How to load data from Polygon Stock API to Firebolt

Learn how to use Airbyte to synchronize your Polygon Stock API data into Firebolt within minutes.

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Set up a Polygon Stock API connector in Airbyte

Connect to or one of 400+ pre-built or 10,000+ custom connectors through simple account authentication.

Set up Firebolt for your extracted Polygon Stock API data

Select where you want to import data from your source to. You can also choose other cloud data warehouses, databases, data lakes, vector databases, or any other supported Airbyte destinations.

Configure the Polygon Stock API to Firebolt in Airbyte

This includes selecting the data you want to extract - streams and columns -, the sync frequency, where in the destination you want that data to be loaded.

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How to Sync to Manually

Step 1: Set Up API Access

To begin, ensure you have access to the Polygon Stock API by signing up for an account and obtaining your API key. This key will be used to authenticate your requests to the API.

Use a programming language of your choice (e.g., Python) to send HTTPS requests to the Polygon API endpoints. Specifically, use the `requests` library in Python to fetch stock data. Ensure you handle API rate limits and pagination if applicable.

```python
import requests

api_key = 'your_polygon_api_key'
url = 'https://api.polygon.io/v2/aggs/ticker/AAPL/prev?adjusted=true&apiKey=' + api_key
response = requests.get(url)
data = response.json()
```

Once you have retrieved the data, transform it into a format suitable for Firebolt ingestion, such as CSV or Parquet. This involves cleaning and structuring the data, including handling any missing values and ensuring data types are consistent.

```python
import pandas as pd

df = pd.json_normalize(data['results'])
df.to_csv('stock_data.csv', index=False)
```

Create an account with Firebolt and set up a new database. This involves logging into the Firebolt console, creating a database, and configuring the necessary compute engine and storage.

Define the schema in Firebolt that matches your data structure. This includes creating tables with the appropriate data types. Use the Firebolt SQL Editor to execute `CREATE TABLE` statements.

```sql
CREATE TABLE stock_data (
ticker STRING,
open_price FLOAT,
close_price FLOAT,
volume INT,
date DATE
);
```

Use the Firebolt Python SDK or SQL interface to load the transformed data into Firebolt. If using the SDK, the data can be uploaded directly from a file.

```python
from firebolt.client import Client
from firebolt.service.manager import ResourceManager

client = Client(api_endpoint='api.app.firebolt.io', username='your_username', password='your_password')
resource_manager = ResourceManager(client)

with open('stock_data.csv', 'rb') as file:
resource_manager.upload_table_file('your_database', 'stock_data', file)
```

After loading the data, verify its integrity by running sample queries to ensure that the data matches what was retrieved from the Polygon API. Use the Firebolt SQL Editor to perform these queries.

```sql
SELECT * FROM stock_data LIMIT 10;
```

By following these steps, you can efficiently move stock data from the Polygon API to Firebolt without relying on third-party connectors or integrations.