semvec/pypi-packages huggingface dataset:
backuptools 1.0.1
Backup, restore, version control local data to google drive
Requires Python: >=3.6

# backup-tools

Backup, restore, version control local data to google drive

# Prerequisites

- Python >= 3.6

# Install

```bash
pip install backuptools
```

# Usage

## Create config file

1. Create and download google account service json file `credentials.json` for **google drive service**
2. Share Google Drive folder for Service Account email
3. Get `id` of Google Drive folder and put to `backuptools.config.json` below
4. Create `backuptools.config.json` with content:

```json
{
  "drive_credentials": "<path/to/credentials.json>",
  "drive_root_id": "<id_of_drive_folder>",
  "resources": [
    {
      "type": "GoogleDriveBackupResource",
      "name": "<resource_name>",
      "args": {
        "local_resource_path": "<path/to/local/source>",
        "local_backup_folder_path": "<path/to/local/backup/folder>",
        "drive_backup_folder_path": "<path/to/drive/backup/folder>"
      }
    }
  ]
}
```

## Backup

With auto name

```bash
backuptools -R <resource> backup
```

With specific name

```bash
backuptools -R <resource> backup <version>
```

## Restore

```bash
backuptools -R <resource> restore <version>
```

## List version

List all local and remote version

```bash
backuptools -R <resource> ls
```

List local only version

```bash
backuptools -R <resource> ls --local
```

List remote only version

```bash
backuptools -R <resource> ls --remote
```

## Create local version

With auto name

```bash
backuptools -R <resource> create
```

With specific name

```bash
backuptools -R <resource> create <version>
```

## Extract local version

```bash
backuptools -R <resource> extract <version>
```

## Push version

Push one local version to remote

```bash
backuptools -R <resource> push <version>
```

Push all local versions to remote

```bash
backuptools -R <resource> push --all
```

## Pull version

Pull one remote version to remote

```bash
backuptools -R <resource> pull <version>
```

Pull all remote versions to local

```bash
backuptools -R <resource> pull --all
```

## Sync versions

Upload all local versions to remote and download all remote versions to local

```bash
backuptools -R <resource> sync
```

## Remove version

Remove one version on local and remote

```bash
backuptools -R <resource> rm <version>
```

Remove one version on local

```bash
backuptools -R <resource> rm <version> --local
```

Remove one version on remote

```bash
backuptools -R <resource> rm <version> --remote
```

Remove all version on local and remote

```bash
backuptools -R <resource> rm --all
```

Remove all version on local

```bash
backuptools -R <resource> rm --all --local
```

Remove all version on remote

```bash
backuptools -R <resource> rm --all --remote
```

# Development

## Prerequisites

```bash
pipenv install
```

## Test

1. Create Google Drive Service account and download json key

2. Copy to file to path **credentials/credentials.json**

3. Create file `test/local_config.py` with content:

```python
ROOT_ID = "1rbi0gr7yMAFKqEgx-pBp6kKJx1Z4Tcgm"
CREDENTIALS_PATH = 'credentials/credentials.json'

```

4. Test command line

```
./test.sh
```
margin-official-strategies 0.0.6
Official strategies by margin for the Margin Strategy Editor
Requires Python: >=3.6

# Official Strategies

This repository contains margin's official strategies for the Python Strategy Editor of the margin
application found at [margin.io]().

This package is available for Python 3.6 or higher through pip
```
pip install margin-official-strategies
```

If you want to write your own strategies, we recommend installing the strategy SDK from
https://github.com/MarginOpenSource/strategy-sdk or using pip
```
pip install margin-strategy-sdk
```
and start by cloning the template strategy from
https://github.com/MarginOpenSource/strategy-template.

Also check out the community created strategies at
https://github.com/MarginOpenSource/community-strategies.

## License
The source code is published under the MIT License:

MIT License

Copyright (c) 2019 Margin Open Source

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
margin-strategy-sdk 0.0.11
Margin Strategy Editor SDK
Requires Python: >=3.6

# Strategy Editor SDK

This repository contains an SDK for writing Python strategies for the margin application
found at [margin.io]().

This package is available for Python 3.6 or higher through pip
```
pip install margin-strategy-sdk
```

You can import all classes and functions in your strategy by calling
```
from margin_strategy_sdk import *
```

**Note: The SDK does not provide any functionalities but merely mimics margin's strategy 
development interface. To actually run your strategy you need to start it from the margin 
application.**

The easiest way to start off your strategy implementation is by cloning the strategy
template found at https://github.com/MarginOpenSource/strategy-template.

Also check out the official strategies by margin at
https://github.com/MarginOpenSource/official-strategies and community created strategies
at https://github.com/MarginOpenSource/community-strategies.

## License
The source code is published under the MIT License:

MIT License

Copyright (c) 2019 Margin Open Source

Permission is hereby granted, free of charge, to any person obtaining a copy
of this software and associated documentation files (the "Software"), to deal
in the Software without restriction, including without limitation the rights
to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
copies of the Software, and to permit persons to whom the Software is
furnished to do so, subject to the following conditions:

The above copyright notice and this permission notice shall be included in all
copies or substantial portions of the Software.

THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE
SOFTWARE.
mygtestabcde 0.0.13
test
Keywords: python,video,stream,video stream,camera stream,sockets

# vidstream

Under construction! Not ready for use yet! Currently experimenting and planning!

Developed by Florian Dedov from NeuralNine (c) 2020

## Examples of How To Use (Buggy Alpha Version)

Creating A Server

```python
from vidstream import StreamingServer

server = StreamingServer('127.0.0.1', 9999)
server.start_server()

# Other Code

# When You Are Done
server.stop_server()
```

Creating A Client
```python
from vidstream import CameraClient
from vidstream import VideoClient
from vidstream import ScreenShareClient

# Choose One
client1 = CameraClient('127.0.0.1', 9999)
client2 = VideoClient('127.0.0.1', 9999, 'video.mp4')
client3 = ScreenShareClient('127.0.0.1', 9999)

client1.start_stream()
client2.start_stream()
client3.start_stream()
```

Check out: https://www.youtube.com/c/NeuralNine
appletrun 1.9.6
✨ Appletrun takes java file as input and runs the applet instantly with out manual compilation and html files
Requires Python: >=3.0,<4.0
Keywords: applet,applet run,appletrun

# APPLETRUN

![](https://img.shields.io/pypi/v/appletrun?style=for-the-badge)
![](https://img.shields.io/apm/l/vim-mode?style=for-the-badge)
![](https://img.shields.io/badge/requires-Java%20%3C%3D%208-red?style=for-the-badge)

AppletRun runs applet code from given java file in a new window

## 👉 Installation

```
pip install appletrun
```

if not working try `python -m pip install appletrun` or `python3 -m pip install appletrun`

## 👉 Usage

```
 appletrun nameOfFile.java
```

<p align="center">
<img src="https://user-images.githubusercontent.com/52039218/127250568-51bfd770-49c3-4d32-9da3-18627d9abde3.gif"/>
 </p>

## 👉 Issues

If you found any bugs or issue post here
https://github.com/Royal-lobster/appletrun-python/issues
nlprep 0.2.1
Download and pre-processing data for nlp tasks
Keywords: nlp tfkit classification generation tagging deep learning machine reading

<p align="center">
    <br>
    <img src="https://raw.githubusercontent.com/voidful/NLPrep/master/docs/img/nlprep.png" width="400"/>
    <br>
</p>
<p align="center">
    <a href="https://pypi.org/project/nlprep/">
        <img alt="PyPI" src="https://img.shields.io/pypi/v/nlprep">
    </a>
    <a href="https://github.com/voidful/NLPrep">
        <img alt="Download" src="https://img.shields.io/pypi/dm/nlprep">
    </a>
    <a href="https://github.com/voidful/NLPrep">
        <img alt="Build" src="https://img.shields.io/github/workflow/status/voidful/NLPrep/Python package">
    </a>
    <a href="https://github.com/voidful/NLPrep">
        <img alt="Last Commit" src="https://img.shields.io/github/last-commit/voidful/NLPrep">
    </a>
</p>

## Feature  
- handle over 100 dataset  
- generate statistic report about processed dataset  
- support many pre-processing ways  
- Provide a panel for entering your parameters at runtime  
- easy to adapt your own dataset and pre-processing utility  

# Online Explorer
[https://voidful.github.io/NLPrep-Datasets/](https://voidful.github.io/NLPrep-Datasets/)   

# Documentation
Learn more from the [docs](https://voidful.github.io/NLPrep/).  

## Quick Start
### Installing via pip
```bash
pip install nlprep
```
### get one of the dataset
```bash
nlprep --dataset clas_udicstm --outdir sentiment
```

**You can also try nlprep in Google Colab: [![Google Colab](https://colab.research.google.com/assets/colab-badge.svg "nlprep")](https://colab.research.google.com/drive/1EfVXa0O1gtTZ1xEAPDyvXMnyjcHxO7Jk?usp=sharing)**

## Overview
```
$ nlprep
arguments:
  --dataset     which dataset to use     
  --outdir      processed result output directory       
  
optional arguments:
  -h, --help    show this help message and exit
  --util        data preprocessing utility, multiple utility are supported 
  --cachedir    dir for caching raw dataset
  --infile      local dataset path
  --report      generate a html statistics report
```

## Contributing
Thanks for your interest.There are many ways to contribute to this project. Get started [here](https://github.com/voidful/nlprep/blob/master/CONTRIBUTING.md).

## License ![PyPI - License](https://img.shields.io/github/license/voidful/nlprep)

* [License](https://github.com/voidful/nlprep/blob/master/LICENSE)

## Icons reference
Icons modify from <a href="https://www.flaticon.com/authors/darius-dan" title="Darius Dan">Darius Dan</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a>    
Icons modify from <a href="https://www.flaticon.com/authors/freepik" title="Freepik">Freepik</a> from <a href="https://www.flaticon.com/" title="Flaticon">www.flaticon.com</a>