semvec/pypi-packages huggingface dataset:
no-spark-in-my-home 1.0.4
Yet another Python package for data generation
Requires Python: >=3.7
Keywords: fake,data,generator

# Fake data generator

This package generates fake sql-like format data from predefined schema.
Data schema is defined using dataclasses. 

# Installation

`
python -m pip install no_spark_in_my_home
`

# Usage

```python
from datetime import datetime
from dataclasses import dataclass
from no_spark_in_my_home.src.generator import FakeDataGenerator


@dataclass
class Dataclass:
    item_id: int
    title: str
    date: datetime
    number: int
    
gen = FakeDataGenerator(
    Dataclass,
    limit=5,
)
spark_dataframe = gen.load()
spark_dataframe.show()
```

### ```FakeDataGenerator``` params:

- ```model```  - dataclass
- ```limit``` - number of records
- ```mask_per_field``` - dict with masks per field. 
Example: ```FakeDataGenerator(..., mask_per_field={"title": "A#### ###."})```
- ```range_per_field``` - dict with ranges per field. Example: ```FakeDataGenerator(..., range_per_field={"number": {"range": range(1, 10)}})```
- ```maxlength_per_field``` - dict with maxlengths for strings per field. Example: ```FakeDataGenerator(..., maxlength_per_field={"field_name": "title", "maxlength": 100, "fixed": True})```. ```fixed=True``` will generate strings with fixed length. ```fixed=False``` will generate strings with non-fixed, but limited lengths.
- ```config``` - path to config. Config should be yaml-formatted.
- ```lang``` - locale. Default - "en"
- ```foreign_keys``` - list of dicts that describes relations. Example: ```FakeDataGenerator(..., foreign_keys=[{"self_field": "item_id", "other_field": "another_item_id", "other_model": OtherDataclass, "other_data": other_dataclass_gen.load(as_dicts=True)}])```

### ```load``` params:

- ```where_clause``` - string with where-clause for post-filtering. Example: ```load(..., where_clause="item_id > 5 and number = 10")```
- ```as_json``` - if True returns generated data as json
- ```as_dicts``` - if True returns generated data as list of dicts

# Building your own package version

In case you want to build your own package version you should follow
this [guide](https://python-packaging-tutorial.readthedocs.io/en/latest/setup_py.html).

And then just build a wheel and install it.

# Making and publishing a new release

1. Update release version in pyproject.toml and setup.py
2. Build package with `python -m build`
3. Publish package with `twine upload dist/*`
pycvtools 0.0.4
A package to take for preprocessing the images and video.
Requires Python: >=3.6
Keywords: video,images,video2images,image crop

# pycvtools

[![forthebadge made-with-python](http://ForTheBadge.com/images/badges/made-with-python.svg)](https://www.python.org/)                 
[![Python 3.10](https://img.shields.io/badge/python-3.10-blue.svg)](https://www.python.org/downloads/)   

## Functionality of the pydlmodels

- Take image snaps from video 

## Usage

- To take snap from video/ camera and save it as .jpg
- To crop person from an image

```
pip install pycvtools
```
##### To run
```
from pycvtools import *
```
##### Functions
* vd2img for Video to image
* cam2img for camera to omage
* person_crop for detection of person from the image

## Note 
- Find detailed functionality on [pycvtools.phaf.in](http://pycvtools.phaf.in)
- Please drop your suggestions on pydev@phaf.in 

## More Information
- Visit [pycvtools.phaf.in](http://pycvtools.phaf.in)