semvec/pypi-packages huggingface dataset:
qc-syn 0.1.0
A quantum circuit synthesis environment for reinforcement learning
Requires Python: >=3.8

# Quantum Circuit Synthesis Environment for Reinforcement Learning

This project provides a quantum circuit synthesis environment for reinforcement learning. The environment is built on top of the Gymnasium framework.

## Installation

To install the environment, you need to have Python and pip installed on your system. If you don't have them installed, you can download them from the official Python website.

Once you have Python and pip installed, you can install the environment by running the following command in your terminal:

```sh
pip install qc_syn
```

## Usage

To create a new instance of the environment, you can use the `gym.make` function:

```python
import gymnasium as gym
import qc_syn

env = gym.make("qc_syn/QuantumCircuit-v0", qubit_count=4)
observation, info = env.reset()

for _ in range(1000):
    action = env.action_space.sample()  # agent policy that uses the observation and info
    observation, reward, terminated, truncated, info = env.step(action)

    if terminated or truncated:
        observation, info = env.reset()

env.close()
```

## Contributing

Contributions are welcome! Please feel free to submit a pull request.

## License

This project is licensed under the terms of the MIT license.
stockdatafetcher 0.1
A comprehensive data retrieval aimed at gathering financial information
Requires Python: >=3.6


# DataFetcher

Fetcher is a Python package designed for retrieving and preprocessing financial information. It gathers historical data for specified companies. The package leverages `yfinance` for financial data, `pandas` for data manipulation, and `requests` for web requests.

## Installation

Install Fetcher using pip:

```bash
pip install stockdatafetcher
```

## Quick Start

To use DataFetcher, import the `Fetcher` class and initialize it with the ticker symbol of the company you're interested in. For example:

```python
from datafetcher import Fetcher

# Initialize with a company ticker
df = Fetcher("AAPL")

# Fetch historical data
historical_data, actual_ticker = df.get_historical_data("AAPL")
print(historical_data)
```

## Dependencies

Fetcher requires the following Python packages:

- pandas
- yfinance
- requests

These dependencies will be automatically installed when you install Fetcher using pip.

## Contributing

Contributions to DataFetcher are welcome! If you have suggestions for improvements or bug fixes, please open an issue or submit a pull request.

## Reporting Issues

If you encounter any problems or have feedback, please open an issue on the project's GitHub page. Your input is valuable in making DataFetcher a better tool for everyone.

## License

DataFetcher is released under the [MIT License](LICENSE). See the LICENSE file for more details.