CodeFaster

CodeFaster is a Substack focused on improving coding efficiency and problem-solving skills. It covers a range of topics from coding practices, debugging tips, command-line utilities, and working with different programming tools. The newsletter aims to help developers code faster, debug efficiently, and master the use of various developer tools.

Coding Practices Debugging Techniques Command-Line Utilities Programming Tools Software Development Unix/Linux Commands API Usage Data Serialization Version Control Network Diagnostics

The hottest Substack posts of CodeFaster

And their main takeaways

Don't use functional programming languages

36 implied HN points • 18 Dec 24
🕹 Technology Programming Software Development Computers Tech Trends
  1. Functional programming languages can be slow and may not match your thinking style. It's better to use a language that feels natural to you.
  2. Python has a lot of library support and community help, making it easier to find solutions and resources.
  3. While functional programming concepts like map and filter are useful, you can learn them without relying on functional programming languages.

Log invalid values

36 implied HN points • 27 Nov 24
🕹 Technology Programming Software Development Coding Data
  1. Logging invalid values helps in debugging and understanding errors better. By including the actual value in the log, you can see what went wrong.
  2. Using clear and structured logging formats, like JSON, makes it easier to extract useful information later. This can save time and make troubleshooting smoother.
  3. Fast programming techniques and commands can enhance your workflow, letting you focus on coding efficiently rather than getting stuck on minor issues.

How to code for the future

36 implied HN points • 19 Nov 24
🕹 Technology Software Development Coding Practices Technical Debt System Design
  1. When coding for the future, it's important not to create more work for yourself later. Focus on avoiding technical debt instead of trying to predict every future need.
  2. Don't go overboard with coding. Keep your code simple and flexible, ensuring it can adapt to changes without adding extra complexity.
  3. Instead of trying to build reusable programs from the start, solve the immediate problem first. You can refactor and create reusable parts later if needed.

Abundance mindset (not LinkedIn cringe)

36 implied HN points • 30 Oct 24
🕹 Technology Programming Mindset Artificial Intelligence Development Coding
  1. An abundance mindset helps you think creatively and work faster by focusing on possibilities instead of limitations. It's about believing that resources, like time and tech, are plentiful.
  2. A scarcity mindset can slow you down and lead to poor decisions, like overcomplicating simple tasks. Thinking that everything is limited makes you hesitant to create and innovate.
  3. In today's tech world, many resources are cheap and accessible. With advancements like AI, we can keep creating without worrying too much about waste or pollution.
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Don't abuse 0

144 implied HN points • 04 Jan 24
🕹 Technology Programming API Software Development
  1. Setting a spend limit of 0 in an API does not mean restricting spending to zero; it actually means allowing infinite spending.
  2. Consider using the string 'infinity' instead of '0' to denote unlimited spending.
  3. If needing to use an integer value for spend limits, consider using -1 to represent infinity, as it is not a common value and prompts further investigation.

Don't serialize money as a float

108 implied HN points • 20 Dec 23
🕹 Technology Coding Finance Math
  1. Avoid serializing money as a float due to precision issues
  2. Use integers and the smallest denomination for accurate calculations
  3. Leading financial institutions prefer integer math over floating point for money handling

Use React, not Svelte

144 implied HN points • 31 Aug 23
🕹 Technology Programming Web Development JavaScript
  1. Consider using React over Svelte for faster coding due to more available libraries and packages
  2. React is more popular than Svelte, making it easier to find maintained and ready-to-use packages
  3. React provides a more concise and declarative coding experience compared to Svelte

Read code when you're somber

72 implied HN points • 02 Feb 24
🕹 Technology Programming Music
  1. Reading code while feeling somber can match personal experience and enhance focus.
  2. Having a specific playlist of somber, melodic music for coding tasks can be effective.
  3. Consider supporting reader-supported publications by becoming a subscriber.

Checklist before asking questions

144 implied HN points • 02 Aug 23
🚌 Education
  1. Check if you spent at least 5 minutes trying to figure it out before asking questions.
  2. Remember to google for answers before seeking help.
  3. Consider asking chat GPT for assistance if needed.

Working with your git diffs

108 implied HN points • 05 Sep 23
🕹 Technology CLI JSON Python
  1. Ignore whitespace in git diffs using -w flag to reduce size and focus on content
  2. Filter diffs using filterdiff CLI tool to include or ignore specific files in your git diffs
  3. Convert git diff output to JSON for easier parsing using tools like diff-to-json or unidiff in Python

bash color sampling 1-liner

108 implied HN points • 20 Aug 23
🕹 Technology Coding
  1. Bash color sampling can be done with a 1-liner script
  2. Special escape sequences can change terminal text color
  3. Using xargs without a command puts all arguments on a single line

unix 1 liner to get total minutes of audio

108 implied HN points • 25 Jul 23
🕹 Technology Programming Unix
  1. The Unix one-liner uses commands like find, grep, xargs, and math-sum to get total minutes of audio files.
  2. The find command lists all files and directories in the current location.
  3. The xargs -L 1 mp3-minutes command calculates the duration in minutes for each mp3 file and then sums up the total duration using math-sum.

Unix 1-liner using jq

108 implied HN points • 20 Jul 23
🕹 Technology Programming Unix JSON Command-line Data processing
  1. The Unix 1-liner using jq efficiently filters and extracts specific data from a JSON response.
  2. Creating a small script like get-all-accounts to gather data beforehand is crucial for this command to work effectively.
  3. The jq command simplifies data processing by breaking down the process into four transformations.

How to design a CLI

108 implied HN points • 09 Jul 23
🕹 Technology Design
  1. Write CLI output to stdout for easy filtering
  2. Include only necessary information in CLI headers
  3. Use precise timestamps in easily parsable formats for data analysis

unix 1 liner to inspect a CSV

72 implied HN points • 23 Jul 23
🕹 Technology Coding Data Analysis Unix
  1. The Unix one-liner uses commands like cat, tac, cut, and less to process a CSV file.
  2. Using 'cat' reads the file, 'tac' prints it in reverse, 'cut' selects specific columns, and 'less' displays data page by page.
  3. This one-liner is handy for quickly examining and navigating through large CSV files in the terminal.

building vs taping things together

0 implied HN points • 27 Nov 24
🕹 Technology Software Programming Web Development Coding Systems
  1. There's a difference between building software properly and just taping things together. Taped together solutions might work for simple tasks, but they can fail under heavy use.
  2. With modern technology, you can create quick, 'hacky' code that surprisingly holds up well. It doesn't have to be perfect to work effectively in the right environment.
  3. Becoming good at fast programming is about avoiding major mistakes. When you learn to do this, you find that coding can be a lot of fun and surprisingly successful even with simple solutions.

Use bad standards

0 implied HN points • 28 Nov 24
🕹 Technology Blockchain Software APIs Development Standards
  1. ChainId is a confusing standard in crypto, but it is universal, which makes it easier to use across different applications. Instead of creating custom names for chains, sticking with chainId saves development time.
  2. Creating custom standards can complicate things, as you might have to map your data to fit different APIs. This can lead to a lot of extra work for developers.
  3. Even if a standard seems bad, if everyone else uses it, it often makes more sense to stick with that standard to avoid unnecessary complications.