SPONSOR WORKSHOP / Paul Prescod / SalesForce
summary
Shows how a YAML-based DSL called Snowfakery is implemented as a Python interpreter, with concrete code hooks for YAML-based DSL, Jinja templating and Faker providers, and examples of plugins and providers. Demonstrates streaming outputs (JSON/CSV/SQL/Cumulus CI/Salesforce), constant-memory generation that scales to generates up to a billion rows, and use of multiprocessing, Click, PyYAML and SQLAlchemy. Includes actual recipe examples, output-stream code, and the simple plugin/provider classes used in production.
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chapters (8)
- 0:00Introduction to Snowfakery
- 1:32Core features and design
- 3:20Design principles and scale
- 6:33Demonstrating the tool
- 11:28Advanced functionality
- 12:40System architecture
- 15:20Output and connectivity
- 19:35Extensibility and scaling
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