oracletrace 2.0.1

Detect Python performance regressions and compare execution traces with lightweight call graph visualization

OracleTrace — Detect Python Performance Regressions with Execution Diff

Detect performance regressions between runs of your Python script in seconds.

Fail your CI when performance regresses. OracleTrace is a git diff for performance. Run your script twice and instantly see what got slower — with function-level precision.

Documentation: https://kaykcaputo.github.io/oracletrace/

Featured in: PyCoder's Weekly #729 • awesome-debugger • awesome-profiling

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Installation

pip install oracletrace

Quick Start

1. See where your program spends time instantly:

oracletrace app.py

2. Compare runs and detect regressions:

oracletrace app.py --json baseline.json
oracletrace app.py --json new.json --compare baseline.json

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See it in action

See exactly which functions got slower between runs:

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Example Output

Starting application...

Iteration 1:
  > Processing data...
    > Calculating results...

Iteration 2:
  > Processing data...
    > Calculating results...

Application finished.

Summary:
                         Top functions by Total Time
┏━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━┳━━━━━━━━━━━━━━━━┳━━━━━━━┳━━━━━━━━━━━━━━━━━━━━━┓
┃ Function                     ┃ Total Time (s) ┃ Calls ┃ Avg. Time/Call (ms) ┃
┡━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━╇━━━━━━━━━━━━━━━━╇━━━━━━━╇━━━━━━━━━━━━━━━━━━━━━┩
│ my_app.py:main               │         0.6025 │     1 │             602.510 │
│ my_app.py:process_data       │         0.6021 │     2 │             301.050 │
│ my_app.py:calculate_results  │         0.4015 │     2 │             200.750 │
└──────────────────────────────┴────────────────┴───────┴─────────────────────┘

Logic Flow:
<module>
└── my_app.py:main (1x, 0.6025s)
    └── my_app.py:process_data (2x, 0.6021s)
        └── my_app.py:calculate_results (2x, 0.4015s)

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Why OracleTrace?

Problem

Performance regressions are hard to detect early.

Solution

OracleTrace compares execution traces and highlights what got slower.

How it works

1. Run your script
2. Generate a trace
3. Compare results
4. Identify slowdowns

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CI Integration

Fail your pipeline when performance degrades:

oracletrace app.py --json current.json --compare baseline.json --fail-on-regression --threshold 25

Add it to your CI to automatically fail on performance regressions.

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Key Features

• Detect slower and faster functions
• Identify new or removed functions
• Execution time and call count analysis
• Call graph visualization
• JSON and CSV export
• Regex-based filtering (--ignore)
• Top-N function focus (--top)
• CI regression gates

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CLI Reference

Flag	Description
--json	Export trace to JSON
--csv	Export trace to CSV
--compare	Compare with another trace
--fail-on-regression	Exit with error if regression detected
--threshold	Regression percentage threshold
--ignore	Ignore functions/files via regex
--top	Show top N functions

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Use Cases

Primary

• Detect performance regressions between runs

Secondary

• CI performance validation
• Execution trace inspection
• Call graph visualization

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How It Works

OracleTrace uses Python’s sys.setprofile() to intercept function calls and returns.

It measures execution time per function and records caller–callee relationships.

Filtering removes external/internal calls to focus on application code.

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Requirements

• Python >= 3.10
• rich

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Contributing

Contributions are welcome.

Please read the Contributing Guide for details on how to get started, coding standards, and the contribution process.

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Contributors

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⭐ Support the Project

If OracleTrace is useful, consider giving it a star:

GitHub Repository

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Maintainers

• Kayk Caputo
• André Gustavo