semvec/pypi-packages huggingface dataset:
pdbio 0.4.2
Pandas-based Data Handler for VCF, BED, and SAM Files
Requires Python: >=3.6

pdbio
=====

Pandas-based Data Handler for VCF, BED, and SAM Files

[![wercker status](https://app.wercker.com/status/fe5472a8f890edd3169e7bae5b648bac/s/master "wercker status")](https://app.wercker.com/project/byKey/fe5472a8f890edd3169e7bae5b648bac)

Installation
------------

```sh
$ pip install -U pdbio
```

Python API
----------

Example of API call

```py
from pprint import pprint
from pdbio.vcfdataframe import VcfDataFrame

vcf_path = 'test/example.vcf'
vcfdf = VcfDataFrame(path=vcf_path)

pprint(vcfdf.header)      # list of header
pprint(vcfdf.samples)     # list of samples
print(vcfdf.df)           # VCF dataframe

vcfdf.sort()              # sort by CHROM, POS, and the other
print(vcfdf.df)           # sorted dataframe
```

Command-line interface
----------------------

Example of commands

```sh
# Convert VCF data into sorted TSV data
$ pdbio vcf2csv --sort --tsv test/example.vcf

# Convert VCF data into expanded CSV data
$ pdbio vcf2csv --expand-info --expand-samples test/example.vcf

# Sort VCF data by CHROM, POS, and the other
$ pdbio vcfsort test/example.vcf
```

Run `pdbio --help` for more information.
btd.sphinx.inheritance-diagram 2.3.1.post1
Embedding diagrams rendered with inheritance_diagram.
Requires Python: >=3.4
Keywords: Sphinx Documentation Inheritance Diagram Graphviz

[![Sourcecode on GitHub](https://img.shields.io/badge/BuildTheDocs-sphinx.inheritance_diagram-323131.svg?logo=github&longCache=true)](https://github.com/buildthedocs/sphinx.autoprogram)
<!--[![License](https://img.shields.io/badge/Apache%20License,%202.0-bd0000.svg?longCache=true&label=code%20license&logo=Apache&logoColor=D22128)](LICENSE.md)-->
[![GitHub tag (latest SemVer incl. pre-release)](https://img.shields.io/github/v/tag/buildthedocs/sphinx.inheritance_diagram?logo=GitHub&include_prereleases)](https://github.com/buildthedocs/sphinx.inheritance_diagram/tags)
[![GitHub release (latest SemVer incl. including pre-releases)](https://img.shields.io/github/v/release/buildthedocs/sphinx.inheritance_diagram?logo=GitHub&include_prereleases)](https://github.com/buildthedocs/sphinx.inheritance_diagram/releases/latest)
[![GitHub release date](https://img.shields.io/github/release-date/buildthedocs/sphinx.inheritance_diagram?logo=GitHub&)](https://github.com/buildthedocs/sphinx.inheritance_diagram/releases)
[![Libraries.io status for latest release](https://img.shields.io/librariesio/release/pypi/btd.sphinx.inheritance_diagram)](https://libraries.io/github/buildthedocs/sphinx.inheritance_diagram)
[![Requires.io](https://img.shields.io/requires/github/buildthedocs/sphinx.inheritance_diagram)](https://requires.io/github/buildthedocs/sphinx.inheritance_diagram/requirements/?branch=master)  
<!--[![Travis](https://img.shields.io/travis/com/buildthedocs/sphinx.inheritance_diagram?logo=Travis)](https://travis-ci.com/buildthedocs/sphinx.inheritance_diagram)-->
[![PyPI](https://img.shields.io/pypi/v/btd.sphinx.inheritance_diagram?logo=PyPI)](https://pypi.org/project/sphinx.inheritance_diagram/)
![PyPI - Status](https://img.shields.io/pypi/status/btd.sphinx.inheritance_diagram?logo=PyPI)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/btd.sphinx.inheritance_diagram?logo=PyPI)
[![Dependent repos (via libraries.io)](https://img.shields.io/librariesio/dependent-repos/pypi/btd.sphinx.inheritance_diagram)](https://github.com/buildthedocs/sphinx.inheritance_diagram/network/dependents)  
<!-- [![Read the Docs](https://img.shields.io/readthedocs/btd-sphinx-inheritance_diagram)](https://btd-sphinx-inheritance_diagram.readthedocs.io/en/latest/)-->

# btd.sphinx.inheritance_diagram

This is a patched version of [`sphinx.ext.inheritance_diagram`](https://github.com/sphinx-doc/sphinx).

--------------------

## Added features

* TBD

--------------------

## Install using `pip`

```
$ pip install btd.sphinx.inheritance_diagram
```

----------------------

SPDX-License-Identifier: BSD-2-Clause
flexfolio 1.0.4
IB FlexStatement to PyFolio bridge
Keywords: flexfolio

|docker build| |docker pulls| |license| 

.. |docker build| image:: https://img.shields.io/docker/cloud/build/xridge/flexfolio.svg
.. |docker pulls| image:: https://img.shields.io/docker/pulls/xridge/flexfolio.svg
.. |license| image:: https://img.shields.io/badge/License-Apache%202.0-blue.svg

=========
flexfolio
=========

Python Package & Docker image to fetch Flex Statements from Interactive Brokers
and convert it into PyFolio compatible data structures.

Usage
-----
.. code-block:: shell

  $ docker run -v $(pwd)/workdir:/workdir xridge/flexfolio:latest fetch_statement IB_API_KEY QUERY_ID /workdir/flex_report.xml
  2019-04-06 16:23:17,097 - flexfolio.cli - INFO - Requesting statement
  2019-04-06 16:23:17,770 - flexfolio.cli - INFO - Downloading statement
  
  $ docker run -v $(pwd)/workdir:/workdir -e IEX_TOKEN=pk_TOKEN_COMES_HERE xridge/flexfolio:latest statement_to_pyfolio --output-format hdf5 /workdir/flex_report.xml /workdir
  2019-04-06 16:24:42,153 - flexfolio.cli - INFO - Storing returns to /workdir/flex_report-returns.hdf5
  2019-04-06 16:24:57,202 - flexfolio.cli - INFO - Storing positions to /workdir/flex_report-positions.hdf5
  2019-04-06 16:24:57,280 - flexfolio.cli - INFO - Storing transactions to /workdir/flex_report-transactions.hdf5

License
-------
Copyright (c) 2019 `xridge.io`_

Licensed under the Apache License, Version 2.0 (the "License");
you may not use this file except in compliance with the License.
You may obtain a copy of the License at

`Apache License Version 2.0`_

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.

.. _`xridge.io`: https://xridge.io
.. _`Apache License Version 2.0`: http://www.apache.org/licenses/LICENSE-2.0
swy 0.0.3
SWY Project
Requires Python: >=3.7

[![Build Status](https://travis-ci.com/Haytek/swy.svg?branch=master)](https://travis-ci.com/Haytek/swy)
[![Coverage Status](https://coveralls.io/repos/github/Haytek/swy/badge.svg?branch=master)](https://coveralls.io/github/Haytek/swy?branch=master)
![PyPI](https://img.shields.io/pypi/v/swy)

# swy

yop

# Pushing 0.0.2
cqupt 0.1.2
CQUPT Piper is a command line tool to get info from jwzx.cqupt.edu.cn
Requires Python: >=3.5

```
  _____  _____  _     _ ______ _______    ______ _
 / ____|/ ___ \| |   | |  __  \__   __|  |  __  (_)
| |    | |   | | |   | | |__| |  | |     | |__| |_ ____    ___ _ __
| |    | |  _| | |   | |  ____/  | |     |  ____/ |  __ \ / _ \ '__\
| |___ | |__\  | |___| | |       | |     | |    | | |__| |  __/ |
 \____/ \____/\_\_____/|_|       |_|     |_|    |_|  ___/ \___|_|
                                                  |_|
```

![](https://img.shields.io/badge/build-passing-brightgreen) ![](https://img.shields.io/badge/license-MIT-blue) ![](https://img.shields.io/badge/Python-3%2B-yellowgreen)


## Documentation

Documentation is at [https://cquptpiper.xjj.pub](https://cquptpiper.xjj.pub)

## Contribution

You can help create better `crawler` under directory [crawler](https://github.com/mivinci/cqupt-piper/tree/master/cqupt/crawlers). 

Fork this repo and commit your request!

## Todo

- [ ] **GUI** Expected in version 2+

## License

© XJJ, 2019~datetime.now()

Released under the [MIT License](https://github.com/mivinci/cqupt-piper/blob/master/LICENSE)
django-cjswidget 0.4.1
A replacement for the Select widget with fancy new features - powered by choices.js!
Requires Python: >=3.6

# django-cjswidget  [![PyPI](https://img.shields.io/pypi/v/django-cjswidget)](https://pypi.org/project/django-cjswidget/)
A replacement for the Select widget with fancy new features - powered by 
[choices.js](https://github.com/jshjohnson/Choices)!

## Install

1.  Add "cjswidget" to your `INSTALLED_APPS`:
```python
INSTALLED_APPS = [
    ...
    'cjswidget',
]
```

## Use
Use in place of a normal select widget, that's all!
```python
from cjswidget.widgets import CJSWidget

class MyForm(ModelForm):
    class Meta:
        model = Profile
        fields = ('country', 'region')
        widgets = {
            'country': CJSWidget(),
            'region': CJSWidget(options={'shouldSort': False}),
        }
```

## License

This software is released under the MIT license.
```
Copyright (c) 2019-2020 Luke Rogers

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.
```
uvarint 1.2.0
Unsigned variable-length integers
Requires Python: >=3.6

# uvarint

Unsigned variable-length integers. A type of [variable-length quantity].

# Usage

    import uvarint

    buffer = uvarint.encode(16384)                  # b'\x80\x80\x01'
    integer, bytes_read = uvarint.decode(buffer)    # 16384

    big = uvarint.encode(2 ** 63)
    uvarint.decode(big)              # Raises OverflowError; decoder limited to 9 bytes by default
    uvarint.decode(big, limit=16)    # Success; use math.inf for unlimited decoding

    multiple  = uvarint.encode(100)
    multiple += uvarint.encode(200)
    multiple += uvarint.encode(300)
    uvarint.expect(3, multiple).integers    # [100, 200, 300]
    uvarint.cut(0, multiple)                # Slice(integers=[], rest=b'd\xc8\x01\xac\x02')
    uvarint.cut(1, multiple)                # Slice(integers=[100], rest=b'\xc8\x01\xac\x02')
    uvarint.cut(2, multiple)                # Slice(integers=[100, 200], rest=b'\xac\x02')
    uvarint.cut(3, multiple)                # Slice(integers=[100, 200, 300], rest=b'')

# References

 - [Specification]

# License

This module is licensed under the MIT license.

[variable-length quantity]: https://en.wikipedia.org/wiki/Variable-length_quantity
[Specification]: https://github.com/multiformats/unsigned-varint
jetkiller 1.1.0
Enhance data visualizations using the "jet" colormap.

# Jet Killer

Jet Killer converts images using the "jet" colormap to a better
one (by default "viridis") by using directly the pixel values,
without any knowledge about the underlying data.

It can be used as a tool to enhance data visualizations for which
the original dataset is unavailable. Use cases include:

* enhancing figures from sources who made an unfortunate
  colormap choice,
* enhancing graphs for which the original data may be lost,
* enhancing visualizations without having to regenerate it from the
  original dataset.

![Principle](docs/schematic_principle.png)


## Installation

To install and use Jet Killer, Python 3 is required.

The following command installs the `jetkiller` command
and the `jetkiller` package:

```
pip3 install jetkiller
```

For details and alternative installation methods,
read the [user guide](docs/user_guide.md).


## Basic Usage

### With the GUI

To launch the GUI, use the following command:

```
jetkiller --gui
```

![Screenshot of the GUI](docs/screenshot_gui.png)


### From the Command Line

Use the following command to convert `input_file` to `output_file`:

```
jetkiller input_file output_file
```

For more details, read the [user guide](docs/user_guide.md).

### From Python

To convert images, import the `jetkiller` package and
use the `jetkiller.convert_file` function:

```python
import jetkiller
jetkiller.convert_file("input_image.png", "output_image.png")
```

For more details, read the [user guide](docs/user_guide.md).

## Documentation

The reference documentation is the [user guide](docs/user_guide.md).

## Release History

All releases of this project are listed on the tag page of this
repository.

See [CHANGES.md](CHANGES.md) for more details on the content of each release.


## Development Roadmap

The standalone version of Jet Killer is considered as complete
and will not have any major new features.

Here are a few ideas on how to further improve the user experience:

- develop an extension for GIMP (probably with Python-Fu)
- develop an extension for Inkscape (probably using Python)


## Versioning

Jet Killer attempts to follow the [Semantic Versioning
Specification](https://semver.org/spec/v2.0.0.html) for its version
numbers.


## License

Jet Killer is distributed under the MIT License. See
[LICENSE-MIT](LICENSE-MIT) for more details.
peperoncino 0.0.5
peperoncino: A library for easy data processing for pandas
Requires Python: >=3.７,<4.0

# peperoncino: A library for easy data processing for pandas

## Install

```
$ pip install peperoncino
```

## How to use

### Processing DataFrame
```python
import peperoncino as pp

pipeline = pp.Pipeline(
    # query data
    pp.Query("bar <= 3"),
    # assign new feature
    pp.Assign(hoge="foo * bar"),
    # generate combination feature
    pp.Combinations(["foo", "baz"], ["*", "/"]),
    # target encoding
    pp.TargetEncoding(["baz"], "y", ref=0),
    # select features
    pp.Select(
        ["hoge", "*_foo_baz", "TARGET_ENC_baz_BY_y", "y"],
        lackable_cols=["y"],
    )
)

# execute the processing
train_df, val_df, test_df = \
    pipeline.process([train_df, val_df, test_df])
```

### Predefined processings

| name | description |
| :--- | :---------- |
| `ApplyColumn` | Apply a function to a column. |
| `AsCategory` | Assign `category` dtype to columns. |
| `Assign` | Assign a feature by a formula. |
| `Combinations` | Create combination features. |
| `DropColumns` | Drop columns. |
| `DropDuplicates` | Drop duplicate rows. |
| `Pipeline` | Chain processings. |
| `Query` | Query rows by a given condition. |
| `RenameCOlumns` | Rename columns. |
| `Select` | Select columns. |
| `StatsEncoding` | Encode columns by statistical values of another column. |
| `TargetEncoding` | Target Encoding with smoothing. |

### Define processing
All processings are subclass of `pp.BaseProcessing`.  
All you need is define the `_process(self, dfs: List[pd.DataFrame]) -> List[pd.DataFrame]` function.

```python
class ExampleProcessing(pp.BaseProcessing):
    def _process(self, dfs: List[pd.DataFrame]) -> List[pd.DataFrame]:
        return [df + 1 for df in dfs]
```

If your processing doesn't depent on each other data frames, then use `pp.SeparatedProcessing`.

```python
class ExampleProcessing(pp.SeparatedProcessing):
    def sep_process(self, df: pd.DataFrame) -> pd.DataFrame:
        return df * 2
```

If you need to merge all dataframes and then apply your processing, use `pp.MergedProcessing`.

```python
class ExampleProcessing(pp.SeparatedProcessing):
    def simul_process(self, df: pd.DataFrame) -> pd.DataFrame:
        return df.assign(col1_mean=df['col1'].mean())
```
gamestart 0.0.1
Pygame wrapper for learners, jammers and educators
Requires Python: >=3.6

# gamestart - a pygame wrapper for beginners and game jammers

This is a high level api wrapper for pygame, for making games with Python easier and quicker.

Heavily inspired by pygame-zero, Scratch, bitsbox, and game engines such as unity,  
I think there is an opportunity to design a set of API both satisfy the need of beginners  
and game makers who wish a quick result.

Some features: 
- some built-in assets for quick starting and code learning scenarios
- draw loops are managed, so users can focus on actor and scene building

# Quick minimal example

```python
from gamestart import *

actor('monster')

start()
```

This draws a monster on the screen...

# Why another pygame wrapper?

## Why not pygame-zero

Gamestart takes over draw loop management. This makes user code shorter and allowing  
future scene management features.

Gamestart also comes with some built-in asset, for starters and prototypers.  

Gamestart games are run with just Python - it is an option for pygame-zero, but a default in gamestart

## Why not processing.py

Gamestart is driven by Python, instead a Python-Java middle layer.  

Gamestart manages the draw loop.

# Some more examples

Look at the root folder - files like 1_quickstart.py are examples.