ARROW-154 Add blacken-docs to pre-commit hook (#133)

Author: juliusgeo

.pre-commit-config.yaml

@@ -61,3 +61,10 @@ repos:
       files: ^\.github/workflows/
       types: [yaml]
       args: ["--schemafile", "https://json.schemastore.org/github-workflow"]
+
+- repo: https://github.com/adamchainz/blacken-docs
+  rev: "1.13.0"
+  hooks:
+  - id: blacken-docs
+    additional_dependencies:
+    - black==22.3.0

bindings/python/README.rst

@@ -12,30 +12,32 @@ PyMongoArrow
 for loading MongoDB query result sets as Apache Arrow tables, Pandas
 DataFrames or NumPy arrays.
 
-.. code-block:: python
+.. code-block:: pycon
 
   >>> from pymongoarrow.monkey import patch_all
-  >>> patch_all()
-  >>> from pymongoarrow.api import Schema
-  >>> schema = Schema({'_id': int, 'qty': float})
-  >>> from pymongo import MongoClient
-  >>> client = MongoClient()
-  >>> client.db.data.insert_many([{'_id': 1, 'qty': 25.4}, {'_id': 2, 'qty': 16.9}, {'_id': 3, 'qty': 2.3}])
-  >>> data_frame = client.db.test.find_pandas_all({}, schema=schema)
-  >>> data_frame
+  ... patch_all()
+  ... from pymongoarrow.api import Schema
+  ... schema = Schema({"_id": int, "qty": float})
+  ... from pymongo import MongoClient
+  ... client = MongoClient()
+  ... client.db.data.insert_many(
+  ...     [{"_id": 1, "qty": 25.4}, {"_id": 2, "qty": 16.9}, {"_id": 3, "qty": 2.3}]
+  ... )
+  ... data_frame = client.db.test.find_pandas_all({}, schema=schema)
+  ... data_frame
      _id   qty
   0    1  25.4
   1    2  16.9
   2    3   2.3
-  >>> arrow_table = client.db.test.find_arrow_all({}, schema=schema)
+  ... arrow_table = client.db.test.find_arrow_all({}, schema=schema)
   # The schema may also be omitted
-  >>> arrow_table = client.db.test.find_arrow_all({})
-  >>> arrow_table
+  ... arrow_table = client.db.test.find_arrow_all({})
+  ... arrow_table
   pyarrow.Table
   _id: int64
   qty: double
-  >>> ndarrays = client.db.test.find_numpy_all({}, schema=schema)
-  >>> ndarrays
+  ... ndarrays = client.db.test.find_numpy_all({}, schema=schema)
+  ... ndarrays
   {'_id': array([1, 2, 3]), 'qty': array([25.4, 16.9,  2.3])}
 
 **PyMongoArrow** is the recommended way to