semvec/pypi-packages huggingface dataset:
shinu 0.0.2
High-performance Rust-based media compression for Python and FastAPI
Requires Python: >=3.10

// README.md
# Shinu

**Shinu** is a blazing-fast, memory-safe media compression library written in Rust with Python . It supports compressing **images**, **videos**, **audio**, and **PDFs** with customizable quality settings.

## 🚀 Features

- 📷 **Images** — JPEG, PNG, WebP, AVIF, BMP, TIFF, GIF, ICO
- 🎞️ **Videos** — MP4, AVI, MKV (via FFmpeg)
- 🎵 **Audio** — MP3, WAV, OGG, etc. (via FFmpeg)
- 📄 **PDFs** — Compressed using Ghostscript
- 🧠 **Memory-safe**, **fast**, and built in Rust
- ✅ Per-media configurable compression settings
- 🔌 Easy integration into Python & FastAPI apps

---
## Install
```bash
pip install shinu
```

## Usage in Python
```python
from shinu import compress_file, CompressorConfig

config = CompressorConfig()
config.quality = 0.7
config.pdf_quality = "ebook"
config.image_format = "png"
config.image_colorspace = "rgb"
config.audio_bitrate = "128k"
config.video_crf = 28

output = compress_file("input.pdf", config)
print(output)
```
najrono 0.0.8
Django library for managing **Jalali (Persian) dates** in your models
Requires Python: >=3.6

# Najrono

Najrono is a Django library for managing **Jalali (Persian) dates** in your models, with built-in **caching capabilities** for optimized data access. The name "Najrono" is inspired by the combination of "Najla" and "Chrono" (referring to time), reflecting its focus on elegant time management.

---

## Features

<!-- - **Jalali DateField**: A custom field for handling Jalali dates in Django models.
- **Built-in Caching**:
  - **Today**: Logs for the current day.
  - **Current Month**: Aggregated data for the current month.
  - **Current Year**: Aggregated data for the current year.
  - **Past Years**: Static cache for previous years.
- **Efficient Querying**: Combines cached data with database queries for the most recent updates.
- **Easy Integration**: Plug-and-play setup for Django projects. -->

---

## Installation

Install Najrono using pip:

```bash
pip install najrono
```

---

## Quick Start

### 1. Add Najrono to Installed Apps

Add `najrono` to your Django project's `INSTALLED_APPS`:

```python
INSTALLED_APPS = [
    ...
    'najrono',
]
```

### 2. Use JalaliDateField in Your Models

<!-- Define your model with the `JalaliDateField` and use `CacheableModelMixin` for caching:

```python
from najrono.models import CacheableModelMixin, JalaliDateField
from django.db import models

class Log(CacheableModelMixin, models.Model):
    user = models.ForeignKey("auth.User", on_delete=models.CASCADE)
    jalali_date = JalaliDateField()

    def __str__(self):
        return f"Log for {self.user} on {self.jalali_date}"
``` -->

### 3. Fetch Logs with Caching

<!-- Use the built-in caching methods to fetch logs efficiently:

```python
from myapp.models import Log

user = User.objects.get(id=1)

# Retrieve cached logs
logs = Log.get_cached_logs(user)

print("Logs for today:", logs["today"])
print("Logs for this month:", logs["month"])
print("Logs for this year:", logs["year"])
print("Logs for past years:", logs["past_years"])
```

--- -->

## Configuration

<!-- Najrono provides default cache timeouts that you can customize in your Django settings:

```python
NAJRONO_CACHE_TIMEOUTS = {
    "today": 60 * 60 * 2,       # 2 hours
    "month": 60 * 60 * 24 * 7,  # 1 week
    "year": 60 * 60 * 24 * 30, # 1 month
    "past_years": None,        # Permanent
}
``` -->

--- 

## Requirements

- Python 3.8+
- Django 3.2+

---

## License

Najrono is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.

---

## Contributing

Contributions are welcome! Feel free to submit a pull request or open an issue to discuss potential changes or improvements.

---

## Acknowledgments

Najrono is inspired by the need for a robust and efficient system to handle Jalali dates and caching in Django projects. Special thanks to the Django community for their continuous support.

---

## Contact

For questions or feedback, please contact [TahaM8000@gmail.com].
nvidia-srl-base 1.6.0
SRL Python base package. Contains base classes, basic types, general tools, and developer utilities.
Requires Python: >=3.7
Keywords: docker

# SRL Python Base Package

<h4>
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/base/">Homepage</a> (
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/base/getting_started.html">Getting Started</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/base/package_info.html">Package Info</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/base/contributing.html">Contributing</a> |
    <a href="https://srl.gitlab-master-pages.nvidia.com/py/base/api.html">API Reference</a> )
</h4>

This package provides abstract base classes (ABCs), a standard SRL base class that includes logger functionality, common types & enums, and basic helper tools.

See the [documentation](https://srl.gitlab-master-pages.nvidia.com/py/base/) for detailed information.

## Quick Start

**Installation**

Use pip to install this Python distribution from the PYPI package registry (https://pypi.org/project/nvidia-srl-base/).

```
pip install nvidia-srl-base
```
dicom-ecg-plot 1.3.5
Plot Dicom ECG Waveforms

[logo]: https://raw.github.com/marcodebe/dicomecg_convert/master/images/logo.png
![ECG Dicom Convert][logo]

# Dicom ECG plot
A python tool to plot Dicom ECG.

The DICOM file can also be specified as `studyUID seriesUID objectUID` and 
retrieved from your WADO server.

Github repository: [here](https://github.com/marcodebe/dicomecg_convert)

**THE PROGRAM IS DISTRIBUTED IN THE HOPE THAT IT WILL BE USEFUL, BUT WITHOUT ANY WARRANTY OF ANY KIND.**


## Online demo
**[demo site](https://ecg.galliera.it)** 
You can convert your own DICOM files or use preloaded sample files from different modality models.

## Install
```bash
python3 -m venv ecg
. ecg/bin/activate
pip install dicom-ecg-plot
```

## Usage of `dicom-ecg-plot` tool
```bash
dicom-ecg-plot <inputfile> [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot <stu> <ser> <obj> [--layout=LAYOUT] [--output=FILE|--format=FMT] --minor-grid
dicom-ecg-plot --help
```
Examples:
```bash
dicom-ecg-plot anonymous_ecg.dcm -o anonymous_ecg.pdf
dicom-ecg-plot anonymous_ecg.dcm --layout 6x2 --output anonymous_ecg.png
dicom-ecg-plot anonymous_ecg.dcm --format svg > anonymous_ecg.svg
```

The input can be a (dicom ecg) file or the triplet `studyUID, seriesUID,
objectUID`. In the latter case dicom file is downloaded via
[WADO](http://medical.nema.org/Dicom/2011/11_18pu.pdf).

If `--output` is given the ouput format is deduced from the extension of the `FILE`.
If the output file is not given `--format` must be defined.
Supported output formats are: eps, jpeg, jpg, pdf, pgf, png, ps, raw, rgba, svg, svgz, tif, tiff.

By default the 5mm grid is drawn, `--minor-grid` add the minor grid (1mm).

The signals are filtered using a lowpass (40 Hz)
[butterworth filter](http://en.wikipedia.org/wiki/Butterworth_filter) 
of order 2.

`LAYOUT` can be one of: 3x4\_1 (that is 3 rows for 4 columns plus 1 row), 3x4, 6x2, 12x1 (default: 3x4_1).
New layouts can be defined adding the corresponding matrix in LAYOUT dictionary in `config.py`.



## References
 * http://medical.nema.org/Dicom/supps/sup30_lb.pdf
 * http://dicomlookup.com/html/03_03PU.html#LinkTarget_229354
 * http://libir.tmu.edu.tw/bitstream/987654321/21661/1/B09.pdf
 * [Mortara ECG Conformance Statement](http://www.mortara.com/fileadmin/user_upload/global/Products/Healthcare/DICOM/ELI%20Electrocardiographs%20DICOM%20Conformance%20Statement.pdf)