semvec/pypi-packages huggingface dataset:
stylobate-mgmt 0.0.2
Manage instances of Stylobate-based projects
License: MIT
Requires Python: >=3.1

# README
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                         Mgmt
</pre>

Script for managing [Stylobate](https://github.com/digitaltembo/stylobate)-based applications.

(Stylobate is a Dockerized FastAPI-React starter project)

Inspired basically by Flask's `manage.py`, it is mostly thin wrappers around bash scripts that would be tedious to type in full each time.
Adapted from a previous collection of a bunch of aliases and bash scripts

## Features

* Build/compile front-end sources and docker images with `stylo build`
* Manage the database with auto-generated migrations and shell access in `stylo db`
* Auto-fork and set up a new stylobate project with `stylo init`
* Follow logs with `stylo logs`
* Run frontend, backend, and dockerized servers with `stylo run`
* Is your web server running? Use `stylo stop`
* Access the docker shells with `stylo shell`

## Installation

If you want to use `stylo init`, you must first install the [GitHub CLI](https://github.com/cli/cli#installation))

After doing or skipping that, simply run ```pip install stylobate-mgmt```

## Usage

Use `stylo --help` to access the help page, or `stylo <command> --help` to access the help page for a specific command

Note that for clarity's sake in most descriptions I use the long version of arguments, e.g. `stylo db --gen-migrations`. All arguments have a shorter form as well that should be intuitive; in this case `stylo db -g`.
scrapesy 1.2.0
Simple Python web scraper/page fetcher with cache
License: MIT
Keywords: scrape,web,scraper,scraping

# scrapesy
[![Build Status](https://api.travis-ci.com/scoopgracie/scrapesy.svg?branch=master)](https://travis-ci.com/scoopgracie/scrapesy)

Easy and Pythonic way to get and parse a Web page

## Usage

To get a `Page` object, use `scrapesy.get(url)`. The `Page` object has two
properties, `page` and `request`. `page` is a `BeautifulSoup` object.
`request` is a Requests `Response` object.

However, if you just want this for the cache (see below), and do not need or
want Beautiful Soup to parse the pages, pass `parse=False` to get(). This will
simply return a Requests request object, not a `Page` object. Disabling
parsing and caching is possible, but rather useless, because parsing and
caching are the main features of Scrapesy. If you find yourself always
disabling both, just use Requests directly.

### Caching

By default, Scrapesy implements a cache, allowing for near-instantaneous
results on pages that have been requested previously. This cache operates
automatically, and it operates transparently to any code that does not
specifically interact with it. It is possible to use Scrapesy without any
understanding of the cache.

However, it is possible to disable the cache. Simply run `scrapesy.caching =
False`. To re-enable it, use `scrapesy.caching = True`. If you simply need to
ignore the cache for a single call, simply add `use_cache=False` to your
`scrapesy.get()` call.

To empty the cache, call `scrapesy.empty_cache()`.

To remove a single page from the cache, call `scrapesy.uncache(url)`.

To enable selective caching, set `scrapesy.cache_check` to a function that
takes `url` as an input and returns `True` if the page should be cached and
`False` otherwise.

Run `demo.py` for a demonstration of the impact of the cache.

## Requirements

* Beautiful Soup 4
* Requests
* Python 3 (it may work on 2.7, but is not tested)

## Note

This project was originally called PyScrape. If you find that name used
anywhere in this repo, please report it as an issue!
estimium 0.2.0
A collection of ML tools written with professor's chalk
License: MIT
Requires Python: >=3.7,<4.0

<h1 align="center">Professor Estimium</h1>

<p align="center">
    <img src="https://raw.githubusercontent.com/mrtovsky/estimium/master/docs/images/professor-estimium.png" alt="Professor Estimium" class="center">
</p>

<h2 align="center">A collection of ML tools written with professor's chalk</h2>

<p align="center">
    <a href="https://github.com/psf/black"><img src="https://img.shields.io/badge/code%20style-black-000000.svg" alt="Code style: black"></a>
    <a href="https://github.com/pre-commit/pre-commit"><img src="https://img.shields.io/badge/pre--commit-enabled-brightgreen?logo=pre-commit&logoColor=white" alt="pre-commit" style="max-width:100%;"></a>
    <a href="https://codecov.io/gh/mrtovsky/estimium/branch/master"><img src="https://codecov.io/gh/mrtovsky/estimium/branch/master/graph/badge.svg" alt="Code style: black"></a>
</p>

<!-- prettier-ignore -->
> _Application of these estimators is left as an exercise for the reader_ - Professor Estimium

**Professor Estimium** is a **Python** package implementing frequently used
functionalities to reduce writing Machine Learning boilerplates to a minimum.

The professor was guided by the principle that:

<!-- prettier-ignore -->
> _If you did something once, you did it enough times._