Deprecated Google APIs Client Libraries

A Practical Guide to GoogleApis: Deprecation, Usage, and Elixir Client Generation

Introduction

In the evolving world of cloud APIs, keeping up with official client libraries is essential. The GoogleApis project, while once a central hub for Elixir-based Google API clients, has entered a deprecation and archiving phase. The repository is described as formally archived and no longer actively maintained. The libraries housed under the clients/ directory are provided “as-is,” without guarantees of future updates or official support. This reality sets the stage for developers to understand what remains useful, what to expect, and how to work with the tooling that still exists in this ecosystem today. The message behind the notice is clear: treat these generated clients as experimental and use them with awareness of their maintenance status.

This guide distills the core ideas, workflows, and practical steps surfaced in the input material. It is organized to help you navigate installation, authentication, API access, and the process for generating new clients, all within an Elixir environment. While the deprecation notice might feel like a blocker, the surrounding tooling and documented workflows still offer valuable insights for experimentation, learning, and understanding how Google’s discovery and Open API ecosystems were integrated with Elixir projects.

Deprecation and Archival: What It Means for You

• The repository has been archived and is not actively maintained.
• The client libraries are provided as-is, with no guarantees of future updates or support.
• Generated clients are described as under development and should be considered experimental.
• If your project depends on long-term stability, plan for alternatives or consider contributing to ongoing maintenance of a fork or newer integration approach.

This reality does not erase the practical knowledge embedded in the project. It still provides a lucid blueprint for how to authenticate, discover APIs, convert discovery formats to OpenAPI, and generate language-specific clients. It also showcases a coherent workflow for testing and experimenting with Google Cloud Platform APIs from an Elixir environment. With that understanding, you can proceed to the practical sections that will help you set up, authenticate, and work with Google APIs in a controlled, exploratory manner.

The Kit: What You’ll Find in the Repository

• A collection of Elixir client libraries designed to interact with Google APIs. These libraries live under a top-level structure called clients/ and each API typically has its own README with usage specifics.
• A master folder that contains the tooling to generate these client libraries. The generation workflow is described as experimental and under active development.
• A set of mix tasks that componentize the build process for selecting APIs, fetching API specifications, converting them to OpenAPI, and generating client code.
• A note that the generated clients can require additional dependencies, particularly for authentication support and HTTP handling.

If you’re exploring this ecosystem, you’ll encounter the following core ideas:

• The libraries are built to be modular, with a focus on generating API clients from Google's discovery documents and then converting them to OpenAPI formats for code generation.
• The workflow is driven by mix tasks that orchestrate discovery, fetch, convert, and build steps, enabling you to target specific APIs for client generation or to perform bulk builds.

Prerequisites: Getting Your Environment Ready

To engage with the GoogleApis tooling in this Elixir ecosystem, you’ll generally need:

• Node.js (for some conversion tooling that relies on a Node-based converter).
• Elixir and Mix to manage dependencies and run the generation tasks.
• A set of dependencies for authentication and API access. The typical setup includes:
• The googleapistorage client library
• The goth library for Google authentication
• A configured environment for authentication, either through service account credentials or OAuth 2.0 tokens.

A practical installation path looks like this:

• Add dependencies to your Mix project
• googleapistorage with a version constraint (for example, "~> 0.19.0")
• goth with a version constraint (for example, "~> 1.2.0")
• Run the dependencies installer:
• mix deps.get
• Be ready to handle authentication via Goth or Application Default Credentials, especially in environments where Google Cloud credentials are provided by the runtime platform.

Authentication: Service Accounts and OAuth 2.0

Authentication is a two-pronged approach in this ecosystem: service accounts and OAuth 2.0. Each serves different use cases and organizational needs.

Service Accounts: Server-to-Server Scenarios

• Create a Service Account key file. This is a JSON file that contains the credentials used to authenticate to Google Cloud Platform services from server environments or CI systems.
• Set the environment variable GOOGLEAPPLICATIONCREDENTIALS to the path of the service account key file. For example:
• export GOOGLEAPPLICATIONCREDENTIALS=/path/to/service_account.json
• In environments such as App Engine, Compute Engine, or Container Engine, credentials are often available by default, simplifying initial experiments and development.

OAuth 2.0: User Consent and Access Tokens

• Many APIs (Drive, Gmail, YouTube, among others) require OAuth 2.0 to authorize requests on behalf of a user.
• A typical flow involves using the oauth2-library and an authentication sample to fetch an access token.
• A practical testing flow often includes:
• Setting the client ID and client secret as environment variables
• Running a mix task to fetch a token, which initiates a browser-based consent flow
• Visiting the consent URL, authorizing the application, and copying the verification code back into the console
• The system then exchanges the code for an access token that you can use for API calls
• The process is designed to be developer-friendly for testing and experimentation, but in production, you’d likely implement a robust OAuth 2.0 token management strategy.

A Concrete Example: Testing with OAuth and a Drive Token

• You can obtain an access token by using Goth:
• {:ok, token} = Goth.Token.for_scope("https://www.googleapis.com/auth/cloud-platform")
• Create a connection using the token:
• conn = GoogleApi.Storage.V1.Connection.new(token.token)
• Call a Storage API method, such as listing buckets:
• {:ok, response} = GoogleApi.Storage.V1.Api.Buckets.storagebucketslist(conn, project_id)
• Work with the response, for example by iterating over buckets and printing their IDs:
• Enum.each(response.items, &IO.puts(&1.id))

This flow illustrates the practical steps for making real API calls against Google Cloud Storage in an Elixir environment. It demonstrates how the authentication token, the connection object, and the API client module come together to fetch data from Google services.

Making a Request: A Minimal Interaction Pattern

• Start by obtaining an access token using Goth or another supported library.
• Create a connection object that carries the token information.
• Use the appropriate API module and method to perform a request, such as listing resources, retrieving metadata, or performing actions like creating or updating resources.
• Process and display or log the results, keeping in mind that this is an experimental setup as described by the deprecation note.

What’s Next? The Generating Clients Workflow The repository provides a four-step, mix-task-driven workflow to generate client libraries. Each step is designed to progressively transform API specifications into usable Elixir clients.

1) mix google_apis.discover — Selecting APIs

• Purpose: Query Google’s API discovery directory to determine which APIs you might want to generate clients for.
• Output: A staging file, api-candidate.json, stored in the config directory. This file is a snapshot of API options you plan to generate against.
• Customization: You can rename the destination file by passing a filename argument, for example:
• mix google_apis.discover foo.json
• Important note: This task is not designed for frequent runs because the generated api.json acts as configuration metadata that you use to control the subsequent steps.

2) mix google_apis.fetch — Download API Specifications

• Purpose: For each API listed in config/api.json, download the API specification files into the specifications/gdd directory with a -.json suffix, representing their downloaded discovery document format.
• Limiting scope: You can specify a particular API name to fetch, for example:
• mix google_apis.fetch CloudTrace
• Outcome: A local collection of API discovery documents ready for conversion.

3) mix google_apis.convert — Convert to OpenAPI v2

• Purpose: Transform Google’s discovery format into an OpenAPI v2 specification (formerly Swagger).
• Configuration: The converter’s behavior can be configured via config.exs, for example:
• config :googleapis, specconverter:
• The default converter uses the node-based api-spec-converter tool. The converter translates discovery documents into a format suitable for the subsequent client generation step.
• Limiting scope: You can similarly limit conversions to a specific API, with:
• mix google_apis.convert CloudTrace

4) mix google_apis.build — Generate API Clients

• Purpose: Use the converted OpenAPI specifications to generate an Elixir client library within the clients directory.
• Configuration: You can select a client generator and the Swagger CLI settings via config.exs, for example:
• config :googleapis, clientgenerator: GoogleApis.Generator.SwaggerCli
• config :googleapis, swaggercli_image: "swagger-cli"
• Limiting scope: You can generate a single API’s client by specifying its name:
• mix google_apis.generate CloudTrace

A Note on Build Details and Customization

• The default generator relies on Docker with an image based on the swagger-codegen project. However, you can customize this in the config.exs file.
• The config supports adjusting the converter and CLI image to fit your environment and constraints.
• The file config.exs allows you to choose how the formatting, naming, and code structure should appear in the generated libraries.

Selecting APIs, Fetching, Converting, and Building: A Cohesive Pipeline

• The selection and generation process emphasizes a deliberate sequence: first decide which APIs to include, then fetch, convert, and finally generate.
• This approach helps you manage scope and control the size of the generated client surface, which is especially valuable when exploring the landscape of Google APIs within an Elixir project.
• While the workflow expresses a powerful concept, remember that the entire process is framed within an experimental and deprecated ecosystem. It’s a practical sandbox rather than a production-grade modernization path.

Contributing and Licensing: Community Involvement

• The repository invites contributions as a long-standing tradition of open collaboration.
• See the CONTRIBUTING.md file for details about how to get involved, submit improvements, report issues, or propose new APIs to add to the client generation flow.
• The project is released under the Apache 2.0 license, with LICENSE as the canonical reference for legal terms and permissions.
• As with any community-driven project, contributions should be approached with an awareness of the deprecation status and the need to consider long-term maintenance strategies.

Disclaimer: Official Support Status

• The material emphasizes that this is not an officially supported Google product.
• As a reader and developer, you should interpret the insights as educational, historical, or experimental guidance rather than a guarantee of official support or continued maintenance.
• In production environments, you should assess alternatives, consider maintaining a fork, or seek updated approaches that align with current Google API client ecosystems and community-supported tooling.

Operational Tips and Best Practices

• Treat the repository as a learning resource to understand how Google APIs can be discovered, transformed, and used from Elixir.
• When experimenting with token generation and API access, keep token lifecycles, scope management, and secure storage in mind. Tokens have lifetimes and scopes, and handling refreshes gracefully is important in real-world usage.
• If you plan to rely on generated clients for more than quick experiments, consider building a lightweight test harness that cleanly mocks API responses to prevent hitting real quotas during development.
• Stay aware of the deprecation status. If you rely on these clients for longer-term projects, explore migration strategies to officially supported clients or modern alternatives that align with current Google API ecosystems.

Images: Availability and What to Expect

• The input material provided does not contain any images. In this post, there are no embedded images to include. If you have images that you want to integrate, you could add visuals that illustrate:
• The flow from API discovery to OpenAPI conversion
• The four GoogleApis mix tasks: discover, fetch, convert, build
• A simple architecture diagram showing the interaction between service accounts, OAuth tokens, and API clients
• For now, this guide remains text-based and structured around sections, bullets, and descriptive narratives.

References to Key Concepts and Links

The original material includes several references and external links that inform the workflows and concepts described:

• Application Default Credentials and service account workflows
• Discovery directory and Google APIs discovery format
• The api-spec-converter tool for converting discovery documents to OpenAPI
• Swagger Codegen for client generation
• The hex.pm package ecosystem for Elixir
• The goth library for Google authentication
• Elixir samples repository with practical usage examples
• The oauth2-library for OAuth flows
• The auth sample repository as a testing example for authentication

If you want to revisit any concept, the core ideas—discovery, conversion, and client generation—remain consistent with the documentation you started from. The deprecation status does not erase the practical value of understanding how these pieces fit together and how you could adapt similar workflows with current tooling in the Elixir ecosystem.

Conclusion: A Devoted Yet Experimental Path

GoogleApis serves as a case study in how a language-agnostic approach to API discovery and client generation can be implemented in a specific language ecosystem like Elixir. The four-step generation process—discover, fetch, convert, and build—offers a clear blueprint for transforming Google’s API surface into usable Elixir clients. Authentication remains a central concern, with two solid paths: service accounts for server-to-server communications and OAuth 2.0 for user-consented access. While the project is deprecated and archived, the documented workflows provide a comprehensive snapshot of early-generation tooling and the practical challenges of integrating Google APIs with Elixir.

If you’re embarking on a project that requires Google API access from Elixir, use this guide as a foundation for understanding the historical approach and the kinds of tooling that were used. Consider the deprecation as a reminder to evaluate current alternatives and to design for maintainability and long-term support. You may, for example, leverage newer libraries and official Google client offerings that align with contemporary authentication strategies and API distributions.

Images: Acknowledgment

• Images: None provided in the input. If you have visuals to accompany this guide, consider diagrams of the API discovery flow, the conversion pipeline, and the token-based authentication process to enhance comprehension.

Final thoughts

This guide captures the essence of a workflow designed to empower Elixir developers to interact with Google APIs—even in a context where official maintenance has ceased. It emphasizes practical steps, clear sequences, and thoughtful caution about the limitations and risks of relying on an archived project for production work. By grounding your approach in the described patterns, you can experiment responsibly, learn the mechanics of API discovery and client generation, and apply those insights to more current ecosystems and tooling.