semvec/pypi-packages huggingface dataset:
chemnames 0.2.1
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Requires Python: >=3.11

# ChemNames

A CLI utility to retrieve chemical data (SMILES, InChI, Full Names) from PubChem and map Compound names to their corresponding identifiers.

## Installation

This package is managed with standard Python tools and can be installed via `pip`.

1. Clone the repository.
2. Install the package in editable mode (or normal mode):

```bash
pip install .
```

Or using `uv` to manage the environment:

```bash
uv pip install .
```

After installation, the CLI tool `addchemnames` will be available in your path.

## Usage

### 1. Retrieve Chemical Data

The main utility reads a CSV file containing a `Compound` column, queries PubChem, and outputs a new CSV with added `SMILES`, `InChI`, and `Full Name` columns.

**Input CSV Format:**
The input file **MUST** contain a column named `Compound`.

Example `input.csv`:
```csv
Compound,ID
Aspirin,1
Caffeine,2
```

**Run the command:**

```bash
addchemnames input.csv output.csv
```

**Output:**
The tool will generate `output.csv` with the enriched data. If a compound is not found, "xxxxxx" will be used as the placeholder.

### 2. Add KEGG IDs

If you have a CSV file that already contains PubChem CIDs (e.g., from a previous step or source), you can use `add_keggs.py` (located in the root of the repository) to append KEGG IDs.

**Run the command:**

```bash
python add_keggs.py input_with_cids.csv output_with_keggs.csv
```

## Notes

- **Network Requests**: This tool makes network requests to PubChem. Large files may take some time to process.
- **Rate Limiting**: The tool uses threading to speed up requests, but be mindful of PubChem's usage policies.
- **Data Accuracy**: Data is fetched "as is" from PubChem.

## License

MIT
ase-protocol 1.2.0
Agent Settlement Extension (ASE) Protocol
Requires Python: >=3.8

# ASE Reference Implementation

This directory contains the Python reference implementation of the Agent Settlement Extension (ASE) protocol.

## Overview

The reference implementation provides:

1. **Core Message Processing** - Serialization, deserialization, and validation
2. **Cryptographic Services** - Signing, verification, and key management
3. **Framework Adapters** - Integration with LangChain and AutoGPT

## Contributing

When extending the reference implementation:

1. Follow snake_case for internal Python code
2. Use Pydantic Field aliases for camelCase JSON output
3. Add property-based tests for new functionality
4. Document extension points and interfaces
5. Maintain backward compatibility
SimpleITK-SimpleElastix 3.0.0a1.post183
SimpleITK is a simplified interface to the Insight Toolkit (ITK) for image registration and segmentation
Requires Python: >=3.8
Keywords: SimpleITK, ITK, InsightToolkit, segmentation, registration, medical imaging, image processing, computer vision, DICOM

Important notice
================

This is an unofficial build of SimpleITK where SimpleElastix is enabled. The codebase is unmodified except for the output package name.

This release is provided by Francesco Santini <francesco.santini@unibas.ch> and is unaffiliated with SimpleITK, The Insight Software Consortium, or NumFOCUS.

Please find the official release at https://github.com/SimpleITK/SimpleITK.

The build script for linux can be found at https://gist.github.com/fsantini/25074839adf5eb089c62d3a00e30e299


Original copyright notice
-------------------------

The SimpleITK project is part of the Insight Software Consortium(ISC) a non-profit educational consortium dedicated to promoting and maintaining open-source, freely available software for bio-medical image analysis. The copyright is held by NumFOCUS. The SimpleITK software is distributed under the Apache License 2.0.