docs: fix factual errors and standardize frontmatter across all doc pages

vdusek · claude · vdusek · commit 8e6ad44317ff · 2026-04-02T09:30:03.000+02:00
Fix several factual errors in docs: wrong error handling pattern (except Exception
as ApifyApiError → except ApifyApiError as err), incorrect default retry count
(8 → 4), outdated parameter name (min_delay_between_retries_millis → min_delay_between_retries),
wrong start() description, outdated README dict access. Add description field to
all frontmatter and standardize guide titles to imperative form.

Co-Authored-By: Claude Opus 4.6 (1M context) &lt;noreply@anthropic.com&gt;
diff --git a/README.md b/README.md
@@ -33,7 +33,8 @@ apify_client = ApifyClient('MY-APIFY-TOKEN')
 actor_call = apify_client.actor('john-doe/my-cool-actor').call()
 
 # Fetch results from the Actor's default dataset
-dataset_items = apify_client.dataset(actor_call['defaultDatasetId']).list_items().items
+if actor_call is not None:
+    dataset_items = apify_client.dataset(actor_call.default_dataset_id).list_items().items
 ```
 
 ## Features
@@ -46,7 +47,7 @@ Based on the endpoint, the client automatically extracts the relevant data and r
 
 ### Retries with exponential backoff
 
-Network communication sometimes fails. The client will automatically retry requests that failed due to a network error, an internal error of the Apify API (HTTP 500+) or rate limit error (HTTP 429). By default, it will retry up to 8 times. First retry will be attempted after ~500ms, second after ~1000ms and so on. You can configure those parameters using the `max_retries` and `min_delay_between_retries_millis` options of the `ApifyClient` constructor.
+Network communication sometimes fails. The client will automatically retry requests that failed due to a network error, an internal error of the Apify API (HTTP 500+) or rate limit error (HTTP 429). By default, it will retry up to 4 times. First retry will be attempted after ~500ms, second after ~1000ms and so on. You can configure those parameters using the `max_retries` and `min_delay_between_retries` options of the `ApifyClient` constructor.
 
 ### Support for asynchronous usage
 
diff --git a/docs/01_introduction/code/03_input_async.py b/docs/01_introduction/code/03_input_async.py
@@ -12,5 +12,5 @@ async def main() -> None:
         'some': 'input',
     }
 
-    # Start an Actor and waits for it to finish.
+    # Start an Actor and wait for it to finish.
     call_result = await actor_client.call(run_input=run_input)
diff --git a/docs/01_introduction/code/03_input_sync.py b/docs/01_introduction/code/03_input_sync.py
@@ -12,5 +12,5 @@ def main() -> None:
         'some': 'input',
     }
 
-    # Start an Actor and waits for it to finish.
+    # Start an Actor and wait for it to finish.
     call_result = actor_client.call(run_input=run_input)
diff --git a/docs/01_introduction/index.mdx b/docs/01_introduction/index.mdx
@@ -1,9 +1,8 @@
 ---
 id: introduction
 title: Overview
-sidebar_label: Overview
 slug: /
-description: "The official Python library to access the Apify API, with automatic retries, async support, and comprehensive API coverage."
+description: The official Python library to access the Apify API, with automatic retries, async support, and comprehensive API coverage.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/01_introduction/quick-start.mdx b/docs/01_introduction/quick-start.mdx
@@ -1,8 +1,7 @@
 ---
 id: quick-start
 title: Quick start
-sidebar_label: Quick start
-description: "Get started with the Apify API client for Python by running an Actor and retrieving results from its dataset."
+description: Get started with the Apify API client for Python by running an Actor and retrieving results from its dataset.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/01_async_support.mdx b/docs/02_concepts/01_async_support.mdx
@@ -1,6 +1,7 @@
 ---
 id: asyncio-support
 title: Asyncio support
+description: Use the async client for non-blocking API calls with Python asyncio.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/02_single_collection_clients.mdx b/docs/02_concepts/02_single_collection_clients.mdx
@@ -1,6 +1,7 @@
 ---
 id: single-and-collection-clients
 title: Single and collection clients
+description: Understand the two types of resource clients, single-resource and collection clients.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/03_nested_clients.mdx b/docs/02_concepts/03_nested_clients.mdx
@@ -1,6 +1,7 @@
 ---
 id: nested-clients
 title: Nested clients
+description: Access related resources directly through nested client methods.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/04_error_handling.mdx b/docs/02_concepts/04_error_handling.mdx
@@ -1,6 +1,7 @@
 ---
 id: error-handling
 title: Error handling
+description: Handle API errors with the ApifyApiError exception and automatic data parsing.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/05_retries.mdx b/docs/02_concepts/05_retries.mdx
@@ -1,6 +1,7 @@
 ---
 id: retries
 title: Retries
+description: Configure automatic retries with exponential backoff for failed requests.
 ---
 
 import Tabs from '@theme/Tabs';
@@ -10,23 +11,23 @@ import CodeBlock from '@theme/CodeBlock';
 import RetriesAsyncExample from '!!raw-loader!./code/05_retries_async.py';
 import RetriesSyncExample from '!!raw-loader!./code/05_retries_sync.py';
 
-When dealing with network communication, failures can occasionally occur. The Apify client automatically retries requests that fail due to:
+The Apify client automatically retries requests that fail due to:
 
 - Network errors
 - Internal errors in the Apify API (HTTP status codes 500 and above)
 - Rate limit errors (HTTP status code 429)
 
-By default, the client will retry a failed request up to 8 times. The retry intervals use an exponential backoff strategy:
+By default, the client retries a failed request up to 4 times. The retry intervals use an exponential backoff strategy:
 
 - The first retry occurs after approximately 500 milliseconds.
 - The second retry occurs after approximately 1,000 milliseconds, and so on.
 
 You can customize this behavior using the following options in the [`ApifyClient`](/reference/class/ApifyClient) constructor:
 
 - `max_retries`: Defines the maximum number of retry attempts.
-- `min_delay_between_retries_millis`: Sets the minimum delay between retries (in milliseconds).
+- `min_delay_between_retries`: Sets the minimum delay between retries as a `timedelta`.
 
-Retries with exponential backoff are a common strategy for handling network errors. They help to reduce the load on the server and increase the chances of a successful request.
+Retries with exponential backoff help reduce the load on the server and increase the chances of a successful request.
 
 <Tabs>
     <TabItem value="AsyncExample" label="Async client" default>
diff --git a/docs/02_concepts/06_logging.mdx b/docs/02_concepts/06_logging.mdx
@@ -1,6 +1,7 @@
 ---
 id: logging
 title: Logging
+description: Configure debug logging to inspect API requests and responses.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/07_convenience_methods.mdx b/docs/02_concepts/07_convenience_methods.mdx
@@ -1,6 +1,7 @@
 ---
 id: convenience-methods
 title: Convenience methods
+description: Use high-level methods for running Actors, waiting for results, and accessing data.
 ---
 
 import Tabs from '@theme/Tabs';
@@ -12,8 +13,9 @@ import CallSyncExample from '!!raw-loader!./code/07_call_sync.py';
 
 The Apify client provides several convenience methods to handle actions that the API alone cannot perform efficiently, such as waiting for an Actor run to finish without running into network timeouts. These methods simplify common tasks and enhance the usability of the client.
 
-- [`ActorClient.call`](/reference/class/ActorClient#call) - Starts an Actor and waits for it to finish, handling network timeouts internally.
-- [`ActorClient.start`](/reference/class/ActorClient#start) - Explicitly waits for an Actor run to finish with customizable timeouts.
+- [`ActorClient.call`](/reference/class/ActorClient#call) - Starts an Actor and waits for it to finish, handling network timeouts internally. Waits indefinitely by default, or up to the specified `wait_duration`.
+- [`ActorClient.start`](/reference/class/ActorClient#start) - Starts an Actor and immediately returns the Run object without waiting for it to finish.
+- [`RunClient.wait_for_finish`](/reference/class/RunClient#wait_for_finish) - Waits for an already-started run to reach a terminal status.
 
 Additionally, storage-related resources offer flexible options for data retrieval:
 
diff --git a/docs/02_concepts/08_pagination.mdx b/docs/02_concepts/08_pagination.mdx
@@ -1,6 +1,7 @@
 ---
 id: pagination
 title: Pagination
+description: Paginate through large result sets using ListPage or generator-based iteration.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/09_streaming.mdx b/docs/02_concepts/09_streaming.mdx
@@ -1,6 +1,7 @@
 ---
 id: streaming-resources
 title: Streaming resources
+description: Stream large datasets, key-value store records, and logs without loading them into memory.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/10_custom_http_clients.mdx b/docs/02_concepts/10_custom_http_clients.mdx
@@ -1,6 +1,7 @@
 ---
 id: custom-http-clients
 title: Custom HTTP clients
+description: Replace the default HTTP client with a custom implementation.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/02_concepts/code/03_nested_async.py b/docs/02_concepts/code/03_nested_async.py
@@ -1,4 +1,5 @@
 from apify_client import ApifyClientAsync
+from apify_client._models import ActorJobStatus
 
 TOKEN = 'MY-APIFY-TOKEN'
 
@@ -9,11 +10,11 @@ async def main() -> None:
     actor_client = apify_client.actor('username/actor-name')
     runs_client = actor_client.runs()
 
-    # List the last 10 runs of the Actor
+    # List the last 10 runs of the Actor.
     actor_runs = (await runs_client.list(limit=10, desc=True)).items
 
-    # Select the last run of the Actor that finished with a SUCCEEDED status
-    last_succeeded_run_client = actor_client.last_run(status='SUCCEEDED')  # ty: ignore[invalid-argument-type]
+    # Select the last run of the Actor that finished with a SUCCEEDED status.
+    last_succeeded_run_client = actor_client.last_run(status=ActorJobStatus.SUCCEEDED)
 
     # Get dataset
     actor_run_dataset_client = last_succeeded_run_client.dataset()
diff --git a/docs/02_concepts/code/03_nested_sync.py b/docs/02_concepts/code/03_nested_sync.py
@@ -1,4 +1,5 @@
 from apify_client import ApifyClient
+from apify_client._models import ActorJobStatus
 
 TOKEN = 'MY-APIFY-TOKEN'
 
@@ -9,11 +10,11 @@ def main() -> None:
     actor_client = apify_client.actor('username/actor-name')
     runs_client = actor_client.runs()
 
-    # List the last 10 runs of the Actor
+    # List the last 10 runs of the Actor.
     actor_runs = runs_client.list(limit=10, desc=True).items
 
-    # Select the last run of the Actor that finished with a SUCCEEDED status
-    last_succeeded_run_client = actor_client.last_run(status='SUCCEEDED')  # ty: ignore[invalid-argument-type]
+    # Select the last run of the Actor that finished with a SUCCEEDED status.
+    last_succeeded_run_client = actor_client.last_run(status=ActorJobStatus.SUCCEEDED)
 
     # Get dataset
     actor_run_dataset_client = last_succeeded_run_client.dataset()
diff --git a/docs/02_concepts/code/04_error_async.py b/docs/02_concepts/code/04_error_async.py
@@ -1,4 +1,7 @@
+import asyncio
+
 from apify_client import ApifyClientAsync
+from apify_client.errors import ApifyApiError
 
 TOKEN = 'MY-APIFY-TOKEN'
 
@@ -7,9 +10,13 @@ async def main() -> None:
     apify_client = ApifyClientAsync(TOKEN)
 
     try:
-        # Try to list items from non-existing dataset
-        dataset_client = apify_client.dataset('not-existing-dataset-id')
+        # Try to list items from a non-existing dataset.
+        dataset_client = apify_client.dataset('non-existing-dataset-id')
         dataset_items = (await dataset_client.list_items()).items
-    except Exception as ApifyApiError:
-        # The exception is an instance of ApifyApiError
-        print(ApifyApiError)
+    except ApifyApiError as err:
+        # The client raises ApifyApiError for API errors.
+        print(f'API error: {err}')
+
+
+if __name__ == '__main__':
+    asyncio.run(main())
diff --git a/docs/02_concepts/code/04_error_sync.py b/docs/02_concepts/code/04_error_sync.py
@@ -1,4 +1,5 @@
 from apify_client import ApifyClient
+from apify_client.errors import ApifyApiError
 
 TOKEN = 'MY-APIFY-TOKEN'
 
@@ -7,9 +8,13 @@ def main() -> None:
     apify_client = ApifyClient(TOKEN)
 
     try:
-        # Try to list items from non-existing dataset
-        dataset_client = apify_client.dataset('not-existing-dataset-id')
+        # Try to list items from a non-existing dataset.
+        dataset_client = apify_client.dataset('non-existing-dataset-id')
         dataset_items = dataset_client.list_items().items
-    except Exception as ApifyApiError:
-        # The exception is an instance of ApifyApiError
-        print(ApifyApiError)
+    except ApifyApiError as err:
+        # The client raises ApifyApiError for API errors.
+        print(f'API error: {err}')
+
+
+if __name__ == '__main__':
+    main()
diff --git a/docs/02_concepts/code/07_call_async.py b/docs/02_concepts/code/07_call_async.py
@@ -7,8 +7,8 @@ async def main() -> None:
     apify_client = ApifyClientAsync(TOKEN)
     actor_client = apify_client.actor('username/actor-name')
 
-    # Start an Actor and waits for it to finish
+    # Start an Actor and wait for it to finish.
     finished_actor_run = await actor_client.call()
 
-    # Starts an Actor and waits maximum 60s (1 minute) for the finish
+    # Start an Actor and wait up to 60 seconds for it to finish.
     actor_run = await actor_client.start(wait_for_finish=60)
diff --git a/docs/02_concepts/code/07_call_sync.py b/docs/02_concepts/code/07_call_sync.py
@@ -7,8 +7,8 @@ def main() -> None:
     apify_client = ApifyClient(TOKEN)
     actor_client = apify_client.actor('username/actor-name')
 
-    # Start an Actor and waits for it to finish
+    # Start an Actor and wait for it to finish.
     finished_actor_run = actor_client.call()
 
-    # Starts an Actor and waits maximum 60s (1 minute) for the finish
+    # Start an Actor and wait up to 60 seconds for it to finish.
     actor_run = actor_client.start(wait_for_finish=60)
diff --git a/docs/03_guides/01_passing_input_to_actor.mdx b/docs/03_guides/01_passing_input_to_actor.mdx
@@ -1,6 +1,7 @@
 ---
 id: passing-input-to-actor
-title: Passing input to Actor
+title: Pass input to an Actor
+description: Run an Actor with custom input data and retrieve results.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/03_guides/02_manage_tasks_for_reusable_input.mdx b/docs/03_guides/02_manage_tasks_for_reusable_input.mdx
@@ -1,6 +1,7 @@
 ---
 id: manage-tasks-for-reusable-input
 title: Manage tasks for reusable input
+description: Create and manage tasks with reusable input configurations.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/03_guides/03_retrieve_actor_data.mdx b/docs/03_guides/03_retrieve_actor_data.mdx
@@ -1,6 +1,7 @@
 ---
 id: retrieve-actor-data
 title: Retrieve Actor data
+description: Fetch, paginate, and merge datasets from Actor runs.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/03_guides/04_integration_with_data_libraries.mdx b/docs/03_guides/04_integration_with_data_libraries.mdx
@@ -1,6 +1,7 @@
 ---
 id: integration-with-data-libraries
-title: Integration with data libraries
+title: Integrate with data libraries
+description: Load Apify dataset items into Pandas DataFrames for analysis.
 ---
 
 import Tabs from '@theme/Tabs';
diff --git a/docs/03_guides/05_custom_http_client.mdx b/docs/03_guides/05_custom_http_client.mdx
@@ -1,6 +1,7 @@
 ---
 id: custom-http-client-httpx
-title: Using HTTPX as the HTTP client
+title: Use HTTPX as the HTTP client
+description: Replace the default Impit HTTP client with one based on HTTPX.
 ---
 
 import ApiLink from '@site/src/components/ApiLink';
diff --git a/docs/04_upgrading/upgrading_to_v2.md b/docs/04_upgrading/upgrading_to_v2.md
@@ -1,6 +1,7 @@
 ---
 id: upgrading-to-v2
 title: Upgrading to v2
+description: Breaking changes and migration guide from v1 to v2.
 ---
 
 This page summarizes the breaking changes between Apify Python API Client v1.x and v2.0.
diff --git a/docs/04_upgrading/upgrading_to_v3.md b/docs/04_upgrading/upgrading_to_v3.md
@@ -1,6 +1,7 @@
 ---
 id: upgrading-to-v3
 title: Upgrading to v3
+description: Breaking changes and migration guide from v2 to v3.
 ---
 
 This page summarizes the breaking changes between Apify Python API Client v2.x and v3.0.

Original file line number	Diff line number	Diff line change
`@@ -12,5 +12,5 @@ async def main() -> None:`
`12`	`12`	`'some': 'input',`
`13`	`13`	`}`
`14`	`14`
`15`		`- # Start an Actor and waits for it to finish.`
	`15`	`+ # Start an Actor and wait for it to finish.`
`16`	`16`	`call_result = await actor_client.call(run_input=run_input)`
Original file line number	Diff line number	Diff line change
`@@ -12,5 +12,5 @@ def main() -> None:`
`12`	`12`	`'some': 'input',`
`13`	`13`	`}`
`14`	`14`
`15`		`- # Start an Actor and waits for it to finish.`
	`15`	`+ # Start an Actor and wait for it to finish.`
`16`	`16`	`call_result = actor_client.call(run_input=run_input)`