https://github.com/rikardfahlstrom/qlik-community-blog-posts-scraper

Download metadata and links for all Qlik community blog posts into an SQLite database and make it explorable through Datasette, deploy with Docker.
https://github.com/rikardfahlstrom/qlik-community-blog-posts-scraper

datasette qlik qliksense qlikview

Last synced: 2 months ago
JSON representation

Download metadata and links for all Qlik community blog posts into an SQLite database and make it explorable through Datasette, deploy with Docker.

• Host: GitHub
• URL: https://github.com/rikardfahlstrom/qlik-community-blog-posts-scraper
• Owner: RikardFahlstrom
• License: mit
• Created: 2021-10-02T08:18:02.000Z (over 3 years ago)
• Default Branch: main
• Last Pushed: 2023-08-29T14:19:15.000Z (almost 2 years ago)
• Last Synced: 2025-03-30T23:43:25.710Z (2 months ago)
• Topics: datasette, qlik, qliksense, qlikview
• Language: Python
• Homepage:
• Size: 18.6 KB
• Stars: 1
• Watchers: 2
• Forks: 1
• Open Issues: 0
• Metadata Files:
  • Readme: README.md
  • License: LICENSE

Awesome Lists containing this project

README

        
# Qlik community blog posts scraper

---

[![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)

[![Checked with mypy](http://www.mypy-lang.org/static/mypy_badge.svg)](http://mypy-lang.org/)

_Download metadata and links for all Qlik community blog posts into a Sqlite database and make it explorable through Datasette, deploy with Docker_

* Find out the most viewed or liked blog post

* Trending writers

* Explore through SQL-queries

## Installation and usage

### Installation

- Create a virtual environment with Python 3.5 or above

- Activate virtualenv and install `requirements.txt`

- Run `python program.py` in order to create `qlik_posts.db`

### Usage

- Create Docker image `docker build -t datasette_qlikposts .`

- Run container `docker run -d --rm -p 8081:8001 --name datasette_qlik datasette_qlikposts`

- Explore data at `http://localhost:8081/`