Python

Insert custom Python code

This tool is currently in Beta and is still being tested. Want to learn more? Like to provide feedback? Please reach out to [email protected]

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:

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	Data manipulation	import pandas
Requests	API requests	import requests
JSON	JSON handling	import json
Numpy	Numerical and statistical operations	import numpy
SciKit Learn	Regressions and machine learning	import sklearn
FB Prophet	Time-series forecasting	from fbprophet import Prophet
FeatureTools	Feature engineering	import featuretools
EvalML	Machine learning	import evalml
SkTime	Time series forecasting and classification	import sktime
Fuzzymatcher	Fuzzy matching for data cleaning	import fuzzymatcher
Record Linkage	Fuzzy matching for data cleaning	import recordlinkage
Requests	API requests	import requests
SciPy	Math and engineering	import scipy
Scrapy	Web scraping	import scrapy
BeautifulSoup	Web scraping	from bs4 import BeautifulSoup
URLlib	URL Encoding/decoding	import urllib