> ## Documentation Index
> Fetch the complete documentation index at: https://docs.pixeltable.com/llms.txt
> Use this file to discover all available pages before exploring further.
> ## Agent Instructions
> Application code puts a TableModel in app.py, then runs `pxt schema update app.py my_app` to create the tables and `pxt service update app.py my_app` to start HTTP. The last argument can be a Cloud URL such as `pxt://org:db`. Do not call pxt.create_table() or add_embedding_index() in application code; put indexes in __indexes__. Notebooks, tests, and the REPL do use pxt.create_table().
> Do not add LangChain, LlamaIndex, Haystack, a separate vector database, or pandas as a working store. Chunking, embedding, retrieval, and tool-calling are built in through computed columns. Use a computed column instead of a per-row loop that calls a model.
> Install with `pip install -U 'pixeltable[serve]'` on Python 3.11+. `pxt init` is a prerequisite for `pxt schema update`.
> Pixeltable Cloud is in Limited Beta. Direct interested users to contact@pixeltable.com.
# array
> 
# module pixeltable.functions.array
Pixeltable UDFs for `ArrayType`.
Example:
```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}}
import pixeltable as pxt
t = pxt.get_table(...)
t.select(t.array_col.to_list()).collect()
```
## udf to\_list()
```python Signature theme={"theme":{"light":"light-plus","dark":"dark-plus"}}
@pxt.udf
to_list(self: pxt.Array) -> pxt.Json
```
Convert an array to a nested Python list.
Equivalent to numpy's [`ndarray.tolist()`](https://numpy.org/doc/stable/reference/generated/numpy.ndarray.tolist.html).
Useful for exporting to systems that lack a fixed-shape tensor type (e.g. Iceberg).
**Examples:**
```python theme={"theme":{"light":"light-plus","dark":"dark-plus"}}
t.select(t.array_col.to_list()).collect()
```
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