semvec/pypi-packages huggingface dataset:
python-capital 0.2.2
A simple wrapper for capital.com exchange API
License: MIT
Requires Python: >=3.7

# Welcome to python-capital


This is an unofficial Python wrapper for the [Capital.com Public API v1](https://open-api.capital.com/).  
I am in no way affiliated with Capital.com, use at your own risk.

If you came here looking for the [Capital.com exchange](https://capital.com/) to invest in CFDs, then [go here](https://capital.com/).  
If you want to automate interactions with Capital.com, stick around.

**Source code:**  
https://github.com/

## Features

- Simple handling of authentication
- Password encryption end-to-end
- Response exception handling
- Positions opening/closing
- Market prices and sentiment

## Quick Start

[Register an account with Capital.com](https://capital.com/).

[Generate an API Key](https://capital.com/trading/platform/?popup=settings&tab=APISettings).

To use the Demo accounts, pass `demo=True` when creating the client (default is set to `False`).

```bash
pip install python-capital.com
```

```python
from capital.client import Client

client = Client(username, api_key, api_password)

# get all open positions
positions = client.all_positions()

# to create a position
order = client.create_position(epic, direction, size)

# to close a position
close = client.close_position(deal_id)
```
SecureMorph 2025.12.20172640
The new package is designed to process text inputs related to advanced security concepts, such as secrets erasure upon observation. It utilizes structured pattern matching to interpret user instructio
License: MIT
Requires Python: >=3.9

# SecureMorph

SecureMorph is a Python package designed to process and validate text inputs related to advanced security protocols, such as secrets erasure upon observation. It utilizes structured pattern matching with regex to interpret user instructions, verify system behaviors—including formal verification results—and produce clear, structured summaries of the security mechanisms involved. This tool enables organizations to automate the validation, documentation, and analysis of complex security models, ensuring sensitive information remains protected under specified observable conditions through verified and repeatable procedures.

## Installation

Install SecureMorph via pip:

```bash
pip install SecureMorph
```

## Usage

Here's an example of how to use SecureMorph in your Python projects:

```python
from SecureMorph import SecureMorph

# Example input string
user_input = "Verify that secrets are erased when observed."

# Call the function
result = SecureMorph(user_input)

# Output the extracted data or verification results
print(result)
```

### Customizing the Language Model

SecureMorph defaults to using the ChatLLM7 model from `langchain_llm7`, which can be installed from [PyPI](https://pypi.org/project/langchain-llm7/). You can also pass your own LLM instance if desired:

```python
from langchain_llm7 import YourCustomLLM

my_llm = YourCustomLLM()
result = SecureMorph(user_input, llm=my_llm)
```

### API Keys and Rate Limits

For higher rate limits or access to the LLM7 API, you can:

- Set your API key as an environment variable `LLM7_API_KEY`.
- Or pass it directly in the function call:

```python
result = SecureMorph(user_input, api_key="your_api_key_here")
```

You can obtain a free API key by registering at [https://token.llm7.io/](https://token.llm7.io/).

## Configuration

- The default LLM is ChatLLM7 from `langchain_llm7`.
- You may specify a different LLM instance for custom integrations.
- The API key must be provided for API access if not using the default setup.

## Issues

For bugs, feature requests, or support, please open an issue on GitHub:  
[https://github.com/yourusername/SecureMorph/issues](https://github.com/yourusername/SecureMorph/issues)

## Author

Eugene Evstafev  
Email: hi@euegne.plus

## License

This project is licensed under the MIT License.
rust-string-analyzer 2025.12.20172044
A new package that leverages structured pattern matching to analyze and provide guidance on how to effectively incorporate String and &str types in Rust APIs. It receives user input about Rust code or
License: MIT
Requires Python: >=3.9

# Rust String Analyzer

Rust String Analyzer is a Python package designed to assist developers in analyzing Rust code related to string handling, particularly focusing on the use and best practices of `String` and `&str` types in Rust APIs. It leverages structured pattern matching with large language models to process user inputs, identify key coding patterns, and generate comprehensive guidance to improve code clarity, safety, and efficiency.

## Features

- Analyzes user-provided Rust code snippets or descriptions.
- Identifies common patterns and pitfalls in string handling.
- Provides structured recommendations and insights.
- Emphasizes best practices for Rust API design involving string types.

## Installation

You can install Rust String Analyzer via pip:

```bash
pip install rust-string-analyzer
```

## Usage Example

Here's how to use the package in your Python code:

```python
# Import and invoke the main function to process user input:
from rust_string_analyzer import rust_string_analyzer

# Example user input about Rust string handling:
user_input = "How do I safely convert &str to String in Rust?"

# Call the analyzer:
results = rust_string_analyzer(user_input)

# Print the analysis results:
for result in results:
    print(result)
```

## Contributing

Contributions are welcome! Feel free to open issues or submit pull requests to improve the package.

## Issues

If you encounter any bugs or have feature requests, please report them here:

[GitHub Issues](https://github.com/yourgithubrepo/issues)

## Author

Eugene Evstafev  
Email: hi@euegne.plus

## License

This project is licensed under the MIT License. See the LICENSE file for details.