semvec/pypi-packages huggingface dataset:
pydmove 1.1
mv (using dd followed by rm) with a progressbar
License: MIT

# pydd: mv (using dd followed by rm) with a progressbar

Sometimes you want to use [`dd`](https://unix.stackexchange.com/questions/12532/dd-vs-cat-is-dd-still-relevant-these-days) instead of mv or cp. This package helps you use `dd` to move emtire contents of a dir to another dir. 

## Installation
Installable via pip`
pyppl-flowchart 0.1.5
Generating flowchart for PyPPL
License: MIT
Requires Python: >=3.6,<4.0

# pyppl_flowchart

[![Pypi][3]][4] [![Github][5]][6] [![PyPPL][7]][1] [![PythonVers][8]][4] [![Travis building][10]][11] [![Codacy][12]][13] [![Codacy coverage][14]][13]

Flowchart generator for [PyPPL](https://github.com/pwwang/PyPPL).

## Installation
```shell
pip install pyppl_flowchart
```

## Usage

### Generating flowchart for your pipeline
```python
# process definition

PyPPL().start(...).flowchart(fcfile = '/path/to/your/flowchart.svg').run()
```

### Hiding some processes from flowchart
```python
# Turn
# p1 -> p2 -> p3 -> p4 -> p5
p3.config.flowchart_hide = True
# into:
# p1 -> p2 -> p4 -> p5
```

### Theming

In your configuration:
```toml
[default.flowchart]
theme = "dark"

# other configuration
```

We have two builtin themes: `default` and `dark`:

![default](https://pyppl.readthedocs.io/en/latest/drawFlowchart_pyppl.png)

![dark](https://pyppl.readthedocs.io/en/latest/drawFlowchart_pyppl_dark.png)

You can also default your own theme in the configuration:
```toml
[default.flowchart.theme]
base = {
    shape = "box",
    style = "rounded,filled",
    fillcolor = "#ffffff",
    color = "#000000",
    fontcolor = "#000000"
}
start = { style = "filled", color = "#259229" }
end = { style = "filled", color = "#d63125" }
procset = { style = "filled", color: "#eeeeee" }
edge = {}
edge_hidden = { style = "dashed" } # for links with hidden processes
```

[1]: https://github.com/pwwang/PyPPL
[2]: https://pyppl_flowchart.readthedocs.io/en/latest/
[3]: https://img.shields.io/pypi/v/pyppl_flowchart?style=flat-square
[4]: https://pypi.org/project/pyppl_flowchart/
[5]: https://img.shields.io/github/tag/pwwang/pyppl_flowchart?style=flat-square
[6]: https://github.com/pwwang/pyppl_flowchart
[7]: https://img.shields.io/github/tag/pwwang/pyppl?label=PyPPL&style=flat-square
[8]: https://img.shields.io/pypi/pyversions/pyppl_flowchart?style=flat-square
[10]: https://img.shields.io/travis/pwwang/pyppl_flowchart?style=flat-square
[11]: https://travis-ci.org/pwwang/pyppl_flowchart
[12]: https://img.shields.io/codeclimate/maintainability-percentage/pwwang/pyppl_flowchart?style=flat-square
[13]: https://app.codacy.com/project/pwwang/pyppl_flowchart/dashboard
[14]: https://img.shields.io/codeclimate/coverage/pwwang/pyppl_flowchart?style=flat-square
pyppl-require 0.0.5
Requirement manager for processes of PyPPL
License: MIT
Requires Python: >=3.6,<4.0

# pyppl_require

Requirement manager for [PyPPL](https://github.com/pwwang/PyPPL).

## Installation
It requires [pyppl_annotate](https://github.com/pwwang/pyppl_annotate).
```shell
pip install pyppl_require
```

## Usage
```shell
> pyppl require
Description:
  Process requirement manager

Usage:
  pyppl require <--pipe AUTO> [OPTIONS]

Required options:
  -p, --pipe <AUTO>     - The pipeline script.

Optional options:
  --install <AUTO>      - Install the requirements.
                          You can specify a directory (default: $HOME/bin) to install the \
                          requirements.
                          Default: None
  -h, -H, --help        - Show help message and exit.
```

To allow your processes to be analyzed, you have to put a section in annotate using `toml` format:
```python
pXXX.config.annotate = """
@requires:
  [bedtools]
  validate: "bedtools --version"
  install: "conda install -c bioconda bedtools"
  # other annotations
"""
```

If you want define those commands using process properties and aggrs:
```python
pXXX.config.annotate = """
@requires:
  [bedtools]
  validate: "{{args.bedtools}} --version"
  install: "conda install -c bioconda bedtools"
  # other annotations
"""
```

Install to a specify directory:

```python
pXXX.config.annotate = """
@requires:
  [bedtools]
  validate: "{{args.bedtools}} --version"
  install: "conda install -c bioconda bedtools; ln -s $(which bedtools) {{bindir}}/bedtools"
  # other annotations
"""
```

`{{bindir}}` will be the directory passed to the command line.
```shell
pyppl require --pipe <your pipeline> --install </path/to/bin>
```
mostx 0.1.1.dev0
Quiz Generator
License: MIT
Requires Python: >=3.7,<4.0
Keywords: Quiz,Game

# Mostx : Quiz Generator

Generates the following quiz.

```text
B is slower than A
A is faster than C
B is faster than C
Which is the slowest one?
```

Supports multiple languages.  
(Japanese, Korean, Traditional-Chinese, English, )

## Installation

```
pip install mostx
```

## Usage

```python
import mostx

print(sorted(mostx.get_available_langs()))
# => ['chinese', 'english', 'japanese', 'korean', ]

qgen = mostx.QuizGenerator(lang='english')
quiz = qgen(choices='ABC', n_adjs=1)
print(quiz)
# Quiz(
#     statements=[
#         'C is larger than A',
#         'A is smaller than B',
#         'C is larger than B',
#     ],
#     question='Which is the smallest?',
#     choices=('A', 'B', 'C'),
#     answer='A'
# )
```

## etc

[Google App](https://play.google.com/store/apps/details?id=jp.gottadiveintopython.mostx) (Mostx + Kivy)
draw-missing 1.0.0
A Python package to visualize missing values in a data frame
License: MIT

# Drawing a Missing Plot

This is a Python package to visualize missing values in a data frame

## Installation

Run the following to install:

```
pip install drawmissing

```
## Usage

```
import drawmissing as d

# Create an object 
obj = d.Draw(df)

#Visualize Missing Values
Obj.draw_missing_plot()

```
torch-layer-normalization 0.11.0
Layer normalization implemented in PyTorch
License: MIT

# PyTorch Layer Normalization

[![Travis](https://travis-ci.org/CyberZHG/torch-layer-normalization.svg)](https://travis-ci.org/CyberZHG/torch-layer-normalization)
[![Coverage](https://coveralls.io/repos/github/CyberZHG/torch-layer-normalization/badge.svg?branch=master)](https://coveralls.io/github/CyberZHG/torch-layer-normalization)

Implementation of the paper: [Layer Normalization](https://arxiv.org/pdf/1607.06450.pdf)

## Install

```bash
pip install torch-layer-normalization
```

## Usage

```python
from torch_layer_normalization import LayerNormalization

LayerNormalization(normal_shape=normal_shape)
# The `normal_shape` could be the last dimension of the input tensor or the shape of the input tensor.
```
yplate 0.0.1
Plate Detection using YOLO v3 powered by OpenCV >=3.x
License: MIT
Keywords: Detect car/vehicle number plates with ease

[![yplate](https://img.shields.io/badge/yplate-v0.0.1-blue)](https://github.com/deepraj1729/yplate/blob/master/)  [![license](https://img.shields.io/badge/License-MIT-yellow)](https://github.com/deepraj1729/yplate/blob/master/LICENSE) [![dependencies](https://img.shields.io/badge/dependencies-packages-orange)](https://github.com/deepraj1729/yplate/blob/master/requirements.txt)
![python](https://img.shields.io/badge/python-3.5%3E-red)
# Yplate

## Detect Vehicle Number plates with YOLOv3 powered by OpenCV 3.x

## This is a dev package and doesn't contain any utilities other than showing version and model configurataion

### Check `yplate` version:

    yplate -v

### Model Configuration:

    yplate --config
s7 0.1.0
Top-level package for Seven.
License: MIT

=====
Seven
=====


.. image:: https://img.shields.io/pypi/v/s7.svg
        :target: https://pypi.python.org/pypi/s7

.. image:: https://img.shields.io/travis/dweemx/s7.svg
        :target: https://travis-ci.com/dweemx/s7

.. image:: https://readthedocs.org/projects/s7/badge/?version=latest
        :target: https://s7.readthedocs.io/en/latest/?badge=latest
        :alt: Documentation Status


.. image:: https://pyup.io/repos/github/dweemx/s7/shield.svg
     :target: https://pyup.io/repos/github/dweemx/s7/
     :alt: Updates



Package bundle to handle structured files


* Free software: MIT
* Documentation: https://s7.readthedocs.io.


Features
--------

* TODO

Credits
-------

This package was created with Cookiecutter_ and the `briggySmalls/cookiecutter-pypackage`_ project template.

.. _Cookiecutter: https://github.com/audreyr/cookiecutter
.. _`briggySmalls/cookiecutter-pypackage`: https://github.com/briggySmalls/cookiecutter-pypackage
faster-than-csv 1.4
Faster & simpler requests replacement for Python
License: MIT

python3, cpython, speed, cython, c, performance, compiled, native, fast, nim, csv, https://nim-lang.org
Platform: Linux
Platform: Darwin
Platform: Windows
Classifier: Development Status :: 5 - Production/Stable
Classifier: Environment :: Console
Classifier: Environment :: Other Environment
Classifier: Intended Audience :: Developers
Classifier: Intended Audience :: Other Audience
Classifier: Natural Language :: English
Classifier: Operating System :: OS Independent
Classifier: Operating System :: POSIX :: Linux
Classifier: Programming Language :: Python
Classifier: Programming Language :: Python :: 3
Classifier: Programming Language :: Python :: 3 :: Only
Classifier: Programming Language :: Python :: 3.8
Classifier: Programming Language :: Python :: Implementation :: CPython
Classifier: Topic :: Software Development
Requires-Python: >=3.8
Description-Content-Type: text/markdown