More on Web3 & Crypto
Ren & Heinrich
3 years ago
200 DeFi Projects were examined. Here is what I learned.
I analyze the top 200 DeFi crypto projects in this article.
This isn't a study. The findings benefit crypto investors.
Let’s go!
A set of data
I analyzed data from defillama.com. In my analysis, I used the top 200 DeFis by TVL in October 2022.
Total Locked Value
The chart below shows platform-specific locked value.
14 platforms had $1B+ TVL. 65 platforms have $100M-$1B TVL. The remaining 121 platforms had TVLs below $100 million, with the lowest being $23 million.
TVLs are distributed Pareto. Top 40% of DeFis account for 80% of TVLs.
Compliant Blockchains
Ethereum's blockchain leads DeFi. 96 of the examined projects offer services on Ethereum. Behind BSC, Polygon, and Avalanche.
Five platforms used 10+ blockchains. 36 between 2-10 159 used 1 blockchain.
Use Cases for DeFi
The chart below shows platform use cases. Each platform has decentralized exchanges, liquid staking, yield farming, and lending.
These use cases are DefiLlama's main platform features.
Which use case costs the most? Chart explains. Collateralized debt, liquid staking, dexes, and lending have high TVLs.
The DeFi Industry
I compared three high-TVL platforms (Maker DAO, Balancer, AAVE). The columns show monthly TVL and token price changes. The graph shows monthly Bitcoin price changes.
Each platform's market moves similarly.
Probably because most DeFi deposits are cryptocurrencies. Since individual currencies are highly correlated with Bitcoin, it's not surprising that they move in unison.
Takeaways
This analysis shows that the most common DeFi services (decentralized exchanges, liquid staking, yield farming, and lending) also have the highest average locked value.
Some projects run on one or two blockchains, while others use 15 or 20. Our analysis shows that a project's blockchain count has no correlation with its success.
It's hard to tell if certain use cases are rising. Bitcoin's price heavily affects the entire DeFi market.
TVL seems to be a good indicator of a DeFi platform's success and quality. Higher TVL platforms are cheaper. They're a better long-term investment because they gain or lose less value than DeFis with lower TVLs.
Ben
3 years ago
The Real Value of Carbon Credit (Climate Coin Investment)
Disclaimer : This is not financial advice for any investment.
TL;DR
You might not have realized it, but as we move toward net zero carbon emissions, the globe is already at war.
According to the Paris Agreement of COP26, 64% of nations have already declared net zero, and the issue of carbon reduction has already become so important for businesses that it affects their ability to survive. Furthermore, the time when carbon emission standards will be defined and controlled on an individual basis is becoming closer.
Since 2017, the market for carbon credits has experienced extraordinary expansion as a result of widespread talks about carbon credits. The carbon credit market is predicted to expand much more once net zero is implemented and carbon emission rules inevitably tighten.
Hello! Ben here from Nonce Classic. Nonce Classic has recently confirmed the tremendous growth potential of the carbon credit market in the midst of a major trend towards the global goal of net zero (carbon emissions caused by humans — carbon reduction by humans = 0 ). Moreover, we too believed that the questions and issues the carbon credit market suffered from the last 30–40yrs could be perfectly answered through crypto technology and that is why we have added a carbon credit crypto project to the Nonce Classic portfolio. There have been many teams out there that have tried to solve environmental problems through crypto but very few that have measurable experience working in the carbon credit scene. Thus we have put in our efforts to find projects that are not crypto projects created for the sake of issuing tokens but projects that pragmatically use crypto technology to combat climate change by solving problems of the current carbon credit market. In that process, we came to hear of Climate Coin, a veritable carbon credit crypto project, and us Nonce Classic as an accelerator, have begun contributing to its growth and invested in its tokens. Starting with this article, we plan to publish a series of articles explaining why the carbon credit market is bullish, why we invested in Climate Coin, and what kind of project Climate Coin is specifically. In this first article let us understand the carbon credit market and look into its growth potential! Let’s begin :)
The Unavoidable Entry of the Net Zero Era
Net zero means... Human carbon emissions are balanced by carbon reduction efforts. A non-environmentalist may find it hard to accept that net zero is attainable by 2050. Global cooperation to save the earth is happening faster than we imagine.
In the Paris Agreement of COP26, concluded in Glasgow, UK on Oct. 31, 2021, nations pledged to reduce worldwide yearly greenhouse gas emissions by more than 50% by 2030 and attain net zero by 2050. Governments throughout the world have pledged net zero at the national level and are holding each other accountable by submitting Nationally Determined Contributions (NDC) every five years to assess implementation. 127 of 198 nations have declared net zero.
Each country's 1.5-degree reduction plans have led to carbon reduction obligations for companies. In places with the strictest environmental regulations, like the EU, companies often face bankruptcy because the cost of buying carbon credits to meet their carbon allowances exceeds their operating profits. In this day and age, minimizing carbon emissions and securing carbon credits are crucial.
Recent SEC actions on climate change may increase companies' concerns about reducing emissions. The SEC required all U.S. stock market companies to disclose their annual greenhouse gas emissions and climate change impact on March 21, 2022. The SEC prepared the proposed regulation through in-depth analysis and stakeholder input since last year. Three out of four SEC members agreed that it should pass without major changes. If the regulation passes, it will affect not only US companies, but also countless companies around the world, directly or indirectly.
Even companies not listed on the U.S. stock market will be affected and, in most cases, required to disclose emissions. Companies listed on the U.S. stock market with significant greenhouse gas emissions or specific targets are subject to stricter emission standards (Scope 3) and disclosure obligations, which will magnify investigations into all related companies. Greenhouse gas emissions can be calculated three ways. Scope 1 measures carbon emissions from a company's facilities and transportation. Scope 2 measures carbon emissions from energy purchases. Scope 3 covers all indirect emissions from a company's value chains.
The SEC's proposed carbon emission disclosure mandate and regulations are one example of how carbon credit policies can cross borders and affect all parties. As such incidents will continue throughout the implementation of net zero, even companies that are not immediately obligated to disclose their carbon emissions must be prepared to respond to changes in carbon emission laws and policies.
Carbon reduction obligations will soon become individual. Individual consumption has increased dramatically with improved quality of life and convenience, despite national and corporate efforts to reduce carbon emissions. Since consumption is directly related to carbon emissions, increasing consumption increases carbon emissions. Countries around the world have agreed that to achieve net zero, carbon emissions must be reduced on an individual level. Solutions to individual carbon reduction are being actively discussed and studied under the term Personal Carbon Trading (PCT).
PCT is a system that allows individuals to trade carbon emission quotas in the form of carbon credits. Individuals who emit more carbon than their allotment can buy carbon credits from those who emit less. European cities with well-established carbon credit markets are preparing for net zero by conducting early carbon reduction prototype projects. The era of checking product labels for carbon footprints, choosing low-emissions transportation, and worrying about hot shower emissions is closer than we think.
The Market for Carbon Credits Is Expanding Fearfully
Compliance and voluntary carbon markets make up the carbon credit market.
A Compliance Market enforces carbon emission allowances for actors. Companies in industries that previously emitted a lot of carbon are included in the mandatory carbon market, and each government receives carbon credits each year. If a company's emissions are less than the assigned cap and it has extra carbon credits, it can sell them to other companies that have larger emissions and require them (Cap and Trade). The annual number of free emission permits provided to companies is designed to decline, therefore companies' desire for carbon credits will increase. The compliance market's yearly trading volume will exceed $261B in 2020, five times its 2017 level.
In the Voluntary Market, carbon reduction is voluntary and carbon credits are sold for personal reasons or to build market participants' eco-friendly reputations. Even if not in the compliance market, it is typical for a corporation to be obliged to offset its carbon emissions by acquiring voluntary carbon credits. When a company seeks government or company investment, it may be denied because it is not net zero. If a significant shareholder declares net zero, the companies below it must execute it. As the world moves toward ESG management, becoming an eco-friendly company is no longer a strategic choice to gain a competitive edge, but an important precaution to not fall behind. Due to this eco-friendly trend, the annual market volume of voluntary emission credits will approach $1B by November 2021. The voluntary credit market is anticipated to reach $5B to $50B by 2030. (TSCVM 2021 Report)
In conclusion
This article analyzed how net zero, a target promised by countries around the world to combat climate change, has brought governmental, corporate, and human changes. We discussed how these shifts will become more obvious as we approach net zero, and how the carbon credit market would increase exponentially in response. In the following piece, let's analyze the hurdles impeding the carbon credit market's growth, how the project we invested in tries to tackle these issues, and why we chose Climate Coin. Wait! Jim Skea, co-chair of the IPCC working group, said,
“It’s now or never, if we want to limit global warming to 1.5°C” — Jim Skea
Join nonceClassic’s community:
Telegram: https://t.me/non_stock
Youtube: https://www.youtube.com/channel/UCqeaLwkZbEfsX35xhnLU2VA
Twitter: @nonceclassic
Mail us : general@nonceclassic.org
Ashraful Islam
4 years ago
Clean API Call With React Hooks
| Photo by Juanjo Jaramillo on Unsplash |
Calling APIs is the most common thing to do in any modern web application. When it comes to talking with an API then most of the time we need to do a lot of repetitive things like getting data from an API call, handling the success or error case, and so on.
When calling tens of hundreds of API calls we always have to do those tedious tasks. We can handle those things efficiently by putting a higher level of abstraction over those barebone API calls, whereas in some small applications, sometimes we don’t even care.
The problem comes when we start adding new features on top of the existing features without handling the API calls in an efficient and reusable manner. In that case for all of those API calls related repetitions, we end up with a lot of repetitive code across the whole application.
In React, we have different approaches for calling an API. Nowadays mostly we use React hooks. With React hooks, it’s possible to handle API calls in a very clean and consistent way throughout the application in spite of whatever the application size is. So let’s see how we can make a clean and reusable API calling layer using React hooks for a simple web application.
I’m using a code sandbox for this blog which you can get here.
import "./styles.css";
import React, { useEffect, useState } from "react";
import axios from "axios";
export default function App() {
const [posts, setPosts] = useState(null);
const [error, setError] = useState("");
const [loading, setLoading] = useState(false);
useEffect(() => {
handlePosts();
}, []);
const handlePosts = async () => {
setLoading(true);
try {
const result = await axios.get(
"https://jsonplaceholder.typicode.com/posts"
);
setPosts(result.data);
} catch (err) {
setError(err.message || "Unexpected Error!");
} finally {
setLoading(false);
}
};
return (
<div className="App">
<div>
<h1>Posts</h1>
{loading && <p>Posts are loading!</p>}
{error && <p>{error}</p>}
<ul>
{posts?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
</div>
);
}
I know the example above isn’t the best code but at least it’s working and it’s valid code. I will try to improve that later. For now, we can just focus on the bare minimum things for calling an API.
Here, you can try to get posts data from JsonPlaceholer. Those are the most common steps we follow for calling an API like requesting data, handling loading, success, and error cases.
If we try to call another API from the same component then how that would gonna look? Let’s see.
500: Internal Server Error
Now it’s going insane! For calling two simple APIs we’ve done a lot of duplication. On a top-level view, the component is doing nothing but just making two GET requests and handling the success and error cases. For each request, it’s maintaining three states which will periodically increase later if we’ve more calls.
Let’s refactor to make the code more reusable with fewer repetitions.
Step 1: Create a Hook for the Redundant API Request Codes
Most of the repetitions we have done so far are about requesting data, handing the async things, handling errors, success, and loading states. How about encapsulating those things inside a hook?
The only unique things we are doing inside handleComments and handlePosts are calling different endpoints. The rest of the things are pretty much the same. So we can create a hook that will handle the redundant works for us and from outside we’ll let it know which API to call.
500: Internal Server Error
Here, this request function is identical to what we were doing on the handlePosts and handleComments. The only difference is, it’s calling an async function apiFunc which we will provide as a parameter with this hook. This apiFunc is the only independent thing among any of the API calls we need.
With hooks in action, let’s change our old codes in App component, like this:
500: Internal Server Error
How about the current code? Isn’t it beautiful without any repetitions and duplicate API call handling things?
Let’s continue our journey from the current code. We can make App component more elegant. Now it knows a lot of details about the underlying library for the API call. It shouldn’t know that. So, here’s the next step…
Step 2: One Component Should Take Just One Responsibility
Our App component knows too much about the API calling mechanism. Its responsibility should just request the data. How the data will be requested under the hood, it shouldn’t care about that.
We will extract the API client-related codes from the App component. Also, we will group all the API request-related codes based on the API resource. Now, this is our API client:
import axios from "axios";
const apiClient = axios.create({
// Later read this URL from an environment variable
baseURL: "https://jsonplaceholder.typicode.com"
});
export default apiClient;
All API calls for comments resource will be in the following file:
import client from "./client";
const getComments = () => client.get("/comments");
export default {
getComments
};
All API calls for posts resource are placed in the following file:
import client from "./client";
const getPosts = () => client.get("/posts");
export default {
getPosts
};
Finally, the App component looks like the following:
import "./styles.css";
import React, { useEffect } from "react";
import commentsApi from "./api/comments";
import postsApi from "./api/posts";
import useApi from "./hooks/useApi";
export default function App() {
const getPostsApi = useApi(postsApi.getPosts);
const getCommentsApi = useApi(commentsApi.getComments);
useEffect(() => {
getPostsApi.request();
getCommentsApi.request();
}, []);
return (
<div className="App">
{/* Post List */}
<div>
<h1>Posts</h1>
{getPostsApi.loading && <p>Posts are loading!</p>}
{getPostsApi.error && <p>{getPostsApi.error}</p>}
<ul>
{getPostsApi.data?.map((post) => (
<li key={post.id}>{post.title}</li>
))}
</ul>
</div>
{/* Comment List */}
<div>
<h1>Comments</h1>
{getCommentsApi.loading && <p>Comments are loading!</p>}
{getCommentsApi.error && <p>{getCommentsApi.error}</p>}
<ul>
{getCommentsApi.data?.map((comment) => (
<li key={comment.id}>{comment.name}</li>
))}
</ul>
</div>
</div>
);
}
Now it doesn’t know anything about how the APIs get called. Tomorrow if we want to change the API calling library from axios to fetch or anything else, our App component code will not get affected. We can just change the codes form client.js This is the beauty of abstraction.
Apart from the abstraction of API calls, Appcomponent isn’t right the place to show the list of the posts and comments. It’s a high-level component. It shouldn’t handle such low-level data interpolation things.
So we should move this data display-related things to another low-level component. Here I placed those directly in the App component just for the demonstration purpose and not to distract with component composition-related things.
Final Thoughts
The React library gives the flexibility for using any kind of third-party library based on the application’s needs. As it doesn’t have any predefined architecture so different teams/developers adopted different approaches to developing applications with React. There’s nothing good or bad. We choose the development practice based on our needs/choices. One thing that is there beyond any choices is writing clean and maintainable codes.
You might also like
The woman
3 years ago
The best lesson from Sundar Pichai is that success and stress don't mix.
His regular regimen teaches stress management.
In 1995, an Indian graduate visited the US. He obtained a scholarship to Stanford after graduating from IIT with a silver medal. First flight. His ticket cost a year's income. His head was full.
Pichai Sundararajan is his full name. He became Google's CEO and a world leader. Mr. Pichai transformed technology and inspired millions to dream big.
This article reveals his daily schedule.
Mornings
While many of us dread Mondays, Mr. Pichai uses the day to contemplate.
A typical Indian morning. He awakens between 6:30 and 7 a.m. He avoids working out in the mornings.
Mr. Pichai oversees the internet, but he reads a real newspaper every morning.
Pichai mentioned that he usually enjoys a quiet breakfast during which he reads the news to get a good sense of what’s happening in the world. Pichai often has an omelet for breakfast and reads while doing so. The native of Chennai, India, continues to enjoy his daily cup of tea, which he describes as being “very English.”
Pichai starts his day. BuzzFeed's Mat Honan called the CEO Banana Republic dad.
Overthinking in the morning is a bad idea. It's crucial to clear our brains and give ourselves time in the morning before we hit traffic.
Mr. Pichai's morning ritual shows how to stay calm. Wharton Business School found that those who start the day calmly tend to stay that way. It's worth doing regularly.
And he didn't forget his roots.
Afternoons
He has a busy work schedule, as you can imagine. Running one of the world's largest firm takes time, energy, and effort. He prioritizes his work. Monitoring corporate performance and guaranteeing worker efficiency.
Sundar Pichai spends 7-8 hours a day to improve Google. He's noted for changing the company's culture. He wants to boost employee job satisfaction and performance.
His work won him recognition within the company.
Pichai received a 96% approval rating from Glassdoor users in 2017.
Mr. Pichai stresses work satisfaction. Each day is a new canvas for him to find ways to enrich people's job and personal lives.
His work offers countless lessons. According to several profiles and press sources, the Google CEO is a savvy negotiator. Mr. Pichai's success came from his strong personality, work ethic, discipline, simplicity, and hard labor.
Evenings
His evenings are spent with family after a busy day. Sundar Pichai's professional and personal lives are balanced. Sundar Pichai is a night owl who re-energizes about 9 p.m.
However, he claims to be most productive after 10 p.m., and he thinks doing a lot of work at that time is really useful. But he ensures he sleeps for around 7–8 hours every day. He enjoys long walks with his dog and enjoys watching NSDR on YouTube. It helps him in relaxing and sleep better.
His regular routine teaches us what? Work wisely, not hard, discipline, vision, etc. His stress management is key. Leading one of the world's largest firm with 85,000 employees is scary.
The pressure to achieve may ruin a day. Overworked employees are more likely to make mistakes or be angry with coworkers, according to the Family Work Institute. They can't handle daily problems, making the house more stressful than the office.
Walking your dog, having fun with friends, and having hobbies are as vital as your office.
Samer Buna
2 years ago
The Errors I Committed As a Novice Programmer
Learn to identify them, make habits to avoid them
First, a clarification. This article is aimed to make new programmers aware of their mistakes, train them to detect them, and remind them to prevent them.
I learned from all these blunders. I'm glad I have coding habits to avoid them. Do too.
These mistakes are not ordered.
1) Writing code haphazardly
Writing good content is hard. It takes planning and investigation. Quality programs don't differ.
Think. Research. Plan. Write. Validate. Modify. Unfortunately, no good acronym exists. Create a habit of doing the proper quantity of these activities.
As a newbie programmer, my biggest error was writing code without thinking or researching. This works for small stand-alone apps but hurts larger ones.
Like saying anything you might regret, you should think before coding something you could regret. Coding expresses your thoughts.
When angry, count to 10 before you speak. If very angry, a hundred. — Thomas Jefferson.
My quote:
When reviewing code, count to 10 before you refactor a line. If the code does not have tests, a hundred. — Samer Buna
Programming is primarily about reviewing prior code, investigating what is needed and how it fits into the current system, and developing small, testable features. Only 10% of the process involves writing code.
Programming is not writing code. Programming need nurturing.
2) Making excessive plans prior to writing code
Yes. Planning before writing code is good, but too much of it is bad. Water poisons.
Avoid perfect plans. Programming does not have that. Find a good starting plan. Your plan will change, but it helped you structure your code for clarity. Overplanning wastes time.
Only planning small features. All-feature planning should be illegal! The Waterfall Approach is a step-by-step system. That strategy requires extensive planning. This is not planning. Most software projects fail with waterfall. Implementing anything sophisticated requires agile changes to reality.
Programming requires responsiveness. You'll add waterfall plan-unthinkable features. You will eliminate functionality for reasons you never considered in a waterfall plan. Fix bugs and adjust. Be agile.
Plan your future features, though. Do it cautiously since too little or too much planning can affect code quality, which you must risk.
3) Underestimating the Value of Good Code
Readability should be your code's exclusive goal. Unintelligible code stinks. Non-recyclable.
Never undervalue code quality. Coding communicates implementations. Coders must explicitly communicate solution implementations.
Programming quote I like:
Always code as if the guy who ends up maintaining your code will be a violent psychopath who knows where you live. — John Woods
John, great advice!
Small things matter. If your indentation and capitalization are inconsistent, you should lose your coding license.
Long queues are also simple. Readability decreases after 80 characters. To highlight an if-statement block, you might put a long condition on the same line. No. Just never exceed 80 characters.
Linting and formatting tools fix many basic issues like this. ESLint and Prettier work great together in JavaScript. Use them.
Code quality errors:
Multiple lines in a function or file. Break long code into manageable bits. My rule of thumb is that any function with more than 10 lines is excessively long.
Double-negatives. Don't.
Using double negatives is just very not not wrong
Short, generic, or type-based variable names. Name variables clearly.
There are only two hard things in Computer Science: cache invalidation and naming things. — Phil Karlton
Hard-coding primitive strings and numbers without descriptions. If your logic relies on a constant primitive string or numeric value, identify it.
Avoiding simple difficulties with sloppy shortcuts and workarounds. Avoid evasion. Take stock.
Considering lengthier code better. Shorter code is usually preferable. Only write lengthier versions if they improve code readability. For instance, don't utilize clever one-liners and nested ternary statements just to make the code shorter. In any application, removing unneeded code is better.
Measuring programming progress by lines of code is like measuring aircraft building progress by weight. — Bill Gates
Excessive conditional logic. Conditional logic is unnecessary for most tasks. Choose based on readability. Measure performance before optimizing. Avoid Yoda conditions and conditional assignments.
4) Selecting the First Approach
When I started programming, I would solve an issue and move on. I would apply my initial solution without considering its intricacies and probable shortcomings.
After questioning all the solutions, the best ones usually emerge. If you can't think of several answers, you don't grasp the problem.
Programmers do not solve problems. Find the easiest solution. The solution must work well and be easy to read, comprehend, and maintain.
There are two ways of constructing a software design. One way is to make it so simple that there are obviously no deficiencies, and the other way is to make it so complicated that there are no obvious deficiencies. — C.A.R. Hoare
5) Not Giving Up
I generally stick with the original solution even though it may not be the best. The not-quitting mentality may explain this. This mindset is helpful for most things, but not programming. Program writers should fail early and often.
If you doubt a solution, toss it and rethink the situation. No matter how much you put in that solution. GIT lets you branch off and try various solutions. Use it.
Do not be attached to code because of how much effort you put into it. Bad code needs to be discarded.
6) Avoiding Google
I've wasted time solving problems when I should have researched them first.
Unless you're employing cutting-edge technology, someone else has probably solved your problem. Google It First.
Googling may discover that what you think is an issue isn't and that you should embrace it. Do not presume you know everything needed to choose a solution. Google surprises.
But Google carefully. Newbies also copy code without knowing it. Use only code you understand, even if it solves your problem.
Never assume you know how to code creatively.
The most dangerous thought that you can have as a creative person is to think that you know what you’re doing. — Bret Victor
7) Failing to Use Encapsulation
Not about object-oriented paradigm. Encapsulation is always useful. Unencapsulated systems are difficult to maintain.
An application should only handle a feature once. One object handles that. The application's other objects should only see what's essential. Reducing application dependencies is not about secrecy. Following these guidelines lets you safely update class, object, and function internals without breaking things.
Classify logic and state concepts. Class means blueprint template. Class or Function objects are possible. It could be a Module or Package.
Self-contained tasks need methods in a logic class. Methods should accomplish one thing well. Similar classes should share method names.
As a rookie programmer, I didn't always establish a new class for a conceptual unit or recognize self-contained units. Newbie code has a Util class full of unrelated code. Another symptom of novice code is when a small change cascades and requires numerous other adjustments.
Think before adding a method or new responsibilities to a method. Time's needed. Avoid skipping or refactoring. Start right.
High Cohesion and Low Coupling involves grouping relevant code in a class and reducing class dependencies.
8) Arranging for Uncertainty
Thinking beyond your solution is appealing. Every line of code will bring up what-ifs. This is excellent for edge cases but not for foreseeable needs.
Your what-ifs must fall into one of these two categories. Write only code you need today. Avoid future planning.
Writing a feature for future use is improper. No.
Write only the code you need today for your solution. Handle edge-cases, but don't introduce edge-features.
Growth for the sake of growth is the ideology of the cancer cell. — Edward Abbey
9) Making the incorrect data structure choices
Beginner programmers often overemphasize algorithms when preparing for interviews. Good algorithms should be identified and used when needed, but memorizing them won't make you a programming genius.
However, learning your language's data structures' strengths and shortcomings will make you a better developer.
The improper data structure shouts "newbie coding" here.
Let me give you a few instances of data structures without teaching you:
Managing records with arrays instead of maps (objects).
Most data structure mistakes include using lists instead of maps to manage records. Use a map to organize a list of records.
This list of records has an identifier to look up each entry. Lists for scalar values are OK and frequently superior, especially if the focus is pushing values to the list.
Arrays and objects are the most common JavaScript list and map structures, respectively (there is also a map structure in modern JavaScript).
Lists over maps for record management often fail. I recommend always using this point, even though it only applies to huge collections. This is crucial because maps are faster than lists in looking up records by identifier.
Stackless
Simple recursive functions are often tempting when writing recursive programming. In single-threaded settings, optimizing recursive code is difficult.
Recursive function returns determine code optimization. Optimizing a recursive function that returns two or more calls to itself is harder than optimizing a single call.
Beginners overlook the alternative to recursive functions. Use Stack. Push function calls to a stack and start popping them out to traverse them back.
10) Worsening the current code
Imagine this:
Add an item to that room. You might want to store that object anywhere as it's a mess. You can finish in seconds.
Not with messy code. Do not worsen! Keep the code cleaner than when you started.
Clean the room above to place the new object. If the item is clothing, clear a route to the closet. That's proper execution.
The following bad habits frequently make code worse:
code duplication You are merely duplicating code and creating more chaos if you copy/paste a code block and then alter just the line after that. This would be equivalent to adding another chair with a lower base rather than purchasing a new chair with a height-adjustable seat in the context of the aforementioned dirty room example. Always keep abstraction in mind, and use it when appropriate.
utilizing configuration files not at all. A configuration file should contain the value you need to utilize if it may differ in certain circumstances or at different times. A configuration file should contain a value if you need to use it across numerous lines of code. Every time you add a new value to the code, simply ask yourself: "Does this value belong in a configuration file?" The most likely response is "yes."
using temporary variables and pointless conditional statements. Every if-statement represents a logic branch that should at the very least be tested twice. When avoiding conditionals doesn't compromise readability, it should be done. The main issue with this is that branch logic is being used to extend an existing function rather than creating a new function. Are you altering the code at the appropriate level, or should you go think about the issue at a higher level every time you feel you need an if-statement or a new function variable?
This code illustrates superfluous if-statements:
function isOdd(number) {
if (number % 2 === 1) {
return true;
} else {
return false;
}
}Can you spot the biggest issue with the isOdd function above?
Unnecessary if-statement. Similar code:
function isOdd(number) {
return (number % 2 === 1);
};11) Making remarks on things that are obvious
I've learnt to avoid comments. Most code comments can be renamed.
instead of:
// This function sums only odd numbers in an array
const sum = (val) => {
return val.reduce((a, b) => {
if (b % 2 === 1) { // If the current number is odd
a+=b; // Add current number to accumulator
}
return a; // The accumulator
}, 0);
};Commentless code looks like this:
const sumOddValues = (array) => {
return array.reduce((accumulator, currentNumber) => {
if (isOdd(currentNumber)) {
return accumulator + currentNumber;
}
return accumulator;
}, 0);
};Better function and argument names eliminate most comments. Remember that before commenting.
Sometimes you have to use comments to clarify the code. This is when your comments should answer WHY this code rather than WHAT it does.
Do not write a WHAT remark to clarify the code. Here are some unnecessary comments that clutter code:
// create a variable and initialize it to 0
let sum = 0;
// Loop over array
array.forEach(
// For each number in the array
(number) => {
// Add the current number to the sum variable
sum += number;
}
);Avoid that programmer. Reject that code. Remove such comments if necessary. Most importantly, teach programmers how awful these remarks are. Tell programmers who publish remarks like this that they may lose their jobs. That terrible.
12) Skipping tests
I'll simplify. If you develop code without tests because you think you're an excellent programmer, you're a rookie.
If you're not writing tests in code, you're probably testing manually. Every few lines of code in a web application will be refreshed and interacted with. Also. Manual code testing is fine. To learn how to automatically test your code, manually test it. After testing your application, return to your code editor and write code to automatically perform the same interaction the next time you add code.
Human. After each code update, you will forget to test all successful validations. Automate it!
Before writing code to fulfill validations, guess or design them. TDD is real. It improves your feature design thinking.
If you can use TDD, even partially, do so.
13) Making the assumption that if something is working, it must be right.
See this sumOddValues function. Is it flawed?
const sumOddValues = (array) => {
return array.reduce((accumulator, currentNumber) => {
if (currentNumber % 2 === 1) {
return accumulator + currentNumber;
}
return accumulator;
});
};
console.assert(
sumOddValues([1, 2, 3, 4, 5]) === 9
);Verified. Good life. Correct?
Code above is incomplete. It handles some scenarios correctly, including the assumption used, but it has many other issues. I'll list some:
#1: No empty input handling. What happens when the function is called without arguments? That results in an error revealing the function's implementation:
TypeError: Cannot read property 'reduce' of undefined.
Two main factors indicate faulty code.
Your function's users shouldn't come across implementation-related information.
The user cannot benefit from the error. Simply said, they were unable to use your function. They would be aware that they misused the function if the error was more obvious about the usage issue. You might decide to make the function throw a custom exception, for instance:
TypeError: Cannot execute function for empty list.Instead of returning an error, your method should disregard empty input and return a sum of 0. This case requires action.
Problem #2: No input validation. What happens if the function is invoked with a text, integer, or object instead of an array?
The function now throws:
sumOddValues(42);
TypeError: array.reduce is not a functionUnfortunately, array. cut's a function!
The function labels anything you call it with (42 in the example above) as array because we named the argument array. The error says 42.reduce is not a function.
See how that error confuses? An mistake like:
TypeError: 42 is not an array, dude.Edge-cases are #1 and #2. These edge-cases are typical, but you should also consider less obvious ones. Negative numbers—what happens?
sumOddValues([1, 2, 3, 4, 5, -13]) // => still 9-13's unusual. Is this the desired function behavior? Error? Should it sum negative numbers? Should it keep ignoring negative numbers? You may notice the function should have been titled sumPositiveOddNumbers.
This decision is simple. The more essential point is that if you don't write a test case to document your decision, future function maintainers won't know if you ignored negative values intentionally or accidentally.
It’s not a bug. It’s a feature. — Someone who forgot a test case
#3: Valid cases are not tested. Forget edge-cases, this function mishandles a straightforward case:
sumOddValues([2, 1, 3, 4, 5]) // => 11The 2 above was wrongly included in sum.
The solution is simple: reduce accepts a second input to initialize the accumulator. Reduce will use the first value in the collection as the accumulator if that argument is not provided, like in the code above. The sum included the test case's first even value.
This test case should have been included in the tests along with many others, such as all-even numbers, a list with 0 in it, and an empty list.
Newbie code also has rudimentary tests that disregard edge-cases.
14) Adhering to Current Law
Unless you're a lone supercoder, you'll encounter stupid code. Beginners don't identify it and assume it's decent code because it works and has been in the codebase for a while.
Worse, if the terrible code uses bad practices, the newbie may be enticed to use them elsewhere in the codebase since they learnt them from good code.
A unique condition may have pushed the developer to write faulty code. This is a nice spot for a thorough note that informs newbies about that condition and why the code is written that way.
Beginners should presume that undocumented code they don't understand is bad. Ask. Enquire. Blame it!
If the code's author is dead or can't remember it, research and understand it. Only after understanding the code can you judge its quality. Before that, presume nothing.
15) Being fixated on best practices
Best practices damage. It suggests no further research. Best practice ever. No doubts!
No best practices. Today's programming language may have good practices.
Programming best practices are now considered bad practices.
Time will reveal better methods. Focus on your strengths, not best practices.
Do not do anything because you read a quote, saw someone else do it, or heard it is a recommended practice. This contains all my article advice! Ask questions, challenge theories, know your options, and make informed decisions.
16) Being preoccupied with performance
Premature optimization is the root of all evil (or at least most of it) in programming — Donald Knuth (1974)
I think Donald Knuth's advice is still relevant today, even though programming has changed.
Do not optimize code if you cannot measure the suspected performance problem.
Optimizing before code execution is likely premature. You may possibly be wasting time optimizing.
There are obvious optimizations to consider when writing new code. You must not flood the event loop or block the call stack in Node.js. Remember this early optimization. Will this code block the call stack?
Avoid non-obvious code optimization without measurements. If done, your performance boost may cause new issues.
Stop optimizing unmeasured performance issues.
17) Missing the End-User Experience as a Goal
How can an app add a feature easily? Look at it from your perspective or in the existing User Interface. Right? Add it to the form if the feature captures user input. Add it to your nested menu of links if it adds a link to a page.
Avoid that developer. Be a professional who empathizes with customers. They imagine this feature's consumers' needs and behavior. They focus on making the feature easy to find and use, not just adding it to the software.
18) Choosing the incorrect tool for the task
Every programmer has their preferred tools. Most tools are good for one thing and bad for others.
The worst tool for screwing in a screw is a hammer. Do not use your favorite hammer on a screw. Don't use Amazon's most popular hammer on a screw.
A true beginner relies on tool popularity rather than problem fit.
You may not know the best tools for a project. You may know the best tool. However, it wouldn't rank high. You must learn your tools and be open to new ones.
Some coders shun new tools. They like their tools and don't want to learn new ones. I can relate, but it's wrong.
You can build a house slowly with basic tools or rapidly with superior tools. You must learn and use new tools.
19) Failing to recognize that data issues are caused by code issues
Programs commonly manage data. The software will add, delete, and change records.
Even the simplest programming errors can make data unpredictable. Especially if the same defective application validates all data.
Code-data relationships may be confusing for beginners. They may employ broken code in production since feature X is not critical. Buggy coding may cause hidden data integrity issues.
Worse, deploying code that corrected flaws without fixing minor data problems caused by these defects will only collect more data problems that take the situation into the unrecoverable-level category.
How do you avoid these issues? Simply employ numerous data integrity validation levels. Use several interfaces. Front-end, back-end, network, and database validations. If not, apply database constraints.
Use all database constraints when adding columns and tables:
If a column has a NOT NULL constraint, null values will be rejected for that column. If your application expects that field has a value, your database should designate its source as not null.
If a column has a UNIQUE constraint, the entire table cannot include duplicate values for that column. This is ideal for a username or email field on a Users table, for instance.
For the data to be accepted, a CHECK constraint, or custom expression, must evaluate to true. For instance, you can apply a check constraint to ensure that the values of a normal % column must fall within the range of 0 and 100.
With a PRIMARY KEY constraint, the values of the columns must be both distinct and not null. This one is presumably what you're utilizing. To distinguish the records in each table, the database needs have a primary key.
A FOREIGN KEY constraint requires that the values in one database column, typically a primary key, match those in another table column.
Transaction apathy is another data integrity issue for newbies. If numerous actions affect the same data source and depend on each other, they must be wrapped in a transaction that can be rolled back if one fails.
20) Reinventing the Wheel
Tricky. Some programming wheels need reinvention. Programming is undefined. New requirements and changes happen faster than any team can handle.
Instead of modifying the wheel we all adore, maybe we should rethink it if you need a wheel that spins at varied speeds depending on the time of day. If you don't require a non-standard wheel, don't reinvent it. Use the darn wheel.
Wheel brands can be hard to choose from. Research and test before buying! Most software wheels are free and transparent. Internal design quality lets you evaluate coding wheels. Try open-source wheels. Debug and fix open-source software simply. They're easily replaceable. In-house support is also easy.
If you need a wheel, don't buy a new automobile and put your maintained car on top. Do not include a library to use a few functions. Lodash in JavaScript is the finest example. Import shuffle to shuffle an array. Don't import lodash.
21) Adopting the incorrect perspective on code reviews
Beginners often see code reviews as criticism. Dislike them. Not appreciated. Even fear them.
Incorrect. If so, modify your mindset immediately. Learn from every code review. Salute them. Observe. Most crucial, thank reviewers who teach you.
Always learning code. Accept it. Most code reviews teach something new. Use these for learning.
You may need to correct the reviewer. If your code didn't make that evident, it may need to be changed. If you must teach your reviewer, remember that teaching is one of the most enjoyable things a programmer can do.
22) Not Using Source Control
Newbies often underestimate Git's capabilities.
Source control is more than sharing your modifications. It's much bigger. Clear history is source control. The history of coding will assist address complex problems. Commit messages matter. They are another way to communicate your implementations, and utilizing them with modest commits helps future maintainers understand how the code got where it is.
Commit early and often with present-tense verbs. Summarize your messages but be detailed. If you need more than a few lines, your commit is too long. Rebase!
Avoid needless commit messages. Commit summaries should not list new, changed, or deleted files. Git commands can display that list from the commit object. The summary message would be noise. I think a big commit has many summaries per file altered.
Source control involves discoverability. You can discover the commit that introduced a function and see its context if you doubt its need or design. Commits can even pinpoint which code caused a bug. Git has a binary search within commits (bisect) to find the bug-causing commit.
Source control can be used before commits to great effect. Staging changes, patching selectively, resetting, stashing, editing, applying, diffing, reversing, and others enrich your coding flow. Know, use, and enjoy them.
I consider a Git rookie someone who knows less functionalities.
23) Excessive Use of Shared State
Again, this is not about functional programming vs. other paradigms. That's another article.
Shared state is problematic and should be avoided if feasible. If not, use shared state as little as possible.
As a new programmer, I didn't know that all variables represent shared states. All variables in the same scope can change its data. Global scope reduces shared state span. Keep new states in limited scopes and avoid upward leakage.
When numerous resources modify common state in the same event loop tick, the situation becomes severe (in event-loop-based environments). Races happen.
This shared state race condition problem may encourage a rookie to utilize a timer, especially if they have a data lock issue. Red flag. No. Never accept it.
24) Adopting the Wrong Mentality Toward Errors
Errors are good. Progress. They indicate a simple way to improve.
Expert programmers enjoy errors. Newbies detest them.
If these lovely red error warnings irritate you, modify your mindset. Consider them helpers. Handle them. Use them to advance.
Some errors need exceptions. Plan for user-defined exceptions. Ignore some mistakes. Crash and exit the app.
25) Ignoring rest periods
Humans require mental breaks. Take breaks. In the zone, you'll forget breaks. Another symptom of beginners. No compromises. Make breaks mandatory in your process. Take frequent pauses. Take a little walk to plan your next move. Reread the code.
This has been a long post. You deserve a break.
Bloomberg
3 years ago
Expulsion of ten million Ukrainians
According to recent data from two UN agencies, ten million Ukrainians have been displaced.
The International Organization for Migration (IOM) estimates nearly 6.5 million Ukrainians have relocated. Most have fled the war zones around Kyiv and eastern Ukraine, including Dnipro, Zhaporizhzhia, and Kharkiv. Most IDPs have fled to western and central Ukraine.
Since Russia invaded on Feb. 24, 3.6 million people have crossed the border to seek refuge in neighboring countries, according to the latest UN data. While most refugees have fled to Poland and Romania, many have entered Russia.
Internally displaced figures are IOM estimates as of March 19, based on 2,000 telephone interviews with Ukrainians aged 18 and older conducted between March 9-16. The UNHCR compiled the figures for refugees to neighboring countries on March 21 based on official border crossing data and its own estimates. The UNHCR's top-line total is lower than the country totals because Romania and Moldova totals include people crossing between the two countries.
Sources: IOM, UNHCR
According to IOM estimates based on telephone interviews with a representative sample of internally displaced Ukrainians, over 53% of those displaced are women, and over 60% of displaced households have children.