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Easy Python SDK to Google Cloud Storage integration with RudderStack
RudderStack’s open source Python SDK allows you to integrate RudderStack with your Python app to track event data and automatically send it to Google Cloud Storage. With the RudderStack Python SDK, you do not have to worry about having to learn, test, implement or deal with changes in a new API and multiple endpoints every time someone asks for a new integration.
Popular ways to use Google Cloud Storage
Load event data
Easily send event stream and batch data to Google Cloud Storage from multiple sources.
Automatic schema creation
Skip the formatting work in Google Cloud Storage and move faster with predefined data structures.
Customize sync scheduling
Easily configure custom sync schedules to Google Cloud Storage that work with your existing data workflows.
Frequently Asked Questions
How do you integrate your Python app with Google Cloud Storage?
With Rudderstack, integration between Python SDK and Google Cloud Storage is simple. Set up a Python SDK source and start sending data.
Is it expensive to integrate Python SDK with Google Cloud Storage?
How long does it take to integrate Python SDK with Google Cloud Storage?
Timing can vary based on your tech stack and the complexity of your data needs for Python SDK and Google Cloud Storage.
RudderStack Google Cloud Storage Documentation
Refer to our step-by-step guide and start using Google Cloud Storage today
RudderStack Python SDK Documentation
Refer to our step-by-step guide and start using Python SDK today
About Python SDK and Google Cloud Storage
Google Cloud Storage is a popular web storage client for storing and accessing your data in the Google Cloud Platform infrastructure. It offers state-of-the-art performance and scalability, along with ensuring the security and privacy of your data.
With RudderStack, you can send data directly from our client library in JSON format to any bucket_name in Google Cloud Storage (we also support BigQuery as part of GCP / GCS) without the pain of having to manually upload files. Authentication is handled automatically and computes runs according to a schedule config.
Cloud import storage and cloud storage buckets are increasingly popular for blob cloud storage clients, but building the pipelines manually can be a pain, even with good tutorials. Even running jobs like create_bucket via the Google Cloud Storage API can become complex to manage at scale, especially when your data flow had multiple dependencies and permissions.
With RudderStack, you can send events in the form of JSON files with rich metadata directly from our Python library, without any custom Python scripts or dealing with Python versions. You can also add a prefix to every load, making it easier to write SQL using Google’s query interface. Having a fully managed pipeline means you can spend more time on data science and machine learning projects.