How to load data from SpaceX API to Postgres destination

Learn how to use Airbyte to synchronize your SpaceX API data into Postgres destination within minutes.

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Set up a SpaceX API connector in Airbyte

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

Set up Postgres destination for your extracted SpaceX 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 SpaceX API to Postgres destination 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 Your Environment

Begin by ensuring that your environment is ready for the task. Install Python, if not already installed, as it will be used to pull data from the SpaceX API and insert it into PostgreSQL. Additionally, ensure PostgreSQL is installed and running on your system. You can download Python from [python.org](https://www.python.org/) and PostgreSQL from [postgresql.org](https://www.postgresql.org/).

Step 2: Create a PostgreSQL Database

Open the PostgreSQL command line or use a GUI like pgAdmin to create a new database. This will serve as the destination for the SpaceX data. Use the command:
```sql
CREATE DATABASE spacex_data;
```
Replace `spacex_data` with your preferred database name.

Step 3: Define the Database Schema

Determine the structure of the data you want to store and create the appropriate tables in your PostgreSQL database. For example, if you're storing launch data, you might create a table with columns for launch date, rocket name, and mission details. Use SQL commands like:
```sql
CREATE TABLE launches (
id SERIAL PRIMARY KEY,
launch_date TIMESTAMP,
rocket_name VARCHAR(255),
mission_details TEXT
);
```

Step 4: Access SpaceX API Data

Use Python to access the SpaceX API. The API provides endpoints for various data types, such as launches, rockets, and capsules. Use the `requests` library to make HTTP GET requests to the API. Install the library using:
```bash
pip install requests
```
Then, fetch data using:
```python
import requests

response = requests.get('https://api.spacexdata.com/v4/launches')
data = response.json()
```

Step 5: Process and Transform Data

Process the JSON data received from the API to match your database schema. This can involve extracting necessary fields and converting data types. For example:
```python
processed_data = [
{
'launch_date': launch['date_utc'],
'rocket_name': launch['name'],
'mission_details': launch['details'] or 'N/A'
}
for launch in data
]
```

Step 6: Insert Data into PostgreSQL

Use Python's `psycopg2` library to connect to your PostgreSQL database and insert the processed data. Install the library using:
```bash
pip install psycopg2-binary
```
Then, insert the data:
```python
import psycopg2

connection = psycopg2.connect(
dbname='spacex_data',
user='your_username',
password='your_password',
host='localhost'
)
cursor = connection.cursor()

for launch in processed_data:
cursor.execute(
"""
INSERT INTO launches (launch_date, rocket_name, mission_details)
VALUES (%s, %s, %s)
""",
(launch['launch_date'], launch['rocket_name'], launch['mission_details'])
)

connection.commit()
cursor.close()
connection.close()
```

Step 7: Automate and Schedule Data Transfers

To keep your database updated, automate the data transfer process. Write a script that fetches and inserts data at regular intervals. Use a task scheduler like `cron` on Unix-based systems or Task Scheduler on Windows to run your script at desired times. For example, to run the script every day at midnight using `cron`, add the following line to your crontab:
```bash
0 0 * * * /usr/bin/python3 /path/to/your_script.py
```
Replace `/path/to/your_script.py` with the path to your Python script.