{"categories":[{"label":"Database","url":"https://skillfed.io/packages/category/database/2"}],"enrichment":{"capability":"Tentaclio opens and manages streams across multiple protocols (file, FTP, SFTP, S3, HTTP/HTTPS) and database connections using a unified URL-based interface, with automatic credential injection and pandas integration.","skillfed_tags":["data-pipeline","multi-protocol","credentials-management"],"use_cases":["Read CSV or Parquet files from S3 or SFTP into pandas DataFrames without writing protocol-specific code.","Write processed data to multiple backends (local, S3, database) using the same `tentaclio.open()` call with different URLs.","Manage credentials centrally via environment variables instead of hardcoding or passing them through application code.","Copy or move files between different storage systems (e.g., local to S3, SFTP to database) with a single `tentaclio.copy()` call.","Query databases and write results to cloud storage in a single script without managing separate connection objects.","List or walk remote directories on S3 or SFTP using familiar Python filesystem patterns."],"what_it_does":"Tentaclio is a Python library that abstracts away the differences between reading and writing data across multiple storage backends\u2014local files, FTP, SFTP, S3, HTTP/HTTPS, and databases\u2014by exposing a single unified interface. Instead of learning separate APIs for each protocol, you use `tentaclio.open()` for streams and `tentaclio.db()` for database connections, always working with standard file-like objects and connection clients.\n\nThe library handles credential management automatically through environment variables, supports pandas DataFrames directly (read and write CSV, Parquet, etc. to any backend), and provides filesystem-like operations such as `listdir`, `scandir`, and `walk` where the underlying protocol supports them. It includes built-in handlers for file, FTP, SFTP, HTTP, and HTTPS; additional schemes (S3, Google Cloud Storage, Databricks, Snowflake, etc.) are available through optional companion packages. Designed for distributed data tasks, it reduces boilerplate and credential-handling complexity in data pipelines.","worth_installing":"Yes. Tentaclio is actively maintained, has no known vulnerabilities, and solves a genuine pain point in data workflows: abstracting protocol differences behind a clean, consistent API. The low install friction, permissive MIT license, and broad protocol support make it a solid choice for any project that moves data across multiple backends. The pandas integration and automatic credential injection are particularly valuable in distributed or CI/CD environments. Start with the built-in protocols; add optional packages only when you need S3, Google Cloud, or specialized databases."},"id":"tentaclio","links":{"html":"https://skillfed.io/packages/tentaclio","md":"https://skillfed.io/packages/tentaclio.md","pypi":"https://pypi.org/project/tentaclio/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-08-05","license_spdx":"MIT","license_treatment":"permissive","name":"tentaclio","python_support":"supports_current","summary":"Unification of data connectors for distributed data tasks"},"popularity":{"monthly_downloads":1715222,"position":3623,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"1.5.1"}