#502: Django Ledger: Accounting with Python

04/21/25 • 63 min

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Do you or your company need accounting software? Well, there are plenty of SaaS products out there that you can give your data to. but maybe you also really like Django and would rather have a foundation to build your own accounting system exactly as you need for your company or your product. On this episode, we're diving into Django Ledger, created by Miguel Sanda, which can do just that.
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Links from the show

Miguel Sanda on Twitter: @elarroba
Miguel on Mastodon: @[email protected]
Miguel on GitHub: github.com
Django Ledger on Github: github.com
Django Ledger Discord: discord.gg
Get Started with Django MongoDB Backend: mongodb.com
Wagtail CMS: wagtail.org
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
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Previous Episode

#501: Marimo - Reactive Notebooks for Python

Have you ever spent an afternoon wrestling with a Jupyter notebook, hoping that you ran the cells in just the right order, only to realize your outputs were completely out of sync? Today's guest has a fresh take on solving that exact problem. Akshay Agrawal is here to introduce Marimo, a reactive Python notebook that ensures your code and outputs always stay in lockstep. And that's just the start! We'll also dig into Akshay's background at Google Brain and Stanford, what it's like to work on the cutting edge of AI, and how Marimo is uniting the best of data science exploration and real software engineering.
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Links from the show

Akshay Agrawal: akshayagrawal.com
YouTube: youtube.com
Source: github.com
Docs: marimo.io
Marimo: marimo.io
Discord: marimo.io
WASM playground: marimo.new
Experimental generate notebooks with AI: marimo.app
Pluto.jl: plutojl.org
Observable JS: observablehq.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy

Next Episode

#503: The PyArrow Revolution

Pandas is at a the core of virtually all data science done in Python, that is virtually all data science. Since it's beginning, Pandas has been based upon numpy. But changes are afoot to update those internals and you can now optionally use PyArrow. PyArrow comes with a ton of benefits including it's columnar format which makes answering analytical questions faster, support for a range of high performance file formats, inter-machine data streaming, faster file IO and more. Reuven Lerner is here to give us the low-down on the PyArrow revolution.
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Links from the show

Reuven: github.com/reuven
Apache Arrow: github.com
Parquet: parquet.apache.org
Feather format: arrow.apache.org
Python Workout Book (45% off with code talkpython45): manning.com
Pandas Workout Book (45% off with code talkpython45): manning.com
Pandas: pandas.pydata.org
PyArrow CSV docs: arrow.apache.org
Future string inference in Pandas: pandas.pydata.org
Pandas NA/nullable dtypes: pandas.pydata.org
Pandas `.iloc` indexing: pandas.pydata.org
DuckDB: duckdb.org
Pandas user guide: pandas.pydata.org
Pandas GitHub issues: github.com
Watch this episode on YouTube: youtube.com
Episode transcripts: talkpython.fm
--- Stay in touch with us ---
Subscribe to Talk Python on YouTube: youtube.com
Talk Python on Bluesky: @talkpython.fm at bsky.app
Talk Python on Mastodon: talkpython
Michael on Bluesky: @mkennedy.codes at bsky.app
Michael on Mastodon: mkennedy