semvec/pypi-packages huggingface dataset:
farmgbm12 0.2.0
Package Simulates Geometric Brownian Motion
Requires Python: <4.0,>=3.12

# FarmGBM12

## Overview
FarmGBM12 simulates 1D Brownian Motion and plots displacement over time for the D400 Research Computing course.

## Installation
Ensure Python is installed. Install packages with:
```bash
pip install -r requirements.txt
```

## Usage
1. Clone the repository:
    ```bash
    git clone https://github.com/Farmer122/farmgbm12.git
    ```
2. Navigate to the project directory:
    ```bash
    cd farmgbm12
    ```
3. Run the scripts or notebooks.

## Contributing
Fork the repository and submit a pull request.

## License
MIT License.

## Contact
Questions? Contact Jamal Lawal at jamallawal1000@gmail.com
scholarversary 0.1.0
Add your description here
Requires Python: >=3.11

# scholarversary

Scholarversary is a milestone-finder for academic careers through the (limited!) lens of publishing.

## Citation Milestones

```python
import scholarversary as sv

sv.Scholarversary().citations()
```

## Citations by year (replicate the "Google Scholar" chart)

```python
import pandas as pd

(
    pd.DataFrame(wcby)
    .fillna(0)
    .astype(int)
    .sort_index()
    .sum(axis=1)
    .plot.bar(title="Total Citations by Year", color="#777")
)
```

![gscholar bar chart](docs/gscholar-barchart.png)

### 1, 10, 20, 50, 100, 200, ... Total Citations

```python
s = Scholarversary()
s.get_author_citation_milestone_dates("Jordan Matelsky")
```

```python
{1: '2017-04-17',
 10: '2019-01-01',
 50: '2020-08-31',
 100: '2021-11-01',
 200: '2023-04-13'}
```

### Surpassing previous year in citations

## Per-Paper Metrics

```python
wcby = s.get_author_work_cites_by_year("Jordan Matelsky", index_by="title")
df = pd.DataFrame(wcby).fillna(0).astype(int).sort_index()
# Get columnwise cumulatives:
dfc = df.cumsum(axis=0)

dfc.plot.line(legend=False, title="Citations by Year")
top_works = dfc.max().sort_values(ascending=False).index[:5]
for work in top_works:
    plt.text(df.index[-1], dfc[work].iloc[-1], work[:30] + "...", ha="right", va="center")
plt.show()
```

![work cites by year chart](docs/work-cites-by-year.png)

### Paper Milestones

#### 1st, 10, 20, 50, 100, 200, ... Citations

#### First collaboration with a new co-author

#### New journal / venue
sdTranslate 0.3
A description of sdTranslate
Requires Python: >=3.6

# sdTranslate

`sdTranslate` is a lightweight Python package that uses Google Translate API to translate text from one language to another. With a straightforward interface, it supports auto-detection of the input language and provides results in JSON format.

## Installation

Clone or download the repository, and install the dependencies.

```bash
pip install sdTranslate
```

## Usage
Import the translate_text function from sdTranslate and provide the text you want to translate, with optional parameters for input and output languages.

```bash
from sdTranslate import translate_text

# Example usage
result = translate_text("Hola, Â¿cÃ³mo estÃ¡s?", input_lang="es", output_lang="en")
print(result)
```

## Function Signature
```bash
translate_text(text, input_lang='auto', output_lang='en')
```

- text: str - The text to be translated. Limited to 4000 characters.
- input_lang: str - Language code for the input text (default is 'auto' for auto-detection).
- output_lang: str - Language code for the output text (default is 'en' for English).

## Example Response
The translate_text function returns a JSON string with the following structure:

```bash
{
  "RESPONSE_STATUS": 200,
  "TranslatedText": "How are you?"
}

```

If thereâ€™s an error in the translation or an invalid text input:

```bash
{
  "RESPONSE_STATUS": 500,
  "TranslatedText": "Something went wrong please pass proper text..."
}
```

## Dependencies
- requests: For making HTTP requests to the Google Translate API.
- unidecode: For converting the translated text into plain ASCII characters.

## License
This project is licensed under the MIT License.

```bash

This `README.md` provides clear instructions on using the `translate_text` function, including details about parameters, expected output, and error handling. It should help users understand and get started with your package quickly.

```
logic-ds3 0.0.5
LogicDS reasoning-based universal language teaching library

Welcome to the Logic-DS Library Repository
by the LogicDS Team, admin: Barnas Monteith, 2024

logic-ds is a Python library aimed at helping students learn functions; in this library we focus on creating functions that gradually introduce students to core programming concepts like inputs, outputs, return values, conditionals, and loops.

distributed as part of the LogicDS Project, housed at Texas Tech University, in conjunction with the University of FLorida, Center for Science Engagement and Concord Consortium
National Science Foundation Award #2201393.  This library is intended to be used as a python teaching library, to aid in student understanding of the universal framework concept of LogicDS, which emphasizes he use of logic and reasoning principles in the pedagogical approaches to teaching fundamental skills behind data science, including math/statistics, computer science as well as AI.
This library focuses on using alternative methods to aid in student understanding of functions with a focus on set theory, tuples, probability and linear regression.  The library is intended to be used along with the documentation and curricula provided through the LogicDS project courses and curricular framework.  

For library usage instructions, see /docs/DOCUMENTATION

More info about this project can be found at www.logicds.org

This library is distributed under the MIT License. see LICENSE file for additional information.
gptcmdfj 0.1.1
Call ChatGPT from the console
Requires Python: >=3.6

# GPTCMD

GPTCMD is a Python library for calling ChatGPT in the command line

## Installation

Use the package manager [pip](https://pip.pypa.io/en/stable/) to install GPTCMD.

```bash
pip install gptcmdfj
```

## Setup
Add your credentials ot .env.example in the site-package file, then delete the '.example' portion (so the file should be called .env)

## Usage

```bash
User> GPTCMD "can you hear me?"
As an artificial intelligence, I don't have the ability to hear. However, I can process and respond to the text inputs you provide.
```
screen-text 0.1.4.0
A tool for capturing and recognizing text on screen using ddddocr and mss.
Requires Python: >=3.6

# Screen Text Recognizer

A Python package to capture and recognize text from a specific screen area using mss and ddddocr.

## Installation

```bash


pip install screen-text

濡傛灉澶辫触锛宲ip install opencv-python-headless --prefer-binary

```

```python

from screen_text import ScreenTextRecognizer

recognizer = ScreenTextRecognizer()
text = recognizer.capture_and_recognize(100, 100, 300, 200)
print("Recognized text:", text)


```
BuildDeck 2.0.8
A CLI tool for managing services and deployments.
Requires Python: >=3.7


# BuildDeck

**BuildDeck** is a powerful CLI tool designed for automating the build, test, deployment, and management of services in your projects. It provides easy-to-use commands for handling Maven builds, Docker Compose setups, and Postman test executions.

## Features

- Automate Maven build, test, clean, and verification tasks.
- Manage Docker Compose setups with easy-to-use commands.
- Run automated Postman tests for your services.
- Flexible command options for specifying environments and services.

## Table of Contents

- [Installation](#installation)
- [Usage](#usage)
- [Commands](#commands)
- [Options](#options)
- [Contributing](#contributing)
- [License](#license)

## Installation

You can install BuildDeck from PyPI using:

```bash
pip install BuildDeck
```

Or install it locally for development:

```bash
git clone https://github.com/yourusername/BuildDeck.git
cd BuildDeck
pip install -e .
```

## Usage

Once installed, you can use the `builddeck` command to run various tasks. Here are some examples:

### Build Services in Development Environment

```bash
builddeck --env dev mvn-build
```

### Test Specific Services

```bash
builddeck --env staging --services service1,service2 mvn-test
```

### Deploy All Services

```bash
builddeck --env prod deploy
```

### Run Docker Compose Setup

```bash
builddeck up
```

## Commands

- `mvn-build` - Build all services using Maven.
- `mvn-test` - Test all services using Maven.
- `mvn-clean` - Clean all services using Maven.
- `mvn-verify` - Verify all services using Maven.
- `test` - Run Postman tests for all services.
- `build` - Build and deploy all services.
- `deploy` - Deploy all services, run Docker Compose, and execute tests.
- `compose` - Generate Docker Compose file.
- `up` - Start Docker Compose services.
- `down` - Stop and remove Docker Compose services.

## Options

### Global Options

- `--env` - Specify the environment (e.g., `dev`, `staging`, `prod`). Default is an empty string.
- `--services` - Comma-separated list of services to include (e.g., `service1,service2`). Default is all services.

### Command-specific Options

- `-s` or `--single` - Operate on a single service instead of all services.

## Contributing

Contributions are welcome! To get started:

1. Fork this repository.
2. Create a new feature branch: `git checkout -b feature-name`.
3. Commit your changes: `git commit -m 'Add some feature'`.
4. Push the branch: `git push origin feature-name`.
5. Submit a pull request.

Please make sure to update tests as appropriate.

## License

This project is licensed under the MIT License. See the [LICENSE](LICENSE) file for details.