Working with the Pixeltable CLI
You defined a multimodal pipeline in Python and now need to inspect tables, debug computed columns, roll back changes, and expose HTTP endpoints without writing more application code.
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Get fast feedback on transformations
You need to iterate on transformation logic before running it on your entire dataset—especially for expensive operations like API calls or model inference.
Core Operations · Notebook · Updated
Colab runs it in your browser. If it calls a model provider, it asks for that provider's API key in a cell.
How it works
You test transformation logic on sample rows before processing your entire dataset using the iterate-then-add workflow. This lets you validate logic on a few rows before committing to your full table.
You use .select() with .collect() to preview transformations—nothing is stored in your table. If you want to collect only the first few rows, use .head(n) instead of .collect(). Once you're satisfied with the results, use .add_computed_column() with the same expression to persist the transformation across your full table.
What it covers
- Test transformations on sample rows before applying to your full dataset
- Save expressions as variables to guarantee consistent logic
- Apply the iterate-then-add workflow with built-in functions, expressions, and custom UDFs
- Annotate columns with comments and custom metadata using ColumnSpec
What it uses
- Install
- terminalpip install pixeltable
- Pixeltable calls
pxt.create_table()@pxt.udfinsert()add_computed_column()add_column()
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