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Lakehouse Observability Platform

Project description

Lakefront

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


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.

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

Project Structure

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

Changelog

v0.4.0 (2026-04-22)

Feat

  • data profile is presented on source selection
  • enable ai powered data source exploration
  • cli: add configuration profile delete and demo commands
  • add anthropic section to configuration model

Fix

  • analyzer mishandles bool types
  • typo on app title

Refactor

  • move data profiling and llm code to analyzer module
  • move data profiling code from tui to core.analyzer
  • split core.main responsibilities across submodules
  • core

v0.3.4 (2026-04-20)

Fix

  • tui: rebuild source list after attach and detach

v0.3.3 (2026-04-19)

Feat

  • add commitizen for automated changelog and versioning

Fix

  • Add a timeout for S3 source path existence check
  • Project init ignores sources if unable to reach them or their existence check fails

v0.3.0 (2026-04-19)

Feat

  • Add support for attaching S3 sources to a project

v0.2.2 (2026-04-18)

Feat

  • Local sources 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)

Refactor

  • core,cli: moving around and renaming things

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