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

Data manipulation

import pandas

API requests

import requests

Numerical and statistical operations

import numpy

URL Encoding/decoding

import urllib

JSON handling

import json

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