{"library":"typedspark","type":"library","category":null,"description":"Typedspark provides column-wise type annotations for PySpark DataFrames, enhancing code readability, enabling static type-checking and linting, and improving auto-completion and refactoring capabilities. It helps define explicit schemas for Spark DataFrames, ensuring data integrity at a structural level. The library is currently at version 1.6.3 and maintains a regular release cadence, often driven by dependency updates.","language":"python","status":"active","version":"1.6.3","tags":["pyspark","spark","typing","type-checking","data-quality","etl","schema-validation"],"last_verified":"Mon May 25","install":[{"cmd":"pip install typedspark","imports":["from typedspark import Column","from typedspark import DataSet","from typedspark import Schema","from pyspark.sql.types import LongType","from pyspark.sql.types import StringType"]},{"cmd":"pip install \"typedspark[pyspark]\"","imports":[]}],"homepage":null,"github":"https://github.com/kaiko-ai/typedspark","docs":null,"changelog":null,"pypi":"https://pypi.org/project/typedspark/","npm":null,"openapi_spec":null,"status_page":null,"smithery":null,"compatibility":{"summary":{"python_range":"3.10–3.9","success_rate":100,"avg_install_s":15.9,"avg_import_s":0.5,"wheel_type":"wheel"},"url":"https://checklist.day/v1/registry/typedspark/compatibility"}}