semvec/pypi-packages huggingface dataset:
jiraclikit 1.0.0
Kit (as in baby bunny) for Jira CLI.
Requires Python: >=3.12

# Jira CLI Kit

> A female rabbit is called a doe. A male rabbit is called a buck. A baby rabbit is called a kit.

This is a command-line tool to interact with Jira Cloud to create tickets and add comments to existing tickets.
It uses a configuration file (`~/.jira.cfg`) for default settings and allows command-line arguments to override these defaults.

## Setup

### Install

```bash
git clone git@gitlab.com:q-os/security.git
pip install ./security/projects/jiracli  # locally
pip install jiraclikit  # from PyPI
```

### 1. Create a Jira API Token

To interact with Jira Cloud, you need to generate an API token:

1. Go to [Jira API Token page](https://id.atlassian.com/manage-profile/security/api-tokens).
2. Log in with your Jira account.
3. Click on **Create API token**.
4. Name the token and click **Create**.
5. Copy the token and save it securely.

### 2. Set Environment Variables

Store the Jira API URL and token as environment variables for secure access:

```bash
export JC_JIRA_URL="https://yourdomain.atlassian.net"  # Replace with your Jira domain
export JC_JIRA_TOKEN="your_jira_api_token"  # Replace with the generated API token
```

### 3. Initial Run Configuration

When you run the tool for the first time, it will prompt you to enter:

- **Default Project ID**: The Jira project ID where tickets will be created.
- **Default Parent Task ID** (optional): A parent ticket ID if you often create subtasks under a specific epic or task.

These will be saved in the `~/.jira.cfg` file.

### Examples

#### Creating a Ticket

To create a new ticket in Jira:

```bash
python jira_cli.py -s "Ticket Title" -m "Detailed description of the ticket" -p "PROJECT_ID" -e "PARENT_TASK_ID" -t "tag1,tag2"
```

- This will create a ticket with the specified title, message, project, parent task, and tags.
- If `-p` or `-e` is not specified, the tool will fall back to the defaults in `~/.jira.cfg`, unless `-n` is used.

#### Adding a Comment to a Ticket

To add a comment to an existing ticket:

```bash
python jira_cli.py -c "TICKET_ID" -m "Your comment here"
```

- This will add the provided comment to the specified ticket.

#### Using "No Defaults" Mode

To ignore the `.jira.cfg` settings and use only the provided CLI arguments:

```bash
python jira_cli.py -s "New Ticket Without Defaults" -p "ANOTHER_PROJECT_ID" -n
```

## Configuration File (`~/.jira.cfg`)

The configuration file will look like this:

```ini
[DEFAULT]
project_id = YOUR_DEFAULT_PROJECT_ID
parent_task = YOUR_DEFAULT_PARENT_TASK_ID
```

The settings here are automatically created on the first run if they don't already exist.

---

### Notes

- **Environment Variables**: Ensure the `JIRA_URL` and `JIRA_API_TOKEN` are set before running the tool.
- **Command-line Override**: CLI arguments override the config file values.
- **Error Handling**: If any required parameter is missing, the script will raise an error and prompt for correction.

## Publish

```bash
python -m pip install --upgrade pip build twine
python -m build --sdist && python -m build --wheel
twine upload ./dist/* -u __token__ -p $PYPI_API_KEY
```
blackboxai-chat 0.1.1
BlackboxAI is AI pair programming in your terminal
Requires Python: >=3.10

# BLACKBOXAI: AI Pair Programming in Your Terminal

BlackboxAI enables pair programming with LLMs directly in your terminal, working seamlessly with your local git repositories. Use it for new projects or existing codebases.

## Getting Started

Quick setup in two steps:

1. Install the package:
```
pip install blackboxai-chat
```

2. Start coding with your AI pair:
```
# Navigate to your git repository
$ cd /to/your/git/repo

# Launch BlackboxAI
$ blackboxai
```


## Features

- **Flexible File Selection**: Edit specific files with `blackboxai <file1> <file2> ...`
- **Intelligent Code Modifications**:
    + Feature implementation
    + Bug fixes
    + Test case generation
    + Code refactoring
    + Documentation updates
- **Git Integration**: Automatic commits with meaningful messages
- **Multi-language Support**: Works with Python, JavaScript, TypeScript, PHP, HTML, CSS, and more
- **Multi-file Capability**: Handles complex changes across multiple files
- **Codebase Awareness**: Utilizes repository mapping for better context
- **Real-time Sync**: Stays updated with your editor changes during chat sessions

Start pair programming with AI today!
lungo-cli 0.5.12
A user-friendly home lab setup designed for small-to-mid-scale on-premises hosting.
Requires Python: <4.0,>=3.12
Keywords: homelab, self-host

<br>

<h1 align="center">
  <a href="https://github.com/raymond-u/lungo">
      <img src="https://github.com/raymond-u/lungo/assets/36328498/5a8a3696-61c1-46cc-a1b4-144141da2d36" alt="Lungo" width="120">
  </a>
  <br>
  <b>Lungo</b>
  <br>
</h1>

<p align="center">
  A user-friendly home lab setup designed for small-to-mid-scale on-premises hosting.
  <br>
</p>

<p align="center">
  <a href="https://pypi.org/project/lungo-cli/" style="text-decoration: none">
    <img src="https://badge.fury.io/py/lungo-cli.svg" alt="PyPI version">
  </a>
  <a href="https://opensource.org/licenses/MIT" style="text-decoration: none">
    <img src="https://img.shields.io/badge/License-MIT-yellow.svg" alt="License: MIT">
  </a>
</p>

<br>

## Features

- **Complete configurability** - manage everything declaratively through YAML files
- **Seamless interoperability** - access all applications via a single sign-on portal
- **Batteries included** - extend functionality with both built-in and custom plugins
- **Containerized solution** - designed to operate in a rootless Docker environment
- **Security by default** - use HTTPS and secure server settings across the system

## Installation

The recommended way to install Lungo is via [pipx](https://pypa.github.io/pipx/):

```bash
pipx install lungo-cli
```

Note that Lungo is built upon [Docker Compose](https://github.com/docker/compose). Before proceeding, please ensure that
Docker is installed on your machine.

Alternatively, you can use [Podman Compose](https://github.com/containers/podman-compose)
with [Podman](https://podman.io/). You can
also [use Docker Compose with Podman](https://fedoramagazine.org/use-docker-compose-with-podman-to-orchestrate-containers-on-fedora/).

For instructions on setting up these tools, please refer to their respective documentation.

## Quickstart

Copy the example configuration files to the platform-specific configuration directory. For example, on Linux, you can
use the following command:

```bash
mkdir -p ~/.config/lungo
cp examples/* ~/.config/lungo
```

Edit the configuration files according to your preferences. Then, launch the Lungo service by running the following
command:

```bash
lungo up
```

## Documentation

For more information, please refer to the [documentation](https://raymond-u.github.io/lungo/).

## License

This project is licensed under the MIT License. See [LICENSE](LICENSE) for details.
pydlr 1.0.1
Discrete Lehmann Representation for imaginary time calculations
Requires Python: >=3.6

# `libdlr`: Imaginary time calculations using the Discrete Lehmann Representation

Authors: [Jason Kaye](https://github.com/jasonkaye) and [Hugo UR Strand](https://github.com/HugoStrand) (2021)

`libdlr` is a library providing Fortran subroutines to build and work with the
discrete Lehmann representation (DLR) of single particle imaginary time Green's functions,
as well as a stand-alone Python module `pydlr` implementing the same functionality.

For more information see the [documentation](https://libdlr.readthedocs.io), and the references below.

For a C++ implementation of the DLR, please see
[cppdlr](https://github.com/flatironinstitute/cppdlr). For a Julia
implementation, see [Lehmann.jl](https://github.com/numericaleft/Lehmann.jl).

## Citation

If this library helps you to create software or publications, please let
us know, and cite

- our repository: https://github.com/jasonkaye/libdlr
- [libdlr: Efficient imaginary time calculations using the discrete Lehmann representation, Jason Kaye, Kun Chen, and Hugo U.R. Strand, Comput. Phys. Commun. 280, 108458, 2022.](https://www.sciencedirect.com/science/article/pii/S0010465522001771) \[[arXiv:2110.06765](https://arxiv.org/abs/2110.06765)\]
- [Discrete Lehmann representation of imaginary time Green's functions, Jason Kaye, Kun Chen, and Olivier Parcollet, Phys. Rev. B 105, 235115, 2022.](https://journals.aps.org/prb/abstract/10.1103/PhysRevB.105.235115) \[[arXiv:2107.13094](https://arxiv.org/abs/2107.13094)\]

## Contact

Please email jkaye@flatironinstitute.org with any and all questions.

## License

`libdlr` is licensed under the Apache License, Version 2.0, for more information see the `LICENSE` file.