We Created a Local Free Coding School Using the freeCodeCamp Curriculum.

While this picture shows an in-person classroom, we have moved our school fully remote as a result of the COVID-19 situation.

If you want to learn how to code, there are generally three options to choose from:

  1. You can teach yourself and find your own curriculum.
  2. Go to college and get a computer science/IT degree.
  3. Or attend a coding school. Coding schools are hands-on crash courses that are designed to get you up to speed quickly so you can find your first software development job within three months to one year.

Option number one is the cheapest, but also the most frustrating and difficult. It’s so easy to get stuck along the way and want to give up.

Options two and three could work out well, if you can afford to take time off work (or at least work fewer hours), pay the tuition plus living expenses while you are attending and looking for a job, and still be able to manage your family and personal life. Not everyone is able to do that.

This is why we created freeCodeSchool Indy. It’s a free coding program based off of the freeCodeCamp curriculum where we guide students through part-time coding school programs for three months.

We have two two-hour classes per week - Monday and Wednesday from 6-8 pm, where we teach them everything from HTML basics to JavaScript and Intro to React.

The students are expected to spend at least 6 hours per week studying on their own, and can optionally attend office hours on Sundays that we hold from 1-5 pm. If they complete the first three months, then they are able to attend a second three month program, where they can learn about back-end web development in Node.js.

We started working on this idea over a year ago and it’s exciting to be able to say that we completed our first cohort in May. Now we can share what we have learned in this article.

#freecodecamp #curriculum #learned #machine learning

What is GEEK

Buddha Community

We Created a Local Free Coding School Using the freeCodeCamp Curriculum.

We Created a Local Free Coding School Using the freeCodeCamp Curriculum.

While this picture shows an in-person classroom, we have moved our school fully remote as a result of the COVID-19 situation.

If you want to learn how to code, there are generally three options to choose from:

  1. You can teach yourself and find your own curriculum.
  2. Go to college and get a computer science/IT degree.
  3. Or attend a coding school. Coding schools are hands-on crash courses that are designed to get you up to speed quickly so you can find your first software development job within three months to one year.

Option number one is the cheapest, but also the most frustrating and difficult. It’s so easy to get stuck along the way and want to give up.

Options two and three could work out well, if you can afford to take time off work (or at least work fewer hours), pay the tuition plus living expenses while you are attending and looking for a job, and still be able to manage your family and personal life. Not everyone is able to do that.

This is why we created freeCodeSchool Indy. It’s a free coding program based off of the freeCodeCamp curriculum where we guide students through part-time coding school programs for three months.

We have two two-hour classes per week - Monday and Wednesday from 6-8 pm, where we teach them everything from HTML basics to JavaScript and Intro to React.

The students are expected to spend at least 6 hours per week studying on their own, and can optionally attend office hours on Sundays that we hold from 1-5 pm. If they complete the first three months, then they are able to attend a second three month program, where they can learn about back-end web development in Node.js.

We started working on this idea over a year ago and it’s exciting to be able to say that we completed our first cohort in May. Now we can share what we have learned in this article.

#freecodecamp #curriculum #learned #machine learning

Tyrique  Littel

Tyrique Littel

1604008800

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

Outline

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:

Scanning

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:

Python

1

import io

2

import tokenize

3

4

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

5

6

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

7

    print(token)

Python

1

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

2

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

3

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

4

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

5

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

6

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

7

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

8

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

9

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

13 Free/Low-Cost Sites to Supercharge Your Programming Self-Education

Noonies 2020 award nominee

johnnythecoder has been nominated for the Hacker Noon Contributor of the Year - LEARNING award!

** Add your vote**

Although we still talk about programming as a standalone career, the dominance of technology in our lives makes it clear that coding is much more than a career path. In my opinion, computer science is more than a college major or a high-paid job; it’s a skill, essential for thriving in a modern-day economy.

Whether you work in healthcare, marketing, business, or other fields, you will see more coding and have to deal with a growing number of technologies throughout your entire life.

Now that we live in a tech-driven world, asking “Should I learn to program” is almost synonymous with “Should I learn to speak, read, or count?”

The short answer is: yes.

How to start your journey in coding? The good news is there are plenty of resources to support you all the way through. To save you the trouble of looking them up and choosing the right ones, I created my list of learning platforms that offer well-rounded programming education and help you stay competitive on the job market.

Here are 12+ useful educational resources every coding student should check out.

1. Codegym

#learning-to-code #learn-to-code #coding #programming #programming-languages #free-programming-sites #self-improvement #learn-to-code-free-online

Samanta  Moore

Samanta Moore

1621137960

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

1604088000

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

Problems

  • Readability
  • Maintainability
  • Code Quality
  • Premature Optimization

Solutions

  1. Refactor the code
  2. Use better names

Examples

  • Optimized loops

Exceptions

  • Optimized code for low-level operations.

Sample Code

Wrong

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

	  for (i = 0; n >= 2; ) {
	     if(n % d == 0){
	       f[i++]=(d); 
	       n /= d;
	    }
	    else{
	      d++;
	    }     
	  }
	  return f;
	}

Right

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

	  while(remainder>=2){
	    if(remainder % divisor === 0){
	       factors.push(divisor); 
	       remainder = remainder/ divisor;
	    }
	    else{
	      divisor++;
	    }     
	  }
	  return factors;
	}

Detection

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