docs: add some more detail on initialize client

docs/InitializeClient.rst

@@ -1,6 +1,10 @@
-Initialize Client
+Setup
 -----------------
-By default, nbiatoolkit uses the guest account to access all collections in the API that are publicly available.
+
+Initialize Client
+^^^^^^^^^^^^^^^^^
+
+By default, the `NBIAClient` uses the guest account to access all collections in the API that are publicly available.
 If you have a user account that has been granted specific access to a collection, you can use your credentials to
 initialize the client when performing a query.
 
@@ -71,11 +75,58 @@ This is especially useful when using the client in a script with a predefined sc
 
       The context manager is not available in the command line interface.
 
+Return Types of Methods
+^^^^^^^^^^^^^^^^^^^^^^^
+By default, most functions that query the API for metadata will return a list of dictionaries.
+Available return types are made available through the `ReturnType` Enum which can be passed in as a parameter,
+or its string representation. The available options as of writing are "list", and "dataframe".
+
+If you would like to return the data as a pandas DataFrame, you can pass the
+`return_type` argument to the respective class method:
+
+.. tabs::
+
+   .. tab:: Python
+
+      .. code-block:: python
+
+         from nbiatoolkit import NBIAClient
+         from nbiatoolkit.utils import ReturnType
+
+         client = NBIAClient()
+         client.getCollections(prefix='TCGA', return_type='dataframe')
+         # equivalent to
+         client.getCollections(prefix='TCGA', return_type=ReturnType.DATAFRAME)
+
+   .. tab:: Command Line
+
+      Return types are not yet available in the command line interface.
+      Feel free to open an issue on the GitHub repository if you would like to see this feature added.
+
+
+Alternatively, you can set the return type for all methods by passing the `return_type` argument to the NBIAClient class.
+
+.. tabs::
+
+   .. tab:: Python
+
+      .. code-block:: python
+
+         from nbiatoolkit import NBIAClient
+
+         client = NBIAClient(return_type='dataframe')
+         client.getCollections(prefix='TCGA')
+
+   .. tab:: Command Line
+
+      Return types are not yet available in the command line interface.
+      Feel free to open an issue on the GitHub repository if you would like to see this feature added.
+
 
 Logging
 ^^^^^^^
 The client can be initialized with a log level to control the verbosity of the logs. This is primarily intended for debugging and development purposes.
-The default log level is 'INFO' and the available log levels are 'DEBUG', 'INFO', 'WARNING', 'ERROR'.
+The default log level is 'INFO' and the available log levels are `DEBUG`, `INFO`, `WARNING`, `ERROR`.
 
 .. tabs::
 
@@ -85,9 +136,10 @@ The default log level is 'INFO' and the available log levels are 'DEBUG', 'INFO'
 
          from nbiatoolkit import NBIAClient
 
-         client = NBIAClient(log_level='DEBUG)
+         client = NBIAClient(log_level='DEBUG')
          client.getCollections(prefix='TCGA')
 
    .. tab:: Command Line
 
-         Logging is not yet available in the command line interface. Feel free to open an issue on the GitHub repository if you would like to see this feature added.
+         Logging is not yet available in the command line interface.
+         Feel free to open an issue on the GitHub repository if you would like to see this feature added.

docs/markdowns/Installation.md

@@ -1,9 +1,8 @@
 # Installation
 
-> [!WARNING]
-> `nbiatoolkit` is currently under development and is not guaranteed to be stable.
-> Please refer to the [1.0.0 Stable Release Milestone](https://github.com/jjjermiah/nbia-toolkit/milestone/1) for the roadmap
-> to the first stable release.
+`nbiatoolkit` is currently under development and is not guaranteed to be stable.
+Please refer to the [1.0.0 Stable Release Milestone](https://github.com/jjjermiah/nbia-toolkit/milestone/1) for the roadmap
+to the first stable release.
 
 ## PyPi
 

src/nbiatoolkit/nbia.py

@@ -36,6 +36,20 @@ def conv_response_list(
     response_json: List[dict[Any, Any]],
     return_type: ReturnType,
 ) -> List[dict[Any, Any]] | pd.DataFrame:
+    """
+    Convert a response JSON to a list or a pandas DataFrame based on the specified return type.
+
+    Args:
+        response_json (List[dict[Any, Any]]): The response JSON to be converted.
+        return_type (ReturnType): The desired return type (LIST or DATAFRAME).
+
+    Returns:
+        List[dict[Any, Any]] | pd.DataFrame: The converted response in the specified return type.
+
+    Raises:
+        AssertionError: If the response JSON is not a list.
+
+    """
     assert isinstance(response_json, list), "The response JSON must be a list"
 
     if return_type == ReturnType.LIST:
@@ -53,7 +67,21 @@ def downloadSingleSeries(
     base_url: NBIA_ENDPOINTS,
     log: Logger,
 ):
-
+    """
+    Downloads a single series from the NBIA server.
+
+    Args:
+        SeriesInstanceUID (str): The unique identifier of the series.
+        downloadDir (str): The directory where the series will be downloaded.
+        filePattern (str): The desired pattern for the downloaded files.
+        overwrite (bool): Flag indicating whether to overwrite existing files.
+        api_headers (dict[str, str]): The headers to be included in the API request.
+        base_url (NBIA_ENDPOINTS): The base URL of the NBIA server.
+        log (Logger): The logger object for logging messages.
+
+    Returns:
+        bool: True if the series is downloaded and sorted successfully, False otherwise.
+    """
     # create query_url
     query_url: str = base_url.value + NBIA_ENDPOINTS.DOWNLOAD_SERIES.value