Performance Benchmarks¶

This page tracks datamodel-code-generator release and main-branch benchmark results collected on GitHub Actions. The data covers only datamodel-code-generator and uses Ubuntu runners so release-to-release changes can be compared without mixing in third-party generator results. Automatic backfills select versions from PyPI download-by-version data when that public dataset is available.

datamodel-code-generator supports many schema styles and production use cases, so it includes a broad set of useful options. As releases add more capabilities, these benchmarks help keep the implementation measured, managed, and tuned so code generation stays fast in everyday use.

Historical Trends¶

Each chart plots median generation time by release version for one benchmark scenario. Each line is a formatter pipeline; missing or unsupported formatter results are skipped. Marked versions have benchmark notes below.

Compatibility backfill: Versions 0.26.4-0.34.0 use Python 3.13.14 because those releases fail during import on Python 3.14.2 before benchmark timing.

Benchmark Notes¶

Version markers in the charts and historical tables point to these benchmark interpretation notes.

• 0.29.0: The inflect dependency range was widened and cold imports became slower. Release 0.29.0 allowed inflect 7.x, which resolves typeguard 4.x in modern environments. That typeguard instrumentation increased fresh-process startup cost. Small OpenAPI is especially visible because the fixture has array component names such as Pets and Users, so class-name singularization initializes inflect while the rest of the generation work is small.
• 0.64.1: This release predates the main-branch inflect import mitigation. The latest release result still includes the inflect/typeguard cold-import cost. The effect is most visible in Small/OpenAPI because the fixture has array component names such as Pets and Users, so class-name singularization initializes inflect while the rest of the generation work is small.

Collection Policy¶

• The benchmark workflow runs on ubuntu-24.04.
• Benchmark results are collected on GitHub Actions CI runners, so median timings can vary slightly with runner load and workflow timing; rerun benchmarks before treating small differences as regressions.
• The Python version is the workflow input, defaulting to the latest configured CI Python.
• Release packages are installed from PyPI in isolated virtual environments.
• The main snapshot is installed from the GitHub repository when it is explicitly selected.
• Input coverage currently focuses on OpenAPI and JSON Schema.
• Historical backfills are produced by the Release Benchmarks workflow and committed after review.

Latest Dataset¶

• Schema version: 1
• Generated at: 2026-06-22T09:37:07Z
• Source workflow: Release Benchmarks
• Primary Python version: 3.14.2
• Entry Python versions: 3.13.14, 3.14.2
• Benchmark runs per case: mixed
• Version selection: clickpy_downloads_with_compatibility_backfill_and_main
• Selected versions: 52
• Download source: clickpy
• Download window: 365 days
• Downloads in window: 117,445,983
• PyPIStats last month: 13,805,155

Latest Release Summary¶

Results below are medians. Built-in and Ruff ratios are relative to the black/isort(Default) formatter for the same scenario.

main¶

Historical Results¶

Rows are release versions, newest first, with main shown before releases when present. Released is the PyPI upload timestamp in UTC; branch refs such as main show -. Formatter cells show median generation time; non-default cells include the speed relative to black/isort(Default) when both results are available. Rows without any successful formatter result are omitted. Version cells marked with * have benchmark notes above.