semvec/pypi-packages huggingface dataset:
pycountssu1 0.1.0
Toy Package for DSCI 524 that counts words in given text.
License: MIT
Requires Python: >=3.9

# pycountssu1

Toy Package for DSCI 524 that counts words in given text.

## Installation

```bash
$ pip install pycountssu1
```

## Usage


`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycountssu1` was created by Salva Umar. It is licensed under the terms of the MIT license.

## Credits

`pycountssu1` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
email_verification_task_ForagerAI 0.1.1
A FastAPI project for email verification.
License: MIT
Requires Python: >=3.11,<4.0

# Email Verification
## Description
This project is a FastAPI application designed to interact with the Hunter.io API. It provides functionality to verify email addresses and search emails by domain, with CRUD operations for managing the results. The application stores results in a local variable and is structured to demonstrate basic API interaction and data handling in FastAPI.

## Features
 - Email verification using Hunter.io API
 - Search for emails associated with a domain
 - CRUD operations for managing email verification results
 - Local storage of verification results
 - Asynchronous request handling

## Installation
Install this package using `pip`:

```bash
pip install email_verification_task_ForagerAI
```
Or install using poetry:
```bash
poetry add email_verification_task_ForagerAI
```
## Usage
After installation, you can use it like this:
```bash
import email_verification_task_ForagerAI
```

## API Endpoints
 - POST /verify-email: Verifies the email address.
 - POST /search-email: Search for email addresses by domain.
 - POST /email-results/: Create a result entry for an email address or domain.
 - GET /email-results/{identifier}: Retrieve a specific verification result by email or domain.
 - PUT /email-results/{identifier}: Update a specific verification result.
 - DELETE /email-results/{identifier}: Delete a specific verification result.

## Configuration
The application can be configured through environment variables. Here are the available configurations:

 - API_KEY: Your Hunter.io API key.

## Contributing
Contributions to this project are welcome. Please ensure to follow the code of conduct and coding standards of the project.
pycounts_sifan 0.1.0
Calculate word counts in a text file.
License: MIT
Requires Python: >=3.9

# pycounts_sifan

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_sifan
```

## Usage

`pycounts_sifan` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_sifan.pycounts_sifan import count_words
from pycounts_sifan.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_sifan` was created by Sifan Zhang. It is licensed under the terms of the MIT license.

## Credits

`pycounts_sifan` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts_sunrc 0.1.0
Calculate word counts in a text file!
License: MIT
Requires Python: >=3.9

# pycounts_sunrc

Calculate word counts in a text file!

## Installation

```bash
$ pip install pycounts_sunrc
```

## Usage

`pycounts` can be used to count words in a text file and plot results
as follows:

```python
from pycounts.pycounts import count_words
from pycounts.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_sunrc` was created by Ruocong Sun. It is licensed under the terms of the MIT license.

## Credits

`pycounts_sunrc` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).
pycounts_chen_test 0.1.0
calculate word counts in a text
License: MIT
Requires Python: >=3.9

# pycounts_chen_test

calculate word counts in a text

## Installation

```bash
$ pip install pycounts_chen_test
```

## Usage

`pycounts_chen_test` can be used to count words in a text file and plot results
as follows:

```python
from pycounts_chen_test.pycounts_chen_test import count_words
from pycounts_chen_test.plotting import plot_words
import matplotlib.pyplot as plt

file_path = "test.txt"  # path to your file
counts = count_words(file_path)
fig = plot_words(counts, n=10)
plt.show()
```

## Contributing

Interested in contributing? Check out the contributing guidelines. Please note that this project is released with a Code of Conduct. By contributing to this project, you agree to abide by its terms.

## License

`pycounts_chen_test` was created by Ben Chen. It is licensed under the terms of the MIT license.

## Credits

`pycounts_chen_test` was created with [`cookiecutter`](https://cookiecutter.readthedocs.io/en/latest/) and the `py-pkgs-cookiecutter` [template](https://github.com/py-pkgs/py-pkgs-cookiecutter).