How to load data from Instagram to JSON File Destination

Learn how to use Airbyte to synchronize your Instagram data into JSON File Destination within minutes.

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Set up a Instagram connector in Airbyte

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

Set up JSON File Destination for your extracted Instagram data

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

Configure the Instagram to JSON File 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 Instagram to JSON File Destination Manually

Prerequisites:

  • An Instagram account
  • Access to Instagram’s API through a Facebook Developer account
  • Basic knowledge of HTTP requests and JSON
  • A programming environment to run your code (e.g., Python, Node.js, etc.)
  1. Go to https://developers.facebook.com/ and sign in with your Facebook account.
  2. Click on “My Apps” and then “Create App”.
  3. Choose an app type that fits your use case (e.g., “For Everything Else”).
  4. Fill in the required details and click “Create App ID”.
  5. Complete the security check if prompted.
  1. In your app dashboard, navigate to the “Products” section.
  2. Find “Instagram” and click “Set Up” on the Instagram Basic Display card.
  3. Fill in the required fields under “Basic Display”, including the “Privacy Policy URL”.
  4. Add a “Valid OAuth Redirect URI” which will be used later during the authentication process.
  5. Save your changes.
  1. Still under the “Instagram Basic Display” section, go to the “Roles” tab.
  2. Add an Instagram Test User by clicking “Add Instagram Testers” and entering the username of the Instagram account you want to use for testing.
  3. The invited user must accept the invitation by going to https://www.instagram.com/accounts/manage_access/.
  1. Direct the test user to the following URL to authenticate and grant permissions to your app (replace {app-id} with your actual app ID and {redirect-uri} with your redirect URI):

https://api.instagram.com/oauth/authorize
 ?client_id={app-id}
 &redirect_uri={redirect-uri}
 &scope=user_profile,user_media
 &response_type=code

  1. After the test user authorizes your app, they will be redirected to your specified redirect URI with a code parameter in the URL.
  2. Exchange this code for an access token by sending a POST request to:

https://api.instagram.com/oauth/access_token

with the following parameters:

  • client_id: Your app’s client ID
  • client_secret: Your app’s client secret
  • grant_type: Authorization code
  • redirect_uri: Your redirect URI
  • code: The code you received after authorization
  1. Use the access token to make requests to the Instagram API. For example, to get the user’s profile and media:

GET https://graph.instagram.com/me?fields=id,username&access_token={access-token}
GET https://graph.instagram.com/me/media?fields=id,caption&access_token={access-token}

  1. The API will return JSON data containing the requested information.
  1. Write a script in your chosen programming language to parse the JSON response from the Instagram API.
  2. Extract the relevant data you want to store in your JSON file.
  3. Save the extracted data to a file with a .json extension.

Here’s a simple example in Python:

import requests
import json

# Replace with your actual access token
access_token = 'your-access-token'

# Fetch user profile
user_profile_response = requests.get(f'https://graph.instagram.com/me?fields=id,username&access_token={access_token}')
user_profile_data = user_profile_response.json()

# Fetch user media
user_media_response = requests.get(f'https://graph.instagram.com/me/media?fields=id,caption&access_token={access_token}')
user_media_data = user_media_response.json()

# Combine data
combined_data = {
   'profile': user_profile_data,
   'media': user_media_data['data']
}

# Save to JSON file
with open('instagram_data.json', 'w') as json_file:
   json.dump(combined_data, json_file, indent=4)

Run the script, and you should have a instagram_data.json file with the fetched data from Instagram.

Notes:

  • Instagram API endpoints and access token requirements may change, so always refer to the latest Instagram API documentation.
  • Access tokens have expiration dates. You’ll need to handle token renewal in your application.
  • Ensure you comply with Instagram’s API usage policies and data privacy regulations.

How to Sync Instagram to JSON File Destination Manually - Method 2:

FAQs

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.

Instagram is a popular photo/video sharing application that enables users to share images and text captions with other people on social media. The app allows users to apply a variety of custom filter effects to enhance their images. Instagram is a free service and offers the ability to follow others, make user profiles private or public, post to other linked social accounts, and tag people or a location.

Instagram's API provides access to a wide range of data related to user accounts, media, and interactions. Here are the categories of data that can be accessed through Instagram's API:  

1. User data: This includes information about a user's profile, such as their username, bio, profile picture, follower count, and following count.  

2. Media data: This includes information about the media that a user has posted, such as the caption, location, likes, comments, and tags.  

3. Hashtag data: This includes information about hashtags that are used in posts, such as the number of posts that have used a particular hashtag, and the top posts for a given hashtag.  

4. Location data: This includes information about the locations that are associated with posts, such as the name of the location, the latitude and longitude, and the number of posts associated with a particular location.  

5. Comment data: This includes information about the comments that are posted on media, such as the text of the comment, the username of the commenter, and the time the comment was posted.  

6. Like data: This includes information about the likes that are given to media, such as the username of the user who liked the media, and the time the like was given.

This can be done by building a data pipeline manually, usually a Python script (you can leverage a tool as Apache Airflow for this). This process can take more than a full week of development. Or it can be done in minutes on Airbyte in three easy steps: 
1. Set up Instagram to JSON File as a source connector (using Auth, or usually an API key)
2. Choose a destination (more than 50 available destination databases, data warehouses or lakes) to sync data too and set it up as a destination connector
3. Define which data you want to transfer from Instagram to JSON File and how frequently
You can choose to self-host the pipeline using Airbyte Open Source or have it managed for you with Airbyte Cloud. 

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.

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?

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