semvec/pypi-packages huggingface dataset:
datacraft-xeger 0.1.1
Custom xeger type extensions for datacraft package
License: MIT

datacraft-xeger
===============

Custom plugin for [datacraft](https://datacraft.readthedocs.io/en/latest) to generate values using regular expressions.
Uses the [rstr](https://github.com/leapfrogonline/rstr) package. `xeger` is regex backwards. Inspiration from the 
original Java Package [xeger](https://code.google.com/archive/p/xeger/).

## Usage in Specs

You can use the `xeger` as a type in your datacraft data specs. See example:

```json
{
  "ssn":{
    "type": "xeger",
    "data": "\\d{3]-\\d{2}-\\d{4}"
  }
}
```

```shell
$ datacraft -s xeger.json -i 3 --format json-pretty -x -l error
[
    {
        "ssn": "322-81-1469"
    },
    {
        "ssn": "697-21-8178"
    },
    {
        "ssn": "340-78-5377"
    }
]
```


## Custom Regex Types

Users can make use of the datacraft_xeger module to create custom datacraft value suppliers with regex patterns. The 
example below shows how to register custom types for different country phone number patterns.

```python
import datacraft
import datacraft_xeger.suppliers as xeger

phone_patterns = {
    # type_name: pattern
    'uk-phone': r'\+44 \d{4} \d{6}',
    'aus-phone': r'\+61 4\d{2} \d{3} \d{3}',
    'nz-phone': r'\+64 \d{2} \d{4} \d{4}',
    # ...
}


@datacraft.registry.types('uk-phone')
def _custom_regex_uk_phone(spec, loader):
    return xeger.xeger_supplier(phone_patterns['uk-phone'])


@datacraft.registry.types('aus-phone')
def _custom_regex_aus_phone(spec, loader):
    return xeger.xeger_supplier(phone_patterns['aus-phone'])


@datacraft.registry.types('nz-phone')
def _custom_regex_nz_phone(spec, loader):
    return xeger.xeger_supplier(phone_patterns['nz-phone'])
```

Once registered these types can be used as part of the data generation process.  See the example data spec:

```json
{
  "name": ["ann", "bob", "carl"],
  "age": { "type":  "rand_int_range", "data":  [25, 75]},
  "phone": {
    "type": "weighted_ref",
    "data": {
      "UK": 0.5, "AUS": 0.3, "NZ": 0.2
    }
  },
  "refs": {
    "UK": { "type": "uk-phone" },
    "AUS": { "type": "aus-phone" },
    "NZ": { "type": "nz-phone" }
  }
}
```

Running datacraft against this spec and using the custom code loading feature:

```shell
datacraft -s custom.json -c custom.py -i 3 --format json-pretty -x -l warn
[
    {
        "name": "ann",
        "age": 67,
        "phone": "+64 07 2500 7403"
    },
    {
        "name": "bob",
        "age": 49,
        "phone": "+61 435 126 947"
    },
    {
        "name": "carl",
        "age": 61,
        "phone": "+44 7693 148185"
    }
]
```