semvec/pypi-packages huggingface dataset:
cap-upload-validator 1.2.0
Python tool for validating H5AD AnnData files before uploading to the Cell Annotation Platform.
Requires Python: >=3.9

# cap-validator

[![PyPI version](https://img.shields.io/pypi/v/cap-upload-validator)](https://pypi.org/project/cap-upload-validator/)  [![License](https://img.shields.io/github/license/cellannotation/cap-validator)](https://github.com/cellannotation/cap-validator/blob/main/LICENSE)  [![Build Status](https://github.com/cellannotation/cap-validator/actions/workflows/unit_testing.yml/badge.svg)](https://github.com/cellannotation/cap-validator/actions)


## Overview

Python tool for validating H5AD AnnData files before uploading to the Cell Annotation Platform. The same validation code is used in [Cell Annotation Platform](https://celltype.info/) following requirements from the CAP-AnnData schema published [here](https://github.com/cellannotation/cell-annotation-schema/blob/main/docs/cap_anndata_schema.md).

## Features
- ✨ Validates all upload requirements and returns results at once
- 🚀 RAM efficient
- 🧬 Provides a full list of supported ENSEMBL gene IDs for *Homo sapiens* and *Mus musculus*


## Installation
```bash
pip install -U cap-upload-validator
```

## Usage

### Basic usage

```python
from cap_upload_validator import UploadValidator

h5ad_path = "path_to.h5ad"

uv = UploadValidator(h5ad_path)
uv.validate()
```

Full documentation could be found in [GitHub Wiki](https://github.com/cellannotation/cap-validator/wiki)

### CLI interface
```console
$ capval tmp/tmp.h5ad
CapMultiException: 
AnnDataMissingEmbeddings: 
        The embedding is missing or is incorrectly named: embeddings must be a [n_cells x 2] 
        numpy array saved with the prefix X_, for example: X_tsne, X_pca or X_umap.
        
AnnDataMisingObsColumns: 
            Required obs column(s) missing: file must contain 
            'assay', 'disease', 'organism' and 'tissue' fields with valid values.
        
For details visit: 
        https://github.com/cellannotation/cap-validator/wiki/Validation-Errors

$ capval --help
usage: capval [-h] adata_path

CLI tool to validate an AnnData H5AD file before uploading to the Cell Annotation Platform.
The validator will raise CAP-specific errors if the file does not follow the CAP AnnData Schema,
as defined in:
https://github.com/cellannotation/cell-annotation-schema/blob/main/docs/cap_anndata_schema.md

Full documentation, including a list of possible validation errors, is available at:
https://github.com/cellannotation/cap-validator/wiki

Usage Example:
    `capval path/to/anndata.h5ad`

positional arguments:
  adata_path  Path to the AnnData h5ad file.

optional arguments:
  -h, --help  show this help message and exit
```

## License
[BSD 3-Clause License](LICENSE)
textcleaner2305 1.0.0
A simple text cleaning library that converts text to clean word arrays
Requires Python: >=3.7

Your `README.md` for **TextCleaner** is off to a solid start—clear, well-organized, and functional. Below is an improved version with a few refinements to grammar, formatting, clarity, and overall polish. I also incorporated your authorship at the end, as you mentioned “my name Emmanuel.”

---

# TextCleaner

A simple Python library for cleaning text and converting it into arrays of clean, lowercase words.

## Installation

Install via pip:

```bash
pip install textcleaner
```

Or install from source:

```bash
git clone https://github.com/yourusername/textcleaner.git
cd textcleaner
pip install -e .
```

## Usage

```python
from textcleaner import clean

# Basic usage
result = clean("Hello, WORLD!! This is an example.")
print(result)
# Output: ['hello', 'world', 'this', 'is', 'an', 'example']

# More examples
print(clean("Python is AWESOME!!! Let's code..."))
# Output: ['python', 'is', 'awesome', 'let', 's', 'code']

print(clean("Remove @#$% special characters & numbers 123"))
# Output: ['remove', 'special', 'characters', 'numbers', '123']
```

## Features

* Converts text to lowercase
* Removes punctuation and special characters
* Tokenizes text into words
* Handles numbers as valid tokens
* Manages empty strings and edge cases gracefully
* Returns a clean list of words

## API Reference

### `clean(text)`

Cleans input text and returns a list of lowercase words.

**Parameters:**

* `text` (`str`): The input string to clean

**Returns:**

* `list`: A list of cleaned, lowercase words

**Example:**

```python
clean("Hello, World!")  
# Returns: ['hello', 'world']
```

## Contributing

Contributions are welcome! Here's how to get started:

1. Fork the repository
2. Create a feature branch:

   ```bash
   git checkout -b feature/amazing-feature
   ```
3. Commit your changes:

   ```bash
   git commit -m 'Add some amazing feature'
   ```
4. Push to your branch:

   ```bash
   git push origin feature/amazing-feature
   ```
5. Open a Pull Request

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

## Changelog

### Version 1.0.0

* Initial release
* Basic text cleaning functionality
* Word tokenization
* Punctuation and special character removal

---

**Author**: Emmanuel