semvec/pypi-packages huggingface dataset:
bindr 0.1.1
Data binding
License: MIT License
Requires Python: >=3.6.0


# bindr

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Bind dictionary data into named tuples and dataclasses automatically
for typed attribute access throughout the rest of your codebase.

```python
from bindr import bind
from typing import Dict, List, NamedTuple
from yaml import safe_load

class Config(NamedTuple):
    class SMSServiceConfig(NamedTuple):
        host: str
        port: int
        username: str
        password: str

    class S3Config(NamedTuple):
        default_bucket: str
        default_region: str
        max_item_size: int

    support_emails: List[str]
    api_key: str
    timeout_ms: int
    pi: float
    sms_providers: List[SMSServiceConfig]
    s3_settings: S3Config
    accounts: Dict[str, str]

config = bind(Config, safe_load("config.yaml"))
config.s3_settings.max_item_size  # <-- int
```

## Installation

Bindr is developed on [GitHub](https://github.com/chrisrink10/bindr) and 
hosted on [PyPI](https://pypi.python.org/pypi/bindr). You can fetch Bindr 
using a simple:

```bash
pip install bindr
```

## Why does this exist?

Bindr is not meant to serve as a replacement for [12Factor](https://12factor.net/)
methodology. There are certain niche cases where you might want to read
in a structured file (such as JSON or YAML) and bind it directly to a
typed object outside of application configuration (as demonstrated in the
example above). In fact, application configuration created as a dictionary
(perhaps from environment variables) is still a valid use case for a bound 
object.

Bindr exists as an alternative to the automatic binding syntax offered
by [PyYAML](https://pyyaml.org/). The default object deserialization syntax
in PyYAML is a leaky abstraction. Declarative data formats such as YAML 
should not be concerned with the details of how objects are deserialized 
in your application code.

Objects generated via Bindr will give you typed objects that can be passed
around and verified by MyPy and hinted in PyCharm, which is a distinct
advantage over accessing multiple levels deep of nested dictionaries.

## License

MIT License