semvec/pypi-packages huggingface dataset:
fakers 0.5.0
A package that provides ready-made objects of fake-data.
Requires Python: >=3.6

# `fakers` Library
***
- __Author:__ Ashish Garg
- __Year of release:__ 2024
- __Description:__
This generates pre-built container objects filled with fabricated data.

<p align="center">
  <b>Embrace the art of deception with our library—where faking it means making it!</b>
</p>


## How it helps?
***
If you need fake data that is structured in groups of fields, it typically requires additional time and effort. The `fakers` library solves this problem & saves you that extra time by providing pre-structured grouped fake data.


## Version History
***
| Version        | Release                         | Description                                                                |
|----------------|---------------------------------|----------------------------------------------------------------------------|
| 0.5.0          | Latest release - (01 Apr, 2024) | Module `temperature device` available (no support for spark and pandas df) |
| 0.1.0 to 0.4.0 | Initial releases                | Fake objects related to two modules were released - `Retail` and `Person`. |

## Module description
***
### Temperature Device
***
This module provide you with the sensor device data particularly for temperature sensor. You can 
generate single or multiple sensors.

__Example:__ <br>
```python
import fakers

sensor = fakers.TemperatureDevice.fake_device()
fake_sensors = fakers.TemperatureDevice.fake_devices_event_pack(4)
fake_sensor_event = fakers.TemperatureDevice.fake_device_event_pack()
fake_sensors_event = fakers.TemperatureDevice.fake_devices_event_pack(5)
```

### Retail
***
This contains the fake objects related to the retail data and with relationship. For example:
```python
import fakers

order = fakers.Retail.fake_order()
fifteen_orders = fakers.Retail.fake_orders(15)
user = fakers.Retail.fake_user()
ten_users = fakers.Retail.fake_users(10)
sale = fakers.Retail.fake_sale()
three_sales = fakers.Retail.fake_sales(3)
product = fakers.Retail.fake_product()
two_products = fakers.Retail.fake_products(2)
```

### Person
***
This contains the fake objects related to the Person module. For example:
```python
import fakers

fake_person = fakers.Person.fake_person()
fake_persons = fakers.Person.fake_persons(10)
fake_address = fakers.Person.fake_address()
fake_addresses = fakers.Person.fake_addresses(100)
```

## Good to have features
***
💡 You can convert these objects directly to `Pandas` and `pyspark` dataframes. At present this is enabled
only for two modules: `Person` & `Retail`. 

The functions you use for it are:
1. `to_pandas`
2. `to_spark`

Exmaple:

```python
import fakers
import pandas as pd

fake_user = fakers.Retail.fake_user()
fake_user_df = fake_user.to_pandas()
```