From 9681802be2fbc1922052eab060efeefa7c29a228 Mon Sep 17 00:00:00 2001
From: Stainless Bot <dev@stainlessapi.com>
Date: Wed, 13 Sep 2023 19:22:34 +0000
Subject: [PATCH] docs: add some missing inline documentation

---
 src/finch/_base_client.py      | 11 +++++++++++
 src/finch/_utils/_transform.py |  4 ++++
 src/finch/_utils/_utils.py     |  6 ++++++
 3 files changed, 21 insertions(+)

diff --git a/src/finch/_base_client.py b/src/finch/_base_client.py
index 58309b6b..9437d66b 100644
--- a/src/finch/_base_client.py
+++ b/src/finch/_base_client.py
@@ -132,6 +132,17 @@ def __init__(
 
 
 class BasePage(GenericModel, Generic[ModelT]):
+    """
+    Defines the core interface for pagination.
+
+    Type Args:
+        ModelT: The pydantic model that represents an item in the response.
+
+    Methods:
+        has_next_page(): Check if there is another page available
+        next_page_info(): Get the necesary information to make a request for the next page
+    """
+
     _options: FinalRequestOptions = PrivateAttr()
     _model: Type[ModelT] = PrivateAttr()
 
diff --git a/src/finch/_utils/_transform.py b/src/finch/_utils/_transform.py
index 9bb71090..c007d8b0 100644
--- a/src/finch/_utils/_transform.py
+++ b/src/finch/_utils/_transform.py
@@ -108,6 +108,10 @@ def _get_annoted_type(type_: type) -> type | None:
 
 
 def _maybe_transform_key(key: str, type_: type) -> str:
+    """Transform the given `data` based on the annotations provided in `type_`.
+
+    Note: this function only looks at `Annotated` types that contain `PropertInfo` metadata.
+    """
     annotated_type = _get_annoted_type(type_)
     if annotated_type is None:
         # no `Annotated` definition for this type, no transformation needed
diff --git a/src/finch/_utils/_utils.py b/src/finch/_utils/_utils.py
index dde4b457..603f7c10 100644
--- a/src/finch/_utils/_utils.py
+++ b/src/finch/_utils/_utils.py
@@ -27,6 +27,12 @@ def extract_files(
     *,
     paths: Sequence[Sequence[str]],
 ) -> list[tuple[str, FileTypes]]:
+    """Recursively extract files from the given dictionary based on specified paths.
+
+    A path may look like this ['foo', 'files', '<array>', 'data'].
+
+    Note: this mutates the given dictionary.
+    """
     files: list[tuple[str, FileTypes]] = []
     for path in paths:
         files.extend(_extract_items(query, path, index=0, flattened_key=None))