{"categories":[{"label":"Software Development","url":"https://skillfed.io/packages/category/software-development/2"}],"enrichment":{"capability":"Papermill parameterizes, executes, and analyzes Jupyter Notebooks programmatically, allowing you to inject parameters into notebooks and run them with different inputs via Python API or CLI.","skillfed_tags":["notebook-automation","data-pipeline","jupyter-tools"],"use_cases":["Run a financial or business report notebook on different dates (month-end, year-end) with parameters controlling the date range.","Build a data pipeline where one notebook's output feeds into another notebook's parameters, automating multi-step analyses.","Batch-execute the same analysis notebook across many datasets or cohorts, storing results in cloud storage.","Integrate notebook-based models or analyses into scheduled jobs or CI/CD workflows without rewriting the logic.","Generate parameterized reports on demand, injecting user-supplied values (thresholds, filters, model hyperparameters) at runtime."],"what_it_does":"Papermill is a tool for turning Jupyter Notebooks into parameterized, reusable components in data pipelines. It lets you inject parameters into a notebook before execution, then run it and capture the output\u2014all without manual intervention. This is useful when you have a notebook-based analysis or report that needs to run with different inputs (e.g., different dates, thresholds, or datasets) or when you want to chain multiple notebooks together in a workflow.\n\nThe package works by looking for a cell tagged 'parameters' in your notebook, then injecting a new cell with your supplied parameter values before execution. You can pass parameters via the Python API, command-line flags, YAML files, or base64-encoded strings. It supports reading from and writing to local files, HTTP URLs, AWS S3, Azure storage, and Google Cloud Storage, making it suitable for both local development and cloud-based data pipelines.","worth_installing":"Yes. Papermill is actively maintained, has low install friction, carries no known vulnerabilities, and solves a real problem for anyone using Jupyter Notebooks in production pipelines or reporting workflows. The permissive BSD license poses no restrictions. Install it if you need to automate notebook execution with varying inputs or integrate notebooks into larger workflows."},"id":"papermill","links":{"html":"https://skillfed.io/packages/papermill","md":"https://skillfed.io/packages/papermill.md","pypi":"https://pypi.org/project/papermill/"},"maintenance":{"status":"active"},"meta":{"latest_release":"2026-02-27","license_spdx":null,"license_treatment":"permissive","name":"papermill","python_support":"supports_current","summary":"Parameterize and run Jupyter and nteract Notebooks"},"popularity":{"monthly_downloads":15388058,"position":1188,"tier":"top_5000"},"security":{"n_vulnerabilities":0},"version":"2.7.0"}