alfig-py 0.1.1

Unified config library — TOML, JSON, YAML, and CONF interchangeably

A config library that lets you use TOML, JSON, YAML, and .conf files interchangeably,
with a single canonical schema, validation, and automatic format conversion.

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Install

pip install alfig-py
# With optional format support:
pip install alfig-py[yaml]   # adds PyYAML
pip install alfig-py[toml]   # adds tomli-w (for writing TOML)
pip install alfig-py[all]    # everything

Python 3.11+ includes tomllib for reading TOML. For writing TOML, tomli-w is required.

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Quick Start

from alfig import Alfig

# Define your schema once
schema = {
    "database": {
        "host": str,
        "port": int,
        "user": str,
        "password": (str, "secret"),   # (type, default)
    },
    "features": {
        "enable_logging": bool,
        "max_threads": (int, 4),
    },
}

# Create instance
config = Alfig(schema)

# Load from any supported format — auto-detected by extension
config.load("settings.yaml")   # or .json, .toml, .conf, .ini

# Validate against schema (fills in defaults for optional fields)
config.validate()

# Access values with dot-notation
db_host = config.get("database.host")
threads = config.get("features.max_threads")   # → 4 (default)

# Modify values
config.set("features.max_threads", 16)

# Save to any format
config.save("settings.json")
config.save("settings.toml")
config.save("settings.conf")

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Schema Reference

Definition	Meaning
"field": str	Required string field
"field": int	Required int field
"field": bool	Required bool field
"field": float	Required float field
"field": list	Required list field
"field": dict	Required dict field
"field": (str, "x")	Optional string, default "x"
"field": (int, 0)	Optional int, default 0
"section": {...}	Nested section

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Supported Formats

Format	Extension	Read	Write	Notes
JSON	.json	✓	✓	Built-in
YAML	.yaml .yml	✓	✓	Requires PyYAML
TOML	.toml	✓	✓	Read: tomllib (builtin 3.11+) / tomli; Write: tomli-w or toml
CONF	.conf .ini	✓	✓	Custom parser (see below)

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CONF Format — Nested Sections

The .conf format uses dot-notation section headers for nesting:

# settings.conf

[database]
host = localhost
port = 5432
enabled = true

[database.replica]
host = replica.local
port = 5433

[features]
max_threads = 8
tags = ["web", "api"]

This maps to the same dict as the equivalent JSON:

{
  "database": {
    "host": "localhost",
    "port": 5432,
    "enabled": true,
    "replica": {
      "host": "replica.local",
      "port": 5433
    }
  },
  "features": {
    "max_threads": 8,
    "tags": ["web", "api"]
  }
}

Auto-coercion rules (all CONF values are strings at parse time):

Raw value	Python type
true / false	bool
42	int
3.14	float
["a", "b"]	list
{"x": 1}	dict
everything else	str

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API Reference

Alfig(schema=None)

Create a config instance. schema is optional — omit it to skip validation.

.load(path, format=None) → self

Load from a file. Format auto-detected from extension unless overridden.

.loads(text, format) → self

Load from a raw string.

.load_dict(data) → self

Load directly from a Python dict.

.validate() → self

Validate against schema, filling defaults. Raises ValidationError on failure.

.get(key_path, default=None) → value

Read a value with dot-notation: config.get("database.host").

.set(key_path, value) → self

Write a value with dot-notation. Creates intermediate dicts as needed.

.delete(key_path) → self

Remove a key.

.as_dict() → dict

Return a deep copy of the internal data.

.save(path, format=None) → self

Save to a file. Format auto-detected from extension unless overridden.

.dumps(format) → str

Serialize to a string in the given format.

Alfig.convert(input_path, output_path, ...) (static)

Convert a file from one format to another without instantiating Alfig.

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CLI

# Convert between formats
alfig convert settings.toml --to json
alfig convert settings.yaml --to conf --out app.conf

# Validate / inspect a file
alfig validate settings.yaml
alfig validate settings.yaml --verbose   # prints parsed JSON

# Read a single value
alfig get settings.yaml database.host

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Project Structure

alfig/
├── __init__.py        # Public API
├── core.py            # Alfig class
├── schema.py          # Validation engine
├── cli.py             # CLI entry point
└── formats/
    ├── __init__.py    # Format registry
    ├── json_fmt.py
    ├── yaml_fmt.py
    ├── toml_fmt.py
    └── conf_fmt.py    # Custom nested INI parser

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License

MIT © dominionthedev

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