Framework for Python

Installing framework-py, its optional extras, and the tools it works with

Global settings, configure_global(), config_sync(), and personal templates

Project folders, dot-notation names, and the naming rules Framework follows

The project settings file, split settings files, environments, and expressions

Making a New Project

Creating a project with fw.new() or the command line, and preparing a cloned project with bootstrap()

Preparing a Python session for work in a project

The project database that records data hashes, cached values, and saved outputs

Managing a project's Python packages with pyproject.toml and uv

Data Management

Reading and saving data through the data catalog, with integrity hashes and locked files

Notebooks and Scripts

Creating notebooks, scripts, and presentations from stubs and templates

How Framework configures Quarto for notebooks, documents, and presentations

Saving tables, figures, models, and reports to the output folders, with public and private outputs

Caching the results of expensive computations between sessions

Database Connections

Defining database connections in the settings and querying them with db_query(), db_execute(), and db_transaction()

Publishing notebooks, data, and files to S3-compatible storage or Framework Cloud

Framework Cloud

Logging in, consent, token storage, settings sync, the integrity ledger, and what the cloud receives

The .gitignore templates, the shared pre-commit hook, git_hooks_*(), and git_security_audit()

AGENTS.md, assistant stubs, Framework skills, and the guards for privacy-sensitive projects

The .env file, keeping secrets out of settings, Framework's environment variables, and scratch helpers

Standard, privacy-sensitive, course, and presentation projects, with their folders, .gitignore rules, and uses

Setting up and managing the working environment

Reading, writing, and managing data files

Package management with uv

Saving figures, tables, reports, and models

Notebooks & Scripts

Creating notebooks, scripts, and presentations

Project Management

Creating and managing projects

Publishing outputs and reports

Framework Cloud login, settings sync, and the integrity ledger

Git hooks and the security audit

Caching computed values for performance

Database connections and queries

AI assistant integration

Errors and Types

Exceptions, warnings, and the result types functions return

All 114 entries

R Python CLI

R Python CLI

Getting Started
Features
Project Types
- Project Types
Reference

Getting Started
Features
Project Types
- Project Types
Reference

Project Management

project_list()

Registered projects, with columns id, path, and created.

Usage

project_list() -> pd.DataFrame

Contents

Usage

Framework for Python · version 0.1.0.dev6

R documentation CLI documentation Framework Public Cloud Source on GitHub

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