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+---
+layout: post
+title: Automating a Parking Expenses Report
+date: 2025-03-02 14:38:00 Europe/Amsterdam
+categories: paperless paperless-ngx nix python python3
+---
+
+For the past year, I was consulting at a place where I could request
+reimbursement of parking expenses. This had to be claimed using a standard Excel
+template.
+
+Doing this manually every month seemed boring, so I automated a significant part
+of that:
+
+- Fetch parking costs for a certain month from my Paperless-ngx instance
+- Calculate costs after taxes and a grand total
+- Fill in an Excel sheet with the details
+- Convert the Excel sheet to PDF and append photos of parking costs
+
+Note: I don't expect anybody to have the same requirements as me here, but
+hopefully pieces can be useful to some. The open-sourced project can be found
+[here](https://git.kun.is/pim/parking-expenses).
+
+# Organizing the Parking Costs
+
+Each time I would park, I would accumulate a parking ticket. This ticket
+contains the following information:
+
+- Date and time
+- Car license plate
+- Price
+- VAT
+
+In order to automate the report, I had to have this information in a structured
+way. Therefore, I turned to [Paperless-ngx](https://docs.paperless-ngx.com/).
+Paperless-ngx is an self-hostable open-source service that helps digitalizing
+paper documents. Third-party mobile apps help quickly scanning documents and
+uploading them to the server. This is exactly what I did with the parking
+tickets as well: each time I received a ticket, I would scan it with the
+Paperless app.
+
+Paperless-ngx uses Optical Character Recognition (OCR) to cleverly extract the
+date of the ticket automatically. I also created a custom label to indicate a
+parking ticket, and I added custom fields to indicate a ticket's cost and VAT
+amount. You can see this information in the screenshot below.
+
+![foo](ticket.png) _Translated from Dutch: aanmaakdatum means creation date,
+parkeerkaart means parking ticket, BTW means VAT and bedrag means cost_
+
+Paperless-ngx will also automatically learn to label the tickets with the
+"parking ticket" label, based on the document's content. That just leaves the
+VAT and price data points. Unfortunately I found the OCR to be too unreliable to
+extract that text from the documents. Therefore, I had to manually set those two
+data points for each ticket.
+
+Neat, we now have all parking tickets organized on Paperless-ngx! In order to
+create a report, we can just query the Paperless-ngx API!
+
+# Using the Paperless-ngx API
+
+The remaining part of this post will be code explanations. You can find the full
+open-sourced Python code
+[here](https://git.kun.is/pim/parking-expenses/src/commit/645fd8b4e4e46bc8f3d8ba831ca28261cd3edb39/main.py).
+
+Paperless-ngx has [an API](https://docs.paperless-ngx.com/api/) we can now use
+to query our parking tickets. I found the filtering logic pretty hard to
+understand. Therefore I simply looked at what API calls the web UI makes with
+the query I needed. This turned out to be something like this:
+
+```python
+response = requests.get(
+    f"{paperless_ngx_url}/api/documents/?page_size=50&query=created:[{start_date} TO {end_date}]&tags__id__all={FILTER_TAG_ID}&correspondent__id__in={FILTER_CORRESPONDENT_ID}",
+    headers={"Authorization": f"Token {token}"},
+)
+```
+
+In the above code snippet, `FILTER_TAG_ID` is the ID of the "Parking ticket"
+label and `FILTER_CORRESPONDENT_ID` is the ID of the correspondent (I included
+this to filter out potential unrelated parking tickets).
+
+Perfect, this returns a JSON list of parking tickets we can use to create the
+report!
+
+# Creating the Report
+
+All that's left is to fill in an Excel template now. This actually proved to be
+the most annoying part but also the most boring part. I used the
+[OpenPyXL](https://openpyxl.readthedocs.io/en/stable/) Python library to
+manipulate the Excel sheets and basically just add a row for each parking
+ticket. For code, check
+[here](https://git.kun.is/pim/parking-expenses/src/commit/645fd8b4e4e46bc8f3d8ba831ca28261cd3edb39/main.py#L104).
+
+To convert the Excel sheet to a PDF, I used the (apparently now deprecated)
+[unoconv](https://github.com/unoconv/unoconv) utility. It uses LibreOffice under
+the hood for the conversion, which adds a 2GiB dependency for the project 🫠.
+
+Finally, to merge the report PDF with photos of the parking tickets, I used the
+[PyPDF2](https://pypdf2.readthedocs.io/en/3.x/) Python library.
+
+I would now show some example output, but it contains quite some sensitive
+information so unfortunately I can't... But I never had any complaints from the
+finance department, so it worked great!
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