How to download configuration file from google sheet api

Service to prepare data for analysis and machine learning. Intelligent data fabric for unifying data management across silos. Metadata service for discovering, understanding, and managing data. Service for securely and efficiently exchanging data analytics assets. Cloud-native wide-column database for large scale, low-latency workloads. Cloud-native document database for building rich mobile, web, and IoT apps.

In-memory database for managed Redis and Memcached. Cloud-native relational database with unlimited scale and Serverless, minimal downtime migrations to Cloud SQL.

Infrastructure to run specialized Oracle workloads on Google Cloud. NoSQL database for storing and syncing data in real time. Serverless change data capture and replication service.

Universal package manager for build artifacts and dependencies. Continuous integration and continuous delivery platform. Service for creating and managing Google Cloud resources. Command line tools and libraries for Google Cloud. Cron job scheduler for task automation and management. Private Git repository to store, manage, and track code. Task management service for asynchronous task execution.

Fully managed continuous delivery to Google Kubernetes Engine. Full cloud control from Windows PowerShell. Healthcare and Life Sciences.

Solution for bridging existing care systems and apps on Google Cloud. Tools for managing, processing, and transforming biomedical data. Real-time insights from unstructured medical text. Integration that provides a serverless development platform on GKE. Tool to move workloads and existing applications to GKE. Service for executing builds on Google Cloud infrastructure.

Traffic control pane and management for open service mesh. API management, development, and security platform.

Fully managed solutions for the edge and data centers. Internet of Things. IoT device management, integration, and connection service. Automate policy and security for your deployments. Dashboard to view and export Google Cloud carbon emissions reports. Programmatic interfaces for Google Cloud services. Web-based interface for managing and monitoring cloud apps. App to manage Google Cloud services from your mobile device. Interactive shell environment with a built-in command line.

Kubernetes add-on for managing Google Cloud resources. Tools for monitoring, controlling, and optimizing your costs. Tools for easily managing performance, security, and cost. Service catalog for admins managing internal enterprise solutions.

Open source tool to provision Google Cloud resources with declarative configuration files. Media and Gaming. Game server management service running on Google Kubernetes Engine. Open source render manager for visual effects and animation. Convert video files and package them for optimized delivery. App migration to the cloud for low-cost refresh cycles. Data import service for scheduling and moving data into BigQuery. Reference templates for Deployment Manager and Terraform. Components for migrating VMs and physical servers to Compute Engine.

Storage server for moving large volumes of data to Google Cloud. Data transfers from online and on-premises sources to Cloud Storage.

Migrate and run your VMware workloads natively on Google Cloud. Security policies and defense against web and DDoS attacks. Content delivery network for serving web and video content.

Domain name system for reliable and low-latency name lookups. Service for distributing traffic across applications and regions. NAT service for giving private instances internet access. Connectivity options for VPN, peering, and enterprise needs. Connectivity management to help simplify and scale networks.

Network monitoring, verification, and optimization platform. Cloud network options based on performance, availability, and cost. VPC flow logs for network monitoring, forensics, and security. Google Cloud audit, platform, and application logs management. Infrastructure and application health with rich metrics. Application error identification and analysis. GKE app development and troubleshooting.

Tracing system collecting latency data from applications. CPU and heap profiler for analyzing application performance. Real-time application state inspection and in-production debugging. Read the client library's developer's guide.

In addition, you may be interested in the following documentation:. Select your build environment Maven or Gradle from the following tabs: Add the following to your pom. See all versions available on the Maven Central Repository. Install the NuGet package: Google. You can either use a package manager or download and install the Python client library manually:. Do if err! Println "No data found. If you're not already signed in to your Google account, you're prompted to sign in.

If you're signed in to multiple Google accounts, you are asked to select one account to use for authorization. This section describes some common issues that you may encounter while attempting to run this quickstart and suggests possible solutions.

If the OAuth consent screen displays the warning "This app isn't verified," your app is requesting scopes that provide access to sensitive user data. If your application uses sensitive scopes, your your app must go through the verification process to remove that warning and other limitations. For further information on the APIs used in this quickstart, refer to the google-api-go-client section of GitHub. Of course, all of this creating and formatting a spreadsheet is meaningless if you don't put any actual data into it.

First let's add a new route to routes. Like the previous route for creating spreadsheets, this one checks for authorization, loads models from the database, and then passes the information to the SheetsHelper which will transform the records to cells and make the API requests. Add the following code the sheets. Here again we're using the batchUpdate method, this time passing in two requests.

The first is an UpdateSheetPropertiesRequest which resizes the sheet to ensure there are enough rows and columns to fit the data it's about to write. The next is another UpdateCells request, which sets the cell values and formatting. The buildRowsForOrders function is where we convert the Order objects into cells. Add the following code to the same file:. The unitsOrdered and unitPrice fields set a number value as well as number format to ensure the values are displayed correctly.

Additionally, the status field has a data validation set in order to display a dropdown of the allowed status values. Although not particularly useful in this codelab, adding data validation to the spreadsheet can be useful if you want to allow users to edit the rows and later impact them back into your application. Reload the application in your browser and click the Sync button next to the spreadsheet link.

The spreadsheet should now contain all your order data. Add a new order and click Sync again to see the changes. You've now got your application exporting to Google Sheets, but honestly a similar result could have been achieved by exporting CSVs and manually importing them into Google Sheets. What separates this API-based approach from CSV is the ability to add complex features to spreadsheets, such as pivot tables and charts.

This allows you to leverage Google Sheets as a dashboard to your data that users can easily customize and extended. To get started, we'll need to add a new sheet to our spreadsheets to contain the pivot table and chart. It's best to keep the sheets of raw data separate from the aggregations and visualizations, so that your syncing code can just focus on the data. Later on in createSpreadsheet method, we'll need capture the ID of the "Pivot" sheet and use it to build some new requests.

Finally, add the following functions to the file, which create requests for building the pivot table, formatting the results, and adding the chart:. The resulting spreadsheet should have a new sheet containing an empty pivot table and chart.

Click the Sync button to add data to the spreadsheet, and watch the pivot table and chart come to life with real data. You've successfully modified an application to export data to Google Sheets. Your users will now be able to build custom reports and dashboards over your data without the need for any additional code, and all while being kept perfectly in sync as the data changes.

Except as otherwise noted, the content of this page is licensed under the Creative Commons Attribution 4.

For details, see the Google Developers Site Policies.