semvec/pypi-packages huggingface dataset:
rofi-tmuxp 0.6.0
Rofi script to launch tmuxp sessions.
Requires Python: ~=3.8
Keywords: rofi, tmux, tmuxp

==========
Rofi TmuxP
==========

.. pull-quote::

   Use Rofi_ to launch tmuxp_ sessions.

.. image:: https://img.shields.io/pypi/v/rofi-tmuxp.svg
    :target: https://pypi.org/project/rofi-tmuxp/

.. image:: https://img.shields.io/pypi/pyversions/rofi-tmuxp.svg
    :target: https://pypi.org/project/rofi-tmuxp/

.. image:: https://img.shields.io/pypi/format/rofi-tmuxp.svg
    :target: https://pypi.org/project/rofi-tmuxp/

.. image:: https://github.com/heindsight/rofi-tmuxp/actions/workflows/test.yaml/badge.svg?branch=master
    :target: https://github.com/heindsight/rofi-tmuxp/actions/workflows/test.yaml?query=branch%3Adevelop

.. image:: https://img.shields.io/badge/code%20style-black-000000.svg
    :target: https://github.com/psf/black

Installation
------------

.. code-block:: shell

   $ pip install rofi-tmuxp

Note
````

The ``rofi-tmuxp`` script uses the `tmuxp python API`_ to find your tmuxp
session config files. This means that you should install it in the same Python
environment as tmuxp.

Usage
-----

Without any command-line arguments, ``rofi-tmuxp`` will print out a list of
tmuxp session names to standard output. If a session name is passed as an
argument, it will attempt to launch that session in a new terminal.

To use with ``rofi``, you will need to add ``rofi-tmuxp`` as a "script" mode to
you rofi config file.  E.g.

.. code-block::

   configuration {
       /* Enable run and tmuxp modes */
       modi: "run,tmuxp:rofi-tmuxp";
   }

Then you can run rofi like:

.. code-block:: shell

   rofi -show tmuxp

License
-------

Copyright (c) Heinrich Kruger. Distributed under the `MIT license`_.


.. _Rofi: https://github.com/davatorium/rofi
.. _tmuxp: http://tmuxp.git-pull.com/
.. _tmuxp python API: https://tmuxp.git-pull.com/en/latest/api.html
.. _MIT license: https://github.com/heindsight/rofi-tmuxp/blob/master/LICENSE
terminal-robot 1.0.0
A fun cool speaking robot right in your terminal.
Requires Python: >=3.12

# Terminal-robot🤖

The terminal-robot is a fun feature you can add to your terminal to get a speaking robot.
You can easily run the python code. Enter the text you would like the robot to say and it will speak in a robotic-y voice with mouth movements!

https://github.com/AnirudhG07/terminal-robot/assets/146579014/24712b57-227b-43e6-8079-54b76c5e3959

## Installation

You can install the terminal-robot using the following ways -

### 1. Using pip

```bash
pip install terminal-robot
```

### 2. Using Homebrew (For MacOS)

```bash
brew install anirudhg07/anirudhg07/terminal-robot
```

### 3. Docker

You can run the docker image of terminal-robot by running -

```bash
docker run -it --rm anirudhg07/terminal-robot
```

### 4. Manual Installation

```bash
git clone https://github.com/AnirudhG07/terminal-robot.git
cd terminal-robot
pip install .
```

And you are good to go!

## Features You can change

1. You can always change features of the robot's voice like voice type, speed, pitch, etc.
2. If you don't like the robot, go to the cloned repository and change the images according to your mouth settings. Don't forget to rename the pics as given.

## Dependencies

The dependencies for the terminal=-robot are automaticaly taken care of by the package managers. You can also download the requirements by running -

```bash
pip install -r requirements.txt
```

Check out the requirements.txt file for more details.

## Future work!

```bash
Hi I am your terminal assistant. How can i help you?
```

2. Make this robot as a terminal assistant with chatbot to actually answer your terminal queries and give suggestions for errors
3. Add more features like changing robot face, robot talking speed and all. Since I have used espeak, it can be done without much difficulty.
4. More ideas and suggestions...
image-processing-lfrossinhole 0.0.2
Image Processing Package using Skimage
Requires Python: >=3.5

# image_processing

Description.
The package image_processing_lfrossinhole is used to: <br>
-	Processing: <br>
		- Histogram matching  <br>
		- Structural similarity <br>
		- Resize image
-	Utils: <br>
		- Read image <br>
		- Save image <br>
		- Plot image <br>
		- Plot result <br>
		- Plot histogram

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install image_processing_lfrossinhole

```bash
pip install image_processing_lfrossinhole
```

## Author
Lucas Feitosa

## License
[MIT](https://choosealicense.com/licenses/mit/)
hamkit-uls 0.0.1a3
A tool for working with local copies of the FCC Universal Licensing System (ULS) database dumps (e.g., to look up information about a US call sign.)
Requires Python: >=3.10

# hamkit.uls

[![PyPI - Version](https://img.shields.io/pypi/v/hamkit-uls.svg)](https://pypi.org/project/hamkit-uls)
[![PyPI - Python Version](https://img.shields.io/pypi/pyversions/hamkit-uls.svg)](https://pypi.org/project/hamkit-uls)

---

> [!NOTE]  
> `hamkit.uls` is a _small standalone component_ of [`hamkit`](https://pypi.org/project/hamkit/). You can use it by itself (see below) if queries against the FCC ULS database is all that you need. Alternatively, install the entire collection of HamKit modules with `pip install hamkit`.

> [!TIP]  
> Even if you do not use `ULS` instances directly (e.g, if you want to run your own database queries), `ULS.download()` is useful for downloading and parsing the data into sqlite.

### A simple library to work with a local copy of the FCC ULS database

```console
pip install hamkit-uls
```

#### Download the ULS data, and load it into a sqlite database

At present, the library is mainly only useful for downloading and parsing the FCC ULS database (from their weekly database dumps), loading it into a sqlite database, and retrieving information about call signs. Here is an example, showing these operations:

```python
import os
import logging
from hamkit.uls import ULS

logging.basicConfig(level=logging.DEBUG)

# Download the database, if not already present
db_file = "uls.db"
if not os.path.isfile(db_file):
    ULS.download("uls.db")

# Query information about a callsign
uls = ULS(db_file)
print(uls.call_sign_lookup("kk7cmt"))
```

which will output the following:

```
UlsRecord(service='AMAT', unique_id='12345678', uls_file_number='', call_sign='KK7CMT', entity_type='L', entity_name='Fourney, Adam', first_name='Adam', middle_initial='', last_name='Fourney', street_address='1234 Streetname ST', city='Cityname', state='WA', zip_code='12345', status_code='', status_date='', linked_call_sign='', operator_class='T', group_code='D', region_code='7')
```

In general, the operation is straightforward enough, but `ULS.download()` has numerous options, as per the following docstring:

```python
"""
Download the amateur and/or GMRS license data from the FCC, and load
it into a local sqlite database.

Parameters:
    db_filename:  The location of the sqlite database to create.
    overwrite:    If true, overwrite any existing file (Default: False)
    amat_uri:     The URI from where to download amateur radio license data.
                  Set to None to skip downloading amateur radio data.
                  (Default: ULS_AMAT_URI)
    gmrs_uri:     The URI from where to download GMRS license data.
                  Set to None to skip downloading GMRS data.
                  (Default: ULS_GMRS_URI)
"""
```

## License

`hamkit-uls` is distributed under the terms of the [MIT](https://spdx.org/licenses/MIT.html) license.
mail-agent 0.0.6
Frappe Mail Agent
Requires Python: >=3.10

# Mail Agent

## Installation

Get started with Mail Agent by following these steps:

```bash
git clone https://github.com/frappe/mail_agent
cd mail_agent
virtualenv venv
source venv/bin/activate
pip install .
```

## Setup

### Development

Follow these steps to set up Mail Agent for development:

- #### Prerequisites

  Before setting up Mail Agent, ensure you have the following:

  - **Yarn**: A package manager that simplifies working with JavaScript projects.
    ```bash
    npm install --global yarn
    ```

- #### Set Up Mail Agent

  This command will install Node packages, set up Haraka, and generate a Procfile to manage processes.

  ```bash
  mail-agent setup
  ```

- #### Start Mail Agent
  ```bash
  mail-agent start
  ```

### Production (Ubuntu)

For production deployment on Ubuntu, follow these steps:

- #### Install Required Packages

  Ensure you have the necessary tools and libraries installed:

  ```bash
  sudo apt install curl build-essential -y
  ```

- #### Install Node.js, npm, and Yarn

  Set up Node.js and Yarn, which are required for running `Haraka`:

  ```bash
  curl -fsSL https://deb.nodesource.com/setup_20.x | sudo -E bash -
  sudo apt install -y nodejs
  sudo npm install -g yarn
  ```

- #### Obtain a TLS Certificate (Optional)

  If you want to obtain TLS certificate for your Mail Agent from Let's Encrypt, follow these steps:

  - Install Certbot:
    ```bash
    sudo apt install certbot -y
    ```
  - Generate a TLS certificate for your host:
    ```bash
    sudo certbot certonly --standalone -d $(hostname -f)
    ```

- #### Set Up Mail Agent

  This command will install Node packages, set up Haraka, generate a Procfile and create systemd services:

  ```bash
  mail-agent setup --prod   # Use --inbound to setup agent for inbound
  ```

- #### Verify Services

  Ensure that all services are running correctly:

  ```bash
  sudo systemctl status haraka

  # Inbound
  sudo systemctl status spamassassin

  # Outbound
  sudo systemctl status mail-agent
  ```

## License

[GNU Affero General Public License v3.0](https://github.com/frappe/mail_agent/blob/develop/license.txt)
dayana-endostat 0.1.0
A library for clinical & statistical calculations in Endodontics
Requires Python: >=3.6

# dayana-endostat

**dayana-endostat** is a Python library designed for statistical analysis and calculations relevant to the field of Endodontics. Created with love for my girlfriend who is a dentist aka toothfairy <3

## Installation

You can install the package using pip:

```bash
pip install dayana-endostat
```

## Table of Contents

- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)
- [Available Functions](#available-functions)
- [Contributing](#contributing)
- [License](#license)

## Features

- Calculate crown-to-root ratios
- Estimate root canal volumes
- Compute anesthesia dosages
- Determine treatment success and failure rates
- Calculate the surface area of teeth
- Convert length units (mm, cm, inches)
- And more...

## Available Functions

### 1. Crown-to-Root Ratio

def crown_to_root_ratio(crown_length, root_length)\
Calculates the ratio of the crown length to the root length.

### 2. Root Canal Volume

def root_canal_volume(radius, length) \
Calculates the volume of the root canal using the formula for a cylinder.

### 3. Pulp Chamber Volume

def pulp_chamber_volume(radius, height) \
Estimates the volume of the pulp chamber, approximated as a cone.

### 4. Anesthesia Dosage

def anesthesia_dosage(weight, dosage_per_kg)\
Calculates the required dosage of local anesthetics based on the patient's weight.

### 5. Success Rate

def success_rate(successes, total_treatments)\
Calculates the treatment success rate as a percentage.

### 6. Failure Rate

def failure_rate(failures, total_treatments)\
Calculates the treatment failure rate as a percentage.

### 7. Surface Area of Tooth

def surface_area_of_tooth(height, radius)\
Calculates the surface area of a tooth, assuming it is conical.

### 8. Average Root Canal Curvature

def average_root_canal_curvature(angles)\
Calculates the average curvature of root canals based on a list of angles in degrees.

### 9. Length Conversion

def convert_length_units(length, from_unit, to_unit)\
Converts lengths between mm, cm, and inches.

### 10. Canal Diameter Calculation

def calculate_canal_diameter(volume, length)\
Calculates the diameter of the canal given its volume and length.

## Contributing

Contributions are welcome! If you have suggestions for improvements or new features, please feel free to submit a pull request or open an issue.

## License
This project is licensed under the MIT License. See the LICENSE file for more details.
terrafai 0.1.7
Apply OpenAI gpt changes to an entire Terraform project directory
Requires Python: >=3.7

# Terrafai: Supercharge Your Terraform Projects with GPT-4

Terrafai is an open-source CLI tool that allows you to edit an entire Terraform project directory with GPT-4, the LLM behind ChatGPT. Make sweeping changes at once:

- Refactor an entire project
- Change resource naming conventions
- Apply your company's latest resource tagging standards
- Anything ChatGPT can do, but at the project level


## Features

🤖 GPT-4 Integration: Utilize the power of OpenAI's GPT-4 to manipulate your Terraform configurations.  
⚙️ Automated Checks: Pre- and post-checks with 'terraform validate' to ensure quality.  
🔄 Diff Output: Visualize changes before they're made.  
🛠️ Flexible Operations: Specify any bulk operations. Will be passed into prompt template. 

All changes will be placed into a timestamped subdirectory of your current project.  

Many improvements to come!  

## Prerequisites

- OpenAI API Key with GPT-4 enabled (https://help.openai.com/en/articles/7102672-how-can-i-access-gpt-4)
- Terraform installed: The CLI tool interacts with Terraform project directories

## Installation

```
pip install terrafai
```

Finally, add your OpenAI API Key to your environment variables:

```
export OPENAI_API_KEY='your-api-key-here'
```

## Usage

Basic usage, from inside your Terraform project directory:

```
terrafai -d -op "Append '-demo' to all resource names."
```
coordstometers 0.0.4
Converts GPS coordinates to meters coordinates centered at some point and back
Requires Python: >=3.7

# Coords to Meters

This is a simple python script that converts coordinates to meters. It uses the haversine formula to calculate the distance between two points on the earth's surface.

(pssst: the haversine formula is kind of like the pythagorean theorem but for the surface of a sphere)
CY3761 2024.1007.2330
CY3761的软件包
Requires Python: >=3.12.5

# Example Package

This is a simple example package. You can use
[GitHub-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.

## 项目信息
+ 项目名称: CY3761
+ 项目作者: CY3761 fb764bc@foxmail.com
+ 项目版本: 2024.1007.2330
+ 环境版本: >=3.12.5

## 依赖项目


## 说明

+ u00.py | 读写文本 | read/save/push | _text/_code/_bytes/_json