ENH: Add Polars engine to read_csv (#61813)

[abujabarmubarak]

What does this PR do?

This PR adds support for engine="polars" in the pandas.read_csv() function. It enables users to leverage the performance of the Polars DataFrame engine when reading CSV files in pandas.

---

Why is this needed?

This enhancement addresses issue #61813. Since Polars is a high-performance DataFrame library with fast CSV parsing, adding it as an engine allows pandas users to benefit from its speed while staying within the pandas API.

---

What changes were made?

✅ Added Polars Support in _read() Function

• Included a conditional block inside the _read() function in pandas/io/parsers/readers.py to handle engine="polars"
• This helps pandas use polars.read_csv() under the hood and convert the result to a pandas DataFrame using .to_pandas()

✅ Updated Engine Validation

• Modified _refine_defaults_read() to accept "polars" as a valid engine
• This ensures pandas doesn’t raise a ValueError when engine="polars" is passed

✅ Created a New Test File

• Created test_read_csv_polars.py inside pandas/tests/io/parser/
• The test verifies that using engine="polars" in read_csv() loads a simple CSV correctly
• Ensures code coverage and prevents future regressions

---

How to use it?

import pandas as pd

# Requires Polars to be installed
# pip install polars

df = pd.read_csv("example.csv", engine="polars")
print(df.head())

This allows pandas users to benefit from Polars' speed and memory efficiency while still using the familiar pandas API.

---

Dependencies

Requires the user to have Polars installed:

pip install polars

If polars is not installed, the engine will raise an ImportError with instructions.

---

Related Issues

Closes #61813

---

Let me know if any additional tests or validations are needed.