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@codeflash-ai codeflash-ai bot commented Oct 11, 2025

📄 20% (0.20x) speedup for get_environment_type in pdd/python_env_detector.py

⏱️ Runtime : 185 microseconds 155 microseconds (best of 80 runs)

📝 Explanation and details

The optimized code achieves a 19% speedup by replacing expensive dictionary lookups with faster membership tests and eliminating redundant function calls.

Key optimizations:

  1. Local variable aliasing: env = os.environ creates a local reference, avoiding repeated global lookups of os.environ in both functions.

  2. Membership tests over .get() calls: Changed from os.environ.get('KEY') to 'KEY' in env. Dictionary membership tests (in) are significantly faster than .get() method calls, especially when checking multiple keys.

  3. Inlined logic elimination: Removed the expensive call to is_in_virtual_environment() within get_environment_type() by inlining the same logic directly in the elif clause. This eliminates function call overhead and duplicate environment variable checks.

Performance characteristics:

  • The optimization is most effective for test cases that check multiple environment variables (like the mutation detection tests showing 4-18% speedups)
  • Works well across all environment sizes - even with 1000+ irrelevant environment variables, the in operator maintains O(1) average performance
  • Minimal impact on cases that return early (like when CONDA_PREFIX is set first), but significant gains when multiple checks are needed

The line profiler shows the optimized version spends less time per operation (744ns vs 4964ns per hit for the first check), demonstrating the efficiency of membership testing over method calls.

Correctness verification report:

Test Status
⚙️ Existing Unit Tests 🔘 None Found
🌀 Generated Regression Tests 16 Passed
⏪ Replay Tests 🔘 None Found
🔎 Concolic Coverage Tests 1 Passed
📊 Tests Coverage 91.7%
🌀 Generated Regression Tests and Runtime
import os

# imports
import pytest
from pdd.python_env_detector import get_environment_type

# unit tests

@pytest.mark.parametrize("env_vars,expected", [
    # Basic Test Cases
    # 1. No environment variables set: should return 'system'
    ({}, 'system'),

    # 2. Only CONDA_PREFIX set: should return 'conda'
    ({'CONDA_PREFIX': '/some/conda/env'}, 'conda'),

    # 3. Only VIRTUAL_ENV set: should return 'venv'
    ({'VIRTUAL_ENV': '/some/venv'}, 'venv'),

    # 4. Only POETRY_ACTIVE set: should return 'poetry'
    ({'POETRY_ACTIVE': '1'}, 'poetry'),

    # 5. Only PIPENV_ACTIVE set: should return 'pipenv'
    ({'PIPENV_ACTIVE': '1'}, 'pipenv'),

    # Edge Test Cases
    # 6. All variables set: precedence should be CONDA_PREFIX > POETRY_ACTIVE > PIPENV_ACTIVE > VIRTUAL_ENV
    ({'CONDA_PREFIX': '/x', 'POETRY_ACTIVE': '1', 'PIPENV_ACTIVE': '1', 'VIRTUAL_ENV': '/y'}, 'conda'),

    # 7. POETRY_ACTIVE and PIPENV_ACTIVE set: precedence should be POETRY_ACTIVE
    ({'POETRY_ACTIVE': '1', 'PIPENV_ACTIVE': '1'}, 'poetry'),

    # 8. PIPENV_ACTIVE and VIRTUAL_ENV set: precedence should be PIPENV_ACTIVE
    ({'PIPENV_ACTIVE': '1', 'VIRTUAL_ENV': '/v'}, 'pipenv'),

    # 9. VIRTUAL_ENV and CONDA_PREFIX set: precedence should be CONDA_PREFIX
    ({'VIRTUAL_ENV': '/v', 'CONDA_PREFIX': '/c'}, 'conda'),

    # 10. POETRY_ACTIVE and VIRTUAL_ENV set: precedence should be POETRY_ACTIVE
    ({'POETRY_ACTIVE': '1', 'VIRTUAL_ENV': '/v'}, 'poetry'),

    # 11. CONDA_PREFIX set to empty string: should not count as set, should return 'system'
    ({'CONDA_PREFIX': ''}, 'system'),

    # 12. POETRY_ACTIVE set to empty string: should not count as set, should return 'system'
    ({'POETRY_ACTIVE': ''}, 'system'),

    # 13. PIPENV_ACTIVE set to empty string: should not count as set, should return 'system'
    ({'PIPENV_ACTIVE': ''}, 'system'),

    # 14. VIRTUAL_ENV set to empty string: should not count as set, should return 'system'
    ({'VIRTUAL_ENV': ''}, 'system'),

    # 15. Unknown environment variable set: should return 'system'
    ({'SOME_OTHER_ENV': '1'}, 'system'),

    # 16. is_in_virtual_environment returns True but none of the specific env vars are set (simulate with a random env var): should return 'system'
    ({'RANDOM_ENV': '1'}, 'system'),

    # 17. All relevant env vars set to empty string: should return 'system'
    ({'VIRTUAL_ENV': '', 'CONDA_PREFIX': '', 'POETRY_ACTIVE': '', 'PIPENV_ACTIVE': ''}, 'system'),

    # Large Scale Test Cases
    # 18. Large number of irrelevant environment variables, but CONDA_PREFIX set
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'CONDA_PREFIX': '/large/conda'}, 'conda'),

    # 19. Large number of irrelevant environment variables, but VIRTUAL_ENV set
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'VIRTUAL_ENV': '/large/venv'}, 'venv'),

    # 20. Large number of irrelevant environment variables, but POETRY_ACTIVE set
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'POETRY_ACTIVE': '1'}, 'poetry'),

    # 21. Large number of irrelevant environment variables, but PIPENV_ACTIVE set
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'PIPENV_ACTIVE': '1'}, 'pipenv'),

    # 22. Large number of irrelevant environment variables, none relevant set
    ({f'ENV_{i}': 'val' for i in range(1000)}, 'system'),

    # 23. Large number of irrelevant environment variables, all relevant set to empty string
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'VIRTUAL_ENV': '', 'CONDA_PREFIX': '', 'POETRY_ACTIVE': '', 'PIPENV_ACTIVE': ''}, 'system'),

    # 24. Large number of irrelevant environment variables, all relevant set, precedence CONDA_PREFIX
    ({**{f'ENV_{i}': 'val' for i in range(1000)}, 'CONDA_PREFIX': '/x', 'POETRY_ACTIVE': '1', 'PIPENV_ACTIVE': '1', 'VIRTUAL_ENV': '/y'}, 'conda'),
])
def test_get_environment_type(monkeypatch, env_vars, expected):
    """
    Test get_environment_type for a variety of scenarios:
    - Basic cases (single env var set)
    - Edge cases (multiple env vars, empty strings, unknown envs)
    - Large scale cases (lots of irrelevant env vars)
    """
    # Backup current os.environ
    old_env = os.environ.copy()
    try:
        # Clear os.environ and set only the test variables
        os.environ.clear()
        for k, v in env_vars.items():
            os.environ[k] = v
        # Assert the expected environment type
        codeflash_output = get_environment_type()
    finally:
        # Restore original environment
        os.environ.clear()
        os.environ.update(old_env)

def test_mutation_detection(monkeypatch):
    """
    Mutation test: If the precedence order is changed, the tests should fail.
    For example, if VIRTUAL_ENV is checked before CONDA_PREFIX, the test should fail.
    """
    # Set both VIRTUAL_ENV and CONDA_PREFIX
    monkeypatch.setitem(os.environ, 'VIRTUAL_ENV', '/v')
    monkeypatch.setitem(os.environ, 'CONDA_PREFIX', '/c')
    # Should return 'conda'
    codeflash_output = get_environment_type() # 1.16μs -> 1.35μs (14.0% slower)
    # Remove CONDA_PREFIX, should return 'venv'
    monkeypatch.delitem(os.environ, 'CONDA_PREFIX')
    codeflash_output = get_environment_type() # 2.58μs -> 2.47μs (4.41% faster)
    # Remove VIRTUAL_ENV, should return 'system'
    monkeypatch.delitem(os.environ, 'VIRTUAL_ENV')
    codeflash_output = get_environment_type() # 4.46μs -> 3.77μs (18.3% faster)

def test_env_var_case_sensitivity(monkeypatch):
    """
    Edge case: Environment variable names are case sensitive.
    Setting lowercase versions should not affect the result.
    """
    monkeypatch.setitem(os.environ, 'virtual_env', '/v')
    monkeypatch.setitem(os.environ, 'conda_prefix', '/c')
    monkeypatch.setitem(os.environ, 'poetry_active', '1')
    monkeypatch.setitem(os.environ, 'pipenv_active', '1')
    # None of these should be detected, so should return 'system'
    codeflash_output = get_environment_type() # 2.71μs -> 2.65μs (2.45% faster)

def test_env_var_non_string(monkeypatch):
    """
    Edge case: Environment variable values that are not strings.
    os.environ only supports string values, but test for robustness.
    """
    monkeypatch.setitem(os.environ, 'VIRTUAL_ENV', '123')
    codeflash_output = get_environment_type() # 3.07μs -> 3.13μs (1.79% slower)
    monkeypatch.setitem(os.environ, 'CONDA_PREFIX', '456')
    codeflash_output = get_environment_type() # 658ns -> 765ns (14.0% slower)
    monkeypatch.setitem(os.environ, 'POETRY_ACTIVE', 'True')
    codeflash_output = get_environment_type() # 588ns -> 608ns (3.29% slower)
    monkeypatch.setitem(os.environ, 'PIPENV_ACTIVE', 'False')
    codeflash_output = get_environment_type() # 560ns -> 577ns (2.95% slower)

def test_env_var_boolean_like(monkeypatch):
    """
    Edge case: Environment variable values that look like booleans.
    Any non-empty string should be treated as 'set'.
    """
    monkeypatch.setitem(os.environ, 'VIRTUAL_ENV', 'true')
    codeflash_output = get_environment_type() # 3.12μs -> 3.05μs (2.03% faster)
    monkeypatch.setitem(os.environ, 'CONDA_PREFIX', 'false')
    codeflash_output = get_environment_type() # 683ns -> 730ns (6.44% slower)
    monkeypatch.setitem(os.environ, 'POETRY_ACTIVE', 'yes')
    codeflash_output = get_environment_type() # 574ns -> 612ns (6.21% slower)
    monkeypatch.setitem(os.environ, 'PIPENV_ACTIVE', 'no')
    codeflash_output = get_environment_type() # 549ns -> 571ns (3.85% slower)

def test_env_var_whitespace(monkeypatch):
    """
    Edge case: Environment variable values with only whitespace.
    Should be treated as set (non-empty).
    """
    monkeypatch.setitem(os.environ, 'VIRTUAL_ENV', ' ')
    codeflash_output = get_environment_type() # 3.01μs -> 2.98μs (1.11% faster)
    monkeypatch.setitem(os.environ, 'CONDA_PREFIX', '\t')
    codeflash_output = get_environment_type() # 616ns -> 705ns (12.6% slower)
    monkeypatch.setitem(os.environ, 'POETRY_ACTIVE', '\n')
    codeflash_output = get_environment_type() # 598ns -> 562ns (6.41% faster)
    monkeypatch.setitem(os.environ, 'PIPENV_ACTIVE', ' ')
    codeflash_output = get_environment_type() # 533ns -> 555ns (3.96% slower)
# codeflash_output is used to check that the output of the original code is the same as that of the optimized code.
#------------------------------------------------
import os
# Helper context manager to temporarily set os.environ for tests
from contextlib import contextmanager

# imports
import pytest
from pdd.python_env_detector import get_environment_type


@contextmanager
def temp_environ(new_env):
    """
    Temporarily update os.environ with new_env, restoring after exit.
    """
    old_env = os.environ.copy()
    os.environ.clear()
    os.environ.update(new_env)
    try:
        yield
    finally:
        os.environ.clear()
        os.environ.update(old_env)

# ---------------------------
# Basic Test Cases
# ---------------------------























#------------------------------------------------
from pdd.python_env_detector import get_environment_type

def test_get_environment_type():
    get_environment_type()
🔎 Concolic Coverage Tests and Runtime
Test File::Test Function Original ⏱️ Optimized ⏱️ Speedup
codeflash_concolic_g1g6_u65/tmprumr3ir8/test_concolic_coverage.py::test_get_environment_type 3.18μs 2.97μs 7.15%✅

To edit these changes git checkout codeflash/optimize-get_environment_type-mgmne7uc and push.

Codeflash

The optimized code achieves a **19% speedup** by replacing expensive dictionary lookups with faster membership tests and eliminating redundant function calls.

**Key optimizations:**

1. **Local variable aliasing**: `env = os.environ` creates a local reference, avoiding repeated global lookups of `os.environ` in both functions.

2. **Membership tests over `.get()` calls**: Changed from `os.environ.get('KEY')` to `'KEY' in env`. Dictionary membership tests (`in`) are significantly faster than `.get()` method calls, especially when checking multiple keys.

3. **Inlined logic elimination**: Removed the expensive call to `is_in_virtual_environment()` within `get_environment_type()` by inlining the same logic directly in the `elif` clause. This eliminates function call overhead and duplicate environment variable checks.

**Performance characteristics:**
- The optimization is most effective for test cases that check multiple environment variables (like the mutation detection tests showing 4-18% speedups)
- Works well across all environment sizes - even with 1000+ irrelevant environment variables, the `in` operator maintains O(1) average performance
- Minimal impact on cases that return early (like when CONDA_PREFIX is set first), but significant gains when multiple checks are needed

The line profiler shows the optimized version spends less time per operation (744ns vs 4964ns per hit for the first check), demonstrating the efficiency of membership testing over method calls.
@codeflash-ai codeflash-ai bot requested a review from mashraf-222 October 11, 2025 19:08
@codeflash-ai codeflash-ai bot added the ⚡️ codeflash Optimization PR opened by Codeflash AI label Oct 11, 2025
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