Why Go succeeded; Java's naming conventions; & Python optimization tips
Arpit Mohan
Posted on November 19, 2019
TL;DR style notes from articles I read today.
5 things Rob Pike attributes Go’s success to
- Writing a formal specification of the language.
- Making Go attractive for app developers to use. Having key software written in Go created confidence in it.
- Establishing a strong open-source community that supported Go. Being prepared for a tricky balancing act while listening and implementing.
- Counterintuitive, but making the language hard to change. Yes, it creates rigidity but also makes it harder for old code to break.
- Constantly listening to the community, but sticking to the things Go team believed are important from their specs.
Full post here, 4 mins read
What’s in a name: Java naming conventions
- In the base package name, put your company’s domain in reverse order & then add the project name & maybe version - all in lower case.
- Use nouns, written in CamelCase (with first letter capital), for class names. Class names should say what function or variable to expect from it as well.
- Choose short, meaningful nouns for variables and fields, saying what values or variables they hold, in camelCase.
- Avoid single character variables. Avoid underscore & dollar as first letters. For boolean values, start with ‘is’ or ‘has’, since they are yes/no questions.
- Put constants in all-caps, with underscores to separate words.
- Make methods and functions verbs, implying what they do in 2-3 words in camelCase. Use ‘get’ & ‘set’ to start the names of data fetching and setting functions.
- Use similar conventions as classes and interfaces for enums and annotations, respectively, with enums in all-caps.
Full post here, 5 mins read
Python code optimization tips for developers
- Optimize the slow code first. In the case of Python, PyPy helps you use less space and work faster than CPython’s typical bulk allows for.
- Profile codes (using CProfile or PyCallGraph, say) to analyze how they work in different situations and estimate the time taken.
- Python strings tend to be immutable and slow. Concatenate them with the .join() method rather than relying on the memory-hungry (+) operator alone.
- Use list comprehension rather than loops for faster coding and execution.
- For memory optimization, prefer xrange over the range function to speed up the creation of integer lists.
Full post here, 4 mins read
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Arpit Mohan
Posted on November 19, 2019
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November 19, 2019