The format is based on Keep a Changelog and this project adheres to Semantic Versioning.
New tutorial exploring the main basic features of atoti.
rank()returns a measure ranking the members of a given hierarchy based on the value of another measure.
array.prefix_sum()performs the prefix sum of array measures.
Hierarchies can have the same name if they are in different dimensions. To avoid conflicts, a hierarchy can be accessed via a tuple containing the dimension and the hierarchy:
Bumped the minimal required version of JupyterLab to 2.1.
Upgraded from ActiveUI SDK 4.3.7 to 4.3.8.
Better messages for Java known errors (#43).
The Auth0 support in Atoti+ has been replaced by the more general OpenID Connect authentication protocol. The structure of the configuration can be seen in the configuration tutorial.
measureparameter accepts any value that can be converted to a measure (#22).
where()support inequalities on dates as conditions.
Issue when loading data into a scenario with
Issue when aggregating
.VALUEmeasures using any of the
Type issue that sometimes happened when chaining operators such as
Blinking cell updates not appearing in pivot tables with real time queries.
agg.min_member()return a measure equal to the member reaching the correspinding extremum of the passed measure on the given level.
query.level.QueryLevel.isin()create conditions expressing that a hierarchy or a level should be on one of the given members.
cube.Cube.schema: SVG graphs of, respectively, all the session’s stores and the stores used by a cube.
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.
BREAKING: Hierarchies, levels, and measures can no longer be passed by name, instances of the corresponding class are expected instead.
sampling_modeparameters and the
ATOTI_URL_PATTERNenvironment variable have been moved to the
config.SessionConfigurationchanging these signatures:
(name='Unnamed', sampling_mode=SamplingMode(name='limit_lines', parameters=), port=None, max_memory=None, java_args=None, config=None, **kwargs)→
(name='Unnamed', *, config=None)
(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 the
configuration tutorial <tutorial/02-configuration:Auth0>.
config.Auth0Authentication.role_mappingdo not accept role instances anymore, only role names.
BREAKING: The wildcard value in measure simulations has been changed from
session.Session.read_numpy()require a name for the created store:
(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)
(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)
(dataframe, keys=None, store_name=None, partitioning=None)→
(dataframe, store_name, *, keys=None, in_all_scenarios=True, partitioning=None)
store.Store.insert_rows(rows)have been renamed
store.Store.append(). They take a variadic
*rowsparameter and in place addition of a single row is still supported with
variancefunctions have been renamed
agg.percentile(measure, percentile_value, mode='inc', interpolation='linear', scope=None)→
(measure, q, *, mode='inc', interpolation='linear', scope=None)
array.percentile(measure, percentile_value, mode='inc', interpolation='linear')→
(measure, q, *, mode='inc', interpolation='linear')
agg.variance(measure, mode='sample', scope=None)→
(measure, *, mode='sample', scope=None)
(measure, *, mode='sample')
avghas been renamed
meanwith .MEAN suffix for automatically created measures instead of .AVG:
(measure, *, scope=None)
BREAKING: Some function signatures have changed:
(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
slicinghas been removed since it can be set afterwards through:
(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.
(level, partitioning=None, window=range(-2147483648, 0), exclude_self=False)→
(level, *, partitioning=None, window=range(-2147483648, 0), exclude_self=False)where
windowcan also accept a tuple of two time offsets to perform a rolling time period aggregation.
(path, *, sep=',')
BREAKING: Some other function signatures have changed only to adopt keyword-only parameters (denoted by a
*in the parameter list):
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.
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.
pathparameter of all CSV loading functions accepts glob patterns (e.g.
simulation.Priority. Directly pass numbers to rank simulation rules instead.
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.
max_memorycan be passed directly as a named-parameter instead. The other properties have been removed.
pow(measure_a, measure_b)replaced by
measure_a ** measure_b.
Inability to install atoti alongside Python > 3.7 when using Conda.
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.
First public release of atoti.