agg.sum_product()return a measure equal to the product and sum of two measures or fields.
%operation between measures (#48).
Support reading Parquet files from AWS S3 (#27).
store.Store.drop()remove rows from a store by specifying column names and values.
atoti widgets are snapshotted as SVG images in the notebook on save. These images will appear in HTML exports or in GitHub previews of the notebook.
Context menu actions for widgets of the atoti JupyterLab extension:
Java is no longer required in the pip installation since the atoti Python wheel now relies on jdk4py.
The Measure simulations and Source simulation editors have been redesigned. They now both have their dedicated page instead of being widgets embeddable in dashboards. The Measure simulations editor also issue more minimal updates to the underlying store (#70).
query.cube.QueryCube.query()return DataFrames displaying formatted values and providing a
styleattribute reflecting the potential styling properties of the corresponding cell set (#91).
The first MDX query ran by an atoti widget in JupyterLab is now executed in Python and its resulting cell set is outputted to the corresponding notebook cell. It allows to ensure that the data displayed by the widget reflects the expected state of the cube without having to block the IPython kernel in a fragile way.
Added ability to append rows in all scenarios of a store with
The creation of calculated measures and the action to add a measure computing the difference between to table columns have been disabled in the JupyterLab widget extension to incentivize creating these measures in Python instead. These features are still available in the app (#21).
The constructors of
config.OidcAuthenticationhave been made private and using them is deprecated. They have been replaced by factory functions:
session.Session.endpoint()decorator adds HTTP endpoints to the session from a Python callback.
array.sort()has a new
Trueby default, it allows to choose the sorting order.
scope.cumulative()has a new
Falseby default, it allows to choose whether to include all of a level’s members in the cumulative aggregation, even those for which the underlying measure has no values.
Atoti+ now supports i18n.
en-USis the only locale supported by default but additional locales can be made available by providing custom translation files. These can be configured with
config.create_config()A good starting point for adding new locales is to use the template containing all the translatable items, which can be obtained by using
name_attributeparameter used to select the displayed username when using an OpenID Connect can be configured.
scopeparameter used to select the requested scopes when using an OpenID Connect provider can be configured. The
openidscope is always passed by default.
Missing images in the tutorial (#80).
Issue when reading pandas DataFrame with
Issue with array types not displayed correctly in the stores schema.
Issue when joining a column of type int to a column of type long if the store is based on a parquet file (#76).
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.
Issue when loading data into a scenario with
Issue when aggregating
.VALUEmeasures using any of the
Blinking cell updates not appearing in pivot tables with real time queries.
query.level.QueryLevel.isin()create conditions expressing that a hierarchy or a level should be on one of the given members.
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
(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:
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.
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.
Metadata DBs created in atoti can be used in Atoti+ and reciprocally (#15).
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.