How to load data from Openweather to S3 Glue

Learn how to use Airbyte to synchronize your Openweather data into S3 Glue within minutes.

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Set up a Openweather connector in Airbyte

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

Set up S3 Glue for your extracted Openweather 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 Openweather to S3 Glue 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 an AWS Account

Before you begin, ensure you have an active AWS account. You'll need access to various AWS services like S3 and Glue. If you don't have an account, you can sign up at aws.amazon.com.

Step 2: Create an S3 Bucket

Navigate to the S3 service in the AWS Management Console and create a new bucket to store your OpenWeather data. Make sure to configure the bucket settings as needed, such as setting permissions and enabling versioning if required.

Step 3: Retrieve OpenWeather API Key

Sign up for an OpenWeather account and subscribe to the API services you need. After that, retrieve your unique API key from the OpenWeather dashboard, which will be used to authenticate your requests to the OpenWeather API.

Step 4: Develop a Python Script to Fetch Weather Data

Write a Python script that uses the `requests` library to fetch data from the OpenWeather API. The script should authenticate using your API key, request the desired data, and handle any JSON responses. Ensure the script can save this data in a structured format (e.g., CSV or JSON) to your local machine or directly to an S3 bucket.

Example code snippet:
```python
import requests
import json
import boto3

def fetch_weather_data(api_key, city):
url = f"http://api.openweathermap.org/data/2.5/weather?q={city}&appid={api_key}"
response = requests.get(url)
data = response.json()
return data

def save_to_s3(bucket_name, file_name, data):
s3 = boto3.client('s3')
s3.put_object(Bucket=bucket_name, Key=file_name, Body=json.dumps(data))

api_key = 'YOUR_OPENWEATHER_API_KEY'
city = 'London'
weather_data = fetch_weather_data(api_key, city)
save_to_s3('your-s3-bucket-name', 'weather_data.json', weather_data)
```

Step 5: Configure AWS Glue

Go to AWS Glue in the AWS Management Console. Set up a Glue job to process the data. Create an IAM role that allows Glue to read from and write to your S3 bucket. Make sure to attach policies like `AmazonS3FullAccess` to this IAM role.

Step 6: Create a Glue Job

In AWS Glue, create a new job that uses the Python script you developed. Choose the IAM role you created in the previous step. Configure the job to read data from the S3 bucket and process it as needed. You can define transformation logic within the script if required.

Step 7: Schedule and Monitor the Glue Job

Set up a schedule for your Glue job to run at intervals that suit your data update needs. You can use AWS Glue triggers or AWS CloudWatch Events to schedule the job. Monitor the job's execution using AWS Glue's monitoring tools or CloudWatch to ensure it runs successfully and troubleshoot any issues that arise.

By following these steps, you can efficiently move data from OpenWeather to an S3 bucket using AWS Glue, without relying on third-party connectors or integrations.