> ## Documentation Index
> Fetch the complete documentation index at: https://docs.bigdata.com/llms.txt
> Use this file to discover all available pages before exploring further.

# Autosuggest

<Note>
  Autosuggest is not yet supported in the API.
</Note>

It's a generic method to explore the Bigdata Knowledge Graph. Ideal if you are implementing an User Interface that only accepts a partial name but no details about the type of Entity.

```python theme={null}
from bigdata_client import Bigdata

# Create a Bigdata object, the main entry point to the API
bigdata = Bigdata()
results = bigdata.knowledge_graph.autosuggest("tesla")

for obj in results:
     print(f"{obj.name}: {obj.id}")
```

As illustrated below, it is possible to easily generate portfolios or
interest lists:

```python theme={null}
tickers = ["META", "AAPL", "AMZN", "NFLX", "GOOGL"]
FAANG = []
for t in tickers:
    FAANG.append(bigdata.knowledge_graph.autosuggest(t, limit=1))

print(FAANG)
```

If you know the type of Entity you are looking for, you can use the `find_{element}()` method.

* [`find_companies()`](./find_companies)
* [`find_etfs()`](./find_etfs)
* [`find_organizations()`](./find_organizations)
* [`find_people()`](./find_people)
* [`find_places()`](./find_places)
* [`find_products()`](./find_products)
* [`find_sources()`](./find_sources)
* [`find_topics()`](./find_topics)