⚡️ Speed up method IndexVariable._to_index by 105%

[codeflash-ai]

📄 105% (1.05x) speedup for IndexVariable._to_index in xarray/core/variable.py

⏱️ Runtime : 2.16 milliseconds → 1.06 milliseconds (best of 24 runs)

📝 Explanation and details

The optimized code achieves a 104% speedup by avoiding unnecessary pandas Index operations through strategic conditional checks. The key optimizations are:

What was optimized:

1. MultiIndex optimization: Added a check to skip set_names() when all level names are already non-None, avoiding expensive MultiIndex reconstruction
2. Regular Index optimization: Added a check to only call set_names() when the current name differs from the target name, preventing unnecessary Index object creation
3. Memory efficiency: Replaced list comprehension with tuple generator expression for level names construction

Why this leads to speedup:

• Pandas Index objects are immutable, so set_names() creates entirely new Index instances even when no changes are needed
• The original code unconditionally called set_names() for both MultiIndex (with reconstructed level names) and regular Index cases
• MultiIndex creation is particularly expensive due to its complex internal structure
• The optimized version short-circuits these expensive operations when they would produce identical results

Performance characteristics:
The optimization is most effective when:

• MultiIndex objects already have properly named levels (common in real-world usage)
• Index objects already have the correct name set
• Working with large indexes where object creation overhead is significant

This optimization maintains identical behavior while eliminating redundant pandas operations, making it particularly valuable in data processing pipelines where _to_index() may be called frequently during coordinate and indexing operations.

✅ Correctness verification report:

Test	Status
⚙️ Existing Unit Tests	🔘 None Found
🌀 Generated Regression Tests	✅ 1 Passed
⏪ Replay Tests	✅ 255 Passed
🔎 Concolic Coverage Tests	🔘 None Found
📊 Tests Coverage	100.0%

🌀 Generated Regression Tests and Runtime

import pandas as pd

# imports
import pytest
from xarray.core.variable import IndexVariable

# Function to test: IndexVariable._to_index
# (Full implementation included above, so we will use it as provided.)


# Helper function to create IndexVariable easily
def make_index_variable(dim, data, name=None):
    # Optionally set index name
    idx = pd.Index(data, name=name)
    return IndexVariable([dim], idx)


def make_multiindex_variable(dim, arrays, names=None):
    # arrays: list of arrays for levels
    mi = pd.MultiIndex.from_arrays(arrays, names=names)
    return IndexVariable([dim], mi)


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


def test_indexvariable_raises_on_ndim_not_1():
    # IndexVariable must be 1-dimensional
    arr = pd.Index([[1, 2], [3, 4]])
    with pytest.raises(ValueError):
        IndexVariable(["x", "y"], arr)

⏪ Replay Tests and Runtime

Test File::Test Function	Original ⏱️	Optimized ⏱️	Speedup
test_pytest_xarrayteststest_concat_py_xarrayteststest_computation_py_xarrayteststest_formatting_py_xarray__replay_test_0.py::test_xarray_core_variable_IndexVariable__to_index	1.45ms	448μs	223%✅

To edit these changes git checkout codeflash/optimize-IndexVariable._to_index-miivbk4v and push.