semvec/pypi-packages huggingface dataset:
nerva-py 1.1.1
Python bindings for the JSON RPC interface of the Nerva (XNV) cryptocurrency.
Requires Python: >=3.10
Keywords: bindings, cryptocurrency, json-rpc, nerva, python

# Nerva (XNV) Python Library

[![Ruff](https://github.com/sn1f3rt/nerva-py/actions/workflows/ruff.yml/badge.svg)](https://github.com/sn1f3rt/nerva-py/actions/workflows/ruff.yml)
[![Build](https://github.com/sn1f3rt/nerva-py/actions/workflows/build.yml/badge.svg)](https://github.com/sn1f3rt/nerva-py/actions/workflows/build.yml)

## Table of Contents

- [About](#about)
- [Installation](#installation)
    * [Requirements](#requirements)
    * [Setup](#setup)
- [Documentation](#documentation)
- [Support](#support)
- [License](#license)

## About

Python bindings for the JSON RPC interface of the [Nerva (XNV)](https://nerva.one/) cryptocurrency.

## Installation

### Requirements

- Python 3.10+
- [`uv`](https://docs.astral.sh/uv/) (for development only)

### Setup

To install current latest release you can use following command:
```sh
pip install nerva-py
```

To install the latest development version you can use following command:
```sh
uv add git+https://github.com/Sn1F3rt/nerva-py.git --branch main
```

## Documentation

Developers please refer to the docstrings in the code for more information. Full API reference will be available soon.

Here is a simple example to get you started:

```python
import asyncio

from nerva.daemon import Daemon


async def main():
    daemon = Daemon(
        host="localhost",
        port=17566,
        ssl=False,
        username="rpcuser", # omit if daemon was not started with the rpc-login flag
        password="rpcpassword" # omit if daemon was not started with the rpc-login flag
    )

    print(await daemon.get_info())


asyncio.run(main())
```

## Support

- [Issues](https://github.com/sn1f3rt/nerva-py/issues)
- [Discord](https://discord.gg/ufysfvcFwe) - `Development > #nerva-py`

## License

[![License](https://img.shields.io/github/license/sn1f3rt/nerva-py)](LICENSE)

Copyright &copy; 2024-present [Sayan "sn1f3rt" Bhattacharyya](https://sn1f3rt.dev)
densitty 1.0.0
densitty - create textual 2-D density plots, heatmaps, and 2-D histograms in Python
Requires Python: >=3.10
Keywords: densitty, ascii, ascii-art, plotting, terminal, Python

<h1 align="center">densitty</h1>
<h2 align="center">Terminal-based 2-D Histogram, Density Plots, and Heatmaps in Python</h2>

Generate 2-D histograms (density plots, heat maps, eye diagrams) similar to [matplotlib's hist2d](https://matplotlib.org/stable/gallery/statistics/hist.html "hist2d"), but with output in the terminal, and no external dependencies.

![Plot Output](https://billtompkins.github.io/densitty/docs/inline-histplot2d.png "example output image")

## [Examples/Gallery](https://billtompkins.github.io/densitty/docs/examples.html)

## [Usage Notes](https://billtompkins.github.io/densitty/docs/usage.html)

## [Color, Size, and Glyph Support](https://billtompkins.github.io/densitty/docs/terminal_support.html)

## [API](https://billtompkins.github.io/densitty/docs/api.html)

## [GitHub](https://github.com/BillTompkins/densitty/tree/main)
typestats 0.0.0.dev0
Type annotation coverage statistics for Python packages
Requires Python: >=3.14

# typestats

A tool to analyze the type annotation coverage of Python projects on PyPI.

## Pipeline

For a given project:

1. Query PyPI for the latest version
2. Download the latest (non-yanked) sdist, and extract it
3. TODO: If there exists a `types-{project}` or `{project}-stubs` package on PyPI, repeat steps
   1-2 for that package, and merge the stubs into the main package source tree.
4. Compute the import graph using `ruff analyze graph`
5. Topologically sort the import graph to get a linear order of `.py` and `.pyi` files
6. For each file in sorted order, parse the file using `libcst`, and extract:
   - all annotatable global symbols and their type annotations
   - the `__all__` exports (if defined)
   - TODO: the imports (module imports, module aliases, object mappings, alias mappings)
   - TODO: type aliases (`_: TypeAlias = ...` and `type _ = ...`)
   - TODO: type-ignore comments (`# (type|pyright|pyrefly|ty): ignore`)
   - TODO: overloads
7. TODO: Inline type aliases where used in annotations (so we can determine the `Any`-ness)
8. TODO: Unify `.py` and `.pyi` annotations for each symbol
9. TODO: Filter out any of the non-public symbols (requires following imports)
10. TODO: Collect the type-checker configs (to see which strictness flags are used and which
    type-checkers it supports)
11. TODO: Compute various statistics:
    - coverage (% of public symbols annotated)
    - strict coverage (% of public symbols annotated without `Any`)
    - average overload ratio (function without overloads counts as 1 overload)
    - supported type-checkers + strictness flags
      annotation kind (inline, bundled stubs, typeshed stubs, third-party stubs, etc)
12. TODO: Export the statistics for use in a website/dashboard (e.g. json, csv, or sqlite)

## Implementation details

All IO (HTTP requests, subprocesses, file IO, etc) is performed asynchronously using `anyio` and
`httpx` (over HTTP/2). This way we effectively get pipeline parallelism for free (i.e. by doing
other things while waiting on IO, instead of blocking).
Use free-threading for best performance (e.g. use `--python 3.14t` with `uv`).
dagster-evidence 0.2.0
Dagster integration with evidence.dev
Requires Python: <3.14,>=3.10

# dagster-evidence

Dagster integration with [Evidence](https://evidence.dev/), enabling you to orchestrate Evidence.dev dashboard projects as Dagster assets.

![architecture](./docs/component-architecture.excalidraw.png)
## Installation

```bash
# Basic installation
uv add dagster-evidence

# With specific data source support
uv add "dagster-evidence[duckdb]"           # DuckDB support
uv add "dagster-evidence[bigquery]"         # BigQuery support
uv add "dagster-evidence[gsheets]"          # Google Sheets support
uv add "dagster-evidence[github-pages]"     # GitHub Pages deployment

# Install multiple extras
uv add "dagster-evidence[duckdb,bigquery,github-pages]"
```

## Features

- **Automatic asset discovery**: Automatically generates Dagster assets from Evidence project sources
- **Build and deployment**: Builds Evidence projects and deploys them to your hosting platform
- **Customizable translation**: Extend the translator to customize how Evidence sources map to Dagster assets
- **Type-safe configuration**: Pydantic-based configuration with YAML support
- **Source change detection**: Optional sensors to detect changes in upstream data sources

## Supported Data Sources

- DuckDB
- MotherDuck
- BigQuery
- Google Sheets

Need additional source types? You can extend the translator to add custom sources, or contribute to the project!

## Deployment Support

**Currently Implemented:**
- GitHub Pages: Deploy to GitHub Pages with automatic git push
- Custom commands: Run any custom deployment script or command

**Need another deployment target?** Open an issue and tag [@milicevica23](https://github.com/milicevica23) with your deployment requirements.

## Quick Start

### Component Configuration (YAML)

```yaml
# defs.yaml
type: dagster_evidence.EvidenceProjectComponentV2
attributes:
  evidence_project:
    project_type: local
    project_path: ./my-evidence-project
    enable_source_assets_hiding: true
    enable_source_sensors: false
    project_deployment:
      type: github_pages
      github_repo: my-org/my-dashboard
      branch: gh-pages
```

## Advanced Usage

### Custom Translator

You can customize how Evidence sources are translated to Dagster assets:

```python
from dagster_evidence import DagsterEvidenceTranslator, EvidenceSourceTranslatorData
import dagster as dg

class MyTranslator(DagsterEvidenceTranslator):
    def get_asset_spec(self, data):
        if isinstance(data, EvidenceSourceTranslatorData):
            # Custom logic for source assets
            return dg.AssetSpec(
                key=dg.AssetKey(["custom", data.query.name]),
                kinds={"evidence", data.source_content.connection.type},
            )
        return super().get_asset_spec(data)
```


## Contributing

Contributions are welcome! Please see the main repository's contribution guidelines.
slidemovie 0.4.0
Markdown and PowerPoint to narration video generator
Requires Python: >=3.8
Keywords: powerpoint, markdown, video, tts, presentation, automation

# slidemovie

[![PyPI version](https://badge.fury.io/py/slidemovie.svg)](https://badge.fury.io/py/slidemovie)
[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT)
[![Documentation](https://img.shields.io/badge/docs-github.io-blue)](https://sekika.github.io/slidemovie/)

**Markdown and PowerPoint to Narration Video Generator.**

`slidemovie` is a Python tool that automates the creation of professional narration videos. By combining the structural simplicity of **Markdown**, the design capabilities of **PowerPoint**, and the power of **AI Text-to-Speech**, you can produce high-quality videos without any video editing software.

---

## 📚 Documentation

**For full tutorials, installation guides, and configuration details, please visit:**

👉 **[https://sekika.github.io/slidemovie/](https://sekika.github.io/slidemovie/)**

---

## ✨ Features

*   **Markdown-Based**: Write your slide content and narration script in a single text file.
*   **AI Narration**: Automatically generates natural voiceovers using **Google Gemini**, **OpenAI** or **Azure** (via `multiai-tts`).
*   **PowerPoint Integration**: Use PowerPoint's AI "Designer" to create professional visuals instantly.
*   **No Video Editing**: Audio and visuals are automatically synchronized.
*   **Incremental Builds**: Only regenerates changed slides to save time and API costs.

## 🎥 Demo

**Watch a video generated entirely by slidemovie:**
[https://www.youtube.com/watch?v=9ZscwE06Pbo](https://www.youtube.com/watch?v=9ZscwE06Pbo)

## 🚀 Quick Start

### 1. Install

```bash
pip install slidemovie
```

*Note: You also need to install **FFmpeg**, **Pandoc**, **LibreOffice**, and **Poppler**, and set up your **AI API Key** (Google or OpenAI). See the [documentation](https://sekika.github.io/slidemovie/installation/) for details.*

### 2. Create a Project

Create a Markdown file (e.g., `demo.md`):

```markdown
# Slide Title

- Bullet point 1
- Bullet point 2

::: notes
This text will be read aloud by the AI narrator.
:::
```

### 3. Generate Slides

Convert Markdown to a draft PowerPoint file:

```bash
slidemovie demo -p
```

Open `demo.pptx` in PowerPoint, apply a design, and save it.

### 4. Build Video

Generate the final video with AI narration:

```bash
slidemovie demo -v
```

The output will be saved in `movie/demo/demo.mp4`.

## 📄 License

MIT License
qrtransfert 1.0.2
Transfert a single file using QRCodes
Requires Python: >=3.9
Keywords: qrcode, qr, tranfert, file, pentesting

# QRTransfert
Transfert a single file using QRCodes.

### Requirements
This package requires Python 3

### Installing
To install this CLI tool you can run the below command
```bash
pip3 install qrtransfert
```

### How to use

#### Transfert a single file using QRCodes

```bash
$ qrtransfert encode --help
Usage: qrtransfert encode [OPTIONS]

  Transfert a single file using QRCodes

Options:
  -f FILENAME                     Path of a single file to transfert
                                  [required]
  -c, --qr-color                  Use color QRCode to increase by 3 the data
                                  content in a QRCode
  -t, --terminal                  Display QRCode in terminal
  -qmax, --qr-max-version INTEGER RANGE
                                  Maximun version of the QRCode to generate
                                  
  -qcor, --qr-correction [l|m|q|h]
                                  Define the error correction level for the
                                  QRCode
  -l, --loop-delay FLOAT          Set the loop rotation delay for the QRCodes
                                  in seconds
  -ww, --window-width INTEGER     Width of the windows to display QRCodes
  -wh, --window-height INTEGER    Height of the windows to display QRCodes
  -o, --out-to-file TEXT          Output filename
  --help                          Show this message and exit.
```

#### Decode a video file with QRCodes info a single file

```bash
$ qrtransfert decode --help
Usage: qrtransfert decode [OPTIONS]

  Decode a video file with QRCodes info a single file

Options:
  -f TEXT                         Path of a movie file to decode  [required]
  -ct, --correction-threshold INTEGER RANGE
                                  Image correction threshold
  -fps, --fps-to-decode INTEGER RANGE
                                  Desired fps for decode QRCode
  -d, --debug                     Only display QRCode to adjust the threshold
                                  variable
  --help                          Show this message and exit.
```
modelbaker 2.4.3
The full model baker core
Requires Python: >=3.7

<img alt="logo" src="https://raw.githubusercontent.com/opengisch/QgisModelBakerLibrary/main/assets/Long-Logo_Green_Modelbaker_RGB.png">

# modelbaker - the library

The modelbaker library is a package containing two main areas:
- Wrapper for ili2db `iliwrapper`
- Modules to generate a QGIS project from it's database source and interacting with this source

This Library is the backend of the QGIS Plugin [QGIS Model Baker](https://github.com/opengisch/QgisModelBaker).
### Installation

```
pip install modelbaker
```
### Structure

```
.
├── __init__.py
├── iliwrapper
│   ├── __init__.py
│   ├── globals.py
│   ├── ili2dbargs.py
│   ├── ili2dbconfig.py
│   ├── ili2dbtools.py
│   ├── ili2dbutils.py
│   ├── ilicache.py
│   ├── iliexecutable.py
│   ├── iliexporter.py
│   ├── iliimporter.py
│   ├── iliupdater.py
│   └── ilivalidator.py
├── dataobjects
│   ├── __init__.py
│   ├── fields.py
│   ├── form.py
│   ├── layers.py
│   ├── legend.py
│   ├── project.py
│   └── relations.py
├── dbconnector
│   ├── __init__.py
│   ├── config.py
│   ├── db_connector.py
│   ├── gpkg_connector.py
│   ├── mssql_connector.py
│   └── pg_connector.py
├── db_factory
│   ├── __init__.py
│   ├── db_command_config_manager.py
│   ├── db_factory.py
│   ├── db_simple_factory.py
│   ├── gpkg_command_config_manager.py
│   ├── gpkg_factory.py
│   ├── gpkg_layer_uri.py
│   ├── layer_uri.py
│   ├── mssql_command_config_manager.py
│   ├── mssql_factory.py
│   ├── mssql_layer_uri.py
│   ├── pg_command_config_manager.py
│   ├── pg_factory.py
│   └── pg_layer_uri.py
├── generator
│   ├── __init__.py
│   ├── config.py
│   ├── domain_relations_generator.py
│   └── generator.py
├── ilitoppingmaker
│   ├── __init__.py
│   ├── ili2dbsettings.py
│   ├── ilidata.py
│   ├── iliprojecttopping.py
│   ├── ilitarget.py
│   ├── metaconfig.py
└── utils
    ├── __init__.py
    ├── db_utils.py
    ├── globals.py
    ├── qgis_utils.py
    └── qt_utils.py
```

### ili2db
In the current release we use ili2db version 4.10

## Infos for Devs

### Code style

Is enforced with pre-commit. To use, make:
```
pip install pre-commit
pre-commit install
```

And to run it over all the files (with infile changes):

```
pre-commit run --color=always --all-file
```

### Needed packages from PyPI

Needed packages from PyPI are downloaded and packaged on deployment to the plugin's libs folder.

Run the script to download and unpack them or install them to your system.

Script:
```
./scripts/package_pip_packages.sh
```