semvec/pypi-packages huggingface dataset:
tobii-recorder 0.1.2
A Python wrapper for Tobii Eye Tracker data recording

# Tobii Eye Tracker Data Recorder Python Wrapper - UEF Course Edition

This project provides a Python interface for collecting data from Tobii Eye Trackers, specifically designed for educational purposes at the University of Eastern Finland (UEF). It includes a Python bindings for Tobii SDK, allowing for efficient data collection and easy integration into Python-based research and applications within the course context.

## Educational Purpose and Usage Restrictions

**IMPORTANT:** This software is exclusively for educational use by enrolled participants of the eye-tracking course at UEF.

- Usage is strictly limited to the duration of the course.
- All collected data must be deleted after the course concludes.
- Compliance with these regulations is mandatory during all phases of software usage.

If you have any questions or concerns about the license agreement or data retention policies, please contact your course instructors or teaching assistants.

## Installation

To install this package, use pip:

```
pip install tobii_recorder
```

## Usage

After installation, you can import and use the EyeTracker class in your Python scripts. For example:

```python
from tobii_recorder import EyeTracker

# Usage example will be provided by your course instructor
```

Detailed usage instructions and examples will be provided during the course.

## License

This project is protected under a proprietary license. See the `LICENSE` file for full terms and conditions.

## Support

For inquiries about licensing, permissions, or any questions related to the use of this software within the course, please contact your course instructors or teaching assistants at the University of Eastern Finland.

---

Remember: This software is a learning tool. Use it responsibly and ethically, adhering to all course guidelines and data protection principles.
vscode-cli-helpers-open-file 0.1.13
Open files (with templates) in VSCode from the command line
Requires Python: <4.0,>=3.10

## vscode-cli-helpers-open-file

- Command line script to open a file in VS Code

## Documentation

See [hakonhagland.github.io/vscode-cli-helpers-open-file/](https://hakonhagland.github.io/vscode-cli-helpers-open-file/)

## PyPI

See [vscode-cli-helper-open-file](https://pypi.org/project/vscode-cli-helpers-open-file/)
drug-repurposing-extract 0.2.3
Library for automatic generation of drug repurposing data

# Project Description for drug-repurposing-extract

This is a Python package for drug repurposing data extraction. You can use it to retrieve and analyze data related to specific compound IDs (CIDs) for potential drug repurposing.

## Installation

You can install the package using `pip`:

```bash
pip install drug-repurposing-extract
```
# Usage

## Import the package

```bash
import drug_repurposing
from drug_repurposing import get_data
```

## Generate CSV File from CID List

### To generate a CSV file from a list of CIDs (Compound IDs), you can use the generate_data_from_list function:

```bash
get_data.generate_data_from_list([942, 1070])
```

## Generate CSV List from Uploading a CSV File of CID List

### You can also generate a CSV file from a list of CIDs by uploading a CSV file containing the CID list. Here's how you can do it in a Google Colab environment:

```bash
from google.colab import files
import io
import pandas as pd

uploaded = files.upload()
uploaded_file = list(uploaded.values())[0]
df = pd.read_csv(io.BytesIO(uploaded_file))
data = df["cid"].values

get_data.generate_data_from_list(data)
```

## Predicting the CIDs Data

### To predict data based on CIDs, you can follow these steps:

Make sure you have a CSV file (e.g., complete_data.csv) generated from the previous steps.

Read the CSV file using pandas:

```bash
import pandas as pd
df = pd.read_csv("complete_data.csv")
```

Use the predict_data function to perform predictions:

```bash
get_data.predict_data(df)
```