Writing Code

The moment you write code, its already technical debt.
Every new code is an investment.
How do you manage your investment?
Aims for writing code
Balance writing for longevity.
How long will your code last?
Write for clarity.
Write for simplicity.
For the long term: simplicity out lives complexity.
Write knowing that it will be read later.
More time will be spent reading and understanding code, than writing it. Reading to writing ratio is really high.
Write so that it is easy to understand.
Write to reduce "WTFs/minute". [WTFs/minute is the only valid measurement of code quality](http://www.osnews.com/story/19266/WTFs_m").
Write with the aim to reduce surprises.
Write code that is easy to test and reproduce.
Write code that is meant to be read, and not meant to solve a problem.
Don't write complex code. Write simple code.
Becareful of death by a thousand cuts/commits/diffs. It is very easy to lose track of the architecture.
Reduce create technical debt.
See Reviewing Code.
What is clarity?
Easy to read
Consistency
Naming
Conventions
Trust
Goals:
Increase signal. Reduce noise.
Reduce petty philsophical disagreements. Avoid bike shed problems.
Save time, energy and resources for the larger technical problems.
Examples:
You should not be wasting time, energy, and resource discussing style. Quickly come to an agreement and stick with it. Use a linter. Don't increase noise.
Writing for a code base of 1,000,000+ Lines
Writing code for a 1,000 line application is very different from writing for 1,000,000 line application.
When the codebase becomes so large, you simply cannot remember everything.
You rely on naming, conventions, and trust.
Conventions
Understand the conventions already used, and stick to them. It makes it easier to read the code, and get it reviewed.
In a large code base, coding conventions may be different from team to team.
Consistency
Use linters.
Don't waste time discussing style
Use linters.
If a discussion about style comes up, quickly agree on something, and implement it in your linter.
Trust in the code base
You will always be using a library written by someone else. You have to trust that it says it does what it does. If it doesn't, then you have to dive deeper down the rabbit hole.
2 biggest problems in programming
Naming
Caching
Off By One Errors
Naming Good Names (files, directories, classes, methods)
Avoid Single Letter Variable Names
Write Code Knowing It Will Be Refactored
Code will always be refactored. Accept this.
Leave It Better Than You Left It
Make It Easy To Reproduce
Write code that is easy to test and reproduce.
The easier it is to reproduce. The easier it is to test. The easier it is to test. The more you will test it.
Small Functions
Input > Process > Output
Output can be an Input for another step
Measure Input > Process > Output
What to Measure:
Input/Output:
Number of Units
Before/After state of the process
Process:
How long did it take
How mucch processing time is used
How much memory did it use
How much bandwidth was used
Output:
How many were successful
How many failed
Why did they fail
Which failed
Funnels
When there are many Input > Process > Output, then you have a funnel.
Break down a Proces
Handling Errors
Silent Errors vs Fataling
Always print IDs
if ($ent === null) {
  printf("Unable to load ent %d", $ent_id);
  exit(1);
}
Write code knowing you will be blamed
Otherwise known as "maintain line history as much as possible".
This is bad because if you wanted to change an argument you would have to change the line history.
printf("Uknown Cop %s %s %s %s", $a, $b, $c, $d);
This is better
printf(
  "Unkown Cop %s %s %s %s",
  $a,
  $b,
  $c,
  $d,
);
80 character limit
Pros:
Forces you to focus on legibility.
Emphasis on short.
Encourages preserving source control blame
Cons:
Some languages may not be suitable for 80 characters.
Can make some functions or conditions longer
When writing conditions, consider breaking them into multiple conditions. See below for easoning.
The focus on short may may become bad.
Example: Bad variable names.
Example: Too many small functions. Makes it difficult to understand flow.
Aim for balance.
Exceptions:
URLs. Always try to use full URLs as much as possible as it helps the reader to intuit the purpose of the URL.
Notes:
Python recommends 79 characters​
I've tested out character length on different sites
Be careful about chaining conditions.
This may dangerous, because it's hard to debug.
For example:
return
  expected.key === actual.key &&
  expected.value === actual.value &&
  expected.concern === actual.concern;
If we broke it down to multiple if conditions it makes it easier to debug.
if (expected.key === actual.key) {
  return false;
}
​
if (expected.value === actual.value) {
  return false;
}
​
if (expected.concern === actual.concern) {
  return false;
}
​
return true;
Pros for using multiple conditions:
If you use Exceptions instead of return statements, you can easily get a stack trace which is extremly useful.
Easier usage of print style debugging.
Cons for using multiple if conditions:
Longer function statements.
Becareful of chains of ternary operators
A chain of ternary operators make it hard to judge what is happening.
Do not do this:
$size = $button === 'submit' ? 'big : 'small';
$text = $button === 'submit'
  ? $l10n->getBigText()
  : $l10n->getSmallText();
$action = $button === 'submit'
  ? '/submit'
  : '/reset'
Do this:
if ($button === 'submit') {
  $size = 'big';
  $text = $l10n->getBigText();
  $action = '/submit';
} else {
  $size = 'small';
  $text = $l10n->getSmallText();
  $action = '/reset';
}
Tuples
Sometimes we need to pair two variables together to represent a single datatype. For example tuple(MetricID, Partner) which tells us that this represents the MetricID for a given Partner.
You may want to consider 2 data structures for this:
Metric(MetricID)
MetricPartner(Metric/MetricID, Partner)
It is easier moving from a data structure that manages one data type, to a data structure that manages 2.
Consider having a function in Metric which takes in a Partner and returns a MetricPartner. For example:
  $metric = new Metric($metric_id);
  $metric_partner = $metric->withPartner($partner);
Becareful of enum in Switch statements
If an enum is in more than one switch statement. Consider making a factory class which returns singleton class for the enum value.
For example, if you only have one instance of this, its ok:
function getName(Color $color) {
  switch($color) {
    case Color::RED:
      return 'Red';
​
    case Color::BLUE:
      return 'Blue';
  }
}
But if you add another function, then make a factory class which returns an instance.
function getRGB(Color $color) {
  switch($color) {
    case Color::RED:
      return '#FF0000';
​
    case Color::BLUE:
      return '#0000FF';
  }
}
Do this instead:
class ColorFactory {
  public static function get(ColorEnum $color) {
    switch ($color) {
      case ColorEnum::RED:
        return ColorRed::get();
​
      case ColorEnum::Blue:
        return ColorBlue::get();
    }
  }
}
​
class Color extends Color {
  public function get(ColorEnum $color) {
    switch ($color) {
      case ColorEnum::RED:
        return ColorRed::get();
​
      case ColorEnum::Blue:
        return ColorBlue::get();
    }
  }
}
​
abstract class ColorBase extends Color {
  public function getName(): string;
  public function getRGB(): string;
}
​
final class ColorRed extends Color {
  public function getID(): Color {
    return Color::RED;
  }
​
  public function getName(): string {
    return 'Red';
  }
​
  public function getRGB(): string {
    return '#FF0000';
  }
}
​
final class ColorBlue extends Color {
  public function getID(): Color {
    return Color::Blue;
  }
​
  public function getName(): string {
    return 'Blue';
  }
​
  public function getRGB(): string {
    return '#0000FF';
  }
}
​
function main() {
  $color = ColorFactory::get($color)
  return $color->getName();
}
Yes there is more code, but its easier to manage the code. When adding a new Enum you are not required to remember which files to update, the compiler will catch any undefined functions.
Deep inheritance trees are bad
Be careful of parameter bags
Single Responsibility Principle (SRP)
Use intention revealing names
2 hardest parts of programming
Write code that is meant to be read, and not meant to solve a problem
Duplicating calls is ok.
Monitoring/Alerts
How many lines of code are being added?
Are there alerts on highly sensitive parts of the codebase?
For user input: consider using Regexes instead of String comparisons
Pros:
More flexibility in matching strings
Regexes don't require precise string matching
Can easily match more than one string, for example to match all branches where node8 work is done: /\.*node8/
Cons:
Regexes are slightly more time consuming
For example:
regex.matches(input)
vs
inputs.split(',').some((input) => input === expected);
Scripts
When writing scripts, always leave a file header about what the script does, or link to a proper resource.
For example:
!/bin/sh
# Reencrypts the keys in our database.
# This is necessary because ....
# http://www.example.com/wiki/details
Logs
Also applies to:
Deployment History
Consider including:
Time
Script used to fire the log
Server/Hostname the log was created
Where this log was fired
Things that make it easy to find the source of the log
Reviewing Code
Engineering Code
Last updated 3 months ago