semvec/pypi-packages huggingface dataset:
tyora 0.1.0
CLI to interact with the mooc.fi instance of CSES
Requires Python: >=3.9
Keywords: cli, cses, data structures and algorithms, dsa, mooc.fi, tira.mooc.fi

# Tyora: mooc.fi CSES exercise task CLI
[![PyPI - Version](https://img.shields.io/pypi/v/tyora?pypiBaseUrl=https%3A%2F%2Ftest.pypi.org&logo=pypi&label=pypitest)](https://test.pypi.org/project/tyora/)
[![Python Version from PEP 621 TOML](https://img.shields.io/python/required-version-toml?tomlFilePath=https%3A%2F%2Fraw.githubusercontent.com%2Fmadeddie%2Ftyora%2Fmain%2Fpyproject.toml&logo=python)](https://github.com/madeddie/tyora/blob/main/pyproject.toml#L15)
[![GitHub Actions Workflow Status](https://img.shields.io/github/actions/workflow/status/madeddie/tyora/ci.yml)](https://github.com/madeddie/tyora/actions/workflows/ci.yml)
[![GitHub License](https://img.shields.io/github/license/madeddie/tyora)](https://github.com/madeddie/tyora/blob/main/LICENSE)


This script interacts with the mooc.fi instance of the CSES (https://cses.fi) website to perform various actions such as logging in, retrieving exercise lists, and submitting solutions.
It provides a convenient way to view and submit tasks.

## Features

- **Login**: Log in to your CSES account using username and password.
- **Retrieve Exercise Lists**: Get a list of exercises available on the CSES platform.
- **Submit Solutions**: Submit your solutions to specific exercises on the platform.

## Installation

   ```bash
   pip install tyora
   ```

## Usage

The script can be used from the command line. The following commands are available:

- `tyora login`: Stores your mooc.fi username and password and tests if we can log in with them.
- `tyora list`: Retrieves and displays a list of exercises available on the CSES platform.
- `tyora show <exercise_id>`: Displays the details of a specific exercise.
- `tyora submit <exercise_id> <path_to_solution_file>`: Submits a solution to a specific exercise.

## Origin of name

The name "tyora" is derived from Finnish words: "työ" meaning "work" and "pyörä" meaning "wheel".
Anyway, `pyora` was already taken, so I went with `tyora`... ;)

## Contributing

Contributions are welcome! If you have any suggestions, bug reports, or feature requests, please open an issue or submit a pull request.

**Rye**

This project uses [Rye](https://rye-up.com/) to manage dependencies, formatting, linting and packaging.
Install it using the instructions on the Rye website, then run `rye sync` in the root of the project to install the necessary tools.

**How to use Rye**

Reading the documentation is probably a good idea, but in short:

- `rye sync` installs the necessary tools.
- `rye format` formats the code.
- `rye lint` lints the code.

**pre-commit**

We use pre-commit to run the linters before each commit. To install it, run `rye sync` and `rye run pre-commit install`.
This is not strictly required, but it'll make your life easier by catching issues before the github actions deny your PR.

## License

This project is licensed under the MIT License - see the [LICENSE](LICENSE) file for details.
beautify-markdown 1.0.1
A tool to beautify markdown output from chatgpt-cli (https://github.com/marcolardera/chatgpt-cli)
Requires Python: >=3.11

# Beautify Markdown

## Overview

`beautify_markdown` is simple cli utility through which you can take output from session json files generated by [chatgpt-cli](https://github.com/marcolardera/chatgpt-cli) and beautify it, getting rid of the escape characters
printipy 1.2.1
Printify API for Python
Requires Python: >=3.8
Keywords: printify, print on demand, api

# PrintiPy
The Printify API for Python

Printify's REST API gives your scripts or applications power to manage Printify shops. Create and update products, submit orders, build custom integrations, and so much more!

Tested with Python 3.9 - 3.12.

## Install

```shell
pipenv install printipy
```

## Example

Quickly connect to the Printify API via PrintiPy. Pass an API token for the Printify account and an optional Shop ID and start automating!

```python
from printipy.api import PrintiPy

api = PrintiPy(api_token='...', shop_id='...')

for product in api.products.get_products():
    print(product)
```

## API

Read the docs [here](https://lawrencemq.github.io/printipy/)!

## Development

`pipenv install`

### Build

`python setup.py sdist bdist_wheel`

### Tests

`pipenv run pytest`

### Documentation

Build docs using `pipenv run mkdocs build`

Deploy docs using `mkdocs gh-deploy`. This pushes the generated `/site` to `gh-pages` branch on Github. 

### Releasing
Specific contributors are allowed to create a tag. Upon a tag's push, Actions will deploy to TestPypi and Pypi
CobwebIT 1.1
This is a Complex of random things
Requires Python: >=3.12

# CobwebProject

Cobweb is a simple Python project containing a class for handling logs and displaying ASCII art of a stick figure. The project demonstrates the basic use of modules, classes, and methods in Python.

## Functionalities

- `Message logging`: Supports three levels of logging - information logs, warnings and errors.
- `Date Display`: Simple method that returns the current date.
- `ASCII Art`: Method to display a simple man in ASCII art.

## Requirements

- Python 3.x
- `colorama` library for coloring text in the console.

## Installation

1. Clone the repository:

    ```sh
    git clone https://github.com/SneakyFrameworkCreator/CobwebIT
    ```

2. Go to the project directory:

    ```sh
    cd cobweb
    ```

3. Install required dependencies:

    ```sh
    pip install colorama
    ```
3. Or download from this command
    ```sh
    pip install CobwebIT
    ```

## Usage

### Importing a class

To use the `Cobweb` class, import it in your Python script:

```python
from cobweb import Cobweb
sreader 0.0.1
space-reader: Convert any file path into LLM-friendly inputs
Keywords: LLM, Large Language Model, data processing, data science

# Space Reader

`space-reader` is a tool that can read a workspace URL and convert the content into LLM-friendly format.

## Installation

```shell
pip install sreader
```

## Usage

```python
from sreader import read

read("<workspace URL>")
```

## Support Workspace

- Local File (e.g., `/Users/user/desktop/demo.pdf`)
- Local Directory (e.g., `/Users/user/desktop/demo`)
- Remote File with Access (e.g., `https://example.com/demo.pdf`)
- GitHub Repo with Access (e.g., `https://github.com/user/demo`)

## Support Formats

#### Markdown

```python
read("<workspace URL>", format="markdown")

"""
## /Users/user/desktop/demo
- ****
  - a.py
  - c.py
  - b.py
  - **d**
    - g.py
    - **f**
      - f.py
  - **e**
"""
```

#### JSON and Dict

```python
read("<workspace URL>", format="json")  # or "dict"

"""
{
    "/Users/user/desktop/demo": {
        "files": [
            "a.py",
            "c.py",
            "b.py"
        ],
        "dirs": {
            "d": {
                "files": [
                    "g.py"
                ],
                "dirs": {
                    "f": {
                        "files": [
                            "f.py"
                        ],
                        "dirs": {}
                    }
                }
            },
            "e": {
                "files": [],
                "dirs": {}
            }
        }
    }
}
"""
```

#### Tree

```python
read("<workspace URL>", format="tree")

"""
/Users/user/desktop/demo
└── 
    ├── a.py
    ├── c.py
    ├── b.py
    ├── d
    │   ├── g.py
    │   └── f
    │       └── f.py
    └── e
"""
```

## Examples

- [Simple print](https://github.com/huangyz0918/space-reader/blob/main/example/simple.py)
- [File system Q&A Chatbot](https://github.com/huangyz0918/space-reader/blob/main/example/chatbot.py)

## License

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