semvec/pypi-packages huggingface dataset:
persian-pdf-converter 2.3.1
persian_pdf_converter by Mahdi Ramazani is a Python package that converts PDF files to Word documents with OCR support for Persian and English. It automatically downloads and sets up necessary tools like Tesseract and Poppler.
Requires Python: >=3.6


```markdown
# persian_pdf_converter

A Python package for converting PDF files to Word documents and modifying URLs. This package utilizes Tesseract OCR for text recognition in PDF files.

## Features

- Convert PDF files to Word documents with text recognition
- Modify URLs based on directory paths

## Requirements

- Python 3.6 or higher
- Tesseract OCR installed and configured

## Installation

To install the package, use pip:

```bash
pip install persian-pdf-converter
```


## Usage

Here is an example of how to use the functions provided by this package:

```python
from persian_pdf_converter.pdf_converter import pdf_to_word

# Path to your PDF file and output directory
pdf_path = 'path/to/example.pdf'
output_dir = 'path/to/output/dir'

# Convert PDF to Word
output_file = pdf_to_word(pdf_path, output_dir, lang="fas+eng", dpi=300)
print(f"Converted file saved as: {output_file}")
```

### pdf_to_word Function

This function converts a PDF file to a Word document with text recognition.

#### Parameters:

- `pdf_path` (str): Path to the PDF file.
- `output_dir` (str): Directory where the output Word file will be saved.
- `lang` (str): Languages to be used by Tesseract for text recognition (default is `"fas+eng"`).
- Additional keyword arguments for `convert_from_path`.

#### Returns:

- `str`: Name of the output Word file.



## Development

To contribute to this project, follow these steps:

1. Clone the repository:
    ```bash
    git clone https://github.com/mahdiramezanii/persian_pdf_converter.git
    ```
2. Navigate to the project directory:
    ```bash
    cd persian_pdf_converter
    ```
3. Create a virtual environment and activate it:
    ```bash
    python -m venv venv
    source venv/bin/activate  # On Windows use `venv\Scripts\activate`
    ```
4. Install the dependencies:
    ```bash
    pip install -r requirements.txt
    ```
5. Make your changes and run tests.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for more details.

## Contact

If you have any questions or suggestions, feel free to contact me at [mahdiramazanii.official@gmail.com](mailto:mahdiramazanii.official@gmail.com).
eink-calendar 0.2.2
Shows Google Calendar events on an Inky Impression display
Requires Python: <4.0,>=3.10

# eInk Calendar

Displays Google Calendar events on an Inky Impression display connected to a
Raspberry Pi.

![Example showing how the UI looks](https://i.imgur.com/cKqnSmU.png)

## Installation

This project is available on PyPI and can be installed with `pipx`.

```bash
pipx install eink-calendar
```

Then, you will need to create a desktop OAuth2 client ID using the Google Cloud
console. For details on how to do this, see
[Google's Documentation][oauth2_client_docs].

Once you have created the client ID, download the client secret JSON file to
`~/.local/share/eink-calendar/credentials.json`.

Then, start the application:

```bash
eink-calendar
```

A browser window will automatically open prompting you to give eInk Calendar
read access to your calendars. Once this process completes, the application
will start. You only need to complete this process once.

## Development

If you want to develop without the eInk display connected, start the
application with the following flag:

```bash
eink-calendar --no-display
```

The generated images will be opened using your image viewer instead.

[oauth2_client_docs]: https://developers.google.com/identity/protocols/oauth2/native-app
django-package-boilerplate 0.1.3
A boilerplate Django app package for easy integration
Requires Python: >=3.6

# django-package-boilerplate
**Current version: 0.1.3**

Boilerplate for a Django Package

## 1. Installation

The preferred installation method is directly from pypi:

```bash
# Create promgen setting directory.
$ pip install -U django-package-boilerplate
```

## 2. Quickstart

In ``settings.py``:

```python
INSTALLED_APPS = [
    ...,
    'django_package_boilerplate'
]
```

2. In ``urls.py``:

```python
from django.urls import path, include

urlpatterns = [
    ...,
    path('django_package_app/', include('django_package_boilerplate.urls')),
]
```

3. Run ``python manage.py migrate``
Create the models.
```bash
$ python manage.py migrate
```

## 3. Configuration
- Language setting: Todo

## 4. Update Package

In ``setup.cfg``, upgrade version
```
[metadata]
name = django-package-boilerplate
version = x.x.x
...
```

Build package
```bash
$ python setup.py sdist bdist_wheel
```

Deploy package
```bash
$ twine upload --verbose dist/django-package-boilerplate-x.x.x.tar.gz
```

## The MIT License

Copyright (c) 2023 Runners Co., Ltd.

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
loan_amount_model_package 0.0.7
A model package to estimate loan amount suitable for a customer
Requires Python: <4.0,>=3.9

# LOAN AMOUNT PREDICTION  

A machine learning program that estimates the amount of loan to be issued as seen in the dataset given. This program uses a **simple hist gradient boosting regressor algorithm** to estimate the likely loan user should be eligible for.  

## Data set and its description  

| Data              | Description                            |
|-------------------|----------------------------------------|
| Loan_ID           | Unique loan request identifier         |
| Gender            | sex of the user                        |
| Married           | Marital status                         |
| Dependents        | Number of dependents                   |
| Education         | if the candidate is graduate or not    |
| Self_Employed     | if the user is working for himself     |
| ApplicantIncome   | total income of the candidate          |
| CoapplicantIncome | total income of the borrower's partner |
| LoanAmount        | Amount requested                       |
| Loan_Amount_Term  | in months                              |
| Credit_History    | 1(okay or eligible), 0(Not eligible)   |
| Property_Area     | nature of where the borrower live      |
| Loan_Status       | if loan was granted or not             |

## Dependencies and packages  

1. python = "^3.9"
2. numpy = "^1.26.4"
3. pandas = "^2.2.2"
4. pydantic = "^2.7.3"
5. scikit-learn = "^1.5.0"
6. strictyaml = "^1.7.3"
7. feature-engine = "^1.8.0"
8. joblib = "^1.4.2"
9. mlflow = "^2.13.2"
10. ipykernel = "^6.29.4"
11. hyperopt = "^0.2.7"
12. scipy = "^1.13.1"
13. loguru = "^0.7.2"

## Source code link  

Source code link:
[Github link](https://github.com/chibuikeeugene/loan-amount-prediction.git)

## Snapshots

![API Documentation 1](<Screenshot 2024-06-22 at 4.15.49 am.png>)
![API Documentation 2](<Screenshot 2024-06-22 at 4.16.43 am.png>)
![API Documentation 3](<Screenshot 2024-06-22 at 4.16.54 am.png>)
aiorubino 2.2
aiorubino is asynchronous Rubino API library in Python
Requires Python: >=3.6

# AIORubino
aiorubino is asynchronous Rubino API library in Python

### Install and update
```bash
pip install -U aiorubino
```

### Start
```python
from aiorubino import Client

client = Client("auth")

async def main():
    result = await client.get_my_profile_info()
    print(result.name)
    

client.run(main())
```

### Contributors
Contributions to the project are welcome! If you find any bugs or have suggestions for improvements, please open an issue or submit a pull request on GitHub.

### License
aiorubino is released under the MIT License. See the bundled [LICENSE](https://github.com/irvanyamirali/aiorubino/blob/main/LICENSE) file for details.