Reverse Dependencies of pyspark

The following projects have a declared dependency on pyspark:

• powerbiclient — A Custom Jupyter Widget Library
• PPISleuth — Snif out targets from a PPI network.
• pramen-py — Pramen transformations written in python
• praxis-ml — A PySpark-based library for transparent and interpretable machine learning
• prda — Prda contains packages for data processing, analysis and visualization. The ultimate goal is to fill the “last mile” between analysts and packages.
• pre-ai-python — Microsoft AI Python Package
• prism-dev — The easiest way to create data pipelines in Python.
• prism-ds — The easiest way to create data pipelines in Python.
• prophecy-build-tool — Prophecy-build-tool (PBT) provides utilities to build and distribute projects created from the Prophecy IDE.
• prt-databricks-simplify-7da-data-ingest — providing creating data layers from pdro s3 buckets
• psdq — Ad Hoc Data Quality Tool for PySpark
• psyaitools — Loudness added.
• publicationpackage — This package contains the functions needed for doing a publication in a Jupyter Notebook.
• pulse-telemetry — Spark applications for transforming raw incoming data into a set of schemas for analysis.
• py-data-modori — LMOps Tool for Korean
• py-dataframe-show-reader — Reads the output of a DataFrame.show() statement into a DataFrame
• py-dbchat — Chat with your existing database without using vector DB.
• py-homepass — Python package for basic interaction with the Plume Homepass API
• py-project-toml-kimtodd — Sample Python Project for creating a new Python Module
• py4phi — A library for encryption/decryption and analysis of sensitive data.
• pyautodata — Python library designed to minimize the setup/arrange phase of your unit tests
• pybda — Analysis of big biological data sets for distributed HPC clusters.
• pyBlindRL — A Python implementation of blind Richardson-Lucy deconvolution
• pycatcher — This package identifies outlier(s) for a given time-series dataset in simple steps. It supports day, week, month and quarter level time-series data.
• pydantic-cereal — Advanced serialization for Pydantic models
• pydantic-kedro — Kedro
• pydantic-spark — Converting pydantic classes to spark schemas
• pydataassist — PyDataUtils
• pydatavec — Python interface for DataVec
• pydeequ — PyDeequ - Unit Tests for Data
• pydeequ2 — PyDeequ2 - aws clone
• pydeequ3 — Pydeequ3: PySpark 3 support for deequ - AWSClone
• pydeequalb — PyDeequ - Unit Tests for Data
• pydisconet — analyzing the co-authorship network of researchers in the field of biology
• pyeqx — no summary
• pyeqx-core — no summary
• pyfate — no summary
• pyIcarus — Tools library for Security Research
• pyjanitor — Tools for cleaning pandas DataFrames
• pyjats — Quick pydantic based parser for parsing JATS xml from e.g. EuropePMC
• pykiwi — pykiwi
• pyMicroeconomics — Functions for microeconomic analysis
• pyod-pyspark — no summary
• pyonion — A minimal implementation of the ONe Instance ONly algorithm
• pyoptimus — Optimus is the missing framework for cleaning and pre-processing data in a distributed fashion.
• pypas — Python wrapper for CyberArk Core PAS REST-API
• pype-spark — no summary
• pypersonality — Identify the personality from a given text using (MBTI) Myers-Briggs Personality Type Dataset
• pyQualitas — A project to ensure the data quality using python
• pyrander — A random test lib
• pyrasterframes — Access and process geospatial raster data in PySpark DataFrames
• pyrecdp — A data processing bundle for spark based recommender system operations
• pyresumize — Resume Parser Written in Python3 . The module supports .pdf and .docx files
• pysarplus — SAR prediction for use with PySpark
• pyschema2 — Schema generation and validation for pyspark
• pyseqtender — Distributed NGS pipelines made easy
• pysequila — An SQL-based solution for large-scale genomic analysis
• pysetl — A PySpark ETL Framework
• pySISF — A Python toolkit for SISF Images
• pyspark-bucketmap — Easily group pyspark data into buckets and map them to different values.
• pyspark-cli — PySpark Project Buiding Tool
• pyspark-config — Configurable data pipeline with Pyspark
• pyspark-connectors — The easy and quickly way to connect and integrate the Spark project with many others data sources.
• pyspark-data-mocker — Mock a datalake easily to be able to test your pyspark data application
• pyspark-datacol-diff — PySpark utility created to quickly provide details regarding which attributes differ between 2 dataframes with same schema and primary key.
• pyspark-dataframe-wrappers — Sample Python Project for creating a new Python Module
• pyspark-dbscan — An "Efficient" Implementation of DBSCAN on PySpark
• pyspark-ds-toolbox — A Pyspark companion for data science tasks.
• pyspark-eda — A Python package for univariate ,bivariate and multivariate data analysis using PySpark
• pyspark-event-correlation — Event Correlation and Changing Detection Algorithm
• pyspark-factories — Create pyspark dataframes with randomly generated data from structschema
• pyspark-flame — A low-overhead sampling profiler for PySpark, that outputs Flame Graphs
• pyspark-functions — no summary
• pyspark-graph — Pure pyspark implementation of graph algorithms
• pyspark-helpers — A collection of tools to help when developing PySpark applications
• pyspark-iomete — IOMETE's PySpark library that contains useful utilities for working with PySpark
• pyspark-json-loader — A package to load and preprocess JSON data using PySpark
• pyspark-pdf — Spark-Pdf is a library for processing documents using Apache Spark
• pyspark-prometheus — Prometheus instrumentation for Spark Streaming metrics.
• pyspark-regression — A tool for regression testing Spark Dataframes in Python
• pyspark-spy — Collect and aggregate on spark events for profitz. In 🐍 way!
• pyspark-stubs — A collection of the Apache Spark stub files
• pyspark-supp — Data Engineer Support PySpark Library
• pyspark-test — Check that left and right spark DataFrame are equal.
• pyspark-testframework — Testframework for PySpark DataFrames
• pyspark-testing — Testing Framework for PySpark
• pyspark-types — `pyspark_types` is a Python library that provides a simple way to map Python dataclasses to PySpark StructTypes
• pyspark-util — PySpark utility functions
• pyspark-utilities — Spark utilities to be used by the Analytics BDA
• pyspark-utility — This project is meant to help pyspark user (Databricks) to get some utility functions.
• pyspark-val — PySpark validation & testing tooling
• pyspark-vector-files — Read vector files into a Spark DataFrame with geometry encoded as WKB.
• pyspark3d — Spark extension for processing large-scale 3D data sets
• pysparkcli — PySpark Project Buiding Tool
• pysparkdt — An open-source Python library for simplifying local testing of Databricks workflows that use PySpark and Delta tables.
• pysparkextra — extra utilities for pyspark.sql
• pysparkifier — Streamlined pyspark usage
• pysparkify — Spark based ETL
• pysparklib — A elaborate and developed PySpark libraries and resources.
• pysparkly — Pyspark useful functions and extensions