semvec/pypi-packages huggingface dataset:
xlsform-filler-data 0.1.2
A tool for generating fake testing data based on an XLSform. 
Requires Python: >=3.8,<4.0

# XLSform filler data

A commandline tool for creating dummy/test data from XLSform surveys.

## Installation
```pip install xlsform-filler-data```

## Usage
To create a dummy dataset, with a default number of rows(100) from a XLSform source:
```xlsform-filler-data <source-file-path>/<filename.xlsx>```

To specify the number of rows to create, use the *-r* flag. Example:
```xlsform-filler-data <source-file-path>/<filename.xlsx> -r 200```

To specify the output path and filename, pass the *-o* flag. Example:
```xlsform-filler-data <source-file-path>/<filename.xlsx> -o <./myfile.xlsx>```

## Roadmap
As of version *0.1.1* the tool does not properly randomise multiple choice questions; omits some variables such as 'start' and 'end'; does not maintain the order of the variables; and does not incorporate constraints or cascading choice lists. These limitations will be adddressed in future releases.
gitlab-search 0.1.0a4
Command line tool for searching across GitLab projects
Requires Python: >=3.10

# gitlab-search

Command line tool for searching for text terms across several GitLab(TM) projects

[![release](https://img.shields.io/pypi/v/gitlab-search?label=release)](https://pypi.org/project/gitlab-search/)
[![python](https://img.shields.io/pypi/pyversions/gitlab-search)](https://pypi.org/project/gitlab-search/)
[![pipeline status](https://gitlab.com/ErikKalkoken/gitlab-search/badges/main/pipeline.svg)](https://gitlab.com/ErikKalkoken/gitlab-search/-/commits/main)
[![license](https://img.shields.io/badge/license-MIT-green)](https://gitlab.com/ErikKalkoken/gitlab-search/-/blob/master/LICENSE)
[![pre-commit](https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white)](https://github.com/pre-commit/pre-commit)
[![Code style: black](https://img.shields.io/badge/code%20style-black-000000.svg)](https://github.com/psf/black)
[![chat](https://img.shields.io/discord/790364535294132234)](https://discord.gg/zmh52wnfvM)

## Contents

- [Description](#description)
- [Features](#features)
- [Installation](#installation)
- [Usage](#usage)

## Description

This tool let's you perform a full text search across your personal projects, your group projects and/or public projects of any user on GitLab (TM).

GITLAB is a trademark of GitLab Inc. in the United States and other countries and regions

>**Note**: This is not an official tool from GitLab and the author has no affiliation with GitLab Inc.

## Features

- Search for occurrences of a text term across all files of all projects known to a user
- Matches are given with exact location and link to file on GitLab
- Search personal projects and group projects
- Search public projects of other users
- Limit search to personal projects or groups
- Exclude specific projects from search
- Limit search to files with specific extensions
- Search for several terms in the same run
- Works with custom gitlab domain

## Installation

You can install this tool from PyPI with the following command:

```bash
pip install gitlab-search
```

## Usage

To use this tool you need a private API token, which you can create on the GitHub profile page.

To run a search over all your projects for the term `kalkoken` you can enter:

```bash
github-search kalkoken
```

> **Note**: The tool will search all personal projects and known group projects by default. You can change the scope of what projects are searches through command line arguments.

When you start the command for the first time it will run setup, e.g. to configure your token. The configuration will be saved and re-used the next time you use the command. If you want to update your configuration your can setup again any time list this:

```bash
github-search --setup
```

> **Hint**: gitlab-search will store the configuration in the home directory of the current user in the file `.gitlabsearch`.

You can get a full overview of the command syntax with:

```bash
github-search -h
```
astrotree 1.1.5
ADS-powered reference tree-builder for the Astro community!
Requires Python: >=3.7, <4
Keywords: academic,references,development

# Welcome to astrotree!

A lightweight, purely python package to handle reference trees.
This project evolved because of a personal urge to organize literature from my day-to-day.
Note that this is not a reference manager: if you are looking for a python-based reference manager, look no further than [Papis](https://pypi.org/project/papis/)!

This project helps you connect literature entries: given an article, you can choose to build a tree of other articles that connect to it. These are articles referenced in the article of interest (references), or works that cited it (citations). Trees can be built to arbitrary depths, limited only by resources available to python and records on the internet, at any level of the tree.

The project presently uses the NASA-ADS API (see [ADS Docs](https://ui.adsabs.harvard.edu/help/api/api-docs.html#servers)) to launch queries and is suited to my use case; any efforts to contribute and extend it to other APIs are welcome!

# Installation

Install directly through pip:

    pip install astrotree

# Prerequisite

Before you can start to use this application, you need to set an environment variable `ADSTOKEN`, which needs to point to your ADS API token.
Follow the instructions [here](https://ui.adsabs.harvard.edu/help/api/) to obtain your ADS API token.
You are subject to the [ADS API Terms of Service](https://ui.adsabs.harvard.edu/help/terms/) through your use of this application.

# Usage
The application is CLI-based and has two modes: you may choose to build either a reference tree or a citation tree.
To build a reference tree, use:

    astrotree -id <ADS id> --ref 

To build a citation tree, use:

    astrotree -id <ADS id> --cite


In either case the output is a list of ADS IDs and the respective article titles, in a tree format. The tool offers you the opportunity to ask to build a tree for any of the listed IDs, restricted to the same mode you started with.

Upon exit (press n when the application asks if you wish to continue), the tree is dumped to a text file containing the tree in the local directory, for future use.
apexmf 0.4.0
apexmf is a set of python modules for APEX-MODFLOW model evaluation and parameter estimation.
Keywords: python,APEX-MODFLOW,PEST

apexmf
------

.. image:: https://img.shields.io/pypi/v/apexmf?color=blue
   :target: https://pypi.python.org/pypi/apexmf
   :alt: PyPI Version
.. image:: https://img.shields.io/pypi/l/apexmf?color=green
   :target: https://opensource.org/licenses/BSD-3-Clause
   :alt: PyPI - License
.. image:: https://zenodo.org/badge/304434074.svg?color=orange
   :target: https://zenodo.org/badge/latestdoi/304434074

`apexmf` is a set of python modules for APEX-MODFLOW model (Bailey et al., 2021) parameter estimation and uncertainty analysis with the open-source suite PEST (Doherty 2010a and 2010b, and Doherty and other, 2010).

.. rubric:: Installation

.. code-block:: python
   
   >>> pip install apexmf


.. rubric:: Brief overview of the API

.. code-block:: python

   from apexmf import apexmf_pst_utils

   >>> wd = "User-APEX-MODFLOW working directory"
   >>> APEX_wd = "User-APEX working directory"
   >>> apexmf_pst_utils.init_setup(wd, APEX_wd)

   'apex.parm.xlsx' file copied ... passed
   'beopest64.exe' file copied ... passed
   'i64pest.exe' file copied ... passed
   'i64pwtadj1.exe' file copied ... passed
   'forward_run.py' file copied ... passed
fling-api 0.1.3
Side Project Management API for Data Storage and Name Searches
Requires Python: >=3.9,<4.0

# Fling
## Fling is a side project management platform.

Fling is a tool for those of us who cannot help but create new side projects - flings. Some flings are started late at night and forgotten about the next day, while others we may continue working on over many weekends. Some may generate income, while others drain our savings. With so many projects in some state of development, keeping track of your flings, your fling's social media accounts, user activity or even where they're hosted can be nothing short of a nightmare. This tool is meant to help with that.

Fling allows you to collect and store "business state" separate
from both the source code (which lives in a git repo), and app
state (which usually lives in a production database somewhere).

Business state is:

 - Hosting details (where is it running)
 - Socials (blog, insta, mastodon)
 - Monthly costs
 - Income (revenue or donations)
 - Basic user stats (views, signups, sessions)
 - Partnership details (who built it with you)
 - History / Timeline (when was it started, deployed etc)

It consists of a CLI tool, a web service, and a cookiecutter template.

The CLI, along with a growing set of plugins, can be used to gather
"business state" about your project, and store that in the Fling service.

The cookiecutter template is language agnostic, and can be used for any 
new side project. It will add a *company-private* web interface that
can be used to browse and visualize your side project state.

<INSERT single side project company view here>

The Fling web service can be authenticated with GitHub, and used to aggregate
the Fling business state from *all* of your side projects.

<INSERT aggregated view screenshot here>

## Fling CLI plugins

### Namer

The namer plugin can be used through the ```search``` command. It uses ChatGPT to 
come up with great domain name ideas, and then the Name.com API to find some that
are available.

### Init

The init plugin is integrated with cookiecutter, and can be used to set up a new
side project with Fling support. Existing projects can be configured by manually 
creating a ```fling.yaml``` file and then running ```fling pull```.
iso3166-scraper 0.0.1
A Python utility that scrapes ISO 3166 country code data from Wikipedia
Requires Python: >=3.9

iso3166-scraper
===============

A simple utility for scraping ISO-3166 country data from a [Wikipedia
article](https://en.wikipedia.org/wiki/List_of_ISO_3166_country_codes) that 
contains all current country codes, names, etc.

In a recent project, I had a need for the ISO 3166 country code data and was
disappointed to discover that there really wasn't a good free source for 
obtaining the data in structured form. I'm sure there's some place where I 
could spend money with ISO to get this data, but that's not a great option 
for an open source project with no revenue stream for such expenses.

However, the above referenced Wikipedia article was pretty cleanly structured 
and easy enough to scrape. The data changes infrequently, so occasionally 
running this utility to get the latest data seems like a decent compromise.
Maybe you'll find it useful too.

This utility scrapes the web page, and outputs the country code data in
JSON and YAML formats.

In addition to the basic country data, the script maps the country codes
to the corresponding Unicode code points for each country's flag and
includes the appropriate escape sequences in a string property of the
output data in every format.

This tool is built using some excellent open source components that make
creating tools like this really easy.

* [Beautiful Soup](https://www.crummy.com/software/BeautifulSoup/) -- HTML
  page scraping
* [Requests](https://requests.readthedocs.io/en/latest/) -- HTTP for Humans
* [ruamel.yaml](https://pypi.org/project/ruamel.yaml/) -- YAML reader/writer


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

This package is available for installation via PyPI and can therefore be 
installed using *pip* as follows.

```bash
python3 -m pip install iso3166-scraper
```

Usage
-----

After installation, you can simply run it.

```
$ iso3166-scraper
retrieving https://en.wikipedia.org/wiki/List_of_ISO_3166_country_codes
writing JSON file: ./iso3166.json
writing YAML file: ./iso3166.yml
```

By default, it fetches the Wikipedia article, scrapes the ISO 3166 country
data from the page, and produces JSON and YAML output files in the current
directory. Using command line options, you can select which output format
you want and where to put it. To see all the options, use

```bash
iso3166-scraper --help
```
squashy 0.1.1
Large scale graph compression and summarization tool built on Memgraph.
Requires Python: >=3.10,<4.0

# ➡️Squashy⬅️

Large scale graph compression and summarization tool for research and analysis.

### Note on suitability for use
➡️Squashy⬅️ is relatively new. It was developed for one of my own academic research projects. The principles behind it are based on published research, however the implementation is my own. I think it works well, however it could do with more testing

## What does it do?

At some point the key tools of network analysis struggle with scale. Beyond a few hundred nodes, graphs become too dense
to visualise. Nodes too numerous to detect communities.

This can become even more of an issue in a research context, where you often want to run analysis multiple times, tweak
settings or actually _see_ your data.

➡️Squashy⬅️can compress graphs made up of millions of nodes and edges into a graph of a few hundred nodes that retains the overall structure.

## How does it work?