gRPC and Protobuf with Python

Think Different - Dhiraj Patra
2 min readFeb 26, 2024

Context and Overview

I am trying to give you a quick learning for GRPC, Protobuf including a Python based application to test.

gRPC (Remote Procedure Call):

- Definition: gRPC is a high-performance, open-source RPC framework developed by Google. It allows you to define remote service methods using Protocol Buffers and then generate client and server code in multiple languages.

- Purpose: gRPC enables efficient communication between distributed systems, allowing services written in different languages to communicate seamlessly.

- Usage: It is commonly used in microservices architectures, where services need to communicate with each other over a network.

Protocol Buffers (protobuf):

- Definition: Protocol Buffers is a language-neutral, platform-neutral, extensible mechanism for serializing structured data. It was developed by Google and used for efficient data serialization.

- Purpose: Protocol Buffers are used to define the structure of data that is transmitted between different systems or components. They offer a compact binary format for data exchange and are language-agnostic.

- Usage: Protocol Buffers are commonly used in scenarios where efficient data serialization is required, such as communication between microservices, storage of data, and configuration files.

Benefits

gRPC:

- Efficiency: gRPC uses HTTP/2 as the underlying protocol, which supports multiplexed streams, header compression, and other features that improve efficiency over traditional HTTP/1.x.

- Language Agnostic: gRPC supports multiple programming languages, making building polyglot systems where services are written in different languages easy.

- Automatic Code Generation: gRPC provides tools to automatically generate client and server code based on the service definition, reducing boilerplate code and making development faster.

- Streaming Support: gRPC supports both unary and streaming RPCs, allowing bidirectional communication between client and server.

Protocol Buffers:

- Efficiency: Protocol Buffers use a binary encoding format, which is more compact and efficient than JSON or XML. This results in smaller message sizes and faster serialization/deserialization.

- Schema Evolution: Protocol Buffers support backward and forward compatibility, allowing you to evolve your data schema over time without breaking existing clients or servers.

- Language Agnostic: Similar to gRPC, Protocol Buffers are language agnostic, enabling interoperability between systems written in different languages.

- Version Control: Protocol Buffers allow you to version your data schema, making it easier to manage changes over time and ensuring compatibility between different software versions.

Links for Further Reading

- gRPC Documentation: https://grpc.io/docs/

- Protocol Buffers Documentation: https://developers.google.com/protocol-buffers

- gRPC GitHub Repository: https://github.com/grpc/grpc

- Protocol Buffers GitHub Repository: https://github.com/protocolbuffers/protobuf

- gRPC vs REST: https://grpc.io/blog/grpc-vs-rest/

- gRPC Python Quick Start: https://grpc.io/docs/languages/python/quickstart/

- Protocol Buffers Language Guide: https://developers.google.com/protocol-buffers/docs/proto3

- GitHub demo application: https://github.com/dhirajpatra/grpc_protobuf_python

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Think Different - Dhiraj Patra

I am a Software architect for AI, ML, IoT microservices cloud applications. Love to learn and share. https://dhirajpatra.github.io