semvec/pypi-packages huggingface dataset:
are-free-robux-games-real-v-7351 8.966
are free robux games real

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3-steps-to-get-free-robux-v-1703 2.865
3 steps to get free robux

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scafl 0.4.1
A Steam game idler for trading card drops
Requires Python: >=3.6

# ScafL - Steam Card Afk Farm for Linux

ScafL (Steam Card Afk Farm for Linux) is a Linux application made with Python to idle Steam games for [Steam Trading Card](https://steamcommunity.com/tradingcards/) drops.
This project was inspired by [Idle Master Extended](https://github.com/JonasNilson/idle_master_extended) and [Idle Master Python](https://github.com/jshackles/idle_master_py).

ScafL features an interface built using Gtk.

This project was made specifically for the "Linux Gamers". Other operating systems may be suported in the future.

## Installing the application

To install ScafL, you first need Python 3.6+ installed and pip. Check your Linux distribution on how to install both of these dependencies.

### Installing on your system

To install ScafL on your system, you need to ensure that [GTK and PyGObject is installed on your system](https://pygobject.readthedocs.io/en/latest/getting_started.html).
Then run the following command on your terminal:

```sh
$ pip install scafl
$ python -m scafl
```

### Installing inside a virtual environment

If you want to install the project in a virtual environment, to avoid any dependency conflict, first ensure venv is installed. Then, run the following:

```sh
$ python -m venv /path/to/your/virtual/environment
$ source /path/to/your/virtual/environment/bin/activate
```

Now, while still in your virtual environment, install the package by running the following command:

```sh
(env) $ pip install pycairo pygobject scafl
```

You now have ScafL installed on your virtual environment. This means that every time you want to run ScafL, you need to have the virtual environment activated, which is done by running:

```sh
$ source /path/to/your/virtual/environment/bin/activate
```

To run ScafL, run this command on your terminal:

```sh
(env) $ python -m scafl
```

To exit the virtual environment, run:

```sh
(env) $ deactivate
```

### Running from source

To run ScafL from source, it is recommended that you run it on a virtual environment. To create a virtual environment, run the following command inside the project directory:

```sh
$ python -m venv .env
```

Then, activate the virtual environment:

```sh
$ source .env/bin/activate
```

After activating the virtual environment, install the project's dependencies:

```sh
(env) $ pip install -e .
(env) $ pip install pycairo pygobject
```

To run the project, you must have the virtual environment activated. After ensuring that you're in a virtual environment, run:

```sh
(env) $ python path/to/main.py
```


## Suport the project!

You can suport the project by [donating to the main maintainer](https://www.paypal.com/donate/?hosted_button_id=TSARHWQFKSEBA), or by contributing code!
free-robux-3d-loto-v-1866 2.50
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linguappt 0.1.22
PPT generator for language learning
Requires Python: >=3.8,<4.0
Keywords: ppt,language,auto

# Installation

```
pip3 install --verbose linguappt 
```

# Usage

Please refer to [api docs](https://qishe-nlp.github.io/linguappt/).

### Execute usage

* Validate ppt template
```
lingua_pptx_validate --pptx [pptx file]
```

* Convert vocabulary csv file into ppt file
```
lingua_vocabppt --sourcecsv [vocab csv file] --lang [language] --title [title shown in ppt] --destpptx [pptx file]
```

* Convert phrase csv file into ppt file
```
lingua_phraseppt --sourcecsv [phrase csv file] --lang [language] --title [title shown in ppt] --destpptx [pptx file]
```


* Convert ppt into pdf
```
lingua_pptx2pdf --sourcepptx [pptx file] --destdir [dest directory storing pdf and images]
```

### Package usage
```
from linguappt import SpanishVocabPPT, EnglishVocabPPT
from linguappt import EnglishPhrasePPT, SpanishPhrasePPT

def vocabppt(sourcecsv, title, lang, destpptx):
  _PPTS = {
    "en": EnglishVocabPPT,
    "es": SpanishVocabPPT
  }

  _PPT = _PPTS[lang]

  vp = _PPT(sourcecsv, title)
  vp.convert_to_ppt(destpptx)

def phraseppt(sourcecsv, title, lang, destpptx):
  _PPTS = {
    "en": EnglishPhrasePPT,
    "es": SpanishPhrasePPT
  }

  _PPT = _PPTS[lang]

  vp = _PPT(sourcecsv, title)
  vp.convert_to_ppt(destpptx)


```

# Development

### Clone project
```
git clone https://github.com/qishe-nlp/linguappt.git
```

### Install [poetry](https://python-poetry.org/docs/)

### Install dependencies
```
poetry update
```

### Test
```
poetry run pytest -rP --capture=sys
```
which run tests under `tests/*`


### Execute
```
poetry run lingua_pptx_validate --help
poetry run lingua_vocabppt --help
poetry run lingua_phraseppt --help

poetry run lingua_pptx2pdf2images --help
poetry run lingua_csv2media --help
```

### Create sphinx docs
```
poetry shell
cd apidocs
sphinx-apidoc -f -o source ../linguappt
make html
python -m http.server -d build/html
```

### Host docs on github pages
```
cp -rf apidocs/build/html/* docs/
```

### Build
* Change `version` in `pyproject.toml` and `linguappt/__init__.py`
* Build python package by `poetry build`

### Git commit and push

### Publish from local dev env
* Set pypi test environment variables in poetry, refer to [poetry doc](https://python-poetry.org/docs/repositories/)
* Publish to pypi test by `poetry publish -r test`

### Publish through CI 
* Github action build and publish package to [test pypi repo](https://test.pypi.org/)

```
git tag [x.x.x]
git push origin master
```

* Manually publish to [pypi repo](https://pypi.org/) through [github action](https://github.com/qishe-nlp/linguappt/actions/workflows/pypi.yml)
linguadoc 0.1.5
DOC generator for language learning
Requires Python: >=3.8,<4.0
Keywords: doc,language,auto

# Installation

```
pip3 install --verbose linguadoc 
```

# Usage

Please refer to [api docs](https://qishe-nlp.github.io/linguadoc/).

### Execute usage

* Convert json into docx
```
gen_lingua_docx --sourcejson [source.json] --lang [en/de/es] --destdocx [output.docx] --title [test_title]
```

### Package usage
```

```

# Development

### Clone project
```
git clone https://github.com/qishe-nlp/linguadoc.git
```

### Install [poetry](https://python-poetry.org/docs/)

### Install dependencies
```
poetry update
```

### Test
```
poetry run pytest -rP --capture=sys
```
which run tests under `tests/*`


### Execute
```
poetry run gen_lingua_docx --help
```

### Create sphinx docs
```
poetry shell
cd apidocs
sphinx-apidoc -f -o source ../linguadoc
make html
python -m http.server -d build/html
```

### Host docs on github pages
```
cp -rf apidocs/build/html/* docs/
```

### Build
* Change `version` in `pyproject.toml` and `linguadoc/__init__.py`
* Build python package by `poetry build`

### Git commit and push

### Publish from local dev env
* Set pypi test environment variables in poetry, refer to [poetry doc](https://python-poetry.org/docs/repositories/)
* Publish to pypi test by `poetry publish -r test`

### Publish through CI 
* Github action build and publish package to [test pypi repo](https://test.pypi.org/)

```
git tag [x.x.x]
git push origin master
```

* Manually publish to [pypi repo](https://pypi.org/) through [github action](https://github.com/qishe-nlp/linguappt/actions/workflows/pypi.yml)