Libraries
The vistazo library every cell can call, and the six Python libraries installed at fixed versions.
Contents
What can a Python cell use?
A Python cell has two things to draw on. The vistazo library brings your workspace data in, and
six scientific libraries, installed at fixed versions, do the analysis.
How does the vistazo library read data?
vistazo is available in every cell without an import. It has four calls. Each is awaited and
returns a pandas DataFrame, and top-level await works as it does in Jupyter.
prices = await vistazo.call('markets', 'closing_prices', {'symbols': ['AAPL'], 'start_date': '2026-01-02'})
sales = await vistazo.dataset('q3-sales.csv')
rows = await vistazo.widget('w_8f2c1d')
conns = await vistazo.tools()
| Call | What it reads |
|---|---|
call |
The result of one read-only tool on one of your connections |
dataset |
A table from a file you uploaded |
widget |
A dashboard widget's rows. It takes no arguments, because the widget already holds them |
tools |
Your connections and the read-only tools on each, with their arguments. Use it to find what to pass to call |
Every call runs under your own access and reaches only read-only tools. No credential reaches the code in a cell, so a notebook someone shares with you can never write to one of your sources.
Which libraries are installed?
Six libraries are installed at fixed versions, and there is no way to add more.
| Library | Version |
|---|---|
| numpy | 2.4.6 |
| pandas | 3.0.2 |
| scipy | 1.18.0 |
| statsmodels | 0.14.6 |
| scikit-learn | 1.8.0 |
| matplotlib | 3.10.8 |
The packages these depend on, such as dateutil, patsy and PIL, import too. pandas is version 3,
and a few APIs moved from version 2, so code copied from an older notebook may need a line changed.
There is no pip. Your code runs with no network and none of your files, so requests, or pd.read_csv
on a path or URL, can't reach your data. Data comes in through the vistazo library.