Earning money by using your coding or programming skills is not that hard nowadays. In this video I will discuss 7 ways you can earn pretty good amount of money by doing coding or programming. Below is the topic list along with the timeline,
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johnnythecoder has been nominated for the Hacker Noon Contributor of the Year - LEARNING award!
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.
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Code Golf is a game that is designed to let programmers show off their excellency in codes by solving problems in the least number of characters. The word “Golf” in code golfing refers to the popular game golf where two players compete with each other, and the one with the fewest club strokes wins.
Similar to the golf game, code golf is a competition where the winner achieves the specifications in the fewest keystrokes. It is basically a kind of recreational computer programming competition where the participants compete to achieve the shortest possible source code that implements a certain algorithm.
Code Golfing can be said as a classic playground for programmers where the main attempt is to solve a problem with the least number of characters. It is written in Go language, licensed under MIT and is available on GitHub.
Below here, we listed general tips of Code Golf that are implemented in popular languages like
Python and others.
Original- if a<b:return a
**Code Golf- **return(b,a)[a<b]
Original- if a > 1 and b > 1 and 3 > a and 5 > b: foo()
Code Golf- if 3 > a > 1 < b < 5: foo()
Original- while foo(a):
**Code Golf- *while foo(a):print a;a=2
**Code Golf- **A+=B,
**Original- **from math import ceil
n = 3/2
Code Golf- n = 3/2
The score of your solution is the count of the Unicode characters in your source code. This means both “A” (U+0041 Latin Capital Letter A) and “” (U+1F609 Winking Face) cost the same despite the 1:4 ratio in byte count in UTF-8.
For each hole, the shortest solution is awarded 1,000 points, with the points decreasing in uniform decrements per rank. Your overall score is simply the sum of your points in each hole. Also, the execution time is limited to 5 seconds.
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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.”
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.
Before a computer can finally “understand” and execute a piece of code, it goes through a series of complicated transformations:
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.,
Bob, 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:
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.)
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While there are many ways you can make money with Bitcoin in the end there are no free meals. Earning Bitcoins online take time and money and most methods promising free Bitcoins will not be worth the time wasted on them.
Here are the different methods I cover in this video:
0:18 - Intro
1:21- Micro earnings
2:25 - Owning a Bitcoin faucet
3:11 - Signature campaigns
4:18 - Bitcoin trading
5:16 - Bitcoin affiliate programs
6:32 - Gambling (very high risk)
7:20 - Crypto blogging
8:26 - Offering crypto services
8:46 - Bitcoin mining
10:20 - Bitcoin lending platforms
11:14 - Coin doublers and HYIPs (avoid)
12:22 - Conclusion + flowchart
📺 The video in this post was made by 99Bitcoins
The origin of the article: https://www.youtube.com/watch?v=EoG482doRv0
🔺 DISCLAIMER: The article is for information sharing. The content of this video is solely the opinions of the speaker who is not a licensed financial advisor or registered investment advisor. Not investment advice or legal advice.
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