+h2(#v2_6_3). v2.6.3 (2023-06-06)
+
+h3. Python SDK automatically retries failed requests much more
+
+The Python SDK has always provided functionality to retry API requests that fail due to temporary problems like network failures, by passing @num_retries=N@ to a request's @execute()@ method. In this release, API client constructor functions like @arvados.api@ also accept a @num_retries@ argument. This value is stored on the client object and used as a floor for all API requests made with this client. This allows developers to set their preferred retry strategy once, without having to pass it to each @execute()@ call.
+
+The default value for @num_retries@ in API constructor functions is 10. This means that an API request that repeatedly encounters temporary problems may spend up to about 35 minutes retrying in the worst case. We believe this is an appropriate default for most users, where eventual success is a much greater concern than responsiveness. If you have client applications where this is undesirable, update them to pass a lower @num_retries@ value to the constructor function. You can even pass @num_retries=0@ to have the API client act as it did before, like this:
+
+{% codeblock as python %}
+import arvados
+arv_client = arvados.api('v1', num_retries=0, ...)
+{% endcodeblock %}
+
+The first time the Python SDK fetches an Arvados API discovery document, it will ensure that @googleapiclient.http@ logs are handled so you have a way to know about early problems that are being retried. If you prefer to handle these logs your own way, just ensure that the @googleapiclient.http@ logger (or a parent logger) has a handler installed before you call any Arvados API client constructor.
+
+h2(#v2_6_2). v2.6.2 (2023-05-22)
+
+"previous: Upgrading to 2.6.1":#v2_6_1
+
+This version introduces a new API feature which is used by Workbench 2 to improve page loading performance. To avoid any errors using the new Workbench with an old API server, be sure to upgrade the API server before upgrading Workbench 2.
+