For the complete documentation index, see llms.txt. This page is also available as Markdown.

Before you begin

Before using the Python Executor step, be aware of the following conditions.

You must install the following Python libraries before using the Python Executor step:

  • Pandas (between 0.18.0 and 1.4.4.) is an open source, BSD-licensed library providing high-performance, easy-to-use data structures and data analysis tools for the Python programming language. The pandas DataFrame along with the Series are the two parts of the pandas data structure, a flexible container for lower dimensional data. For example, DataFrame is a container for Series, and Series is a container for scalars. Ultimately, you want to be able to insert and remove objects from these containers in a dictionary-like fashion.

  • NumPy (1.14.0 or later) is a library for the Python programming language which adds both robust support for multi-dimensional arrays and matrices, and a large collection of high-level mathematical functions to operate on these arrays. A NumPy array is a table of values, all of the same type, which is indexed by a tuple of positive integers. NumPy arrays can be fast, easy to work with, providing users opportunities to perform calculations across entire arrays.

  • Py4J (0.10.2 or later) is a bridge between Python and Java, permitting Python programs running with a Python interpreter to dynamically access Java objects in a JVM. It also allows Java programs to access Python objects.

  • Matplotlib(1.5.3 or later) is a plotting library for Python and NumPy.

Note: If you install Python using the Anaconda distribution, all the required libraries will be installed.

Last updated

Was this helpful?