atoti.query package¶

Submodules¶

atoti.query.auth module¶

atoti.query.auth.Auth = typing.Callable[[str], typing.Union[typing.Mapping[str, str], NoneType]]¶: Called with the URL of the request and return the HTTP headers necessary to authenticate it.

atoti.query.basic_auth module¶

class atoti.query.basic_auth.BasicAuthentication(username, password)¶

Bases: object

Basic Authentication.

password: str = None¶

username: str = None¶

atoti.query.basic_auth.create_basic_authentication(username, password)¶

Create a basic authentication.

It can be used on ActivePivots’s sandbox for instance.

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

atoti.query.cube module¶

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

Bases: object

Query cube.

name¶: Cube name.

hierarchies¶: Cube hierarchies.

measures¶: Cube measures.

hierarchies: QueryHierarchies = None

property levels¶

Levels of the cube.

Return type: QueryLevels

measures: QueryMeasures = None

name: str = None

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 are specified, all the measures are returned.
levels (Union[QueryLevel, Sequence[QueryLevel], None]) – The levels to split on. If none are specified, the value of the measures at the top level 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.

atoti.query.hierarchies module¶

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

Bases: atoti._mappings.ImmutableMapping

Manage the query hierarchies.

atoti.query.hierarchy module¶

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

Bases: object

Hierarchy for query cube.

name¶: Hierarchy name.

dimension¶: Hierarchy dimension.

levels¶: Levels of the hierarchy.

slicing¶: Whether the hierarchy is slicing or not.

dimension: str = None

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: ImmutableMapping[str, QueryLevel] = None

name: str = None

slicing: bool = None

atoti.query.level module¶

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

Bases: object

Level for query cube.

name¶: Level name.

dimension¶: Dimension of the level’s hierarchy.

hierarchy¶: Hierarchy the level is member of.

dimension: str = None

hierarchy: str = None

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 = None

atoti.query.levels module¶

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

Bases: atoti._base_levels.BaseLevels

Flat representation of all the levels in the cube.

atoti.query.measure module¶

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

Bases: object

Query measure.

name¶: Measure name.

visible¶: Whether the measure is visible or not.

folder¶: Measure folder.

formatter¶: Measure formatter.

folder: Optional[str] = None

formatter: Optional[str] = None

name: str = None

visible: bool = None

atoti.query.measures module¶

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

Bases: atoti._mappings.ImmutableMapping

Manage the query measures.

atoti.query.query_result module¶

class atoti.query.query_result.QueryResult(data=None, index=None, columns=None, *, cube, 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¶

exception atoti.query.session.HttpException(parent)¶

Bases: Exception

Exception representing and HTTP error.

class atoti.query.session.QuerySession(url, auth, name)¶

Bases: object

Used to query an existing session.

property cubes¶

Cubes of the session.

Return type: QueryCubes

property name¶

Name of the session.

Return type: str

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

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

Parameters

mdx (str) –
The MDX SELECT query to execute. Requirements to guarantee that the DataFrame is well shaped:
- No more than two axes.
- No grand or sub totals.
- Nothing else but measures on the COLUMNS axis.
timeout (int) – The query timeout in seconds.

Return type

QueryResult

property url¶

URL of the session.

Return type: str

Module contents¶

atoti.query.open_query_session(url, name=None, *, auth=None)¶

Open an existing session to query it.

This can be used to connect to:

Other sessions built with another atoti process

ActivePivot cubes built with a classic Java project, if version >= 5.7.0

Parameters

url (str) – The server base URL, if {url} is given, {url}/versions/rest is expected to exist.
name (Optional[str]) – The name to give to the session. Defaults to the passed url.
auth (Optional[Callable[[str], Optional[Mapping[str, str]]]]) – The authentication to use.

Return type

QuerySession

Returns

The query session.