pyrasgo 0.5.2

Alpha version of the Rasgo Python interface.

pyRasgo is a python SDK to interact with the Rasgo API. Rasgo accelerates feature engineering for Data Scientists.

Visit us at https://www.rasgoml.com/ to turn your data into Features in minutes!

Documentation is available at: https://docs.rasgoml.com/rasgo-docs/pyrasgo/

Package Dependencies

• idna>=3.3
• more-itertools
• pandas
• pyarrow>=5.0.0
• pydantic
• pyyaml
• requests
• snowflake-connector-python>=2.7.0
• tqdm

Release Notes

• v0.5.2 (Apr 5, 2022)

  • Adds param table_name for rasgo.publish.dataset() for specifying the table name you want to set for the dataset

• v0.5.1 (Apr 4, 2022)

  • Add deprecation warnings for pre-1.0 functions

• v0.5.0 (Mar 23, 2022)

  • Update Snowflake connection to use correct role

• v0.4.36 (Mar 22, 2022)

  • Make ds.refresh_table() complete refresh when function finishes running always

• v0.4.35 (Mar 16, 2022)

  • Adds a PyRasgo Primitive for an Accelerator
  • Adds the following methods for working with Accelerators in PyRasgo
    • rasgo.get.accelerator()
    • rasgo.get.accelerators()
    • rasgo.create.accelerator()
    • rasgo.delete.accelerator()
    • rasgo.create.dataset_from_accelerator()
    • Accelerator.apply()

• v0.4.34 (Mar 11, 2022)

  • Add to_dbt() function to Datasets
    • Use this method to export a published Dataset as a DBT Model
  • Support tracking of dataset dependencies passed transforms that accept lists of datasets (multi-join)

• v0.4.33 (Mar 11, 2022)

  • Handles long running ds.refresh_table() process

• v0.4.32 (Mar 10, 2022)

  • Fixed uses of apply transform

• v0.4.31 (Mar 04, 2022)

  • Raise an error if you supply an arg to transform which doesn't exist
  • Fix dependency management for transform arguments of type table_list

• v0.4.30 (Mar 01, 2022)

  • Cache and return dataset columns if not set when calling ds.columns and ds from API
  • New method rasgo.update.column() to set/update metadata about a ds column

• v0.4.29 (Mar 01, 2022)

  • Bugfixes

• v0.4.28 (Feb 28, 2022)

  • Fetches all datasets on a call to rasgo.get.datasets()

• v0.4.27 (Feb 25, 2022)

  • Adds ability to set tags when creating a transform in the function rasgo.create.transform()

• v0.4.26 (Feb 22, 2022)

  • Allow published datasets with tables as their output to be refreshed using dataset.refresh_table()

• v0.4.25 (Feb 22, 2022)

  • Creates more informative generated Data Warehouse Table names; Now tables/views names made in PyRasgo will look like the folowing below
    • RASGO_SDK__OP<op_num>__<transform_name>_transform__<guid>
  • Adds proper error message with steps to take to fix, when publishing a DF with incompatible pandas date types

• v0.4.24 (Feb 21, 2022)

  • Adds the optional parameter generate_stats to toggle stats generation when publishing with rasgo.publish.table/df() (defaults to True if not passed)

• v0.4.23 (Feb 17, 2022)

  • Adds the parameter parents to specify parent dataset dependencies of table or pandas dataframe when publishing with rasgo.publish.table/df()

• v0.4.22 (Feb 15, 2022)

  • Allows users to get the PyRasgo code used to generate a dataset with the function dataset.generate_py()

• v0.4.21 (Feb 08, 2022)

  • Enable users to append to an existing Rasgo Dataset using rasgo.publish.df(fqtn="MY.FQTN.STRING", if_exists="append")

• v0.4.20 (Feb 07, 2022)

  • Add render_only optional parameter to Dataset.transform() to support printing the SQL that will be executed by an applied transform instead of creating a new Dataset.
    • This option allows testing of transform arguments without having to execute the transform

• v0.4.19 (Feb 02, 2022)

  • Bug fixes

• v0.4.18 (Feb 02, 2022)

  • Add optional rasgo.publish.dataset() parameter table_type to support materializing a dataset as a table instead of a view.

• v0.4.17 (Feb 01, 2022)

  • Add Dataset.generate_yaml() to allow users to export their datasets and associated operation sets as a YAML string
  • Add Dataset.versions attribute to support retrieving all versions of a Dataset

• v0.4.16 (Jan 31, 2022)

  • Add Dataset.run_stats() to allow users to trigger stats generation for a dataset
  • Add Dataset.profile() to give users a link to the Rasgo UI, where they can view details on their Dataset, including any generated stats

• v0.4.15 (Jan 27, 2022)

  • Update timeseries tracking attribute name to time_index to match keyword

• v0.4.14 (Jan 26, 2022)

  • Remove unnecessary import

• v0.4.13 (Jan 26, 2022)

  • Add the ability to publish dataset attributes when publishing a dataset

• v0.4.12 (Jan 21, 2022)

  • Change experimental_async to async_compute, default to True

• v0.4.11 (Jan 25, 2022)

  • Bug fixes

• v0.4.10 (Jan 24, 2022)

  • Adds dataset snapshot information to Dataset.snapshots and provides a hook to return a snapshot's data with Dataset.to_df(snapshot_index=<int>)

• v0.4.9 (Jan 17, 2022)

  • Adds parameters filters, order_by, and columns to dataset.to_df() and dataset.preview() methods

• v0.4.8 (Jan 14, 2022)

  • Adds experimental_async flag to transforms to take advantage of experimental long-running operation creation

• v0.4.7 (Jan 13, 2022)

  • Return errors for operation creation

• v0.4.6 (Jan 12, 2022)

  • Adds support for long running operation creations

• v0.4.5 (Dec 21, 2021)

  • Fixes dependency installation

• v0.4.4 (Dec 21, 2021)

  • Adds support for Python versions 3.7.12, 3.8, 3.9, and 3.10

• v0.4.3 (Dec 17, 2021)

  • Method added rasgo.update.transform() to update a transform

• v0.4.2 (Dec 15, 2021)

  • Adds the ability to reference Dataset attributes directly
    • Dataset.id
    • Dataset.name
    • Dataset.description
    • Dataset.status
    • Dataset.fqtn
    • Dataset.columns
    • Dataset.created_date
    • Dataset.update_date
    • Dataset.attributes
    • Dataset.dependencies
    • Dataset.sql
  • Adds ability function for getting Datasets by fqtn
    • rasgo.get.dataset(fqtn='MY_FQTN'>)

• v0.4.1 (Dec 13, 2021)

  • "Updates"

• v0.4.0 (Dec 07, 2021)

  • Add Rasgo Datasets
    • Datasets are the new, single primitive available in Rasgo. Users can explore, transform, and create new data warehouse tables using this single primitive object.
    • Transforming a previously saved Dataset will produce a new Dataset definition that builds on top of the transformed Dataset. This new dataset will consist of a new operation that references the transformed Dataset as the source_table in the applied transform. Further transforms will add to the list of operations until .save is called to persist the created operations as a new Dataset in Rasgo.
    • New Rasgo Functions:
      • rasgo.get.datasets - Get a list of all available Datasets
      • rasgo.get.dataset - Get a single Dataset by ID, including the list of operations that created it (if they exist)
      • rasgo.update.dataset - Update name and description
      • rasgo.delete.dataset - Delete a Dataset
      • rasgo.publish.dataset - Save a new dataset to Rasgo. Can only save new Datasets that have been created by transforming old Datasets
      • rasgo.publish.df - Publish a Pandas DataFrame as a Rasgo Dataset
      • rasgo.publish.table - Publish an existing table as a Rasgo dataset
    • Dataset Primitive Functions:
      • Dataset.transform - Transform a previously existing Dataset with a given Transform to create a new Dataset definition
        • You can also reference transforms by name directly.
        • e.g. dataset.join(...) as opposed to dataset.transform(transform_name='join', ...)
      • Dataset.to_df - Read a Dataset into a Pandas DataFrame
      • Dataset.preview - Get a Pandas DataFrame consisting of the top 10 rows produced by this Dataset
    • Dataset Attributes:
      • Dataset.sql - A sql string representation of the operations that produce this dataset (if they exist)

• v0.3.4 (Dec 03, 2021)

  • Temporary hotfix: DataSource.to_dict() returns sourceTable attribute as a table name, instead of fqtn. Plan is to revert to fqtn in a future version when publish methods offer first-class handling of fqtn.

• v0.3.3 (Nov 08, 2021)

  • Added detailed Transform Argument Definitions during Transform creation
  • Allow null values for User Defined Transform arguments

• v0.3.2 (Oct 13, 2021)

  • Adds Jinja as the templating engine for User Defined Transforms
  • Source transforms may now be previewed, tested and deleted to enable a full creation experience.
  • Adds Rasgo template functions to enable dynamic template building

• v0.3.1 (Sept 27, 2021)

  • Adds filter and limit params to read.collection_snapshot_data function
  • Fixes Collection response model bug

• v0.3.0 (Sept 22, 2021)

  • Deprecates FeatureSet primitive (see docs for migration path: https://docs.rasgoml.com/rasgo-docs/pyrasgo-version-log/version-0.3)
  • Adds support for creating features using python source code
  • Adds support for user-defined transformation functionality
  • Adds methods to interact with Collection snapshots (DEPRECATED):
    • get.collection_snapshots()
    • read.collection_snapshot_data()
  • Adds methods to Collection primitive:
    • .preview() to view data in a pandas df
    • .get_compatible_features() to list features available to join
  • Adds .to_dict and .to_yml methods to DataSource primitive

• v0.2.5 (Aug 18, 2021)

  • adds handling and user notification for highly null dataframes which would otherwise not function well with evaluate.profile or evaluate.feature_importance

• v0.2.4 (Aug 4, 2021)

  • supports tables named as restricted Snowflake keywords (e.g. ACCOUNT, CASE, ORDER) to be registered as Rasgo Sources

• v0.2.3 (July 30, 2021)

  • introduces publish.features_from_source_code() function. This function allows users to pass a custom SQL string to create a view in Snowflake using their own code. This function will: register a child source based off the parent source provided as input, register features from the new child source table.
  • introduces new workflow to publish.source_data() function. Pass in source_type="sql", sql_definition="<valid sql select string>" to create a new Rasgo DataSource as a view in Snowflake using custom SQL.
  • makes the features parameter optional in publish.features_from_source() function. If param is not passed, all columns in the underlying table that are not in the dimensions list will be registered as features
  • adds trigger_stats parameter to all publish method. When set to False, statistical profiling will not run for the data objects being published. Default = True
  • adds verbose parameter to all publish methods. When set to True, prints status messages to stdout to update users on progress of the function. Default = False.
  • introduces .sourceCode property on Rasgo DataSource and FeatureSet classes to display the SQL or python source code used to build the underlying table
  • introduces .render_sql_definition() method on Collection class to display the SQL used to create the underlying collection view
  • introduces .dimensions property on Rasgo Collection class to display all unique dimension columns in a Collection
  • introduces trigger_stats parameter in collection.generate_training_data() method to allow users to generate a sql view without kicking off correlation and join stats. Set to False to suppress stats jobs. Default=True.
  • Add support for optional catboost parameter train_dir in evaluate.feature_importance() function, which allows users to dictate where temporary training files are generated

• v0.2.2(July 14, 2021)

  • Allow for consistency in evaluate.feature_importance() evaluation metrics for unchanged dataframes
  • Allow users to control certain CatBoost parameters when running evaluate.feature_importance()

• v0.2.1(July 01, 2021)

  • expand evaluate.feature_importance() to support calculating importance for collections

• v0.2.0(June 24, 2021)

  • introduce publish.experiment() method to fast track dataframes to Rasgo objects
  • fix register bug

• v0.1.14(June 17, 2021)

  • improve new user signup experience in register() method
  • fix dataframe bug when experiment wasn't set

• v0.1.13(June 16, 2021)

  • intelligently run Regressor or Classifier model in evaluate.feature_importance()
  • improve model performance statistics in evaluate.feature_importance(): include AUC, Logloss, precision, recall for classification

• v0.1.12(June 11, 2021)

  • support fqtn in publish.source_data(table) parameter
  • trim timestamps in dataframe profiles to second grain

• v0.1.11(June 9, 2021)

  • hotfix for unexpected histogram output

• v0.1.10(June 8, 2021)

  • pin pyarrow dependency to < version 4.0 to prevent segmentation fault errors

• v0.1.9(June 8, 2021)

  • improve model performance in evaluate.feature_importance() by adding test set to catboost eval

• v0.1.8(June 7, 2021)

  • evaluate.train_test_split() function supports non-timeseries dataframes
  • evaluate.feature_importance() function now runs on an 80% training set
  • adds timeseries_index parameter to evaluate.feature_importance() & prune.features() functions

• v0.1.7(June 2, 2021)

  • expands dataframe series type recognition for profiling

• v0.1.6(June 2, 2021)

  • cleans up dataframe profiles to enhance stats and visualization for non-numeric data

• v0.1.5(June 2, 2021)

  • introduces pip install "pyrasgo[df]" option which will install: shap, catboost, & scikit-learn

• v0.1.4(June 2, 2021)

  • various improvements to dataframe profiles & feature_importance

• v0.1.3(May 27, 2021)

  • introduces experiment tracking on dataframes
  • fixes errors when running feature_importance on dataframes with NaN values

• v0.1.2(May 26, 2021)

  • generates column profile automatically when running feature_importance

• v0.1.1(May 24, 2021)

  • supports sharing public dataframe profiles
  • enforces assignment of granularity to dimensions in Publish methods based on list ordering

• v0.1.0(May 17, 2021)

  • introduces dataframe methods: evaluate, prune, transform
  • supports free pyrago trial registration

• v0.0.79(April 19, 2021)

  • support additional datetime data types on Features
  • resolve import errors

• v0.0.78(April 5, 2021)

  • adds include_shared param to get_collections() method

• v0.0.77(April 5, 2021)

  • adds convenience method to rename a Feature’s displayName
  • adds convenience method to promote a Feature from Sandbox to Production status
  • fixes permissions bug when trying to read Community data sources from a public org

• v0.0.76(April 5, 2021)

  • adds columns to DataSource primitive
  • adds verbose error message to inform users when a Feature name conflict is preventing creation

• v0.0.75(April 5, 2021)

  • introduce interactive Rasgo primitives

• v0.0.74(March 25, 2021)

  • upgrade Snowflake python connector dependency to 2.4.0
  • upgrade pyarrow dependency to 3.0