Learning Resources
Learning resources that you can go through on your own time. Or take a look at the instructor-led training catalog as well as our upcoming training schedule.
Prerequisites of this course include familiarity with Emme Desktop and Emme Modeller and some basic Python knowledge.
View the course notebooks in your browser, or download the notebooks and follow along on your own with demonstration data. These materials are developed for Emme 4.5.0 and later, but may be adapted on previous versions.
You must be logged in and have active Software Maintenance for Emme to download these lessons. Please contact us to learn more.
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Lesson 0: Python Basics
This is a simple tutorial covering the basics of the Python programming language.
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Lesson 1: Modeller API - Running Tools and Workflows
Learn how to run a script execution of any Emme Modeller tool. Work effectively with tool specifications, implement model workflows using iterative or conditional control flow, and write comments to the Logbook for auditing.
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Lesson 2: Network API - Read, Write and Process Network Data
Learn how to read, manipulate and publish Emme network data using the Emme Network API.
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Lesson 3: Matrix API - Read, Write and Process Matrix Data
Learn how to access, manipulate, import and export matrix data using the Matrix API.
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Lesson 4: Desktop API - Automate Charts and Reports
Learn how to automate Emme Desktop using the Desktop API.
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Lesson 5: Running Emme Workflows outside Emme Desktop
Learn how to start Emme from a simple Python call to achieve Emme workflows without having to use the software interactively. Useful to automate workflows from A to Z, to implement distributed model computing etc.
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Lesson 6: Building Modeller Tools and Modules
Learn how to create and distribute our own toolboxes and tools.
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