semvec/pypi-packages huggingface dataset:
pySolution 0.0.2.1.4.3
Computes details of solution for modeling purposes
Keywords: python,solution chemistry,activity coefficient,osmosis,reverse osmosis,chemistry

A package that was created for the purpose of process modeling in different membranes. This is a solution chemistry toolkit
that can compute details of "saline" solutions such as the activity coefficient of each ion (using the Pitzer model),
osmotic coefficient, ionic strength, density of the solution, etc.
meme-lang 1.0.2
Package for meme language
Requires Python: >=3.6

# Meme

A string template language hosted by Python3 runtime. Conventionally, the source code of this language is written in plain text with utf-8 encoding and stored in a file with extension ".meme".

## Philosophy

Human beings repeat one another, even themselves from time to time. Emerging from the dark flow of collective intelligence, memes are how we degenerated web inhabitants express our feelings, thoughts and our very existence. Yet, such expression is causing more and more brothers to suffer from language or behavioral disorders (e.g. little-pinky or vim-handicapped). The meme language is therefore introduced to DRY the web environment and encourage diversity across our mental homeland.

## Grammar

To keep the language implementation concise, the grammar of said language is aligned with the syntax described in [PEP 498](https://www.python.org/dev/peps/pep-0498/). 

Later you may find a detailed and formalized specification in `spec.pdf`, if the author (?) is charged up and functional.

## Implementation

Following the creed of DRY, we can use only 6\* lines of code to implement said language. You may inspect the source code if you like. Low code, low errors; no code, no error. Think about it.

\* As the development goes on, this may no longer be true; yet the creed shall guide us.

## Installation

The language is based on [Python 3](https://www.python.org/), which can be installed [directly](https://www.python.org/downloads/) or via your system package manager. Make sure that you install a version that is superior than or equal to Python 3.6. Make sure that you also install [pip](https://pypi.org/project/pip/), the package manager for Python as well.

Then run

```bash
pip install --upgrade meme-lang
```

and meme-lang will be installed to your device.

## Usage

Using meme is easy.

```python
# import
from meme import Meme

# your meme template name
meme_name = ".meme"
# the contents to be filled into the meme template
meme_content = {}
# get the str of meme
meme = Meme(meme_name).print(**meme_content)

# output
print(meme)
```

You may also create various memes and collect them for future use.

## Disclaimer

This is merely a joke. Don’t take this seriously.
my-first-plugin-goahead-jakemyday 0.0.1
A small example package to learn how to upload packages
Requires Python: >=3.6

# opensesame_plugin_0.1

README to be completed after initial setup is successful

This is a simple example package. You can use
[Github-flavored Markdown](https://guides.github.com/features/mastering-markdown/)
to write your content.
phrase-tokenizer 0.1.3
Tokenize an English sentence to phrases
Requires Python: >=3.7,<4.0

# Phrase Tokenizer
[![pytest](https://github.com/ffreemt/phrase-tokenizer/actions/workflows/on-push.yml/badge.svg)](https://github.com/ffreemt/phrase-tokenizer/actions)[![python](https://img.shields.io/static/v1?label=python+&message=3.7%2B&color=blue)](https://www.python.org/downloads/)[![Codacy Badge](https://app.codacy.com/project/badge/Grade/d7e1c1f44dbb423099a929aadd7db2fd)](https://www.codacy.com/gh/ffreemt/phrase-tokenizer/dashboard?utm_source=github.com&amp;utm_medium=referral&amp;utm_content=ffreemt/phrase-tokenizer&amp;utm_campaign=Badge_Grade)[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)[![docstyle: google](https://img.shields.io/badge/docstyle-google-green.svg)](https://google.github.io/styleguide/pyguide.html)[![License: MIT](https://img.shields.io/badge/License-MIT-yellow.svg)](https://opensource.org/licenses/MIT) [![PyPI version](https://badge.fury.io/py/phrase-tokenizer.svg)](https://badge.fury.io/py/phrase-tokenizer)

Tokenize an English sentence to phrases via benepar.

## Installation

```bash
pip install phrase-tokenizer
# pip install phrase-tokenizer -U to update
# or to install the latest from github:
# pip git+https://github.com/ffreemt/phrase-tokenizer.git
```

Or clone the repo `https://github.com/ffreemt/phrase-tokenizer.git`:

```bash
git clone https://github.com/ffreemt/phrase-tokenizer.git
cd phrase-tokenizer
pip install logzero benepar tensorflow
```
Or use `poetry`, e.g.
```bash
git clone https://github.com/ffreemt/phrase-tokenizer.git
cd phrase-tokenizer
poetry install
```

## Usage

```python
from phrase_tokenizer import phrase_tok

res = phrase_tok("Short cuts make long delays.")
print(res)
# ['Short cuts', 'make long delays']

# verbose=True turns on verbose to see the tokenizing process
res = phrase_tok("Short cuts make long delays", verbose=True)
# ',..Short.cuts,.make..long.delays..'
```

Consult the source code for details.

## For Developers

```bash
git clone https://github.com/ffreemt/phrase-tokenizer.git
cd phrase-tokenizer
pip install -r requirements-dev.txt
```

In `ipython`, ``plot_tree`` is able to draw a nice tree to aid the development, e.g.,

```python
from phrase_tokenizer.phrase_tok import plot_tree

plot_tree("Short cuts make long delays.")
```
![img](https://github.com/ffreemt/phrase-tokenizer/blob/master/img/short_cuts.png?raw=true)