0.4.0 (2020-05-25)

Added

• agg.max_member() and agg.min_member() return a measure equal to the member reaching the corresponding extremum of the passed measure on the given level.

• hierarchy.Hierarchy.isin(), query.hierarchy.QueryHierarchy.isin(), level.Level.isin(), and query.level.QueryLevel.isin() create conditions expressing that a hierarchy or a level should be on one of the given members.

• stores.Stores.schema and cube.Cube.schema: SVG graphs of, respectively, all the session’s stores and the stores used by a cube.

• Python package installation guide.

• store.StoreScenarios.load_csv() loads a directory of CSV files into a store, automatically generating scenarios based on the directory’s structure.

• total() returns the total value on each hierarchy member.

• session.Session.create_store() creates an empty store from a schema.

• Exponentiation operation between measures: measure_a ** measure_b.

Changed

• BREAKING: Hierarchies, levels, and measures can no longer be passed by name, instances of the corresponding class are expected instead.

• BREAKING: create_session()’s port, max_memory, java_args and sampling_mode parameters and the ATOTI_URL_PATTERN environment variable have been moved to the config.SessionConfiguration changing these signatures:

  • create_session(): (name='Unnamed', sampling_mode=SamplingMode(name='limit_lines', parameters=[10000]), port=None, max_memory=None, java_args=None, config=None, **kwargs) → (name='Unnamed', *, config=None)

  • config.create_config(): (inherit=True, metadata_db=None, roles=None, authentication=None, properties=None) → (*, inherit=True, port=None, url_pattern=None, metadata_db=None, roles=None, authentication=None, sampling_mode=None, max_memory=None, java_args=None)

• BREAKING: New structure for the authentication configuration in YAML as shown in config.create_config().

• BREAKING: config.BasicUser.roles and config.Auth0Authentication.role_mapping do not accept role instances anymore, only role names.

• BREAKING: The wildcard value in measure simulations has been changed from * to None.

• BREAKING: session.Session.read_pandas(), session.Session.read_spark() and session.Session.read_numpy() require a name for the created store:

  • session.Session.read_numpy(): (data, columns, store_name, keys, in_all_scenarios=True, partitioning=None, sep='|') → (array, columns, store_name, *, keys=None, in_all_scenarios=True, partitioning=None, **kwargs)

  • session.Session.read_pandas(): (dataframe, keys=None, store_name=None, partitioning=None, types=None, **kwargs) → (dataframe, store_name, *, keys=None, in_all_scenarios=True, partitioning=None, types=None, **kwargs)

  • session.Session.read_spark(): (dataframe, keys=None, store_name=None, partitioning=None) → (dataframe, store_name, *, keys=None, in_all_scenarios=True, partitioning=None)

• BREAKING: simulation.Scenario.insert(row) and store.Store.insert_rows(rows) have been renamed simulation.Scenario.append() and store.Store.append(). They take a variadic *rows parameter and in place addition of a single row is still supported with +=.

• BREAKING: percentile and variance functions have been renamed quantile and var:

  • agg.percentile(measure, percentile_value, mode='inc', interpolation='linear', scope=None) → agg.quantile() and (measure, q, *, mode='inc', interpolation='linear', scope=None)

  • array.percentile(measure, percentile_value, mode='inc', interpolation='linear') → array.quantile() and (measure, q, *, mode='inc', interpolation='linear')

  • agg.variance(measure, mode='sample', scope=None) → agg.var() and (measure, *, mode='sample', scope=None)

  • array.variance(measure, mode='sample') → array.var() and (measure, *, mode='sample')

• BREAKING: avg has been renamed mean with .MEAN suffix for automatically created measures instead of .AVG:

  • agg.avg(measure, scope=None) → agg.mean() and (measure, *, scope=None)

  • array.avg() → array.mean()

• BREAKING: Some function signatures have changed:

  • cube.Cube.create_static_parameter_hierarchy: (level_and_hierarchy_name, members, indices=None, slicing=True, index_measure='', level_type=None) → (name, members, *, data_type=None, index_measure=None, indices=None, store_name=None) where slicing has been removed since it can be set afterwards through: hierarchy.Hierarchy.slicing.

  • parent_value(): (measure, on_hierarchies=None, top_value=None) → (measure, on, *, apply_filters=False, degree=1, total_value=None). The two new parameters default to values equivalent to the previous behavior; see the function documentation for more details.

  • scope.cumulative(): (level, partitioning=None, window=range(-2147483648, 0), exclude_self=False) → (level, *, partitioning=None, window=range(-2147483648, 0), exclude_self=False) where window can also accept a tuple of two time offsets to perform a rolling time period aggregation.

  • simulation.Scenario.load_csv(): (file, delimiter=',') → (path, *, sep=',')

• BREAKING: Some other function signatures have changed only to adopt keyword-only parameters (denoted by a * in the parameter list):

  • agg.count_distinct()

  • agg.long()

  • agg.max()

  • agg.median()

  • agg.min()

  • agg.prod()

  • agg.short()

  • agg.single_value

  • agg.square_sum()

  • agg.std()

  • agg.sum()

  • array.std()

  • cube.Cube.setup_simulation()

  • date_diff()

  • open_query_session()

  • query.session.QuerySession.query_mdx()

  • scope.siblings()

  • session.Session.create_cube()

  • session.Session.explain_mdx_query()

  • session.Session.query_mdx()

  • session.Session.read_csv()

  • session.Session.read_parquet()

  • shift()

  • simulation.Simulation.load_csv()

  • store.Store.join()

  • store.Store.load_csv()

  • store.Store.load_pandas()

  • store.Store.load_parquet()

  • store.Store.load_spark()

• Upgraded from ActiveUI SDK 4.3.5 to 4.3.7. Pivot tables support new Tree, Pivot, and Table layouts, the latter making the Tabular View widget redundant so it has been removed from the available widgets.

• session.Session.read_pandas(), store.Store.load_pandas(), simulation.Simulation.load_pandas(), and simulation.Scenario.load_pandas() automatically load columns made of numerical Python lists or Numpy one-dimensional ndarrays as arrays.

• Stores without key columns are partitioned on their non-numerical columns by default.

• Changed the behavior of agg.single_value() aggregation function to be more consistent with other aggregation functions (#40).

• Cube names are not restricted to alphanumeric strings without spaces anymore.

• The path parameter of all CSV loading functions accepts glob patterns (e.g. /path/**/*.csv).

Removed

• BREAKING: simulation.Priority. Directly pass numbers to rank simulation rules instead.

• BREAKING: Cube.create_bucketing() has moved to Cube._setup_bucketing() and is not part of the public API anymore. It might change in future releases without notice.

• BREAKING: config.create_config()’s properties parameter. max_memory can be passed directly as a named-parameter instead. The other properties have been removed.

• BREAKING: pow(measure_a, measure_b) replaced by measure_a ** measure_b.

Fixed

• Inability to install atoti alongside Python > 3.7 when using Conda.

• Issue with filter() not being aggregated correctly (#17, #28).

• Metadata DBs created in atoti can be used in Atoti+ and reciprocally (#15).

• Inability to create some measures or hierarchies after some partial joins (#4, #10).

• Inability to load CSV folders from AWS S3 storage.

• Slow read of files on AWS S3 when anonymous due to multiple timeouts in the credentials provider (#26).

• Inability to use wildcards on fields types other than strings.

• Inability to use numeric levels for measure simulations.