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Learning Google Protocol Buffers with Python - Part 2

This post is part of a tutorial series:

In the previous post, we introduced the basics of using Google Protocol Buffers (proto3) with Python. In this post, we’ll delve further into some key syntax and features of proto3.

Posted on Nov 3, 2018 in Python Programming - Advanced Level by Amo Chen ‐ 4 min read

Learning Google Protocol Buffers with Python - Part 1

This article is part of a series:

The blog post What I Learned from Quip on How to Build a Product on 8 Different Platforms with Only 13 Engineers explains how Quip managed to build products for 8 different platforms with only a 13-member team. It’s definitely something worth learning from.

A key concept from the post is Build once, use multiple times. It encourages minimizing the repetition of creating the same components, thereby increasing the reusability of components. The article also reveals that Quip heavily uses Google Protocol Buffers. By defining data structures using Google Protocol Buffers, automatic code generation can occur for reading and writing the same data structure across various languages or platforms. It can even act as a data exchange format to transfer between different platforms, reducing repetitive development costs and thus improving development efficiency.

With such a handy tool, let’s learn Google Protocol Buffers using Python!

Posted on Oct 27, 2018 in Python Programming - Advanced Level by Amo Chen ‐ 5 min read

Python Module - jsonschema Part 3

This post is part of a series on the Python module - jsonschema:

In Part 2 of the Python Module - jsonschema, we covered the complex usage of types like number, string, array, and object. However, most examples focused on validating individual data types, while in practice, JSON data can often involve a mixture of multiple data types. For example, an array might contain object elements, and an object might include nested objects. Consider the following JSON data:

[
    {
        "user_id": 1,
        "preference": {
            "cooking": True,
            "fishing": False,
        }
    },
    {
        "user_id": 1,
        "preference": {
            "cooking": True,
            "fishing": False,
        }
    },
]

This section will introduce how to write JSON Schemas that are more practical for real-world use and easier to maintain.

Posted on Mar 28, 2018 in Python Module/Package Recommendations by Amo Chen ‐ 4 min read

Python Module - jsonschema Part 2

This article is a part of a series on the Python module - jsonschema:

In the previous article, Python Module - jsonschema Part 1, we introduced six data types defined by JSON Schema and covered some basic validation techniques.

In this post, we will dive deeper into more complex usages of several types, namely number, string, array, and object.

Posted on Mar 23, 2018 in Python Module/Package Recommendations by Amo Chen ‐ 6 min read

Python Module - jsonschema Part 1

This article is part of a tutorial series about the Python module - jsonschema:

JSON is currently one of the mainstream data interchange formats. However, if you want to validate the format of JSON data in your program, you’ll need to spend some effort writing validation code. Fortunately, JSON Schema simplifies the process of validating JSON formats. If you’re using JSON as the data exchange format for an API, you might consider using JSON Schema for validation.

JSON Schema is a vocabulary that allows you to annotate and validate JSON documents.

Posted on Mar 20, 2018 in Python Module/Package Recommendations by Amo Chen ‐ 5 min read

Recording Test Duration with Python pytest

Recently, I read an article titled Timing Tests in Python for Fun and Profit, which is well worth a read. The article discusses how to find test cases that need speed improvement by recording their execution time (and in the process, you might also discover code with poor performance).

However, I often use pytest, so I spent some extra time finding out how to achieve the same in pytest.

Posted on Nov 20, 2016 in Python Module/Package Recommendations by Amo Chen ‐ 2 min read

Efficient MySQL Pagination

When I first started learning programming, I followed examples in textbooks using LIMIT offset, row_count for pagination. However, as the volume of data increased, this pagination method caused longer query times for later pages. In MySQL, when an offset is specified, it does not directly start retrieving data from that offset. Instead, it fetches all data based on the ‘where’ conditions first, and then retrieves the required number of rows beginning from the offset.

Posted on May 29, 2016 in MySQL by Amo Chen ‐ 3 min read

Know Your VIM - Basic Cursor Movement

Up, Down, Left, and Right

Remembering how to move up, down, left, and right in VIM doesn’t require any secret tricks. The reason h, j, k, l are used for left, down, up, and right is because on the developer’s keyboard at the time, hjkl also represented those directions.

Left, Down, Up, Right h j k l

Historical Note: ADM-3A Keyboard

Last updated on Sep 29, 2024 in Vim by Amo Chen ‐ 2 min read

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Up, Down, Left, and Right #

Up, Down, Left, and Right