Union Pandera Integrations

Pandas is an open-source data analysis and manipulation tool that is fast, flexible, flexible, and easy to use. It was built on top the Python programming language. Tools for reading and writing data between memory data structures and various formats: CSV, text files, Microsoft Excel, SQL databases and the fast HDF5 format. Intelligent data alignment and integrated handling missing data: Use a powerful group engine to perform split-apply/combine operations on data sets. Time series-functionality: date range generation and frequency conversion, moving window statistics, date shifting and lagging. You can even create domain-specific offsets and join time sequences without losing data.

GeoPandas, an open-source project that makes it easier to work with geospatial data using Python, is GeoPandas. GeoPandas extends pandas' datatypes to allow spatial operations on geometries. Shapely performs geometric operations. Geopandas also depends on fiona to access files and matplotlib to plot. GeoPandas' goal is to make it easier to work with geospatial data using python. It combines the capabilities from pandas with shapely, providing geospatial operations using pandas and a high level interface to multiple geometries in shapely. GeoPandas allows you to perform operations in Python that would otherwise require a spatial data base such as PostGIS. GeoPandas is a community-led, community-driven project that has been used and supported by many people from all walks of the world. GeoPandas will remain 100% open-source software and be available for everyone to use under the BSD-3 Clause license.

Dask is free and open-source. It was developed in collaboration with other community projects such as NumPy and pandas. Dask uses existing Python data structures and APIs to make it easy for users to switch between NumPy/pandas and scikit-learn-powered versions. Dask's schedulers can scale to thousands of node clusters, and its algorithms have been tested at some of the most powerful supercomputers around the world. You don't necessarily need a large cluster to get started. Dask ships schedulers that can be used on personal computers. Many people use Dask to scale computations on their laptops, using multiple cores and their disk for extra storage. Dask exposes lower level APIs that allow you to build custom systems for your own applications. This allows open-source leaders to parallelize their own packages, and business leaders to scale custom business logic.

PySpark is a Python interface for Apache Spark. It allows you to create Spark applications using Python APIs. Additionally, it provides the PySpark shell that allows you to interactively analyze your data in a distributed environment. PySpark supports Spark's most popular features, including Spark SQL, DataFrame and Streaming. Spark SQL is a Spark module that allows structured data processing. It can be used as a distributed SQL query engine and a programming abstraction called DataFrame. The streaming feature in Apache Spark, which runs on top of Spark allows for powerful interactive and analytic applications across streaming and historical data. It also inherits Spark's ease-of-use and fault tolerance characteristics.

The Fugue Platform equips teams with the tools they need to create, deploy, and maintain cloud security at all stages of the development cycle. Fugue is a tool that will bring you immediate value. We guarantee it. Fugue uses the open-source Open Policy Agent (OPA), which is a standard for IaC, and cloud infrastructure policy as code. Regula, an open-source tool powered OPA, can be used to build IaC checks into git workflows or CI/CD pipelines. Use Rego, an open-source language that allows you to create custom rules. You can manage your IaC security for containers, Kubernetes and cloud resources from one place. This will ensure consistent policy enforcement throughout the development lifecycle. You can view the results of security- and compliance checks for IaC throughout your organization. Access and export tenant-specific IaC security and compliance reports.

FastAPI is an advanced web framework that allows you to build APIs using Python 3.7+. It uses standard Python type hints. Fast: Very high-performance, on par with NodeJS or Go (thanks Pydantic and Starlette). One of the fastest Python Frameworks available. Reduce code duplication and get multiple features out of each parameter declaration.