![Python SDK](https://cdn.sanity.io/images/97bpcflt/production/61a645edb1f93d39de595890dd26f47c647e2f93-200x200.png?bg=0fff&w=80&fit=crop&dpr=2&fm=webp&h=80)
![Google Cloud Storage](https://cdn.sanity.io/images/97bpcflt/production/88592e41ba2fed1715cdac7672a43b66b982fcd4-226x200.png?bg=0fff&w=80&fit=crop&dpr=2&fm=webp&h=71)
Integrate your Python app with Google Cloud Storage
Don't go through the pain of direct integration. RudderStack’s Python SDK makes it easy to send data from your Python app to Google Cloud Storage and all of your other cloud tools.With Rudderstack, integration between Python SDK and Google Cloud Storage is simple. Set up a Python SDK source and start sending data.
Pricing Python SDK and Google Cloud Storage can vary based on the way they charge. Check out our pricing page for more info. Or give us a try for FREE.
Timing can vary based on your tech stack and the complexity of your data needs for Python SDK and Google Cloud Storage.
Yes, RudderStack streamlines the integration and management of your connection between Python SDK & Google Cloud Storage, but you check out our guide on How To Send Data From Your Python App to Microsoft Azure Synapse Analytics to learn how to connect the tools manually.
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.