lcl-fastapi

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lcl-fastapi is a small Python 3.14+ service framework combining FastAPI with lclang==1.0.10 configuration, logging, CLI infrastructure, and Snowflake IDs. Write business routes, a trusted .lclcfg file, and an optional business lifespan. The framework owns worker startup, request IDs, health sampling, local operations, and bundled offline Swagger UI.

Version 0.3.0 provides use_lcl_frame() for nested configuration scopes and uncaught_exception_handler for custom HTTP error responses with detailed default traceback logging, plus managed background_workers on dedicated threads and event loops. Background registration forces one API worker. See the application reference and composed example.

Install version 0.3.0 with python -m pip install lcl-fastapi==0.3.0 in a Python 3.14 virtual environment. See the release process for version notes, publication requirements, and artifact verification.

Start a service

New to the framework? Follow Build a product catalog service from scratch for a complete step-by-step project with configuration, routes, logging, verification, and deployment preparation.

Use a Python 3.14+ virtual environment. Install the built artifact with python -m pip install path/to/lcl_fastapi-0.3.0-py3-none-any.whl. Dependencies must also be installed; offline Swagger means that documentation serving does not require a CDN after installation.

Save this application as app.py in your downstream project:

from lcl_fastapi import LclFastAPI, get_logger

service = LclFastAPI()


@service.get("/hello")
async def hello() -> dict[str, str]:
    logger = await get_logger(__name__)
    logger.info("hello requested")
    return {"message": "hello"}

Save service.lclcfg alongside it:

__LCL_VERSION__: 1
app.name: "example-service"
app.version: "1.0.0"
app.target: "app:service"
server.host: "127.0.0.1"
server.port: 8080
server.workers: 1
logger.file.default.directory: "./logs"
logger.file.controller.filename: f"{app.name}.controller.log"
logger.file.service.filename: f"{app.name}.{worker_pid}.log"
logger.level: "INFO"

From that project directory, run:

lcl-fastapi serve -o config service.lclcfg

Open http://127.0.0.1:8080/hello, /health, or /docs in a browser. Swagger's JavaScript, stylesheet, favicon, and OpenAPI schema are served locally. Its remote validator is disabled. Responses normally carry a newly generated X-Request-ID; incoming client IDs do not replace it. If the upstream generator cannot issue an ID because of clock rollback or exhaustion, the response is 503 without a fabricated ID and the access log marks the failure. Business logs automatically include the current ID, and each worker writes its own file.

Run operations in another terminal using the same configuration file:

lcl-fastapi status -o config service.lclcfg
lcl-fastapi logs -o config service.lclcfg
lcl-fastapi stop -o config service.lclcfg

The CLI follows lclang.cli syntax: -c/--config and the existing -o config select the service file. Any setting can be overridden, for example -o server.port "LCL[9000]"; CLI values take precedence over the file. status and logs always return JSON. Add your own pyproject.toml console command with catalog = "lcl_fastapi.cli:run_cli", or wrap run_cli to supply a default configuration. See the CLI reference. Configuration supports native using, including using f"{lcl_fastapi_defaults}" to extend the bundled defaults. Controller lifecycle events and worker request logs use separate filename patterns under the shared log directory. Log paths are the most recently published live-worker observations, so rollover updates are eventually consistent. Stop uses a local control token and waits for graceful termination, including business teardown and logger flush.

Application and deployment boundaries

Windows uses Uvicorn with automatically installed Winloop; Linux uses Gunicorn to manage ASGI workers. You run the same lcl-fastapi serve command on both. Only 127.0.0.1 and 0.0.0.0 are accepted listener addresses; the default is loopback. Nginx can provide external HTTPS and port forwarding, and systemd is optional. The render commands produce files without installing them or running deployment commands.

Business Routers own their prefixes. There is no api.prefix setting. server.root_path is optional external origin metadata such as https://api.example.com:8443; it does not add a route prefix or set ASGI root_path. Nginx's actual listener/TLS fields remain independent because a public origin may describe an upstream proxy or port mapping.

The supported deployment scope is one service per machine. Configure separate machines' Snowflake worker-ID ranges through LCL's environment-variable support. Concurrent worker leases do not promise unlimited historical ID uniqueness across crashes or rapid reuse. Do not edit configuration while the service is running: a replacement worker reads the changed file while older workers retain their original values. Use a complete externally managed restart for consistent changes. Development Python reload is available with serve -o config service.lclcfg -o hot_reload; configure one or more server.reload_dirs in the file. Reload forces one worker and warns if the configured count is higher. See the runtime contract. There is no configuration watching, snapshot distribution, or restart API.

User routes with the same HTTP method and exact path override built-in routes. Overriding health or documentation replaces those defaults; overriding POST /_lcl/shutdown can prevent the local stop command from working. The default shutdown route is absent from OpenAPI and blocked by generated Nginx configuration. There is no business authentication, management port, HTTP log endpoint, or log streaming feature.

Documentation

The reference pages below own the public contracts. The development plan maps those contracts to acceptance requirements; AGENTS.md governs engineering policy.

Two independent downstream projects demonstrate the installed public package: minimal service and composed Router, configuration, and lifespan. GitHub Actions builds the current source wheel, then installs that artifact and each example in a separate environment on Windows/Uvicorn and Linux/Gunicorn. Each run checks service availability, business and built-in HTTP APIs, all CLI commands, and graceful shutdown. The example projects are excluded from the wheel.

• Application and lifespan
• Managed background workers
• Configuration
• Request logging
• Health and observations
• CLI reference
• Windows runtime and Linux runtime
• Nginx rendering and systemd rendering
• Runtime ownership and state
• Development plan and acceptance requirements
• Implemented feature inventory and engineering checks

The Python package is MIT-licensed. Bundled Swagger UI retains its Apache 2.0 license and third-party notices; see asset provenance.