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I Coded A Trading Bot for Uniswap | Sniping Bot
#developer
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The Uniswap crypto trading bot is trending in recent times across the globe. Millions of users are getting addicted to the digital transition change happening right now in the world. The introduction of a crypto-trading bot helps entrepreneurs and investors handle the trade from buying to selling to reap more profits. Crypto-trading bots are consistent and monotonous in managing simple to complex skills, but humans cannot attain everything that is highly challenging for them. The capacity of crypto bots has gigabytes of data per second to handle the trade, whereas humans can’t process that much data within that time frame. Infinite Block Tech provides complete assistance for clients across the globe to benefit from growing their business revenue from being a part of their success.
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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., 7
, 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:
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
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Cryptocurrency trading bots have become trending in recent years as it has an enormous desire to provide an automation solution for development. The trading is done 24 x 7 significantly to attain a high exchange rate by executing the strategies in an orderly manner and placing orders quickly.
Trading bots are developed based on the preference of traders’ usage in the marketplace to trend their business. You can buy a ready-to-launch crypto trading bot from a professional development team at a minimal cost to generate high revenue for your business. It takes more time, money, and effort for someone to excel in coding and build a trading bot.
You will need to pay around to create the trading bot’s own code. If you want to test your trading bot, ensure it handles everything thrown to it and stands firm during any risk and errors.
Infinite Block Tech is a trending industry in blockchain platform with professional experience. Our experts are highly skilled in developing a valuable crypto trading bot with the market’s latest features. We have a dedicated tech support team to handle our clients’ queries to satisfy their requirements. Most happy to welcome our clients to suggest ideas for improving the build quality of your trading bot.
#crypto trading bot development #cryptocurrency trading bot #ready-to-launch crypto trading bot
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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!
NullPointerException
…
#java #code quality #java tutorial #code analysis #code reviews #code review tips #code analysis tools #java tutorial for beginners #java code review
1604088000
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.
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
Solutions
Examples
Exceptions
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