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Export to QIF/CSV from 28degrees Master Card website

Description

This utility logs into https://28degrees-online.gemoney.com.au website, using your username and password, and simply grabs all your transactions from there, saving them into QIF file.

Installation

You will need some things for this tool to work:

1. Python
2. Mechanize
3. PyQuery
4. Git

As installation instructions for the things above vary for different platforms, I assume you know how install them, otherwise please let me know and I'll extend this section with detailed steps for your platform.

Usage

Simply start export.py in your shell of choice (cmd.exe, bash, zsh etc). You will be prompted for your username & password. THESE details will not be used for anything but logging into the 28degrees' website.

Then the tool will go through several stages, printing some supplementary information into console. Do not worry about that unless these are actually error messages.

When it's done, you should see file that looks like YYYY.MM.DD-YYYY.MM.DD.qif under the 'export' folder, where YYYY.DD.MM are the dates for the first and last transactions in the exported dataset. It will also create a transactions.db file (sqlite database) but you can ignore this one - we simply need it to keep track of transactios that have already been recorded.

If you want to re-start the process, just delete (or re-name, which is safer) transactions.db file.

Errors / support

As this is a very first and rough cut of the tool, errors to be expected - please DO let me know of any issues you have with it.

Also please feel free to submit your ideas/improvement suggestions.

Disclaimer

I am not affiliated in any way with this website, and this utility has not been endorsed or banned by the company-operator of the website.

Please feel free to use it and report on any issues/bug/problems, yet you shall agree beforehand that you are using this utility at your own risk - I accept no liability whatsoever for anything what can possibly go wrong.

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Scraping utility for 28degrees Master Card website

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  • Python 100.0%