semvec/pypi-packages huggingface dataset:
masktunnel 1.1.3
HTTP MITM proxy with browser fingerprinting (CFFI backend)
Requires Python: >=3.9

# MaskTunnel Python Bindings

[![PyPI version](https://img.shields.io/pypi/v/masktunnel.svg)](https://pypi.org/project/masktunnel/)

Python bindings for MaskTunnel — an HTTP(S) MITM proxy that adapts its browser fingerprint based on the request User-Agent.

This package wraps the Go implementation and exposes a Python-friendly API.

## Overview

MaskTunnel is an HTTP proxy that dynamically changes its fingerprint to mimic real browsers (Chrome / Firefox / Safari / Edge) according to the User-Agent header in requests.

Key capabilities:

- Browser-like TLS fingerprints (JA3 / JA4)
- Browser-like HTTP/2 fingerprints (e.g. Akamai-style settings and frame patterns)
- Automatic selection based on User-Agent
- Optional response JavaScript injection
- Optional upstream proxy chaining

## Installation

### Using pip (Recommended)

```bash
pip install masktunnel
```

### Build from source (sdist)

Building from source requires:

- Python 3.9+
- Go toolchain
- A C toolchain suitable for building Python extensions

## Quick Start

### Run a proxy server

```python
from masktunnel import Server

server = Server()
print(f"Proxy running at: {server.addr}")

# Blocking; run in a thread if needed
server.start()
```

### Use CLI

After installation:

```bash
masktunnel server --port 8080
```

## API

### `Server`

Create a server with options:

```python
from masktunnel import Server, ServerOptions

opts = ServerOptions(
	port="8080",
	username="",
	password="",
	payload="",
	upstream_proxy="",
	user_agent="",
	verbose=0,
)

server = Server(options=opts)
```

Common operations:

```python
server.start()
server.stop()
server.reset_sessions()
```

## Notes

- The native module is generated at build time into `masktunnellib/`.
- Prefer installing wheels when available; building from source depends on the local toolchain.

## Links

- Source: https://github.com/cloudflyer-project/masktunnel
summarizedpy 0.5.0
A differential expression analysis package for proteomics data, which leverages transcriptomics tools.
Requires Python: >=3.11

# DEPy

<img src="https://raw.githubusercontent.com/SebastianDHA/DEPy/main/docs/images/depy_banner.svg">

A differential expression analysis package for bulk proteomics (and metabolomics) data, which leverages transcriptomics tools.
Inspired by R tools like DEP and SummarizedExperiment, it brings the power of Bioconductor to Python.
All you need is a matrix of features and their intensity values.

* PyPI package: https://pypi.org/project/summarizedpy/
* GitHub: [SebastianDHA/DEPy](https://github.com/SebastianDHA/DEPy)
* Free software: MIT License

## Features

* SummarizedPY: A container for your -omics data, much like SummarizedExperiment or DEP in R.
* Filtering and subsetting your samples and features
* Missing value filtering
* Imputation using ImputeLCMD (many methods)
* Transforming (log, centering, standardizing, vsn)
* Leverage surrogate variable analysis (sva) to adjust for latent batch effects
* Use the flexibility and power of limma-trend to improve your DEA results and accommodate mixed effects
* Limma arrayWeights to adjust variable sample quality (often an issue in human and animal datasets)
* Visualize your DEA results with elegant volcano plots
* Highly-variable feature selection
* PCA plots
* Saving & loading SummarizedPy objects to & from disk

## Installation
### conda
This is the best way to install DEPy.
```Sh
conda env create -f environment.yml
```
Note that DEPy (summarizedpy) must be run within the [depy conda environment](environment.yml) or a cloned version of it.
This is because summarizedpy needs an isolated environment to run R in due to the complex loading behavior of Bioconductor packages.

## Using pip
```Sh
pip install summarizedpy
```

## Quick start
```Py
import depy as dp

sp = dp.SummarizedPy()
sp = sp.import_from_delim_file(path="path/to/pgroup.tsv", delim="\t")
```
See the full [tutorial](docs/usage.md) for more.

## Documentation
- [GitHub pages](https://sebastiandha.github.io/DEPy/)
- [ReadTheDocs](https://depy.readthedocs.io/en/latest/)

## Credits
This package leverages amazing packages from the R and Bioconductor community, including [limma](https://bioconductor.org/packages/3.20/bioc/html/limma.html), [vsn](https://bioconductor.org/packages/release/bioc/html/vsn.html), [sva](https://bioconductor.org/packages/release/bioc/html/sva.html), [ImputeLCMD](https://cran.r-project.org/package=imputeLCMD), and [Tidyverse](https://www.tidyverse.org/).
This package was created with [Cookiecutter](https://github.com/audreyfeldroy/cookiecutter) and the [audreyfeldroy/cookiecutter-pypackage](https://github.com/audreyfeldroy/cookiecutter-pypackage) project template.
dagster-polars 0.27.9
Dagster integration library for Polars
Requires Python: >=3.10

# dagster-polars

This library provides [Dagster](https://dagster.io/) integration with [Polars](https://pola.rs).
It allows using Polars DataFrames as inputs and outputs with Dagster's `@asset` and `@op`.
Type annotations are used to control whether to load an eager or lazy DataFrame, or other types supported by `dagster-polars`.
Multiple serialization formats (Parquet, Delta Lake, BigQuery) and filesystems (local, S3, GCS, ...) are supported.

The docs for `dagster-polars ` can be found
[here](https://docs.dagster.io/api/python-api/libraries/dagster-polars).
Topsis-JaspreetSingh-102303163 0.3
TOPSIS implementation using command line

# 🧮 Topsis-JaspreetSingh-102303163

A simple and powerful Python implementation of the **TOPSIS (Technique for Order Preference by Similarity to Ideal Solution)** method that runs directly from the command line after installation.

This package allows users to rank alternatives based on multiple criteria using weights and impacts — without writing any code.

---

## 🚀 Features

- Works directly from command line
- Reads any CSV file with numeric criteria
- Accepts custom weights and impacts
- Calculates **Topsis Score** and **Rank**
- Generates output CSV automatically
- Easy to install using `pip`

---

## 📦 Installation

```bash
pip install Topsis-JaspreetSingh-102303163
```

---

## ▶️ How to Use

After installation, simply run:

```bash
topsis data.csv "1,1,1,2" "+,+,-,+" result.csv
```

### Arguments Explained

| Argument | Description |
|---|---|
| `data.csv` | Input CSV file |
| `"1,1,1,2"` | Weights for each numeric column |
| `"+,+,-,+"` | Impacts (`+` for benefit, `-` for cost) |
| `result.csv` | Output file with Topsis Score and Rank |

---

## 📄 Input CSV Format

- First column: Alternative names (non-numeric)
- Remaining columns: Numeric criteria values

Example:

| Model | Price | Mileage | Safety | Comfort |
|------|------|------|------|------|
| A | 25000 | 18 | 7 | 8 |
| B | 27000 | 15 | 9 | 6 |

---

## 📤 Output

The output CSV will contain two extra columns:

- **Topsis Score**
- **Rank**

---

## 🧠 About TOPSIS

TOPSIS is a multi-criteria decision-making method that identifies solutions closest to the ideal and farthest from the worst case.

---

## 👨‍💻 Author

**Jaspreet Singh**  
Roll No: 102303163

---

## 🌐 Project Links

- PyPI: https://pypi.org/project/Topsis-JaspreetSingh-102303163/
- GitHub: https://github.com/JaspreetSingh33
pyclickplc 0.0.1
Utilities for AutomationDirect CLICK Plcs
Requires Python: <4.0,>=3.11

# Pyrung

Utilities to work with AutomationDirect CLICK Plcs

## Status

PLANNING ONLY * INITIAL COMMIT

## Goals

- Provide shared utility library for reading/writing Nickname csv files, 
Dataview .cdv file, communicating via Modbus, and parsing the BlockTag comment specification
sysand 0.0.9
A package manager for SysML v2 and KerML
Requires Python: >=3.8

# Sysand: a package manager for SysML v2 and KerML

> [!important]
> This is an early preview release, intended for early adopters
> to test, integrate, and give feedback. While we hope to keep the tool in a
> usable state, interfaces are subject to change and usability will likely not
> yet be representative of a stable release.

This repository contains Sysand, a [package
manager](https://en.wikipedia.org/wiki/Package_manager) for SysML v2 and KerML
similar to package managers for programming languages such as Pip for Python,
NPM for JavaScript, Maven for Java, and NuGet for .NET. Sysand is based on a
concept of a model interchange project, a slight generalization of a project
interchange file (`*.kpar`), defined in [KerML clause
10.3](https://www.omg.org/spec/KerML/1.0/PDF#page=432).

Sysand can be used as a standalone tool through its command line interface (CLI)
or be integrated into other tools through one of its APIs (currently, Python and
Java are supported).


## Documentation

Sysand usage documentation is provided in User Guide at
[docs.sysand.org](https://docs.sysand.org/).


## Installation

See [installation section in User Guide](http://docs.sysand.org/getting_started/installation.html)
for various ways to download Sysand.


## Contributing

### Development

Development instructions are provided in [DEVELOPMENT.md](DEVELOPMENT.md).

### Legal

For contributors' guidelines regarding legal matters, please see the
[CONTRIBUTING.md](CONTRIBUTING.md) file.

## Licensing

The implementation is dual-licensed under the MIT and Apache-2.0 licenses,
meaning users may choose to use the code under *either* license. Contributors
agree to provide contributed code under **both** licenses.

Sysand is maintained by [Sensmetry](https://www.sensmetry.com), with
contributions from the community. To see the complete list of contributors,
please see the git history.
ical2jcal 1.0.5
Convert between iCalendar and jCalendar formats.
Requires Python: >=3.10

# ical2jcal

[![GitHub Actions][github-actions-badge]](https://github.com/niccokunzmann/ical2jcal/actions)
[![PyPI version](https://badge.fury.io/py/ical2jcal.svg)](https://badge.fury.io/py/ical2jcal)
[![uv][uv-badge]](https://github.com/astral-sh/uv)
[![Nox][nox-badge]](https://github.com/wntrblm/nox)
[![Ruff][ruff-badge]](https://github.com/astral-sh/ruff)
[![Type checked with mypy][mypy-badge]](https://mypy-lang.org/)

[github-actions-badge]: https://github.com/niccokunzmann/ical2jcal/actions/workflows/ci.yml/badge.svg
[uv-badge]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/uv/main/assets/badge/v0.json
[nox-badge]: https://img.shields.io/badge/%F0%9F%A6%8A-Nox-D85E00.svg
[ruff-badge]: https://img.shields.io/endpoint?url=https://raw.githubusercontent.com/astral-sh/ruff/main/assets/badge/v2.json
[mypy-badge]: https://www.mypy-lang.org/static/mypy_badge.svg

Convert between iCalendar and jCalendar formats.