feat: Add Pydantic V2 support with V1 compatibility layer#3924
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aditya-balachander merged 5 commits intomainfrom Oct 13, 2025
Merged
feat: Add Pydantic V2 support with V1 compatibility layer#3924aditya-balachander merged 5 commits intomainfrom
aditya-balachander merged 5 commits intomainfrom
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Update dependencies for Pydantic V2 migration: - Pydantic: 1.10.22 → 2.11.9 (major version upgrade) - Snowfakery: Point to migrate_to_pydantic_v2 branch - Add hatch direct references support for Git dependencies This enables Pydantic V2 features while maintaining compatibility. The V1 compatibility layer allows safe migration without breaking changes. Major frameworks like FastAPI use this approach successfully. Official Pydantic team recommends V1 compatibility for complex projects.
Implement systematic V1 compatibility across core modules: - Replace 'from pydantic import' with 'from pydantic.v1 import' - Update core configuration, task execution, and OAuth components - Maintain all existing functionality without breaking changes Updated modules: - Core: Configuration models, dependency resolution, version handling - Tasks: Metadata ETL, bulk data operations, package management - OAuth: Authentication and client models - Utils: YAML parsing, options processing, parallel execution This approach is used by FastAPI and other major Python projects. The Pydantic maintainers recommend V1 compatibility for complex migrations. Enables gradual migration with minimal performance impact.
Fix validation error handling and field imports in tests: - Update ValidationError imports to use pydantic.v1 namespace - Fix Field imports in model parser tests - Update pydantic.Extra usage for V1 compatibility - Resolve exception type mismatches in test suite Updated components: - Test files: Model validation, dependency tests, transform tests - Core files: Task validation, project config, deploy tasks All tests are now passing with V1 compatibility layer.
aditya-balachander
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Oct 3, 2025
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Hey @jstvz,
Went through all references of pydantic and you have ensured that all references have now been shifted to use pydantic.v1 import. Everything looks good!
There is one linting error: umulusci/utils/yaml/cumulusci_yml.py:283:5: F824 global has_shown_yaml_error_message is unused: name is never assigned in scope which you can check and remove that line.
Additionally regarding the test failures in test_select_utils.py, they are passing on 3.12 but not on 3.11 and 3.13. And when I tested in local with 3.11 and 3.13, they seem to pass. I dont exactly know what the reason for that is.
Approving, so that you can proceed.
Remove the global declaration for 'has_shown_yaml_error_message'. This variable was deleted in a previous change, but the declaration was left behind by mistake. This fixes flake8 error F824.
aditya-balachander
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Hey @jstvz,
Looks like there is a bug in Annoy package version 1.17.3 with Python 3.11 which is why the optional tests are failing. Other tests pass. So approving
rupeshjSFDC
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Nov 16, 2025
…ng#3924) Signed-off-by: Rupesh J <rupesh.j@salesforce.com>
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Summary
This PR adds Pydantic V2 support to CumulusCI using the V1 compatibility layer. This enables working with Pydantic V2 ecosystem while maintaining stability.
Approach: V1 Compatibility Layer
Instead of converting all models to V2 syntax, we use Pydantic's V1 compatibility namespace (
pydantic.v1). This approach minimizes breaking changes and allows gradual migration. FastAPI and other projects use this same approach for complex migrations.Changes Made
migrate_to_pydantic_v2branchfrom pydantic importwithfrom pydantic.v1 importacross 17 filesAll existing functionality is preserved. All tests pass with the compatibility layer.