ohmyscrapper 0.2.1

This project aims to create a text-based scraper containing links to create a final PDF with general information about job openings.

OhMyScrapper - v0.2.1

This project aims to create a text-based scraper containing links to create a final PDF with general information about job openings.

This project is using uv by default.

Scope

• Read texts;
• Extract links;
• Use meta og:tags to extract information;

Installation

I recomend to use the uv, so you can just use the command bellow and everything is installed:

uv sync

How to use and test (development only)

OhMyScrapper works in 3 stages:

1. It collects and loads urls from a text (by default input/_chat.txt) in a database;
2. It scraps/access the collected urls and read what is relevant. If it finds new urls, they are collected as well;
3. Export a list of urls in CSV files;

You can do 3 stages with the command:

make start

Remember to add your text file in the folder /input with the name _chat.txt!

You will find the exported files in the folder /output like this:

• /output/report.csv
• /output/report.csv-preview.html
• /output/urls-simplified.csv
• /output/urls-simplified.csv-preview.html
• /output/urls.csv
• /output/urls.csv-preview.html

BUT: if you want to do step by step, here it is:

First we load a text file you would like to look for urls, the idea here is to use the whatsapp history, but it works with any txt file.

The default file is input/_chat.txt. If you have the default file you just use the command load:

make load

or, if you have another file, just use the argument -file like this:

uv run main.py load -file=my-text-file.txt

That will create a database if it doesn't exist and store every url the oh-my-scrapper find. After that, let's scrap the urls with the command scrap-urls:

make scrap-urls

That will scrap only the linkedin urls we are interested in. For now they are:

• linkedin_post: https://%.linkedin.com/posts/%
• linkedin_redirect: https://lnkd.in/%
• linkedin_job: https://%.linkedin.com/jobs/view/%
• linkedin_feed" https://%.linkedin.com/feed/%
• linkedin_company: https://%.linkedin.com/company/%

But we can use every other one generically using the argument --ignore-type:

uv run main.py scrap-urls --ignore-type

And we can ask to make it recursively adding the argument --recursive:

uv run main.py scrap-urls --recursive

!!! important: we are not sure about blocks we can have for excess of requests

And we can finally export with the command:

make export

That's the basic usage! But you can understand more using the help:

uv run main.py --help