Using Python Packages

One of the powers of Python is its ability to use thousands of additional modules in its scripts. There are 4 main sources of Python packages that may be installed or loaded into Python 3.

Built-in Modules

Rhino comes with many built-in modules that add functionality. To use methods within built-in modules they simply need to be imported first:

import math

Here’s a list of most useful predefined modules within Python:

  • Date and Time
    • datetime — Basic date and time types
    • time — Time access and conversions
  • Numeric and Mathematical Modules
    • math — Mathematical functions
    • fractions — Rational numbers
    • random — Generate pseudo-random numbers
  • File and Directory Access
    • System.IO — Common pathname manipulations
    • tempfile — Generate temporary files and directories
    • csv — CSV File Reading and Writing
  • String Services
    • string — Common string operations
    • StringIO — Read and write strings as files
    • fpformat — Floating point conversions

A complete list of predefined modules in Python, see the Python Standard Library modules

Local Modules

Other Python files can be used to import functions using Def

For instance in a file here are two defined functions print_rhino_version and get_python_version

import Rhino
import sys

def print_rhino_version():
    ver = str(Rhino.RhinoApp.Version)
    versp = ver.split(".")
    print("Major version: " + versp[0])
    print("Service Release: " + versp[1])

def get_python_version():
    ver = sys.version
    print("Python version: " + ver)

Those functions then can be imported and called by:

import python_functions as pf


Additonal details can be found on Functions in Python

Python Package Index (PyPI)

PyPI is a repository of software for the Python programming language with over 500,000 packages.
You can specify the packages required for your scripts inside the script source. This creates self-contained scripts that carry all their requirements with them. Python 3 will use pip to install packages from Note: pip does not support Python 2 any longer.

Popular PyPI packages are:

  • Pandas - data analysis toolkit
  • Numpy - popular scientific computing with Python
  • Scipy - modules for statistics, optimization, integration, linear algebra, Fourier transforms, signal and image processing
  • pyyaml - human-readable YAML-serialized data
  • Pillow - Python Imaging Library
  • openpyxl - library to read/write Excel 2010 xlsx/xlsm/xltx/xltm files.

Looking at a Python 3 default script, we can specify required packages using this syntax:

# r: numpy


# requirements: numpy

Let’s create a new Python 3 script and add numpy as a package and use that in our script:

# r: numpy

import numpy

print(f"using numpy: {numpy.version.full_version}\n")

for i in numpy.random.rand(10):

Click Run, and the script editor will attempt to install the required packages before running the script. This process might take some time and the editor is going to be disabled. Once the packages are installed, editor will continue to execute the script:

Multiple packages can be install and are recommended to be listed on the same line:

#r: numpy, scipy

Additional PyPI version specifiers can also be used as referenced in Install PyPI Syntax Guide

You may search the PyPI website for the many available packages.

Downloading Python Libraries (Modules)

The last way that packages can be used is to download the packages and put them into a library on the computer. This allows very tight control of the packages. This is also a good way to install packages that are not available on PyPI.

Another method of adding local packages to Python scripts is by adding their path to the sys.path. You can simplify this step by using the # env: specifier in your scripts to automatically add a path to the sys.path before running your script. Note: Create a customer folder for the downloaded modules as Rhino updates may overwrite the internal defaults folders.

# env: C:/Path/To/Where/My/Library/Is/Located/

import mylibrary