docs: Add versioned docs for v0.6 (#725)

- Add versioned docs for Client v0.6 docs (last zero-based version)
- Fix `SUCEEDED` → `SUCCEEDED` typo in v0.6 API typedoc
- Add `**/changelog.md` exclusion to `typos.toml`
- Remove inner `.gitignore` files from versioned docs dirs, use
top-level `.gitignore` instead

---------

Co-authored-by: Claude Opus 4.6 (1M context) <noreply@anthropic.com>

Author: vdusek

.gitignore

@@ -63,6 +63,7 @@ Session.vim
 
 # Docs
 docs/changelog.md
+website/versioned_docs/*/changelog.md
 
 # Website build artifacts, node dependencies
 website/build

typos.toml

@@ -13,7 +13,8 @@ extend-exclude = [
     "*.lock",
     "*.min.js",
     "*.min.css",
-    "CHANGELOG.md",
+    "**/CHANGELOG.md",
+    "**/changelog.md",
 ]
 
 [default.extend-words]

website/versioned_docs/version-0.6/01_introduction/index.mdx

@@ -0,0 +1,41 @@
+---
+id: introduction
+title: Overview
+sidebar_label: Overview
+slug: /
+description: "The official Python library to access the Apify API, with automatic retries and convenience functions."
+---
+
+The [Apify client for Python](https://github.com/apify/apify-client-python) (`apify_client`) is the official library to access the [Apify REST API](https://docs.apify.com/api/v2) from your Python applications. It provides useful features like automatic retries and convenience functions that improve the experience of using the Apify API.
+
+## Prerequisites
+
+`apify-client` requires Python 3.7 or higher. Python is available for download on the [official website](https://www.python.org/downloads/). Check your current Python version by running:
+
+```bash
+python --version
+```
+
+## Installation
+
+The Apify client is available as the [`apify-client`](https://pypi.org/project/apify-client/) package on PyPI.
+
+```bash
+pip install apify-client
+```
+
+## Quick example
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+# Start an actor and wait for it to finish
+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
+```
+
+> You can find your API token in the [Integrations section](https://console.apify.com/account/integrations) of Apify Console. See the [Quick start guide](./quick-start) for more details.

website/versioned_docs/version-0.6/01_introduction/quick-start.mdx

@@ -0,0 +1,51 @@
+---
+id: quick-start
+title: Quick start
+sidebar_label: Quick start
+description: "Get started with the Apify client for Python."
+---
+
+## Installation
+
+```bash
+pip install apify-client
+```
+
+## Authentication
+
+To use the Apify API, you need an API token. You can find your token in the [Integrations section](https://console.apify.com/account/integrations) of Apify Console.
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+```
+
+## Running an Actor
+
+The simplest way to run an Actor is to use the `call` method, which starts the Actor and waits for it to finish.
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+# Start an actor and wait for it to finish
+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
+```
+
+## Working with datasets
+
+```python
+# Get (or create, if it doesn't exist) a dataset with the name of my-dataset
+my_dataset = apify_client.datasets().get_or_create(name='my-dataset')
+
+# Append items to the end of the dataset
+apify_client.dataset(my_dataset['id']).push_items([{'foo': 1}, {'bar': 2}])
+
+# List items in the dataset
+items = apify_client.dataset(my_dataset['id']).list_items().items
+```

website/versioned_docs/version-0.6/02_concepts/01_single_collection_clients.mdx

@@ -0,0 +1,46 @@
+---
+title: Single and collection clients
+---
+
+The `ApifyClient` interface follows a generic pattern that is applicable to all of its components. By calling individual methods of `ApifyClient`, specific clients which target individual API resources are created. There are two types of those clients. A client for management of a single resource and a client for a collection of resources.
+
+### Collection clients
+
+```python
+from apify_client import ApifyClient
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+# Collection clients do not require a parameter
+actor_collection_client = apify_client.actors()
+# Create an actor with the name: my-actor
+my_actor = actor_collection_client.create(name='my-actor')
+# List all of your actors
+actor_list = actor_collection_client.list().items
+```
+
+```python
+# Collection clients do not require a parameter
+dataset_collection_client = apify_client.datasets()
+# Get (or create, if it doesn't exist) a dataset with the name of my-dataset
+my_dataset = dataset_collection_client.get_or_create(name='my-dataset')
+```
+
+### Resource clients
+
+```python
+# Resource clients accept an ID of the resource
+actor_client = apify_client.actor('john-doe/my-actor')
+# Fetch the john-doe/my-actor object from the API
+my_actor = actor_client.get()
+# Start the run of john-doe/my-actor and return the Run object
+my_actor_run = actor_client.start()
+```
+
+```python
+# Resource clients accept an ID of the resource
+dataset_client = apify_client.dataset('john-doe/my-dataset')
+# Append items to the end of john-doe/my-dataset
+dataset_client.push_items([{'foo': 1}, {'bar': 2}])
+```
+
+> The ID of the resource can be either the `id` of the said resource, or a combination of your `username/resource-name`.

website/versioned_docs/version-0.6/02_concepts/02_nested_clients.mdx

@@ -0,0 +1,21 @@
+---
+title: Nested clients
+---
+
+Sometimes clients return other clients. That's to simplify working with nested collections, such as runs of a given actor.
+
+```python
+from apify_client import ApifyClient
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+actor_client = apify_client.actor('john-doe/my-actor')
+runs_client = actor_client.runs()
+# List the last 10 runs of the john-doe/hello-world actor
+actor_runs = runs_client.list(limit=10, desc=True).items
+
+# Select the last run of the john-doe/hello-world actor that finished
+# with a SUCCEEDED status
+last_succeeded_run_client = actor_client.last_run(status='SUCCEEDED')
+# Fetch items from the run's dataset
+dataset_items = last_succeeded_run_client.dataset().list_items().items
+```

website/versioned_docs/version-0.6/02_concepts/03_error_handling.mdx

@@ -0,0 +1,18 @@
+---
+title: Error handling
+---
+
+Based on the endpoint, the client automatically extracts the relevant data and returns it in the expected format. Date strings are automatically converted to `datetime.datetime` objects.
+
+For exceptions, we throw an `ApifyApiError`, which wraps the plain JSON errors returned by API and enriches them with other context for easier debugging.
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+try:
+    actor = apify_client.actor('non-existent-actor').get()
+except Exception as e:
+    print(f'Error: {e}')
+```

website/versioned_docs/version-0.6/02_concepts/04_retries.mdx

@@ -0,0 +1,15 @@
+---
+title: 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.
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient(
+    'MY-APIFY-TOKEN',
+    max_retries=8,
+    min_delay_between_retries_millis=500,
+)
+```

website/versioned_docs/version-0.6/02_concepts/05_pagination.mdx

@@ -0,0 +1,18 @@
+---
+title: Pagination
+---
+
+Most methods named `list` or `list_something` return a `ListPage` object, containing properties `items`, `total`, `offset`, `count` and `limit`. There are some exceptions though, like `list_keys` or `list_head` which paginate differently. The results you're looking for are always stored under `items` and you can use the `limit` property to get only a subset of results. Other properties can be available depending on the method.
+
+```python
+from apify_client import ApifyClient
+
+apify_client = ApifyClient('MY-APIFY-TOKEN')
+
+# List first 10 actors
+actors = apify_client.actors().list(limit=10)
+print(f'Total actors: {actors.total}')
+print(f'Returned: {actors.count}')
+for actor in actors.items:
+    print(actor['name'])
+```

website/versioned_docs/version-0.6/api-packages.json

@@ -0,0 +1,10 @@
+[
+    {
+        "entryPoints": { "index": { "label": "Index", "path": "src/apify_client" } },
+        "packageRoot": "..",
+        "packagePath": ".",
+        "packageSlug": ".",
+        "packageName": "apify-client",
+        "packageVersion": "0.6.0"
+    }
+]