semvec/pypi-packages huggingface dataset:
tic-watch 0.1.4
TIC Watch package
Requires Python: >=3.7

# TIC Watch

📊 **TIC Watch** is a lightweight Python package to enable telemetry and short-term monitoring for FastAPI applications using Azure Monitor — in just a few lines of code.

---

## 🚀 Features

- 📈 Tracks key performance metrics:
  - API Latency
  - HTTP Status Codes
  - Unhandled Exceptions
  - Failure Rate
  - Latency Spikes
  - Resource Failures
- 🔗 Sends data to Azure Application Insights
- 🛠️ Plug-and-play setup (under 5 lines of code)
- 📦 Suitable for 25+ apps with centralized monitoring

---

## 📦 Installation

```bash
pip install tic-watch


## Hard Code these line in yout Application
from fastapi import FastAPI
from tic-watch import init_monitoring

app = FastAPI()

init_monitoring(
    app,
    service_name="MyFastAPIApp",
    connection_string="InstrumentationKey=YOUR_APP_INSIGHTS_KEY"
)
dragon-eval 0.2.11
Evaluation method for the DRAGON benchmark
Requires Python: >=3.7

# DRAGON Evaluation

Evaluation method for the DRAGON (Diagnostic Report Analysis: General Optimization of NLP) challenge. 

If you are using DRAGON resources, please cite the following article:

> J. S. Bosma, K. Dercksen, L. Builtjes, R. André, C, Roest, S. J. Fransen, C. R. Noordman, M. Navarro-Padilla, J. Lefkes, N. Alves, M. J. J. de Grauw, L. van Eekelen, J. M. A. Spronck, M. Schuurmans, A. Saha, J. J. Twilt, W. Aswolinskiy, W. Hendrix, B. de Wilde, D. Geijs, J. Veltman, D. Yakar, M. de Rooij, F. Ciompi, A. Hering, J. Geerdink, and H. Huisman on behalf of the DRAGON consortium. The DRAGON benchmark for clinical NLP. *npj Digital Medicine* 8, 289 (2025). [https://doi.org/10.1038/s41746-025-01626-x](https://doi.org/10.1038/s41746-025-01626-x)

Download the citation file for your reference manager: [BibTeX](https://github.com/DIAGNijmegen/dragon/blob/main/citation.bib) | [RIS](https://github.com/DIAGNijmegen/dragon/blob/main/citation.ris)


## Installation
A pre-built Docker container with the DRAGON evaluation method is available:

```
docker pull joeranbosma/dragon_eval:latest
```

The DRAGON evaluation method can be pip-installed:

```
pip install dragon_eval
```

Or, alternatively, it can be installed from source:

```
pip install git+https://github.com/DIAGNijmegen/dragon_eval
```

The evaluation method was tested with Python 3.10. See [requirements.txt](requirements.txt) for a full list of exact package versions.

## Usage
The Docker container can be used to evaluate the synthetic datasets as specified in [evaluate.sh](evaluate.sh). To evaluate the synthetic tasks, place the predictions to evaluate in the `test-predictions` folder and run `./evaluate.sh`.

The DRAGON evaluation method can also be used from the command line (if installed with pip):

```
python -m dragon_eval --ground-truth-path="ground-truth" --predictions-path=test-predictions --output-file=metrics.json --folds 0 1 2 3 4 --tasks 000 001 002 003 004 005 006 007
```

The command above should work when executed from the `dragon_eval` folder, which needs to be cloned locally for the ground truth and prediction files to be present. Change the paths above when executing the command from a different place or storing the files in a different place. The tasks and folds to evaluate can be changed with the respective parameters.

## Managed By
Diagnostic Image Analysis Group, Radboud University Medical Center, Nijmegen, The Netherlands

## Contact Information
Joeran Bosma: Joeran.Bosma@radboudumc.nl
krstool 1.0.0
Perform simple operations on the MySQL database without entering SQL commands.
Keywords: python, windows, mysql


# Krlrtear's Toolbox

## Installation
```shell
pip3 install krstool
pip3 uninstall krstool
```

## Table of Contents

- MySQL
  - getcolumnname 按序获取列名
  - selectitems 查找返回指定行信息
  - insert 插入行信息
  - closeconn 终端数据库连接
gbrown-django-todo 0.2
A Django app to track todo items.
Requires Python: >=3.12

============
django-todo
============

django-polls is a Django app to help users keep track of their TODO items.
Detailed documentation is in the "docs" directory.

Quick start
-----------

1. Add "todo" to your INSTALLED_APPS setting like this::

    INSTALLED_APPS = [
        ...,
        "django_todo",
    ]

2. Include the polls URLconf in your project urls.py like this::

    path("todos/", include("django_todo.urls")),

3. Run ``python manage.py migrate`` to create the models.

4. Start the development server and visit the admin to create a todo.

5. Visit the ``/todos/`` URL to create and view todos.
ddmail-openpgp-encryptor 0.0.2
Program to encrypt incoming emails with OpenPGP for the DDMail project.
Requires Python: >=3.8

# What is ddmail_openpgp_encryptor
Program to encrypt incoming emails with OpenPGP for the ddmail project.

## What is DDMail
DDMail is a e-mail system/service that prioritizes security. A current production example can be found at www.ddmail.se

## Operating system
Developt for and tested on debian 12.

## Installing using pip
`pip install ddmail-openpgp-encryptor`

## Building and installing from source using hatchling.
Step 1: clone github repo<br>
`git clone https://github.com/drzobin/ddmail_openpgp_encryptor [code path]`<br>
`cd [code path]`<br>
<br>
Step 2: Setup python virtual environments<br>
`python -m venv [venv path]`<br>
`source [venv path]/bin/activate`<br>
<br>
Step 3: Install package and required dependencies<br>
`pip install -e .[dev]`<br>
<br>
Step 4: Build package<br>
`python -m pip install --upgrade build`<br>
`python -m build `<br><br>
Packages is now located under [code path]/dist folder<br>

## Run
`source [venv path]/bin/activate`<br>
`ddmail_openpgp_encryptor --config-file [config file].toml`

## Coding
Follow PEP8 and PEP257. Use Flake8 with flake8-docstrings for linting. Strive for 100% test coverage.
preflibtools 2.0.33
A set of tools to work with preference data from the PrefLib.org website.
Requires Python: >=3.7

# Preflibtools

[![PyPI Status](https://img.shields.io/pypi/v/preflibtools.svg)](https://pypi.python.org/pypi/preflibtools)
[![Build badge](https://github.com/PrefLib/preflibtools/workflows/build/badge.svg?branch=main)](https://github.com/PrefLib/preflibtools/actions?query=workflow%3Abuild)
[![codecov](https://codecov.io/gh/PrefLib/preflibtools/branch/main/graphs/badge.svg)](https://codecov.io/gh/PrefLib/preflibtools/tree/main)

## Overview

The PrefLib-Tools is a set of Python tools developed to work with preference data from the
[PrefLib.org website](https://www.preflib.org/).

This package provides input and output operations on PrefLib instances, together with some additional functionalities
on the instances: Testing whether a Condorcet winner exists, whether the instance is single-peaked, etc...

We developed this package in the hope of making the use of PrefLib instances easy. This has been done in the same
spirit as PrefLib: Providing tools for the community with the help of the community. If you want to contribute, feel
free to create pull requests. If you have a question, a remark, or encounter a problem, please open an issue, create a
pull request etc...

The full documentation of the package can be found there: https://preflib.github.io/preflibtools/.

If, for some reasons, you are looking for the older version of the PrefLib-Tools, it is still available in the GitHub
repository [Preflib-Tools-Old](https://github.com/PrefLib/Preflib-Tools-Old).

## Installation

The installation is as easy as:

```shell
pip3 install preflibtools
```

## Documentation

The complete documentation is available [here](https://preflib.github.io/preflibtools/).

## GitHub Workflow

### Publishing on PyPI

The pipeline between GitHub and PyPI is automatised. To push a new version do the following:
- Update the `pyproject.toml` with the new version number.
- Update the `pabutools/__init__.py` with the new version number.
- On GitHub, create a new release tagged with the new version number (only admins can do that), on [this page](https://github.com/PrefLib/preflibtools/releases/new).
- You're done, the new version of the package is automatically pushed to PyPI after the creation of a GitHub release.

### Building the Docs

If the docs-source has been updated but the `docs/` folder has not, you can build the docs via
a GitHub action here: https://github.com/PrefLib/preflibtools/actions/workflows/docs.yml.
Simply click "Run workflow" and the docs will be built and the built files will be pushed back to
the server.