f40-toolkit 1.0.9

Shared config, logging, cache and common tooling for 40F services.

f40-toolkit

Shared configuration, logging, caching, and common utilities for 40F services.

f40-toolkit is a dependency-light Python package intended to provide a stable set of building blocks that multiple services can share without duplicating glue code.

It currently focuses on four areas:

• Config (f40_toolkit.config) — local single-file and layered config loading, env overrides, canonical key aliases, and optional remote config overlays from HTTP or S3-compatible object storage.
• Logging (f40_toolkit.logging) — opinionated logging setup with console / rotating-file handlers and channel-based level overrides.
• Cache (f40_toolkit.cache) — backend-agnostic cache manager with memory, file, and optional Redis backends.
• Common (f40_toolkit.common) — shared utilities used across the modules above.

Requirements

• Python 3.12+

Installation

Core package, with minimal dependencies:

pip install f40-toolkit

Optional extras:

# Marker extra for cache (memory/file backends; no extra dependency)
pip install f40-toolkit[cache]

# Redis backend support for cache
pip install f40-toolkit[cache-redis]

# YAML support for config loading
pip install f40-toolkit[config]

# S3-compatible remote config support
pip install f40-toolkit[config-s3]

# YAML + S3-compatible remote config support
pip install f40-toolkit[config,config-s3]

# Convenience install for all optional runtime features
pip install f40-toolkit[all]

What is included

f40_toolkit.config

The configuration subsystem is designed to let services use a homogeneous API while staying flexible about where configuration comes from.

Highlights:

• single-file mode via <PREFIX>CONFIG_PATH
• layered mode via <PREFIX>CONFIG_DIR, <PREFIX>PROJECT, and <PREFIX>ENV
• deep env var overrides with __
• canonical key aliases for migrations
• optional remote overlay support from:
  • HTTP/HTTPS
  • S3-compatible object storage (for example Scaleway object storage)
• optional mirrored remote layered loading

Typical usage:

from f40_toolkit.config import get_config

cfg = get_config()
include_system = cfg.get("ops.include_system_in_health", False)

f40_toolkit.logging

Logging is explicit and does not configure itself at import time.

Highlights:

• console + file logging configuration helpers
• channel-based level overrides
• session-aware loggers
• safe defaults for service startup

f40_toolkit.cache

The cache module provides a common cache API that can be backed by different storage implementations.

Highlights:

• memory backend
• file backend
• optional Redis backend
• cache key helpers
• simple observability / health-check support
• get_or_set(...) convenience flow

f40_toolkit.common

Shared helpers used by the rest of the toolkit, including:

• env parsing
• deep merge / dict helpers
• config redaction for logging
• small filesystem / path helpers

Quickstart

Configuration

Minimal usage:

from f40_toolkit.config import configure_global_config, get_config

configure_global_config()
cfg = get_config()

port = cfg.get("server.port", 8080)

Using canonical keys during a migration:

from f40_toolkit.config import configure_global_config, get_config

CANONICAL_KEYS = {
    "server.port": ["server.backend_port", "server_settings.port"],
}

configure_global_config(canonical_keys=CANONICAL_KEYS)

cfg = get_config()
port = cfg.get_canonical("server.port", default=8080)

Logging

from f40_toolkit.logging import configure_logging, get_logger

configure_logging()
log = get_logger("service.startup", channel="service")
log.info("Service booted")

Cache

from f40_toolkit.cache import create_cache_from_config, InvalidCacheValue

cfg = {
    "env": "prod",
    "service": {"name": "billing"},
    "customer": "acme",
    "cache": {
        "backend": "memory",      # "memory" | "file" | "redis"
        "default_timeout": 300,
        "serializer": "json",
    },
}

cache = create_cache_from_config(cfg)
cache.set("example", {"ok": True}, timeout=60)

try:
    value = cache.get("example")
except InvalidCacheValue:
    value = None

print(value)

Memoization helper:

def expensive(a: int, b: int) -> int:
    return a + b

value = cache.get_or_set(
    key="sum:1:2",
    func=expensive,
    f_args=[1, 2],
    timeout=120,
)

Configuration conventions

By default the config loader uses the F40_ env prefix.

Important env vars:

• F40_CONFIG_PATH — enables single-file mode
• F40_CONFIG_EXTRA — optional extra files appended after local config
• F40_CONFIG_DIR — root directory for layered mode
• F40_PROJECT — project name for layered mode
• F40_ENV — environment / stage for layered mode

F40_CONFIG_EXTRA uses the platform path separator:

• Linux / macOS: :
• Windows: ;

Deep env var overrides use __ as a path separator:

export F40_DB__HOST="db.internal"
export F40_SERVER__PORT="8080"
export F40_FEATURES__0__NAME="beta"

Those can be read back with the same dotted path style:

cfg.get("features.0.name")

Remote config

Remote config is bootstrapped from local config and/or environment variables.

Supported remote providers:

• http
• s3

Supported remote modes:

• overlay
• mirrored_layers

Example HTTP overlay bootstrap:

[remote_config]
enabled = true
provider = "http"
mode = "overlay"
url = "https://example.internal/config/my-service.toml"

Example S3-compatible overlay bootstrap:

[remote_config]
enabled = true
provider = "s3"
mode = "overlay"
bucket_name = "service-config"
object_path = "my-service/prod.toml"
endpoint_url = "https://s3.fr-par.scw.cloud"
region_name = "fr-par"
access_key_env = "SCW_ACCESS_KEY"
secret_key_env = "SCW_SECRET_KEY"

Effective precedence is:

1. local main file or local layered files
2. local extra files from <PREFIX>CONFIG_EXTRA
3. remote overlay or remote mirrored layers
4. env var overrides

Env vars always win.

Development

Editable install:

pip install -e .[dev]

Run checks:

pytest
ruff check .
mypy src

Local documentation

The repository includes Markdown docs under docs/.

They can be:

• read directly in the repository
• served locally with MkDocs

To run a local docs site:

pip install -e .[docs]
mkdocs serve

Building and publishing

Build artifacts:

python -m build

Validate distribution metadata and README rendering:

twine check dist/*

Upload with Twine:

twine upload dist/*

Recommended release checks before upload:

• verify the package version in pyproject.toml
• confirm README.md reflects the current extras and module behavior
• inspect the wheel / sdist contents to ensure repo-only folders such as tools/ are not included
• run twine check dist/*

License

MIT. See LICENSE.