semvec/pypi-packages huggingface dataset:
pyrecist 0.1.0
A package for evaluating RECIST criteria from CSV files
License: MIT
Requires Python: >=3.7

# pyrecist
A Python package for computing RECIST 1.1 assessments from lesion measurements stored in tabular format.

## Instalation

To install the package, run the following command in your terminal:

```bash
pip install pyrecist
```

## Features
- RECIST classification for each follow-up study based exclusively on **target lesions**.
- Evaluations are performed in chronological order based on study dates, assuming the first study is the baseline and all others are follow-ups.
- Once Progressive Disease (PD) is reached, subsequent classifications are marked as `None`. 
- Supports input in CSV format.
- **Not yet supported:**
    - Appearance of new lesions.
    - Evaluation of non-target lesions.

## Usage
The CLI script takes a `.csv` file containing RECIST measurements and generates an output `.csv` file with the corresponding classifications for each follow-up. 

For example, to evaluate the measurements on `example.csv` and save the results to `/home/example_user`, run:

```bash
pyrecist example.csv -o /home/example_user
```

You can test the package using the synthetic measurements available in the `tests/data` directory.

## Input format
The input should be a CSV file where each row represents a RECIST measurement taken from a study. The following five columns are **required**:

| Column header     | Type        | Description                                                  | Example        |
|-------------------|-------------|--------------------------------------------------------------|----------------|
| `patient_id`      | Integer     | Pseudonymized identifier of the patient             		 | `1`       	  |
| `study_date`      | String      | Date of the study in the format `YYYYMMDD`                   | `20190220`     |
| `measurement`     | Float       | RECIST measurement in `mm`                                   | `15.43` |
| `lesion_label_alias`| String    | Letter used as an alias to identify a lesion within a patient| `A` |
| `lesion_category`| String       | Lesion category (`target`, `non-target`)                     | `target` |

Run `pyrecist -h` to see how to customize the name of the expected column headers. For example, if your CSV file contain the measurements in a column called `recist_measurements`, then you can run:

```bash
pyrecist example.csv -o /home/example_user --measurement_header recist_measurements
```
PyDCSL 0.4.0
A compact Python tool to check if a Widevine device certificate (DCSL) is revoked or valid.
License: MIT
Requires Python: >=3.7

# PyDCSL 🛡️🔐  
*A compact Python tool to check if a Widevine device certificate (DCSL) is revoked or valid.*

## 📦 What is PyDCSL?
**PyDCSL** is a lightweight Python utility that interacts with a custom API to process **Widevine license components** — specifically `.wvd`, `client_id`, and `private_key` files — and fetch the corresponding DRM metadata.  
It acts as a tool for **DRM inspection**, metadata extraction, and license validation purposes. The tool provides both a command-line interface (CLI) and an importable Python module.

---

## ⚙️ Features

- 🧾 Accepts `.wvd`, `client_id`, and `private_key` inputs
- 🌐 Sends requests to a Widevine DCSL-compatible API
- 📊 Pretty-prints extracted metadata using `rich` (if available)
- 🧪 Supports both CLI and importable module
- 📁 Optionally saves results to a JSON file

---

## 🚀 Usage

### 🔧 Command-Line Interface

To get started with the CLI, simply run:

```bash
pydcsl -h
```

<img width="774" height="492" alt="CLI screenshot" src="https://github.com/user-attachments/assets/817e105f-c266-4381-89d9-12697c297ac7" />

---

## 📋 Output Example

Here’s an example of what the output looks like when you run the tool:

<img width="956" height="764" alt="Output example" src="https://github.com/user-attachments/assets/a36ec35a-11ec-43d6-be98-33eff5a5be92" />

## 🧾 License

This project is licensed under the **MIT License**. See the [LICENSE](./LICENSE) file for more details.

---

## ❗ Disclaimer

> This tool is intended for educational, debugging, and interoperability purposes only. Usage of Widevine-protected materials must comply with relevant laws and terms of service. The authors of this project do not condone or support illegal or unethical use.

---

## 🤝 Contributions

Contributions, fixes, and improvements are welcome! Feel free to open an issue or submit a pull request (PR).

---
KIB-LAP 0.4.3.7
A package for structural engineering calculations
License: MIT
Requires Python: >=3.6

# KIB Package
Berechnungstool für konstruktiven Ingenieurbau. In der derzeitigen Version sind verschiedene Berechnungstools enthalten:
- Betonbau: Bemessungstools für den konstruktiven Betonbau nach DIN EN 1992
- Plattenbeulen: Eigenwertermittlung von einfachen, rechteckigen Beulfeldern nach dem Ritz'schen Verfahren  für übliche Randlagerungen (Gelenkig, Frei, Eingespannt)
- Plattentragwerke: Berechnung linearer Plattentragwerke nach dem Ritz'schen Verfahren für übliche Randlagerungen (Gelenkig, Eingespannt)
- Querschnittswerte: Berechnungstool für die Berechnung der Querschnittswerte von dünnwandigen Querschnitten, inklusive der 
Ermittlung des Schubmittelpunkts und sekundärer Torsionskennwerte für nicht-wölbfreie Querschnitte
- STABRAUM: 3D Stabwerkprogramm mit Wölbkrafttorsion


## Betonbau