konvigius 0.0.4
Python library for managing application config objects with validation and a CLI parser included.
Requires Python: >=3.10
Keywords: config, configuration, validation, CLI

# Dynamic Configuration System with Validation and Metadata

This module provides a flexible and extensible system for defining, validating, and
managing configuration fields using metadata.


## Main Features

- Dynamic class creation with named fields (using the Schema object)
- Schema-based configuration definition using Schema and Option objects
- Builtin type and range/length validation, including mandatory-check (required)
- Support for custom defined validation functions
- Support for loading from dictionaries (e.g. parsed from JSON/YAML)
- Access to current config values and their metadata
- Serialization via `to_dict()` and `to_json()`
- Peek-into-utils  like `info_vars', 'get_meta` and more
- A Config object is an iterable (`for field, value in my_config: ...`)
- Suppport CLI out of the box, often no additional configuration needed
- Auto-generation of inverted-bool fields (e.g. --debug field ➡  --no-debug field)
- Support for auto generated fields by defining custom functions (e.g. --minutes ➡ --in-seconds)


## Example Usages

First you must create a list that contains so called Schema objects; a Schema oject
represents a typical configuration item such as:

- `--userrole`
- `--timeout`
- `--port`

A single Schema-object defines a single fieldname (like `--userrole`) and the associated
metadata of that field such as:

- field type (e.g. `int str float list set tuple`)
- default value (e.g. userrole `admin`)
- is-required (bool `True False`)
- domain (a  tuple)
- minimum value, length string or number of cells 
- maximum value, length string or number of cells 
- custom validation functions (raising exceptions)
- custom auto-field-creation functions
- help text for the field (to support CLI mode help info)
- short flag (single char names to support options in CLI mode)

Then you pass that schema with 1 or more Schema-objects as a list to the factory
function of the Config class; that produces a config object.

Here are some simple examples. The package also comes with a subdirectory (examples) 
containing more elaborate, working demo Python files. Each file includes a short manual.

``` python
schema = [
  Schema("debug", default=False, field_type=bool),
  Schema("timeout", default=5, r_min=1, r_max=60, field_type=int),
  Schema("userrole", field_type=str, domain=("guest", "admin", "tester")),
]

cfg_1 = Config.config_factory(schema)

print(cfg_1.timeout)       # 5
print(cfg_1.debug)         # False
print(cfg_1.no_debug)      # True   (auto generated config-var)
print(cfg_1.info_vars())   # markdown overview vars

cfg_1.timeout = 99       # raises ConfigRangeError
cfg_1.timeout = 'abc'    # raises ConfigTypeError
```

Now create an _additional_ new config instance using the _same schema_, but with a _different_ 
default value for the timeout option.

``` python
cfg_2 = Config.from_dict(schema, {'timeout': 10})

print(cfg_2.timeout)     # 10      (no longer 5 on initialization)
```

Force that timeout can only be a multiple of 5 (5, 10, 15...).
For that a custom validation function is used:

``` python
def fn_multiple_of_5(value, cfg):
    if values % 5 != 0:
        raise ConfigValidationError(
                "Value Must be a multiple of 5"

schema = [
  Schema("debug", default_value=False, field_type=bool),
  Schema("timeout", default=5, r_min=5, r_max=60, field_type=int),
         fn_validator=fn_multiple_of_5)
]

cfg = Config.config_factory(schema)
cfg.timeout = 33       # raises ConfigValidationError
```

Below is a example that demonstrates the auto-create field.
It creates derived fields for the values of the fields 'minutes' and 'num_spaces':

- cfg.spaces     : a string with spaces based on the value of field cfg.num_spaces
- cfg.in_seconds : the time in seconds based on the value of field cfg.minutes

``` python
@with_field_name('spaces')
def fn_spaces(value, cfg):
    return ' ' * cfg.num_spaces 

@with_field_name('in_seconds')
def fn_seconds(value, cfg):
    return 60 * cfg.minutes 

schema = [
    Schema("num_spaces|s", default=2, fn_computed=fn_spaces, field_type=int, help_text="Number of spaces."),
    Schema("minutes|m", default=5, fn_computed=fn_seconds, field_type=int, help_text="Duration in minutes"),
]

# Create a config instance
cfg = Config.config_factory(schema)

# Parse the CLI arguments from the terminal.

cli_parser.run_parser(cfg)

print("num-spaces", cfg.num_spaces)
print(f"spaces: '{cfg.spaces}'  (computed)")

print("minutes:", cfg.minutes)
print("seconds:", cfg.in_seconds, "  (computed)")

```

## Key Components

### Schema
    Defines metadata for a config field, including default value, type constraints,
    and optional numeric bounds or testing on length of 'sized' objects like str and
    list.
    A one or more Schema-objects are as a list passed to the config-factory which 
    produces a Config-instance with field properties according the Schema definitions.

### Option
    A Schema-object is in the Config object converted into an Option object.
    These objects contain the metadata from the Schema-objects and control the
    validators.

### Config
    The base class for config objects. Config instances are created dynamically using
    the `config_factory()` or `from_dict()` methods.


## Intended Use Cases

- Application configuration
- Plugin settings
- User preference systems
- Validated parameter schemas for dynamic interfaces