Dylan  Iqbal

Dylan Iqbal


Translating Chinese Into Morse Code!

How do you translate Chinese into Morse code?

In the late 1800s, China was connected to the international telegraph network, and this was the big question! Morse code was originally conceived for transmitting English, and while it was extended to support other alphabetic languages, this didn’t work out of the box for character-based languages like Chinese.

In this talk, we’ll walk through the different encoding schemes used to convert characters to Morse code, their tradeoffs, and how some of the challenges are relevant to us still today!

#developer #programming

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Translating Chinese Into Morse Code!
mishel salsa

mishel salsa


Morse Code Translator - Convert text to morse code online

Welcome on, one of the best Morse Code Translator (morsecode übersetzer) website. On this website, you can convert English text to morse code or morse code to English text.

What is Morse Code?
Morse Code is a combination of dots, dashes and spaces that together make letters and words. It is an alphabet that has ben invented to simplify communication and create letters using only dots, dashes and spaces.

What is Morse Code used for?
Morse Code was, and still is, used a lot during war and combat as it is a quick way to get messages across the country. The most famous word used in Morse Code is S.O.S which means Save Our Souls. This is a distress message for anyone who is in danger!

#morse code translator #morse code numbers chart #morse code alphabets

Tyrique  Littel

Tyrique Littel


Static Code Analysis: What It Is? How to Use It?

Static code analysis refers to the technique of approximating the runtime behavior of a program. In other words, it is the process of predicting the output of a program without actually executing it.

Lately, however, the term “Static Code Analysis” is more commonly used to refer to one of the applications of this technique rather than the technique itself — program comprehension — understanding the program and detecting issues in it (anything from syntax errors to type mismatches, performance hogs likely bugs, security loopholes, etc.). This is the usage we’d be referring to throughout this post.

“The refinement of techniques for the prompt discovery of error serves as well as any other as a hallmark of what we mean by science.”

  • J. Robert Oppenheimer


We cover a lot of ground in this post. The aim is to build an understanding of static code analysis and to equip you with the basic theory, and the right tools so that you can write analyzers on your own.

We start our journey with laying down the essential parts of the pipeline which a compiler follows to understand what a piece of code does. We learn where to tap points in this pipeline to plug in our analyzers and extract meaningful information. In the latter half, we get our feet wet, and write four such static analyzers, completely from scratch, in Python.

Note that although the ideas here are discussed in light of Python, static code analyzers across all programming languages are carved out along similar lines. We chose Python because of the availability of an easy to use ast module, and wide adoption of the language itself.

How does it all work?

Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:

static analysis workflow

As you can see in the diagram (go ahead, zoom it!), the static analyzers feed on the output of these stages. To be able to better understand the static analysis techniques, let’s look at each of these steps in some more detail:


The first thing that a compiler does when trying to understand a piece of code is to break it down into smaller chunks, also known as tokens. Tokens are akin to what words are in a language.

A token might consist of either a single character, like (, or literals (like integers, strings, e.g., 7Bob, etc.), or reserved keywords of that language (e.g, def in Python). Characters which do not contribute towards the semantics of a program, like trailing whitespace, comments, etc. are often discarded by the scanner.

Python provides the tokenize module in its standard library to let you play around with tokens:



import io


import tokenize



code = b"color = input('Enter your favourite color: ')"



for token in tokenize.tokenize(io.BytesIO(code).readline):





TokenInfo(type=62 (ENCODING),  string='utf-8')


TokenInfo(type=1  (NAME),      string='color')


TokenInfo(type=54 (OP),        string='=')


TokenInfo(type=1  (NAME),      string='input')


TokenInfo(type=54 (OP),        string='(')


TokenInfo(type=3  (STRING),    string="'Enter your favourite color: '")


TokenInfo(type=54 (OP),        string=')')


TokenInfo(type=4  (NEWLINE),   string='')


TokenInfo(type=0  (ENDMARKER), string='')

(Note that for the sake of readability, I’ve omitted a few columns from the result above — metadata like starting index, ending index, a copy of the line on which a token occurs, etc.)

#code quality #code review #static analysis #static code analysis #code analysis #static analysis tools #code review tips #static code analyzer #static code analysis tool #static analyzer

Morse Code Translator Detect Blinks — Python, OpenCV, MediaPipe

Hello everyone,

It has been a while since the last time I posted a tutorial, or something in general. Basically life happened and I decided not to share rather than sharing low quality content. Today, I’ll walk you through a computer vision project that takes your live video input and translates your blinks into Morse Alphabet so you can blink short and long to write messages.

The source code for the project is here, I also used this awesome tutorial as a boiler plate to start with, if you want to learn more about Computer Vision applications you can check the channel owner’s channel from the link I posted. So without further ado let’s dive right into it.

As for the beginning I want to explain MediaPipe library a little bit, “MediaPipe offers open source cross-platform, customizable ML solutions for live and streaming media.”, this definition is from their own website and explains what you can do with that library shortly and cleanly, they offer several other solutions that can run on different platforms and I’ll explain all of them in a different post in the future. The feature that we’ll use today is called “Face Mesh”, this solution provides us a face landmark map with the most important 468 landmarks that can be seen in a human’s face. Using that map we’ll calculate the ratio between some particular points in the face and with that information we’ll detect if the person on the camera blinked or not.

#python #opencv #mediapipe #computer-vision #morse code translator detect blinks — python, opencv, mediapipe #morse code translator detect blinks

Samanta  Moore

Samanta Moore


Guidelines for Java Code Reviews

Get a jump-start on your next code review session with this list.

Having another pair of eyes scan your code is always useful and helps you spot mistakes before you break production. You need not be an expert to review someone’s code. Some experience with the programming language and a review checklist should help you get started. We’ve put together a list of things you should keep in mind when you’re reviewing Java code. Read on!

1. Follow Java Code Conventions

2. Replace Imperative Code With Lambdas and Streams

3. Beware of the NullPointerException

4. Directly Assigning References From Client Code to a Field

5. Handle Exceptions With Care

#java #code quality #java tutorial #code analysis #code reviews #code review tips #code analysis tools #java tutorial for beginners #java code review

Houston  Sipes

Houston Sipes


How to Find the Stinky Parts of Your Code (Part II)

There are more code smells. Let’s keep changing the aromas. We see several symptoms and situations that make us doubt the quality of our development. Let’s look at some possible solutions.

Most of these smells are just hints of something that might be wrong. They are not rigid rules.

This is part II. Part I can be found here.

Code Smell 06 - Too Clever Programmer

The code is difficult to read, there are tricky with names without semantics. Sometimes using language’s accidental complexity.

_Image Source: NeONBRAND on _Unsplash


  • Readability
  • Maintainability
  • Code Quality
  • Premature Optimization


  1. Refactor the code
  2. Use better names


  • Optimized loops


  • Optimized code for low-level operations.

Sample Code


function primeFactors(n){
	  var f = [],  i = 0, d = 2;  

	  for (i = 0; n >= 2; ) {
	     if(n % d == 0){
	       n /= d;
	  return f;


function primeFactors(numberToFactor){
	  var factors = [], 
	      divisor = 2,
	      remainder = numberToFactor;

	    if(remainder % divisor === 0){
	       remainder = remainder/ divisor;
	  return factors;


Automatic detection is possible in some languages. Watch some warnings related to complexity, bad names, post increment variables, etc.

#pixel-face #code-smells #clean-code #stinky-code-parts #refactor-legacy-code #refactoring #stinky-code #common-code-smells