semvec/pypi-packages huggingface dataset:
reproduce-wem-taxonomy 2020.1.29
Reproduce the database of use cases for WEMs.
Requires Python: >=3.7

# Towards a Taxonomy of Word Embedding Models: The Database

This repository contains the code that was used to collect relevant 
publications and store them in a Postgres Database.
You are welcome to reproduce our database!
Note however that the search results on Google Scholar may have been updated
since our publication, leading to slightly different results.

As a prerequisite, you must have set up a Postgres database with the proper 
database schema. To do this, you can execute our Postgres schema dump provided 
in `data/wem_taxonomy_schema.sql` with the `psql` shell:
```bash
psql dbname < data/wem_taxonomy_schema.sql
```
where `dbname` is the name of an empty database that you have already created 
for this purpose.
You must also create a user called 'taxonomist' who will own the created
tables. If you intend to use the database with our Use Case Collector (UCC)
tool later on, you should execute the above schema dump with a Postgres user 
who has root privileges.
The root privileges are needed to install the Postgres trigram extension (pg_trgm).

## Step 1a): Installing from PyPI

Simply execute
```bash
python3 -m pip install reproduce_wem_taxonomy
```
to install the needed packages.


## Step 1b): Installing from source

First, clone this repository. Then, from within the repository root directory,
pull in the `pubfisher` submodule:
```bash
git submodule update --remote lib/pubfisher
```
Now, install this module from source using pip:
```bash
python3 -m pip install -e lib/pubfisher
```
After that, you can install the `reproduce_wem_taxonomy` package as well:
```bash
python3 -m pip install -e .
```

## Step 2: Collecting the publications from Google Scholar

In order to finally collect the publications,
simply execute the module `fish_wem_taxonomy`:
```bash
python3 -m reproduce_wem_taxonomy.collect_relevant_publications
```

The publications are now stored in the database table 'publications' of
your previously created Postgres database.
bio-jtools 0.2.3
Various bioinformatics tools in one package

# bio-jtools

Various bioinformatics tools in one package

[![Conda](https://img.shields.io/conda/pn/jrhawley/bio-jtools.svg)](https://anaconda.org/jrhawley/bio-jtools)
[![Python version](https://img.shields.io/pypi/pyversions/bio-jtools.svg)](https://pypi.python.org/pypi/bio-jtools)
[![PyPI](https://img.shields.io/pypi/v/bio-jtools.svg)](https://pypi.python.org/pypi/bio-jtools)
[![Wheel](https://img.shields.io/pypi/wheel/bio-jtools.svg)](https://pypi.python.org/pypi/bio-jtools)
[![Implementation](https://img.shields.io/pypi/implementation/bio-jtools.svg)](https://pypi.python.org/pypi/bio-jtools)

[![Python build](https://github.com/jrhawley/bio-jtools/workflows/Python%20packaging/badge.svg)](https://github.com/jrhawley/bio-jtools/actions?workflow=Python+packaging)
[![Conda build](https://github.com/jrhawley/bio-jtools/workflows/Conda%20packaging/badge.svg)](https://github.com/jrhawley/bio-jtools/actions?workflow=Conda+packaging)

## Usage

```shell
jtools <sub-command>
```

## Installation

```shell
# pip
pip install bio-jtools

# conda
conda install -c jrhawley bio-jtools
```

## Documentation

For detailed documentation, see the [GitHub Wiki](https://github.com/jrhawley/bio-jtools/wiki).
cli-changelog 1.3.0
A changelog update cli tool

# changelog-cli

This tool is aiming at reducing conflicts in trunk-based or feature-based git developement.

## Install

```shell
> pip install cli_changelog
```

## Usage

```text
usage: changelog [-h] [-c message] [-r version] [-f FILENAME]

Changelog administration tool.

optional arguments:
  -h, --help            show this help message and exit
  -c message, --create message
                        creates an entry with this actual message to be added
                        to the changelog
  -r version, --release version
                        releases the changelog byt gathering all entries
  -f FILENAME, --filename FILENAME
                        the filename to put the message in if you don't want
                        to use the branch name
  -t, --commit          commit the created/deleted/modified files by this
                        command
```

## Flow example 

```shell
> changelog -c "Initial import" -f init
> changelog -c "Added readme content" -f readme
```

will give this layout

```text
├── CHANGELOG.md
├── README.md
├── changelog.py
└── changelogs/
│  └──── unreleased/
│     ├──── init.md
│     └──── readme.md
└── requirements.txt
```

And now releasing version 1.0.0 like this

```shell
> changelog -r 1.0.0
```

will give this layout

```text
├── CHANGELOG.md
├── README.md
├── changelog.py
└── requirements.txt
```

## Requirements

* tested with python3