Google Drive API Python Quickstart and Best Practices

To get started with the Google Drive API in Python, you'll need to enable the Drive API in the Google Cloud Console. This will give you a chance to set up credentials for your project, which are essential for accessing the API.

First, install the Google API Client Library for Python using pip. This library provides a simple interface for interacting with the Google Drive API.

You can authenticate with the Google Drive API using OAuth 2.0, which allows your application to access user data without compromising security. The Client Library handles the OAuth flow for you, making it easy to get started.

The Google Drive API allows you to perform various actions, including creating, updating, and deleting files and folders. You can also use the API to retrieve file metadata and list files and folders.

To set up your environment for working with the Google Drive API in Python, you'll need to start by installing the necessary tools. You'll need Python, which should be version 3.10.7 or greater, and the pip package management tool.

You'll also need a Google Cloud project where your app will live. Create a new one or reuse an old one, and enter your preferred name and organization settings.

You'll need a Google account to use as the test account for this tutorial, and you'll need to create three Google Drive folders in this account to test your app.

To enable the Google Drive API, head over to the Google Cloud console and enable the API. You can find all the available APIs in the API Library.

Here's a list of the tools you'll need to install:

After installing the necessary tools and setting up your Google Cloud project, you'll need to install the Google client library for Python using pip.

To configure API access for your Google Drive API project, you need to enable the Drive API in your Google Cloud Console.

Navigate to the Google Cloud Console, confirm your project, and click on Enable to enable the Drive API.

You also need to configure the OAuth consent screen, which is the screen users will see when they request permission to access their folders.

To do this, navigate to the OAuth consent screen console and select the user type, which should be External user type for this tutorial.

Enter your app information, which will be presented to the end user in the consent screen, and click Save and Continue.

Next, you need to add test users, which are the accounts that can use the app before it is published.

For this tutorial, add the Google account in which you created the Drive folders described in the Prerequisites section.

You also need to create credentials that authenticate your Python application.

These credentials help Google understand that the request to retrieve Drive information is coming from an authentic application.

To create credentials, navigate to the credentials console by clicking on Credentials on the left of your screen.

Choose Desktop app as the application type since you will be running the app from your desktop in this tutorial.

Download the JSON file with the app's credentials to the folder in which you will be developing your app.

Here's a step-by-step list to help you remember the process:

Remember to also install the Google API Client and Flask, which are required to run the script.

To get a list of folders in your Google Drive, you can use the files.list method of the REST API with the query string mimeType = 'application/vnd.google-apps.folder'. This will filter down to just the folders.

The method extracts the id and name file fields, and saves the page_token for the next page of results. This is useful if you have a large number of folders and want to retrieve them in batches.

Using the files.list method, you can also list files and directories in your Google Drive. To do this, you'll need to specify a page size and pass some useful fields to the fields parameter. For example, you can get details about the listed files, such as mimeType, size in bytes, parent directory IDs, and the last modified date time.

By default, the results are returned as a list of dictionaries, which can be a bit hard to read. To make the output more human-readable, you can use the list_files(items) function, which takes the results and prints them out in a more user-friendly format.

If you want to search for files and directories in your Google Drive, you can use the list() method with the 'q' parameter. This allows you to filter the results based on a query, such as mimeType or name. For example, you can search for text/plain files by using "mimeType='text/plain'" as the query parameter.

To manage files with the Google Drive API in Python, you first need to search for the file you want to download. You can do this by using the code from the "Download Files" section, which searches for the file by name and downloads it to your local disk.

To download a file, you need to create permission to make the file shareable and downloadable. This is done by adding two scopes to the code, which allows you to create a shareable link button in the Google Drive web interface.

You can use the tqdm library to print a progress bar to see when the download will finish, which is handy for large files. The code makes a GET request to the target URL constructed by passing the file ID as params in the session.get() method.

Uploading files to your Google Drive is a straightforward process. You can use the MediaFileUpload class to upload files of any type, just like I did with a text file called test.txt.

To upload a file, you need to create a folder first. You can use the service.files().create() method to create a new folder and pass the folder_metadata dictionary with the type and name of the folder you want to create. I used this method to create a new folder in my Google Drive.

You can specify the "parents" attribute in the metadata dictionary to upload a file into a specific folder. I passed the folder I just created as the "parents" attribute to upload the file. Make sure you have a test file of your choice ready to upload.

Uploading a file to your Drive is pretty straightforward too. You can add the file metadata to the file_metadata dict and specify the MIME type of the file. I chose a text/csv MIME type, but you can choose a Google-specific MIME type such as a spreadsheet (application/vnd.google-apps.spreadsheet) if you want.

If you're importing a large file, you may want to perform a resumable upload to minimize the impact of network interruptions. To do this, you can add the resumable=True parameter when uploading the file. This will help ensure that your upload is less sensitive to network issues.

To store a file locally from your Google Drive, you can use a file ID. This method is useful when the file type is not supported by the native library.

You can build a query to execute using the MediaIoBaseDownload object. This is necessary because the native library may not be able to handle certain file types.

The file can be retrieved as a string through the variable file, and you can write it into a format you want, such as a CSV file. The extension of the file should be specified in the name, for example, .csv.

The export_media method is used instead of get_media because the file is in a Google MIME type that is not recognizable to computers. You can find a list of all MIME types on the Mozilla website or on Google's documentation.

To retrieve all information about files stored on your Drive, you'll need to share access for your service account to your desired folders and files.

The first step is to retrieve your service account email, which can be found in the JSON key associated with the client_email key. You can also find it in Figure 5 of a previous article on creating a service account.

Once you have the service account email, you can share files and folders just like you would with a user. You can specify the information you want to retrieve, such as id, name, mimeType, size, and modifiedTime.

You can find more information about fields in the documentation, and you may want to have more or other information. To process the information, you'll need to do some treatment on it, as the items variable is a dict.

You can iterate through the dict items, preprocess the data for every row, and store them into a list. This will allow you to put them into a pandas dataframe. Note that you'll want to exclude files with a mimeType of a Google Drive folder from the process.

You can convert the size from bytes to megabytes as part of the preprocessing. This is all the preprocessing you'll need to do on the data to make it more readable for humans.

You can quickly retrieve metadata about a file by using its ID. This metadata includes the file's kind, id, name, and mimeType.

To do this, you'll use a command that queries the file's metadata. The command is straightforward: simply replace "your_file_id" with the actual ID of your file.

The result will be a dictionary containing the main information about the file. This dictionary will include the file's kind, id, name, and mimeType.