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Before you start, ensure you have Python installed on your system, as it will be used to fetch data from the Polygon API and interact with DuckDB. Install the necessary Python libraries by running `pip install requests duckdb`.
To access the Polygon Stock API, you need an API key. Sign up at Polygon.io, navigate to the API keys section in your account settings, and note your API key.
Use Python's `requests` library to make HTTP requests to the Polygon API. For example, to fetch daily stock prices, you can use:
```python
import requests
api_key = 'YOUR_API_KEY'
url = f'https://api.polygon.io/v2/aggs/ticker/AAPL/prev?apiKey={api_key}'
response = requests.get(url)
data = response.json()
```
Replace `AAPL` with your desired stock ticker and adjust the URL for different endpoints as needed.
Once you receive the JSON response from the Polygon API, parse it to extract the relevant data. You can use Python's built-in JSON handling capabilities to navigate through the JSON structure.
```python
stock_data = data['results']
for entry in stock_data:
print(entry)
```
DuckDB is an in-process SQL OLAP database management system. With DuckDB installed via `pip install duckdb`, create and configure a new database file if necessary:
```python
import duckdb
conn = duckdb.connect('my_database.duckdb')
```
Define a table schema in DuckDB that matches the structure of the data you extracted from the Polygon API. Use SQL commands to create the table and insert data:
```python
conn.execute('''
CREATE TABLE IF NOT EXISTS stock_data (
ticker VARCHAR,
date DATE,
open FLOAT,
high FLOAT,
low FLOAT,
close FLOAT,
volume INT
)
''')
for entry in stock_data:
conn.execute('''
INSERT INTO stock_data (ticker, date, open, high, low, close, volume)
VALUES (?, ?, ?, ?, ?, ?, ?)
''', (entry['T'], entry['t'], entry['o'], entry['h'], entry['l'], entry['c'], entry['v']))
```
Once the data is inserted, run a simple query to verify the data is correctly stored:
```python
result = conn.execute('SELECT * FROM stock_data LIMIT 5').fetchall()
for row in result:
print(row)
```
This step ensures that your data movement was successful and that your data is correctly structured within DuckDB.
By following these steps, you can effectively move data from the Polygon Stock API to DuckDB without relying on third-party connectors or integrations.
FAQs
What is ETL?
ETL, an acronym for Extract, Transform, Load, is a vital data integration process. It involves extracting data from diverse sources, transforming it into a usable format, and loading it into a database, data warehouse or data lake. This process enables meaningful data analysis, enhancing business intelligence.
Polygon Stock API is a financial data provider that offers real-time and historical stock market data for developers and investors. The API provides access to a wide range of financial data, including stock prices, volume, market capitalization, and more. It also offers advanced features such as technical indicators, news feeds, and sentiment analysis. The API is designed to be easy to use and integrate into existing applications, making it a valuable tool for financial professionals and developers looking to build financial applications. With Polygon Stock API, users can access accurate and reliable financial data to make informed investment decisions.
Polygon Stock API provides access to a wide range of financial data related to the stock market. The API offers real-time and historical data for various financial instruments, including stocks, options, and cryptocurrencies. Here are the categories of data that the Polygon Stock API provides:
1. Stock Data: The API provides real-time and historical data for stocks listed on various exchanges, including NYSE, NASDAQ, and BATS.
2. Options Data: The API offers real-time and historical data for options contracts, including strike price, expiration date, and implied volatility.
3. Cryptocurrency Data: The API provides real-time and historical data for various cryptocurrencies, including Bitcoin, Ethereum, and Litecoin.
4. News Data: The API offers access to news articles related to the stock market, including company news, market trends, and economic indicators.
5. Financial Data: The API provides access to various financial data, including earnings reports, financial statements, and analyst ratings.
6. Market Data: The API offers real-time and historical market data, including market indices, volume, and price movements.
7. Fundamental Data: The API provides access to fundamental data, including company profiles, financial ratios, and dividend information.
What is ELT?
ELT, standing for Extract, Load, Transform, is a modern take on the traditional ETL data integration process. In ELT, data is first extracted from various sources, loaded directly into a data warehouse, and then transformed. This approach enhances data processing speed, analytical flexibility and autonomy.
Difference between ETL and ELT?
ETL and ELT are critical data integration strategies with key differences. ETL (Extract, Transform, Load) transforms data before loading, ideal for structured data. In contrast, ELT (Extract, Load, Transform) loads data before transformation, perfect for processing large, diverse data sets in modern data warehouses. ELT is becoming the new standard as it offers a lot more flexibility and autonomy to data analysts.
What should you do next?
Hope you enjoyed the reading. Here are the 3 ways we can help you in your data journey: