### What changes were proposed in this pull request?

As a follow-up to #24830, this PR adds the `recursiveFileLookup` option to the Python DataFrameReader API.

### Why are the changes needed?

This PR maintains Python feature parity with Scala.

### Does this PR introduce any user-facing change?

Yes.

Before this PR, you'd only be able to use this option as follows:

```python
spark.read.option("recursiveFileLookup", True).text("test-data").show()
```

With this PR, you can reference the option from within the format-specific method:

```python
spark.read.text("test-data", recursiveFileLookup=True).show()
```

This option now also shows up in the Python API docs.

### How was this patch tested?

I tested this manually by creating the following directories with dummy data:

```
test-data
├── 1.txt
└── nested
   └── 2.txt
test-parquet
├── nested
│  ├── _SUCCESS
│  ├── part-00000-...-.parquet
├── _SUCCESS
├── part-00000-...-.parquet
```

I then ran the following tests and confirmed the output looked good:

```python
spark.read.parquet("test-parquet", recursiveFileLookup=True).show()
spark.read.text("test-data", recursiveFileLookup=True).show()
spark.read.csv("test-data", recursiveFileLookup=True).show()
```

`python/pyspark/sql/tests/test_readwriter.py` seems pretty sparse. I'm happy to add my tests there, though it seems we have been deferring testing like this to the Scala side of things.

Closes #26718 from nchammas/SPARK-27990-recursiveFileLookup-python.

Authored-by: Nicholas Chammas <nicholas.chammas@gmail.com>
Signed-off-by: HyukjinKwon <gurwls223@apache.org>