semvec/pypi-packages huggingface dataset:
uw-highP-geophysics-tools 0.8.1.post1
load and evaluate splines developed in MatLab -- for Gibbs energy splines, also calculates several other thermodynamic variables for pure substances or single-solute solutions

These packages have been tested with Python 3.7 on OSX and with Python 3.6.8 on Windows. 
Although they are intended to be platform-independent, they have not been tested on other operating systems.

Installation requires [git](https://www.git-scm.com/book/en/v2/Getting-Started-Installing-Git).  
Also make sure you have the [most recent version of pip](https://pip.pypa.io/en/stable/installing/#upgrading-pip) 
installed.  

The following packages will be installed:
- [scipy](https://scipy.org/scipylib/index.html) (also installs [numpy](http://numpy.org/))
- [hdf5storage](https://pythonhosted.org/hdf5storage/)
- [psutil](https://pypi.org/project/psutil/)

Demo scripts may also require the following packages, which must be 
[installed](https://packaging.python.org/tutorials/installing-packages/) manually:
- [matplotlib](https://matplotlib.org/users/installing.html)
- [jupyter](https://jupyter.readthedocs.io/en/latest/install.html)

Run the following command in Terminal on OSX or in Git Bash on Windows.  

``pip3 install uw-highP-geophysics-tools``

Note that scripts can be run in the regular command prompt on Windows; it is only the install that needs to be done 
in Git Bash.
dfreduce 1.7
Automatic size reduction for pandas dataframe

# dfreduce

[![PyPI version](https://badge.fury.io/py/dfreduce.svg)](https://badge.fury.io/py/dfreduce)

Description: Automatically reduce the memory size of your pandas dataframe

## Installation
pip install dfreduce

## Usage
```
from dfreduce.core import DFReduce
import pandas as pd

df = pd.read_csv('https://ed-public-download.app.cloud.gov/downloads/Most-Recent-Cohorts-Scorecard-Elements.csv')
df_reduced = DFReduce(df).reduce()

# Alternatively, you can also use the inplace parameter to overwrite input dataframe
DFReduce(df, inplace=True).reduce()
```

## Uninstallation

```
pip uninstall dfreduce
```
humulus 0.1.0
Humulus is a beer recipe builder.

.. image:: https://drone.shoup.io/api/badges/shouptech/humulus/status.svg
  :target: https://drone.shoup.io/shouptech/humulus
  :alt: Drone build status

.. image:: https://codecov.io/gh/shouptech/humulus/branch/master/graph/badge.svg
  :target: https://codecov.io/gh/shouptech/humulus
  :alt: Code Coverage

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

.. image:: https://badge.fury.io/py/humulus.svg
  :target: https://badge.fury.io/py/humulus
  :alt: PyPi version

Humulus
=======

Humulus is an open-source homebrew beer recipe webapp built using Flask_ and
CouchDB_.

.. _Flask: http://couchdb.apache.org/
.. _CouchDB: http://flask.pocoo.org/

Documentation
-------------

For help installing and using Humulus, please visit the documentation_.

.. _documentation: https://humulus.shoup.io/

License
-------

Humulus is licensed under the `Apache Version 2.0 license`_.

.. _`Apache Version 2.0 license`: LICENSE
sungear 1.1.3
Web based Sungear visualization.
Requires Python: >=3.6

# Sungear

## Introduction

Sungear visulization.

## Install

```bash
# if you want the standalone web app
$ pip install sungear[web]

# if you only want to use the python fuctions
$ pip install sungear

```

## Example

### See It In Action

https://sungear.herokuapp.com/

### Standalone Web App

```bash
$ python -m sungear
```

Then open browser to http://localhost:5000 to use.

### Python Functions

```python
import sungear

item_lists = {
    'name1': ['item1', 'item2', ...],
    'name2': ['item1', 'item2', ...],
}

result = sungear.sungear(item_lists)
```

This contains coordinates of nodes and vertices.

## Development Notes

```bash
# clone with submodules
$ git clone --recurse-submodules https://github.com/zachary822/sungear.git
# build web assets
$ python setup.py webpack
```

## License

[MIT](./LICENSE)

## Reference

1. Christopher S. Poultney, Rodrigo A. Gutiérrez, Manpreet S. Katari, Miriam L. Gifford, W. Bradford Paley, Gloria M. Coruzzi, Dennis E. Shasha, Sungear: interactive visualization and functional analysis of genomic datasets, Bioinformatics, Volume 23, Issue 2, 15 January 2007, Pages 259–261, https://doi.org/10.1093/bioinformatics/btl496
dropboxignore 0.2.0
Tool allowing for watching sync directory and setting Dropbox to ignore paths using .dropboxignore

# dropboxignore
Python implementation of Dropbox equivalent of .gitignore: .dropboxignore.
At the beginning tool will exclude using Selective Sync in Dropbox all directories matching rules stored in .dropboxignore. Later it will monitor the Dropbox's directory using inotify and exclude them before Dropbox sync them.

![Azure DevOps builds](https://img.shields.io/azure-devops/build/michalpkarol/dropboxignore/1.svg?style=flat-square)
![Azure DevOps tests (compact)](https://img.shields.io/azure-devops/tests/michalpkarol/dropboxignore/1.svg?compact_message&style=flat-square)
![Azure DevOps coverage](https://img.shields.io/azure-devops/coverage/michalpkarol/dropboxignore/1.svg?style=flat-square)

## Usage
1) Create .dropboxignore file
2) Run `dropboxignore $PATH_TO_DROPBOX_DIRECTORY`