# Python

{% hint style="info" %}
This tool is currently in Beta and is still being tested. Want to learn more? Like to provide feedback? Please reach out to <support@cascade.io>
{% endhint %}

Code allows for custom Python to be executed against tables and objects inside a Cascade Workflow. One can ingest any number of sources and output any number of objects.

### Accessing Objects & Variables

Any source linked to the Code tool is accessible using the `sources` dictionary, and objects can be accessed by their index or by their name. For example:

```
df1 = sources[0].df        # access table by index
df1 = sources["foo"].df    # access table by name
```

Similarly, workflow variables are available using the `variables` dictionary. It's recommended to access variables by their name:&#x20;

```
foo = variables["foo"]
```

### Returning Objects

Cascade allows the return of `Table,` `Chart` , `Json`, or `Markdown` objects for use in downstream tools. Objects can be returned as a single object or an array of objects.

#### Table

To create and return a table, provide a `name` and pandas `df` attribute to the `Table` object.

```
return Table (
     name = "foo"
     df = df1
)
```

#### Chart

To create and return a chart, provide a `name` and plotly `figure` attribute to the `Chart` object.

```
import plotly.graph_objects as go

fig = go.Figure(
    data=[go.Bar(x=[1, 2, 3], y=[1, 3, 2])],
    layout=go.Layout(
        title=go.layout.Title(text="A Figure Specified By A Graph Object")
    )
)

return Chart(name="foo", figure=fig)
```

#### JSON

To create and return a json, provide a `name` and python `dict` attribute to the `JSON` object.

```
return Json(name="foo", json={"counter": 1})
```

#### Markdown

To create and return a json, provide a `name` and python `dict` attribute to the `JSON` object.

```
return Markdown(name="foo", markdown="# Hello")
```

### Available Libraries

Within the Code tool, the following libraries are accessible by default. Import libraries using `import`:

| Library                                                                               | Description                                | Import                          |
| ------------------------------------------------------------------------------------- | ------------------------------------------ | ------------------------------- |
| [**Pandas**](https://pandas.pydata.org/)                                              | Data manipulation                          | `import pandas`                 |
| [**Requests**](https://requests.readthedocs.io/en/master/)                            | API requests                               | `import requests`               |
| [**JSON**](https://docs.python.org/3/library/json.html)                               | JSON handling                              | `import json`                   |
| [**Numpy**](https://numpy.org/)                                                       | Numerical and statistical operations       | `import numpy`                  |
| [**SciKit Learn**](https://scikit-learn.org/stable/)                                  | Regressions and machine learning           | `import sklearn`                |
| [**FB Prophet**](https://facebook.github.io/prophet/docs/quick_start.html#python-api) | Time-series forecasting                    | `from fbprophet import Prophet` |
| [**FeatureTools**](https://featuretools.alteryx.com/en/stable/#)                      | Feature engineering                        | `import featuretools`           |
| [**EvalML**](https://evalml.alteryx.com/en/stable/start.html)                         | Machine learning                           | `import evalml`                 |
| [**SkTime**](https://github.com/alan-turing-institute/sktime)                         | Time series forecasting and classification | `import sktime`                 |
| [**Fuzzymatcher**](https://github.com/RobinL/fuzzymatcher)                            | Fuzzy matching for data cleaning           | `import fuzzymatcher`           |
| [**Record Linkage**](https://recordlinkage.readthedocs.io/en/latest/about.html)       | Fuzzy matching for data cleaning           | `import recordlinkage`          |
| [**Requests**](https://realpython.com/python-requests/)                               | API requests                               | `import requests`               |
| [**SciPy**](https://docs.scipy.org/doc/scipy/reference/)                              | Math and engineering                       | `import scipy`                  |
| [**Scrapy**](https://docs.scrapy.org/en/latest/)                                      | Web scraping                               | `import scrapy`                 |
| [**BeautifulSoup**](https://www.crummy.com/software/BeautifulSoup/bs4/doc/)           | Web scraping                               | `from bs4 import BeautifulSoup` |
| **URLlib**                                                                            | URL Encoding/decoding                      | `import urllib`                 |


---

# Agent Instructions: Querying This Documentation

If you need additional information that is not directly available in this page, you can query the documentation dynamically by asking a question.

Perform an HTTP GET request on the current page URL with the `ask` query parameter:

```
GET https://docs.cascade.io/cascade/tools/code/pythoncode.md?ask=<question>
```

The question should be specific, self-contained, and written in natural language.
The response will contain a direct answer to the question and relevant excerpts and sources from the documentation.

Use this mechanism when the answer is not explicitly present in the current page, you need clarification or additional context, or you want to retrieve related documentation sections.