Quick start
Learn how to authenticate, run Actors, and retrieve results using the Apify API client for Python.
Step 1: Authenticate the client
To use the client, you need an API token. You can find your token under the Integrations tab in Apify Console. Copy the token and initialize the client by providing it (MY-APIFY-TOKEN) as a parameter to the ApifyClient constructor.
- Async client
- Sync client
from apify_client import ApifyClientAsync
TOKEN = 'MY-APIFY-TOKEN'
async def main() -> None:
# Client initialization with the API token.
apify_client = ApifyClientAsync(TOKEN)
from apify_client import ApifyClient
TOKEN = 'MY-APIFY-TOKEN'
def main() -> None:
# Client initialization with the API token.
apify_client = ApifyClient(TOKEN)
The API token is used to authorize your requests to the Apify API. You can be charged for the usage of the underlying services, so do not share your API token with untrusted parties or expose it on the client side of your applications.
Step 2: Run an Actor
To start an Actor, you need its ID (e.g., john-doe/my-cool-actor) and an API token. The Actor's ID is a combination of the username and the Actor owner's username. Use the ActorClient to run the Actor and wait for it to complete. You can run both your own Actors and Actors from Apify store.
- Async client
- Sync client
from apify_client import ApifyClientAsync
# You can find your API token at https://console.apify.com/settings/integrations.
TOKEN = 'MY-APIFY-TOKEN'
async def main() -> None:
apify_client = ApifyClientAsync(TOKEN)
# Start an Actor and wait for it to finish.
actor_client = apify_client.actor('john-doe/my-cool-actor')
call_result = await actor_client.call()
if call_result is None:
print('Actor run failed.')
return
# Fetch results from the Actor run's default dataset.
dataset_client = apify_client.dataset(call_result['defaultDatasetId'])
list_items_result = await dataset_client.list_items()
print(f'Dataset: {list_items_result}')
from apify_client import ApifyClient
# You can find your API token at https://console.apify.com/settings/integrations.
TOKEN = 'MY-APIFY-TOKEN'
def main() -> None:
apify_client = ApifyClient(TOKEN)
# Start an Actor and wait for it to finish.
actor_client = apify_client.actor('john-doe/my-cool-actor')
call_result = actor_client.call()
if call_result is None:
print('Actor run failed.')
return
# Fetch results from the Actor run's default dataset.
dataset_client = apify_client.dataset(call_result['defaultDatasetId'])
list_items_result = dataset_client.list_items()
print(f'Dataset: {list_items_result}')
Step 3: Provide input to an Actor
Actors often require input, such as URLs to scrape, search terms, or other configuration data. You can pass input as a JSON object when starting the Actor using the ActorClient.call method. Actors respect the input schema defined in the Actor's input schema.
- Async client
- Sync client
from apify_client import ApifyClientAsync
TOKEN = 'MY-APIFY-TOKEN'
async def main() -> None:
apify_client = ApifyClientAsync(TOKEN)
actor_client = apify_client.actor('username/actor-name')
# Define the input for the Actor.
run_input = {
'some': 'input',
}
# Start an Actor and waits for it to finish.
call_result = await actor_client.call(run_input=run_input)
from apify_client import ApifyClient
TOKEN = 'MY-APIFY-TOKEN'
def main() -> None:
apify_client = ApifyClient(TOKEN)
actor_client = apify_client.actor('username/actor-name')
# Define the input for the Actor.
run_input = {
'some': 'input',
}
# Start an Actor and waits for it to finish.
call_result = actor_client.call(run_input=run_input)
Step 4: Get results from the dataset
To get the results from the dataset, you can use the DatasetClient (ApifyClient.dataset) and DatasetClient.list_items method. You need to pass the dataset ID to define which dataset you want to access. You can get the dataset ID from the Actor's run dictionary (represented by defaultDatasetId).
- Async client
- Sync client
from apify_client import ApifyClientAsync
TOKEN = 'MY-APIFY-TOKEN'
async def main() -> None:
apify_client = ApifyClientAsync(TOKEN)
dataset_client = apify_client.dataset('dataset-id')
# Lists items from the Actor's dataset.
dataset_items = (await dataset_client.list_items()).items
from apify_client import ApifyClient
TOKEN = 'MY-APIFY-TOKEN'
def main() -> None:
apify_client = ApifyClient(TOKEN)
dataset_client = apify_client.dataset('dataset-id')
# Lists items from the Actor's dataset.
dataset_items = dataset_client.list_items().items
Running an Actor might take time, depending on the Actor's complexity and the amount of data it processes. If you want only to get data and have an immediate response you should access the existing dataset of the finished Actor run.
Next steps
Concepts
To learn more about how the client works, check out the Concepts section in the sidebar:
- Asyncio support - asynchronous programming with the client
- Single and collection clients - resource clients and collection clients
- Error handling - debugging API errors
- Retries - automatic retries with exponential backoff
- Pagination - iterating through large result sets
Examples
For practical examples of common tasks, see the Examples section: