We (me and @aarondia) built a tool to help you turn psuedo-software Excel files into real-software Python. Ideally, Pyoneer helps you automate your manual Excel processes. You can try it today here: https://pyoneer.ai.
How it works:
1. You upload an Excel file
2. We statically parse the Excel file and build a dependency graph of all the cells, tables, formulas, and pivots.
3. We do a graph traversal, and translate nodes as we hit them. We use OpenAI APIs to translate formulas. There’s a bunch of extra work here — because even with the best prompt engineering a fella like me can do, OpenAI sucks at translating formulas (primarily because it doesn’t know what datatypes its dealing with). We augment this translation with a mapping from ranges to variable names and types, which in our experience can improve the percentage of correctly translatable formulas by about 5x.
4. We generate test cases for our translations as well, to make sure the Python process matches your Excel process.
5. We give you back a Jupyter notebook that contains the code we generated.
If there are pieces of the Excel we can’t translate successfully (complex formulas, or pivot tables currently), then we leave them as a TODO in the code. This makes it easy for you to hop in and continue finishing the script.
Who is this for:
Developers who know Python, primarily! Pyoneer might be useful if:
1. You’ve got an Excel file you’re looking to move to Python (usually for speed, size, or maintenance reasons).
2. There’s enough logic contained in the notebook that it’s going to be a hassle for you to just rewrite it from scratch.
3. Or you don’t know the logic that is in the Excel workbook well since you didn’t write it in the first place :)
Post translation, even if Pyoneer doesn't nail it perfectly or translate all the formulas, you'll be able to pop into the notebook and continue cleaning up the TODOs / finish writing the formulas.
What the Alpha launch supports:
Launched early! Currently we’re focused on supporting:
1. Any number of sheets, with any reference structure between them.
2. Cells that translate as variables directly. We’ll translate the formulas to Python code that has the same result, or else we’ll generate a TODO letting you know we failed translating this cell.
3. Tables that translate as Pandas dataframes. We support at most one table per sheet, at the tables must be contigious. If the formulas in a column are consistent, then we will try and translate this as a single pandas statement.
We do not support: pivot tables or complex formulas. When we fail to translate these, we generate TODO statements. We also don’t support graphs or macros - and you won’t see these reflected in the output at all currently.
Why we built this:
We did YCS20 and built an open source tool called Mito(https://trymito.io). It’s been a good journey since then - we’ve scaled revenue and to over 2k Github stars (https://github.com/mito-ds/mito). But fundamentally, Mito is a tool that’s useful for Excel users who wanted to start writing Python code more effectively.
We wanted to take another stab at the Excel -> Python pain point that was more developer focused - that helped developers that have to translate Excel files into Python do this much more quickly. Hence, Pyoneer!
I’ll be in the comments today if you’ve got feedback, criticism, questions, or comments.
Comments URL: https://news.ycombinator.com/item?id=40457631
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