lakefront 0.3.3

Lakehouse Observability Platform

Lakefront

A terminal-based lakehouse observability platform for exploring and managing data sources from your command line.

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About

Working with lakehouse data — Parquet files on local disk or S3, DuckDB queries, materialized views — usually means jumping between tools, writing throwaway scripts, or wrestling with heavyweight UIs. Lakefront puts it all in one place: a fast TUI and CLI for data engineers who live in the terminal.

Problems it solves:

• No single tool for lakehouse exploration — Lakefront combines DuckDB-powered SQL querying, S3 source management, and dataset browsing in one cohesive interface.
• Configuration sprawl — profiles let you switch between environments (local dev, staging, production S3) with a single command, keeping credentials out of your scripts.
• Context switching — instead of firing up a Jupyter notebook or a GUI just to peek at a Parquet file, you stay in the terminal.

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Examples

Initialise Lakefront

Bootstrap the ~/.lakefront directory structure and create a default profile:

uv run lakefront init

Config Management

# List all profiles
uv run lakefront config list

# Show config directories and paths
uv run lakefront config info

# Create a new profile
uv run lakefront config create --profile staging

# Inspect a profile's current settings
uv run lakefront config inspect --profile staging

# See which profile is active
uv run lakefront config get-active

# Switch to a different profile
uv run lakefront config set-active --profile staging

Secrets (S3 access keys etc.) can be written to the TOML profile or set via environment variables instead:

export LAKEFRONT_S3__ACCESS_KEY=...
export LAKEFRONT_S3__SECRET_KEY=...

Project Management

Projects are the top-level organisational unit in Lakefront. Each project lives in its own directory under ~/.lakefront/projects/ and can be pinned to a config profile.

~/.lakefront/projects/
└── my-project/
    ├── project.toml      ← metadata + pinned profile
    └── results/          ← analysis outputs

# List all projects
uv run lakefront projects list

# Create a new project
uv run lakefront projects create my-project -d "EDA on S3 parquet" -p staging

# Inspect a project
uv run lakefront projects inspect my-project

# Delete a project (prompts for confirmation)
uv run lakefront projects delete my-project
uv run lakefront projects delete my-project --yes

Source Management

Data sources are attached to a project and point to a local path or S3 prefix.

# Add a source
uv run lakefront projects source add -p my-project -n raw -k s3 --path s3://bucket/raw/
uv run lakefront projects source add -p my-project -n local -k local --path /data/parquet/

# Remove a source
uv run lakefront projects source remove -p my-project -n raw

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Project Structure

src/
├── core/   # config models, settings, project & source service
├── cli/    # Typer entrypoint and sub-commands
└── tui/    # Textual TUI app (in progress)

Changelog

v0.3.3 (2026-04-19)

Fix

• push and commit automation
• use annotated tag to ensure push with --follow-tags

v0.3.2 (2026-04-19)

Fix

• tag still not pushed

v0.3.1 (2026-04-19)

Fix

• workflow glitches
• unable to parse pyproject.toml

v0.3.0 (2026-04-19)

Feat

• add commitizen for automated changelog and versioning

Fix

• cz command not found

v0.2.2 (2026-04-18)

Feat

• s3 support; added util.fs
• source can be attached to and detached from a project during runtime (#4)
• tui: basic source navigation and query execution
• core: can attach and query csv, parquet and parquet datasets (#3)
• tui: preliminary layout
• core: project context registers sources for querying (#2)
• wip: project lifecycle management (#1)

Fix

• unable to connect to s3

Refactor

• core,cli: moving around and renaming things