semvec/pypi-packages huggingface dataset:
tiingo-fetcher 0.1.1
Fetch large amounts of historical stock data from Tiingo for free.
Requires Python: >=3.7

# 📈 Tiingo Fetcher - A Python Library for Fetching Market Data

## 📌 About
`tiingo_fetcher` is a **lightweight Python library** that allows users to **fetch large amounts of historical stock data** for free using the **[Tiingo API](https://www.tiingo.com/)**.

Unlike other APIs that limit minute-level data to **7 days**, **Tiingo Fetcher** allows you to retrieve **up to 9 years** of minute, hourly, and daily data efficiently.

---

## 📦 Installation
You can install the package using `pip`:

```bash
pip install tiingo-fetcher
```

---

## 🔑 Setup: Get a Tiingo API Key
To use this package, you need a **Tiingo API key**:
1. **Sign up for a free Tiingo account**: [https://www.tiingo.com/](https://www.tiingo.com/)
2. **Generate your API key** from the **Account → API Section**.
3. **Use the API key directly in your script** (no `.env` file is required).

---

## 🚀 Usage
### **1️⃣ Fetching Historical Stock Data**
You can fetch stock data by calling `fetch_data()` and passing the **stock symbol, API key, start date, end date, and frequency**:

```python
from tiingo_fetcher.fetch_data import fetch_data

data = fetch_data("AAPL", "your_api_key_here", "2023-01-01", "2023-02-01", "1min")

print(data.head())
```

### **Parameters:**
- `symbol` (**str**) - Stock ticker symbol (e.g., "AAPL").
- `api_key` (**str**) - Your **Tiingo API Key** (must be provided directly in the function call).
- `start_date` (**str**) - Start date in `YYYY-MM-DD` format.
- `end_date` (**str**) - End date in `YYYY-MM-DD` format.
- `freq` (**str**) - Frequency (**'1min', '5min', '15min', '30min', '60min', 'daily'**).

---

## 🏗 Project Structure
```
tiingo_fetcher/
├── tiingo_fetcher/         # Package folder
│   ├── __init__.py         # Marks it as a package
│   ├── fetch_data.py       # Core data-fetching logic
├── example_usage/          # Example scripts
│   ├── test.py             # Example usage script
├── README.md               # Documentation
├── setup.py                # Package setup
├── requirements.txt        # Dependencies
```

---

## 🔧 Troubleshooting
### **"ModuleNotFoundError: No module named 'tiingo_fetcher'"**
- Ensure the package is installed:
  ```bash
  pip install --upgrade tiingo-fetcher
  ```
- If running locally, try:
  ```bash
  python -m example_usage.test
  ```

---

## 📜 License
This project is licensed under the **MIT License**. You are free to use, modify, and distribute it.

---

## ⭐ Support
If you find this project useful, consider giving it a ⭐ on GitHub!
pybelt 1.2.4
An Python library to control the feelSpace naviBelt from your application
Requires Python: >=3.3

# pyBelt

PyBelt is a Python library to control the feelSpace naviBelt from your application. The feelSpace naviBelt is a device that provides tactile feedback using vibration motors located in a belt. The naviBelt can be controlled by an application via Bluetooth Low-Energy or USB.

The naviBelt can be used in various domains, for instance:
* navigation applications, 
* VR, 
* simulation, 
* research experiments that require tactile feedback,
* outdoor and video-games,
* applications that require tactile feedback to improve focus or attention.

## Installation

```
pip install pybelt
```

## Documentation

* [pyBelt documentation](https://github.com/feelSpace/pybelt/blob/main/docs/README.md)
* Developer page (coming soon)


## About feelSpace

* Learn more about feelSpace at [www.feelspace.de](https://www.feelspace.de/?lang=en)

## Copyright and license notice

Copyright 2020, feelSpace GmbH.

Licensed under the Apache License, Version 2.0: http://www.apache.org/licenses/LICENSE-2.0

**Note on using feelSpace Trademarks and Copyrights:**

*Attribution:* You must give appropriate credit to feelSpace GmbH when you use feelSpace products in a publicly disclosed derived work. For instance, you must reference feelSpace GmbH in publications, conferences or seminars when a feelSpace product has been used in the presented work.

*Endorsement or Sponsorship:* You may not use feelSpace name, feelSpace productsâ€™ name, and logos in a way that suggests an affiliation or endorsement by feelSpace GmbH of your derived work, except if it was explicitly communicated by feelSpace GmbH.
omop 0.2.1
OMOP Common Data Model [`source <https://github.com/laminlabs/omop/blob/main/omop/models.py>`__].

# OMOP: OMOP Common Data Model

OMOP (Observational Medical Outcomes Partnership) is a common data model (CDM) that standardizes the structure and content of disparate healthcare data for large-scale observational research.
This schema models the OMOP data model accurately allowing for validation of OMOP modeled data.

More about OMOP can be found at the [OHDSI website](https://ohdsi.org) and on the [OMOP GitHub](https://github.com/OHDSI/CommonDataModel).