.filter(
    measures["Price"],
    levels["City"].isin("Paris", "London")
)

The behavior is the following one:

City	Price	measures[“Price in Paris and London”]
Paris	200.0	200.0
Berlin	150.0
London	240.0	240.0
New York	270.0

Parameters: members (Any) – One or more members on which the level should be.
Return type: LevelIsInCondition

name: str¶: Name of the level.

atoti.query.levels module¶

class atoti.query.levels.QueryLevels(_hierarchies)¶

Bases: atoti._base_levels.BaseLevels

Flat representation of all the levels in the cube.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

values() → an object providing a view on D’s values¶

atoti.query.measure module¶

class atoti.query.measure.QueryMeasure(name, visible, folder, formatter, description)¶

Bases: object

Measure of a query cube.

description: Optional[str]¶: Description of the measure.

folder: Optional[str]¶: Folder in which the measure is.

formatter: Optional[str]¶: Formatter of the measure.

name: str¶: Name of the measure.

visible: bool¶: Whether the measure is visible or not.

atoti.query.measures module¶

class atoti.query.measures.QueryMeasures(_data)¶

Bases: atoti._mappings.ImmutableMapping

Manage the query measures.

get(k[, d]) → D[k] if k in D, else d. d defaults to None.¶

items() → a set-like object providing a view on D’s items¶

keys() → a set-like object providing a view on D’s keys¶

values() → an object providing a view on D’s values¶

atoti.query.query_result module¶

class atoti.query.query_result.QueryResult(data=None, index=None, *, context=None, formatted_values, get_styler, mdx=None)¶

Bases: pandas.core.frame.DataFrame

Custom pandas DataFrame that can be converted to a widget by our JupyterLab extension.

property style¶

Return a Styler object.

If the DataFrame has not been changed in place since its creation, the returned object will follow the styling included in the cellset from which the DataFrame was converted.

Return type: Styler

atoti.query.session module¶

class atoti.query.session.QuerySession(url, *, auth=None, name=None)¶

Bases: object

Used to query an existing session.

Query sessions are considered immutable: the structure of their cubes is not expected to change.

property cubes¶

Cubes of the session.

Return type: QueryCubes

property name¶

Name of the session.

Return type: str

property port¶

Port of the session.

Return type: Optional[int]

query_mdx(mdx, *, timeout=30, **kwargs)¶

Execute an MDX query and return its result as a pandas DataFrame.

Resulting cells representing totals are ignored, they will not be part of the returned DataFrame. Members for which all the measures are None are ignored too.

Example

An MDX query that would be displayed as this pivot table:

Country	Total Price.SUM	2018-01-01	2019-01-01	2019-01-02	2019-01-05
Country	Total Price.SUM	Price.SUM	Price.SUM	Price.SUM	Price.SUM
Total Country	2,280.00	840.00	1,860.00	810.00	770.00
China	760.00			410.00	350.00
France	1,800.00	480.00	500.00	400.00	420.00
India	760.00	360.00	400.00
UK	960.00		960.00

will return this DataFrame:

Date	Country	Price.SUM
2019-01-02	China	410.0
2019-01-05	China	350.0
2018-01-01	France	480.0
2019-01-01	France	500.0
2019-01-02	France	400.0
2019-01-05	France	420.0
2018-01-01	India	360.0
2019-01-01	India	400.0
2019-01-01	UK	960.0

Parameters

mdx (str) – The MDX SELECT query to execute.
timeout (int) – The query timeout in seconds.

Return type

QueryResult

property url¶

URL of the session.

Return type: str

visualize(name=None)¶

Display an atoti widget to explore the session interactively.

Attention

This method requires the atoti-jupyterlab plugin.

The widget state will be stored in the cell metadata. This state should not have to be edited but, if desired, it can be found in JupyterLab by opening the “Notebook tools” sidebar and expanding the the “Advanced Tools” section.

Parameters: name (Optional[str]) – The name to give to the widget.

Module contents¶

atoti.query.create_basic_authentication(username, password)¶

Create a basic authentication.

Return type: Callable[[str], Optional[Mapping[str, str]]]

atoti.query.create_token_authentication(token)¶

Create an authentication based on a Bearer token.

Parameters: token (str) – The token to use to authenticate, such as a JWT.
Return type: Callable[[str], Optional[Mapping[str, str]]]