PythonCode

Allows for custom Python code to be executed against tables and objects inside an AuditBoard Analytics Workflow. One can ingest any number of sources and output any number of objects.

Input, Output

Input	Output
No requirements, any number of tables or inputs is allowed	Any python altered data frames or charts dictated by return

Accessing Objects & Parameters

Any source linked to the Python 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 parameters are available using the variables dictionary. It's recommended to access parameter by their name:

foo = variables["foo"]

Returning Objects

AuditBoard Analytics allows the return of Table or Chart 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.

import pandas as pd
tbl = sources[0]
df = tbl.df 
return [Table(df=df, name="DataFrame")]

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)

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
Numpy	Numerical and statistical operations	import numpy
URLlib	URL Encoding/decoding	import urllib
JSON	JSON handling	import json