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You can pay a tiny amount for the tablet now and receive a bigger discount. The OnePlus Pad Go is an affordable tablet that was released in some markets...

OnePlus Pad Go lands in Europe on April 23 alongside new OnePlus Watch 2 version - GSMArena.com news

It&#x27;s rumored to launch in H2 2024. Last week, tipster Max Jambor claimed the OnePlus Pad 2 will be launched in the second half of 2024, which, he now says,...

OnePlus Pad 2's processor tipped - GSMArena.com news

MOBILES &amp; TABLETS News: OnePlus introducing the 8GB RAM Solar Red OnePlus 11R in India with Rs 1250 instant discount on Amazon. This model offers a 6.74-inch AMOLED display,

OnePlus 11R Solar Red colour Variant with 8GB RAM to launch in India on April 18: All details - Times of India

OnePlus 11, the flagship phone from OnePlus in 2023, has received a price cut. OnePlus 11 a better phone than the OnePlus 12R.

OnePlus 11 5G Gets a Price Cut in India

South Indian Organised Retailers Association (ORA), in its April 10 letter to OnePlus India’s director of sales, Ranjeet Singh, threatened to discontinue the sale the brand’s products in 4,500 stores across Southern and Western states

OnePlus reacts to Indian retailers' boycott threat, says working to resolve issues

Check out a detailed camera comparison of the Rs 24,999-worth OnePlus Nord CE4 and Rs 23,999-worth Rs OPPO F25 Pro.

OnePlus Nord CE4 vs OPPO F25 Pro camera comparison

On our first set of data structures, we get into the definition and scope of non-primitive structures. Have a look at the previous read on in case you feel a little lost. Right off the batt, we define what it means to be a non-primitive set, and how this can be further broken down. The Power of Data structures Let's get right into it. A non-primitive structure is what happens when you combine two or more primitives. What we mean is simple. A and , for instance,  are primitives. The simplest representations of data. char int Broadly speaking, linear non-primitives can be grouped further as below: Linear Non-Primitives Stacks Queues Linked lists Arrays Here, as stated before, data is sequential - one after another. Some of these structures might , stackify, is that you?. ring a bell Arrays These are what we call stores of homogeneous (meaning similar) data. So one might have an array like this: my_array = [ , , , , , , , , ] ;

vowels = [ , , , , ] ; 1 2 3 4 5 6 7 8 9 ' a' 'e' 'i' 'o' 'u' Note how has only integers while has . In both instances, our array has a collection of primitives - . my_array vowels char one type of primitive per array Arrays are of a fixed size. Once declared, the computer knows the amount of memory reserved for items to be stored there.  You might ask: "But what if the type of data I have changes in size greater than the array?" Well, you might need to consider a different type of structure to store this data. Use arrays, for instance, to store months of the year. We will not be changing this count anytime. Above declared, the sizes of the arrays are inferred. Meaning the types, since not defined per se, are  'figured out' based on the values and how we use them. We might as well have this: For python. array

count_down = array.array( , [ , , , , ]) import 'i' 5 4 3 2 1 # where *i* stands for int (an array of integers). Types may go on as: for c char for f float for d double for and so forth. u Unicode Have a look at the for more insight into this. As well, take note that the has different functions to enable array manipulation. documentation array module Rust: count_down: [ ; ] = [ , , , , ]; let i32 5 5 4 3 2 1 // where *i32* is signed integers, and *5* in *[i32; 5]* is the size of the array. i.e have five integers Important pointer: Python lists and arrays are not the same! Operations on an array will be based on the of the array element, with indexing starting from . Hence, the first item, in either case, would be: index 0 count_down [0] The result from the above is 5 (the semi-colon has been left out for brevity but should be used based on the language you are using). Let's take a look at another structure that looks similar, but is not the same - Linked lists. Linked lists Unlike arrays, linked lists store data in a non-contiguous form. This implies one piece of data is not placed side by side to the other as: `[1,2,3,4,5]`, rather it is stored in form of nodes with pointers to the next as so: [data1, pointer_to_data2] ...  [data1, pointer_to_data3] ... so and on The last item in our linked list, since there is no pointer to the next, would have . null As well, linked lists are dynamic-  their size is not fixed at initialization. Linked lists will be further broken to: a) Singular linked lists (used in the elaboration of linked lists above) b) Circular linked lists c) Doubly linked lists Circular Linked Lists These have three items in a node: the previous data, the data, and finally, the next data in the sequence. ... [null, data1, pointer_to_data2] [pointer_to_data_1 ,data1, pointer_to_data3] The first item (the head), has a as the previous pointer while the last node has on the next pointer. null null Doubly linked lists Similar to circular linked lists, these have two pointers as well. The only difference would be the last node, instead of a , has a pointer back to the first item in the list. 1 + 1 = circular. null In most of what we implement through code, we have implementations of linked lists. You will hardly get yourself doing this manually, but understanding that some of the things we call 'mutable arrays ' are actually implementations or wrappers around more complex structures. Example: If navigating through my directory, my computer needs to know where I am, where I'm from, and possibly have the correct link/structure to the nested directory I'm navigating to. So to the top-level directory, I cannot go any higher, no previous node. Likewise to the last directory or file, there is no 'next' option. Till now, we have come to understand the importance of data structures, the groups they have been placed into, and we have an idea of what some of the linear data structures involved. We could go on and on on the details of each, but that is a tale for another day. A breather for us both at this point.  Go read something non-algorithm-like for a moment. We'll still meet here, same time, the same drive. Previously published at: https://thegreencodes.com/data-structures-the-linear-non-primitives

Representations of Data: One Primitive Plus One Primitive Equals Linear Non-Primitives

Analysts often encounter outliers in data during their work, such as during AB-test analysis, creating predictive models, or tracking trends. Decisions are usually based on the sample mean, which is very sensitive to outliers and can dramatically change the value. So, it is crucial to manage outliers to make the correct decision. Let's consider several simple and fast approaches for working with unusual values. Problem Formulation Imagine that you need to conduct an experiment analysis using an average order value as a primary metric. Let's say that our metric usually has a normal distribution. Also, we know that the metric distribution in the test group is different from that in the control. In other words, the mean of the distribution in control is 10, and in the test is 12. The standard deviation in both groups is 3. However, both samples have outliers that skew the sample means and the sample standard deviation. import numpy as np

N = 1000

mean_1 = 10
std_1 = 3

mean_2 = 12
std_2 = 3

x1 = np.concatenate((np.random.normal(mean_1, std_1, N), 10 * np.random.random_sample(50) + 20))
x2 = np.concatenate((np.random.normal(mean_2, std_2, N), 4 * np.random.random_sample(50) + 1)) NB that considering metric could have outliers from both sides. If your metric could have outliers only from one side, methods could easily be transformed for that purpose. Cut Off Tails The easiest method is to cut off all observations before the 5% percentile and after the 95% percentile. In this case, we lost 10% of the information as a con. However, the distributions look more formed, and the sample moments are nearer to the distribution moments. import numpy as np

x1_5pct = np.percentile(x1, 5)
x1_95pct = np.percentile(x1, 95)
x1_cutted = [i for i in x1 if i > x1_5pct and i < x1_95pct]

x2_5pct = np.percentile(x2, 5)
x2_95pct = np.percentile(x2, 95)
x2_cutted = [i for i in x2 if i > x2_5pct and i < x2_95pct] Another way is to exclude observations outside the specific range. The low band equals the 25% percentile minus one-half of the interquartile range, and the high band equals the 75% percentile plus one-half. Here, we will lose only 0.7% of information. The distributions look more formed than the initial. The sample moments are even more equal to the distribution moments. import numpy as np

low_band_1 = np.percentile(x1, 25) - 1.5 * np.std(x1)
high_band_1 = np.percentile(x1, 75) + 1.5 * np.std(x1)
x1_cutted = [i for i in x1 if i > low_band_1 and i < high_band_1]

low_band_2 = np.percentile(x2, 25) - 1.5 * np.std(x2)
high_band_2 = np.percentile(x2, 75) + 1.5 * np.std(x2)
x2_cutted = [i for i in x2 if i > low_band_2 and i < high_band_2] Bootstrap The second method we considered here is a bootstrap. In this approach, the mean is constructed like a mean of subsamples. In our example, the mean in the control group equals 10.35, and the test group is 11.78. It is still a better result compared to additional data processing. import pandas as pd

def create_bootstrap_samples(
    sample_list: np.array,
    sample_size: int, 
    n_samples: int
    ):
    
    # create a list for sample means
    sample_means = []
    
    # loop n_samples times
    for i in range(n_samples):
        
        # create a bootstrap sample of sample_size with replacement
        bootstrap_sample = pd.Series(sample_list).sample(n = sample_size, replace = True)
        
        # calculate the bootstrap sample mean
        sample_mean = bootstrap_sample.mean()
        
        # add this sample mean to the sample means list
        sample_means.append(sample_mean)
    
    return pd.Series(sample_means)

(create_bootstrap_samples(x1, len(x1), 1000).mean(), create_bootstrap_samples(x2, len(x2), 1000).mean()) Conclusion Outlier detection and processing are significant for making the right decision. Now, at least three fast and straightforward approaches could help you check the data before analysis. However, it is essential to remember that detected outliers could be unusual values and a feature for the novelty effect. But it is another story :) Analysts often encounter outliers in data during their work, such as during AB-test analysis, creating predictive models, or tracking trends. Decisions are usually based on the sample mean, which is very sensitive to outliers and can dramatically change the value. So, it is crucial to manage outliers to make the correct decision. Let's consider several simple and fast approaches for working with unusual values. Problem Formulation Imagine that you need to conduct an experiment analysis using an average order value as a primary metric. Let's say that our metric usually has a normal distribution. Also, we know that the metric distribution in the test group is different from that in the control. In other words, the mean of the distribution in control is 10, and in the test is 12. The standard deviation in both groups is 3. However, both samples have outliers that skew the sample means and the sample standard deviation. import numpy as np

N = 1000

mean_1 = 10
std_1 = 3

mean_2 = 12
std_2 = 3

x1 = np.concatenate((np.random.normal(mean_1, std_1, N), 10 * np.random.random_sample(50) + 20))
x2 = np.concatenate((np.random.normal(mean_2, std_2, N), 4 * np.random.random_sample(50) + 1)) import numpy as np

N = 1000

mean_1 = 10
std_1 = 3

mean_2 = 12
std_2 = 3

x1 = np.concatenate((np.random.normal(mean_1, std_1, N), 10 * np.random.random_sample(50) + 20))
x2 = np.concatenate((np.random.normal(mean_2, std_2, N), 4 * np.random.random_sample(50) + 1)) NB that considering metric could have outliers from both sides. If your metric could have outliers only from one side, methods could easily be transformed for that purpose. NB Cut Off Tails The easiest method is to cut off all observations before the 5% percentile and after the 95% percentile . In this case, we lost 10% of the information as a con. However, the distributions look more formed, and the sample moments are nearer to the distribution moments. before the 5% percentile after the 95% percentile import numpy as np

x1_5pct = np.percentile(x1, 5)
x1_95pct = np.percentile(x1, 95)
x1_cutted = [i for i in x1 if i > x1_5pct and i < x1_95pct]

x2_5pct = np.percentile(x2, 5)
x2_95pct = np.percentile(x2, 95)
x2_cutted = [i for i in x2 if i > x2_5pct and i < x2_95pct] import numpy as np

x1_5pct = np.percentile(x1, 5)
x1_95pct = np.percentile(x1, 95)
x1_cutted = [i for i in x1 if i > x1_5pct and i < x1_95pct]

x2_5pct = np.percentile(x2, 5)
x2_95pct = np.percentile(x2, 95)
x2_cutted = [i for i in x2 if i > x2_5pct and i < x2_95pct] Another way is to exclude observations outside the specific range . The low band equals the 25% percentile minus one-half of the interquartile range, and the high band equals the 75% percentile plus one-half. Here, we will lose only 0.7% of information. The distributions look more formed than the initial. The sample moments are even more equal to the distribution moments. outside the specific range import numpy as np

low_band_1 = np.percentile(x1, 25) - 1.5 * np.std(x1)
high_band_1 = np.percentile(x1, 75) + 1.5 * np.std(x1)
x1_cutted = [i for i in x1 if i > low_band_1 and i < high_band_1]

low_band_2 = np.percentile(x2, 25) - 1.5 * np.std(x2)
high_band_2 = np.percentile(x2, 75) + 1.5 * np.std(x2)
x2_cutted = [i for i in x2 if i > low_band_2 and i < high_band_2] import numpy as np

low_band_1 = np.percentile(x1, 25) - 1.5 * np.std(x1)
high_band_1 = np.percentile(x1, 75) + 1.5 * np.std(x1)
x1_cutted = [i for i in x1 if i > low_band_1 and i < high_band_1]

low_band_2 = np.percentile(x2, 25) - 1.5 * np.std(x2)
high_band_2 = np.percentile(x2, 75) + 1.5 * np.std(x2)
x2_cutted = [i for i in x2 if i > low_band_2 and i < high_band_2] Bootstrap The second method we considered here is a bootstrap. In this approach, the mean is constructed like a mean of subsamples. In our example, the mean in the control group equals 10.35, and the test group is 11.78. It is still a better result compared to additional data processing. import pandas as pd

def create_bootstrap_samples(
    sample_list: np.array,
    sample_size: int, 
    n_samples: int
    ):
    
    # create a list for sample means
    sample_means = []
    
    # loop n_samples times
    for i in range(n_samples):
        
        # create a bootstrap sample of sample_size with replacement
        bootstrap_sample = pd.Series(sample_list).sample(n = sample_size, replace = True)
        
        # calculate the bootstrap sample mean
        sample_mean = bootstrap_sample.mean()
        
        # add this sample mean to the sample means list
        sample_means.append(sample_mean)
    
    return pd.Series(sample_means)

(create_bootstrap_samples(x1, len(x1), 1000).mean(), create_bootstrap_samples(x2, len(x2), 1000).mean()) import pandas as pd

def create_bootstrap_samples(
    sample_list: np.array,
    sample_size: int, 
    n_samples: int
    ):
    
    # create a list for sample means
    sample_means = []
    
    # loop n_samples times
    for i in range(n_samples):
        
        # create a bootstrap sample of sample_size with replacement
        bootstrap_sample = pd.Series(sample_list).sample(n = sample_size, replace = True)
        
        # calculate the bootstrap sample mean
        sample_mean = bootstrap_sample.mean()
        
        # add this sample mean to the sample means list
        sample_means.append(sample_mean)
    
    return pd.Series(sample_means)

(create_bootstrap_samples(x1, len(x1), 1000).mean(), create_bootstrap_samples(x2, len(x2), 1000).mean()) Conclusion Outlier detection and processing are significant for making the right decision. Now, at least three fast and straightforward approaches could help you check the data before analysis. However, it is essential to remember that detected outliers could be unusual values and a feature for the novelty effect. But it is another story :)

Outlier Detection: What You Need to Know

Hi everyone, my name is Max Nechaev. I'm an iOS developer and a startup founder. Over the last six months I've traveled a really interesting path, which is full of complexity, uncertainty, trial, error, and fan. We've all thought about our own business at some point. What if you don't work for someone else? What if you could try starting something of your own? Would I be able to do it? I run into these questions quite often. But what's the reasoning here? The point is that if you put your fears aside and try to answer this question as truthfully as possible, you most likely won't be able to give a clear and concise answer. This is where we run into that winged phrase "You won't know until you try". It was after this realization that a seed settled in my mind that sprouted and gave me more and more food for thought each day and each week. Eventually, I realized that I was going to try and create my startup in the IT industry. Market preparation and analysis The first thing that was important to me was mental preparation. I read books on management and business. I spent a lot of time watching videos on different niches, analyzing entrepreneurs and their strategic decisions. Before starting work on any project, it is very important to be ready for it from the inside, not just "think of something and do it". YouTube Second, analyze the market. You can't just take and make any application, because the market is big, there are prevalent trends, there are leaders and outsiders, there are money niches, and there are niches where there is no money in general, no matter how much marketing budgets you pour into it. There are plenty of niche analytics sites out there, at first I used . It helps us in finding apps in different niches in different countries. Moreover, you can see who is earning how much (the only issue I have is that it doesn't show how much someone spends on marketing, so you won't see the real net profit). SensorTower In this article, I would like to share the steps we have taken, not a specific case study, so I will not go into the details of the research. We are not a million-dollar company yet, so there are no working cases yet, but those who are interested in this topic will find a lot of useful tips here. So I will say this. We've settled on a niche of apps that help content creators and SMM specialists. Team building "One man can't fight alone." I keep bombarding you with catchphrases. But in the 21st century, this is the purest truth. I am not used to hearing "success stories" about how some programmer from the village did something and became a millionaire. Because even if there are such cases, it is rather an exception to the rule. It is very important not to fall into the "survivor's syndrome". Don't get me wrong, every good developer can write his first alone. But only if we are talking about real commercial success, multiple financial growth, and high productivity, we are talking about a team. MVP In the first stages, we don't need a big office and several development departments. We need to cover several areas: frontend, backend, design, marketing. You don't necessarily need 4 people, because, often, many mobile apps don't need a backend, plus one person can fulfill multiple roles. I'm lucky here, I have a background as a marketer. I understand how metrics work, ad rooms, what creatives are, what they should look like, and what it takes to get the whole thing up and running. I'm not saying I'm the best at it, but this level is enough for the first stages of a startup's life. So I've been doing iOS development and marketing for the project. Going through a cool school from I realized that a co-founder is needed. A person who will share my values and move in the same direction as me. Startups with co-founders are many times more likely to succeed than those with a single founder. This is shown by the statistics that the folks at have compiled. If you're interested in specific numbers, I encourage everyone to go to their school. Y Combinator Y Combinator My co-founder (surprise surprise) is a backend developer. This means in addition to some business decisions, he'll be able to take on that role as well. This will greatly simplify iOS development (because most of the logic will be put on the backend). And of course, it will increase our speed a lot. We are both senior developers, which means that we will be able to think through everything competently and do it optimally with minimal financial and time investments. There is one last role left uncovered. UX/UI Designer. Because of where I am in the IT industry, I have a lot of talented people around me. So to be honest, I found the designer even earlier than the co-founder. She will also get a share of ownership of the startup and the head designer position when the staff grows. So together we are covering all the initial needs. With a team like this, we can make neither one nor two apps. Maybe we will expand our team and take new people. For now, we plan to take only some temporary outsourcing for adequate money (if necessary). From the start, we build in processes. Set goals and objectives. We make development boards, put up milestones, and spread everything out by dates. We calculate the economics of projects, plan investments, how much, and at what stages. In general, operational activities are also starting to go full speed. Design development At this stage, we have started on the application’s UI. Our goal is style, usability, and beauty from the user's point of view. We have thoroughly analyzed the competitors and identified the weaknesses of each. After that, by improving their apps we create our own. As part of the design, I also laid out a set of objectives. The designer has deadlines for working out each screen. She has a description of the functionality. The goals of the app and the problem it solves. We average 4-5 days of work (not full-time) per screen. Again, some people will find it too long, and some will find it too fast, but at this stage, it works and we are satisfied with it. We work out the entire design in . All task descriptions, boards, and project descriptions are in . Figma Notion Our application allows users to create and generate text content for social networks. That's why we developed the most simple and understandable design, which will completely cover the problem with writing posts, scripts, their organization, etc. Application Architecture Now I'm not talking about the architecture of the iOS part, but mostly about the architecture in general. I'll be honest, initially, the app was made only for the iOS platform and stores everything locally. I didn't intend to add a backend, but later on, I reconsidered my decision. For this purpose, I had to rewrite parts of the functionality. At the same time, it was an important note not to break the existing one. So, it turns out that we are making a full-fledged client-server application, so everything becomes clearer with the architecture. We have a "service" that is responsible for user registration and authorization, it simplifies the work of the iOS application because you just need to send a couple of requests to the backend and the "magic" begins. For the next step, we needed to pull up the database. That's where we will store users, their IDs, data, and content. Separate from that, we need to create a service for working with the database. Because the application should synchronize well with it every time the user opens the application. Yes, yes, you heard right. For now, we are running with somewhat limited functionality of full synchronization, as we don't need it that much. The main point of creating a backend and pulling user-generated content there is to preserve progress. No one wants to delete an app or change phones and lose all their data and all their content. So at this stage, it's still the goal to preserve, not to make seamless instant synchronization for cross-platforming. This is where I'd like to bring up the topic of "optimality". Often, aspiring startups (like us) make a huge mistake of trying to make the perfect product. They spend a huge amount of time (and some even financial resources) to make an ideal product to beat everyone else in the market. But the truth is, it's likely that they'll never make it to release. With limited resources, the word "perfect" is inapplicable. Even the first versions of were pretty ridiculous (not to mention ). I, on the other hand, am a stickler for the word "optimality". It's much more important and more succinct. Instead of making the perfect product, the perfect design, the perfect architecture, and the perfect servers that can handle colossal loads, I will make an optimal solution. It will work fine. NORMAL. And no more. I can refine everything else gradually, as long as the optimal solution generates some cash for me. Facebook Amazon The iOS architecture Now for the most interesting part. Since I'm an iOS developer, I'd like to write more technical "stuff" here. What we used, why, and what problems we encountered. SwiftUI Oh, yeah. We gave up on UIKit. It's even more accurate to say that "I gave up". I decided that since I'm starting to write something from scratch, let it be new and promising technologies. Moreover, SwiftUI is quite easy to layout, screens are made fast. Animations are also easy to implement. Moreover, SwiftUI is reactive, we are working with the Combine framework and it works quite well, no matter what anyone says. Moreover for future hiring, I believe this will be a big plus. There are a huge number of talented developers who already really want to move to 100% SwiftUI but are not yet able to do so. The overwhelming number of apps are still on UIKit. Rewriting them to a new framework is long and expensive, and businesses don't like those words. Did I regret choosing ? SwiftUI To be honest, despite all the pluses of the new framework, there are some outright minuses. For example, navigation. Yes, most developers have problems with it. It's not obvious enough how to take the routing logic into a separate entity, encapsulate it there, and take this responsibility away from the UI (like we're used to in UIKit). With iOS 16 this has gotten a lot easier and clearer, but the problem is that we're still supporting iOS 15 after all. Some guys write their extensions and somehow find a way to bring out the logic of routing through several levels of abstraction, we didn't have the resources for that. That's why we got the classic SwiftUI routing. We also encountered problems with the custom TabBar, which did not want to work correctly. Spent about 4 days doing everything competently. Is reactivity a pain? For many developers, creating reactive applications is a challenge. Especially for those who have never worked with this paradigm. I had a pretty good experience working with RxSwift, so in general, the approach was familiar. I just needed to understand how it all worked inside SwiftUI and how to build the architecture. At the dawn of SwiftUI's launch, everyone was talking about how MVVM was the perfect design pattern for it. Over the last six months, I've been hearing the opposite viewpoint, that MVVM is not suitable for SwiftUI, but that MVI is already laying down quite interestingly. I took the classic approach that Apple recommends. I had several managers that were needed in many places in the application, created one instance, and passed it throughout the UI hierarchy as an Environment variable. Admittedly, I made separate ViewModels for screens a couple of times, as I didn't see the point of making the class an observable manager. Conclusions So, I would like to summarize the above and the results of the first launch. Would I choose SwiftUI for my next application? Most likely yes. But while writing the application, I will be more careful in writing code, create more reusable UI components, and adhere to MVI architecture more strictly. Is a team really necessary? Yes, when you are not alone, you feel more confident, and you feel responsible not only for your destiny but also for your guys. It is always more interesting and precise to think through business or technical architecture together. Plus the saying "one head is good, but two are better" works perfectly here. Now the desire is only to increase the company's staff. What about the finances? It would be foolish to expect big income at the start of the project, so I consider only investments, investments, and once again investments. Of course, a small income begins to appear, and people buy subscriptions, but it is not comparable to the amount of money that comes from investments. I understand these risks and take them into account. Building your own business is a long-term game, full of risks and costs. Emotionally, I am ready for it. It is not an easy path, but I think it is quite realistic for me. Would I advise all developers to follow this path? Of course not. There are dozens of talented developers around me, they are happy, and they earn a lot of money with rather low responsibility. They have a lot of free time. They travel and spend money on whatever they want. Do they need to throw money into the bonfire of a business that could go out at any moment? Probably not. Everyone chooses their own way. I, for example, can't live without it all, and for some people, it's a real hell. I do not condemn either of them, and I am very glad that each person chooses his own way. Thanks for your time, for any questions you can contact me by mail or on Telegram (@maxnech) (or ). LinkedIn

How We Launched Our First MVP in the iOS App Market

Introduction: If you search the internet for a library that can generate sequences, you can hardly find one, although sequences are a core concept of discrete mathematics and computer science. In this short article, we will take a look at a library I wrote for the sequence generation called . SeqGen What Is A Sequence? A sequence (informally speaking ) is a set of elements (mostly numbers) where the production of each element is based on the preceding element(s). The most basic example is a simple linear sequence of positive integers where the first element is 0 and the next element is the preceding element plus one, so we can get the second element by adding one to the first one, and we can get the third element by adding one to second one, and so on. The linear sequence would look like this: . {0, 1, 2, 3, …, n} A more complex example could be the Fibonacci sequence where the first two elements are 0 and 1, and the next element is the sum of the two preceding elements. The Fibonacci sequence would look like this: {0, 1, 1, 2, 3, 5, 8, 13, 21, …, n} We can notice from above that a sequence is defined with two properties: The initial elements A function that produces the next element Using the Library: Dependencies: The SeqGen library is written in the Rust programming language; to follow up, you need to have . Rust installed Creating A Project: Let’s create a new project to use the SeqGen library; we can do so with cargo: $ cargo new --bin sequence && cd sequence Now, let’s add the library as a dependency to our project: $ cargo add seqgen Now, we are ready to use the library. Creating A Sequence: In SeqGen, the sequence creation process maps directly to the two properties of the sequence that we concluded in the What is A Sequence section; we have to define the initial elements and the function that produces the next element (called the transition function in SeqGen). Let’s create the linear sequence: use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new()
        .initial_elements(vec![0])
        .transition_function(|alive_elements, current_element_index| {
            alive_elements.last_element().unwrap() + 1
        });
} The type is a struct that represents a sequence; by calling the associated function on this type, we get a new instance that is undefined. On this undefined instance, we can call methods to define it. Sequence new() The first method is which accepts a vector of elements as an argument, and sets it as the initial elements of the instance. initial_elements() The second method is which takes as an argument a closure that represents the transition from the currently available elements to the next element. transition_function() This closure has access to two arguments: the first is which represents the currently available elements, and the second is (of type ) which is the index of the current element in generation. See the table below for an illustration of the transition function. alive_elements current_element_index usize Current Element in Generation alive_elements current_element_index 1 [0] 1 2 [0, 1] 2 3 [0, 1, 2] 3 n [0, 1, 2, 3, …, n] n is of type , we will take a look at the type later in this article alive_elements SequencePart SequencePart Since the index of the element is also its value in the linear sequence, we can simplify the example above to: use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new().transition_function(|_, i| i);
} Here, we do not need to define the initial elements, and we do not need access to the live elements; we just need the index (which is named in this case), and we simply return it. i In the same manner, we can define the Fibonacci sequence: use seqgen::prelude::*;

fn main() {
    let fib_seq = Sequence::new()
        .initial_elements(vec![0, 1_u128])
        .transition_function(|alive_elements, i| {
            let x = alive_elements.nth_element(i - 1).unwrap();
            let y = alive_elements.nth_element(i - 2).unwrap();

            x + y
        });
} Since the Fibonacci sequence grows exponentially, generating more than 187 elements with this definition will cause to overflow. A better definition would use big int instead of . u128 u128 : Using the Sequence After we defined our sequence, we can access its elements: use seqgen::prelude::*;

fn main() {
    let mut linear_seq = Sequence::new().transition_function(|_, i| i);
    let some_element = linear_seq.nth_element(111);
    println!("{some_element}");
} Here, we are accessing the 111th element using method which returns an immutable reference to the element ( in this case). nth_element() &usize Notice that we made mutable. That’s because the method will mutate the alive elements of the sequence. linear_seq nth_element() In this way, we can access any element of the sequence (from the element with an index of to the element with an index of .) 0 usize::MAX We can also iterate over the sequence like any Rust iterator: use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new().transition_function(|_, i| i);
    linear_seq.for_each(|e| println!("{e}"));
} This code will print all the elements of the sequence (from the element to the element ): 0 usize::MAX $ cargo run -q
0
1
2
3
4
5
6
7
8
9
10
11
12
13
... We can get the odd elements from the sequence using the following code: use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new().transition_function(|_, i| i);
    let odd_elements = linear_seq.filter(|e| e % 2 != 0);

    odd_elements.for_each(|e| println!("{e}"));
} Output: $ cargo run -q                                                            
1
3
5
7
9
11
13
... The sequence we define is lazy, meaning the elements won’t be generated unless needed (in case of iteration), or explicitly requested (using the method or other methods). nth_element() : Working With Parts of the Sequence Sometimes, we need to only work with parts of a sequence, in this case, we have sequence parts. There are three types of the sequence part: AliveElementsPart ImmutableRangePart MutableRangePart AliveElementsPart: We can get the live elements using the method on the sequence: alive_elements() use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new()
        .transition_function(|_, i| i)
        .pre_generate(111);

    let alive_elements = linear_seq.alive_elements();

    for alive_element in alive_elements {
        print!("{alive_element} ");
    }
} This code will print all the alive elements (0 to 110 in this case because we pre-generated 111 elements). ImmutableRangePart: Immutable ranges are ranges of the alive elements; they cannot mutate the sequence. If you will create an immutable range and not all its elements are alive, you will get an error ( error). DeadRange We can create an immutable range using the method which returns a . The variant is , and the variant is . The could be the variant (in case the start of the range is greater than its end), or it could be variant (in case not all elements of the range are alive): range() Result Ok ImmutableRangePart Err RangeError RangeError InvalidRange DeadRange use seqgen::prelude::*;

fn main() {
    let linear_seq = Sequence::new().transition_function(|_, i| i);
    let range = linear_seq.range(0, 3).unwrap();

    for e in range {
        println!("{e}")
    }
} This code will panic with error because there is no alive element. We can correct this with the following: DeadRange use seqgen::prelude::*;

fn main() {
    let mut linear_seq = Sequence::new().transition_function(|_, i| i);

    linear_seq.generate(3);

    let range = linear_seq.range(0, 3).unwrap();

    for e in range {
        println!("{e}")
    }
} Here, we generated 3 elements to make the range valid. MutableRangePart: A mutable range can mutate the sequence (generate elements). We can use a mutable range like so: use seqgen::prelude::*;

fn main() {
    let mut linear_seq = Sequence::new().transition_function(|_, i| i);
    let mut_range = linear_seq.range_mut(0, 111).unwrap();

    for e in mut_range {
        println!("{e}");
    }
} This code will print the elements from 0 to 110. Outroduction: Thank you for reading this article to the end, and I hope you found something useful in it. If you have any suggestions that can improve this library, please , and if you want to , that would be wonderful. open an issue on GitHub contribute to the library Also published here

SeqGen: The Library I Created for Sequence Generation

SeqGen: লাইব্রেরি আমি সিকোয়েন্স জেনারেশনের জন্য তৈরি করেছি

SeqGen: Die Bibliothek, die ich für die Sequenzgenerierung erstellt habe

SeqGen: la biblioteca que creé para la generación de secuencias

SeqGen : la bibliothèque que j'ai créée pour la génération de séquences

SeqGen: वह लाइब्रेरी जो मैंने अनुक्रम निर्माण के लिए बनाई थी

SeqGen: シーケンス生成用に作成したライブラリ

SeqGen: 시퀀스 생성을 위해 만든 라이브러리

SeqGen: a biblioteca que criei para geração de sequências

SeqGen: библиотека, которую я создал для генерации последовательностей

SeqGen: Dizi Oluşturma için Oluşturduğum Kütüphane

SeqGen: Thư viện tôi đã tạo để tạo trình tự

SeqGen：我为序列生成创建的库

In a bold move that redefines the blockchain landscape, announces the launch of its innovative WOW EARN Chain, now operating as a . This significant technological advancement positions the WOW EARN Chain at the forefront of blockchain innovation, offering unmatched efficiency, global accessibility, and a suite of unique features. WOW EARN Layer 1 blockchain Helping developers at all stages of development, WOW EARN Chain's mission goes beyond being just a public chain. It focuses on discovering and supporting innovative, high-potential developers and projects. WOW EARN chain will continuously improve the efficiency of Ethereum, providing supplementary expansion and support for the Ethereum ecosystem. By leveraging WOW EARN's comprehensive web3 ecosystem, the chain aims to become the birthplace of innovative technologies and businesses, establishing a complete cycle of technology development, application promotion, and efficient transactions. Key Highlights of WOW EARN Chain Strategic Shift to Layer 1: By building a Layer 1 blockchain, WOW EARN Chain has enhanced its core infrastructure, offering a more robust and scalable foundation for blockchain applications. This shift signifies a commitment to providing a high-performance platform capable of supporting the growing demands of the blockchain community. Low Transaction Fees with WOW coin: Emphasizing economic accessibility, the WOW EARN Chain features extremely low transaction fees, with transactions being processed for as little as 100 WOW. This approach makes blockchain participation more affordable, encouraging a wider adoption among users and developers. Global Node Deployment for Enhanced Connectivity: Recognizing the importance of a global presence, WOW EARN Chain has strategically deployed official nodes across key regions, including Asia-Pacific, Australia, Europe, and the Americas. This expansive network ensures that developers around the world can enjoy high-speed and reliable network connectivity, facilitating seamless blockchain experiences. Exceptional Current Limit for High-Volume Processing: With an impressive current limit of 100 qps, significantly surpassing the typical 5 qps offered by other public chains, WOW EARN Chain sets a new standard in transaction processing. This capability is pivotal for applications requiring high transaction throughput, offering an efficient and reliable platform for various blockchain use cases. Innovative Hybrid Proof of Stake (HPoS) Consensus Mechanism: The WOW EARN Chain employs the HPoS consensus mechanism, blending the benefits of Proof-of-Equity (PoE) and Proof-of-Stake (PoS). This hybrid model ensures a balance between security, speed, and cost-effectiveness, reducing transaction costs while maintaining competitive transaction speeds. Ethereum Virtual Machine (EVM) Compatibility for Seamless Integration: Continuing its alignment with Ethereum, WOW EARN Chain supports EVM compatibility, enabling developers to create and deploy decentralized applications (dApps) with ease. This compatibility facilitates seamless integration with the broader Ethereum ecosystem, enhancing the chain's utility and appeal. Cross-Chain Functionality for Expanded Reach: The WOW EARN Chain is not limited to its native capabilities; it extends its reach through integration with These integrations are carefully chosen to enhance various aspects of the chain, from liquidity and security to scalability and transaction efficiency. 10 diverse blockchain chains, such as Base, OkEX, Velas, and ZkSync. Empowering Developers with Resources and Support: Understanding the critical role of developers in the blockchain ecosystem, WOW EARN Chain is committed to providing extensive support and resources. This includes special funds for high-potential projects, hosting developer-centric activities, and fostering a collaborative environment for innovation and growth. Advancing the Blockchain Industry With WOW EARN Chain “The WOW EARN Chain is not merely a technological leap; it's a comprehensive blockchain solution designed to empower developers, streamline transactions, and expand the global reach of blockchain technology,” says Yara, VP of Marketing at WOW EARN. “Our transition to Layer 1, coupled with our commitment to providing a high-speed, economically accessible, and developer-friendly platform, marks a new chapter in blockchain evolution.” The opportunity to become a validator is open to any participant in the network. Should an individual's stake rank within the Top 21, they ascend to the role of an active validator for the forthcoming period. The operational dynamics of active validators are governed by a set of pre-established rules, under which they sequentially partake in the block packaging process. When a validator does not fulfill their block packaging duty within their designated time slot, other validators who have been less active in the recent cycle (specifically those not participating in the last half of the blocks) are randomly selected to execute this task. It is imperative that a minimum of half the number of validators, plus one, are functioning to ensure the smooth and uninterrupted operation of the blockchain. About WOW EARN As a leading innovator in the blockchain space, WOW EARN is dedicated to connecting users with decentralized opportunities in mining, earning, and trading. Following its strategic move to Layer 1 and a successful $30 million Series A funding round, WOW EARN is well-positioned to drive significant advancements in the DeFi ecosystem. For further information, visit WOW EARN's: | | | | Official Website Twitter Telegram Discord Medium Contact Yara G WOW EARN yara@wowearn.com This story was distributed as a release by Chainwire under HackerNoon’s Business Blogging Program. Learn more about the program . here

WOW EARN Redefines Efficiency and Accessibility with the Introduction of Layer 1 Blockchain

In an age where attention spans are fleeting and choices abundant, the success of any online platform hinges on its ability to provide seamless, swift, and engaging interactions. In fact, will leave a website if it takes longer than three seconds to load. 40% of visitors With just a one-second delay potentially causing a significant drop in user engagement, conversion rates, and overall satisfaction, it’s imperative that web developers prioritize immediacy. This rings especially true for applications, the backbone of many dynamic websites and web services. Ruby on Rails At JetRocket we care about our applications’ performance a lot. Performance in my opinion is not only a server response time. Of course, responses should always be fast, but deployments, tests, and application front-end should also run at maximum speed. Spanning almost 15 years of our history, we collected a quite vast collection of tools and techniques that help us to provide the best performance to our clients’ projects. Database Problems & Tools # 1 Bullet https://github.com/flyerhzm/bullet The first that comes to mind when you hear about database performance issues in Rails would probably be an N+1 problem. The N+1 problem occurs when an application makes N+1 database queries to retrieve related data. In the context of Rails, this often happens when you have a parent model and associated child models, and you retrieve a list of parent records along with their associated child records. Each parent record is retrieved with an additional query to fetch its associated child records. This can lead to a significant increase in the number of database queries and negatively impact the application's performance. The Bullet Gem is designed to enhance your application's performance by minimizing the frequency of queries it executes. During your application development, it actively monitors your queries and provides alerts when you should consider implementing eager loading (to avoid N+1 query issues), when unnecessary eager loading is detected, or when you should make use of counter cache. Bullet alerts can be sent via browser JavaScript-based popups, log files, with different monitoring systems, or even with Slack. # 2 N+1 Control https://github.com/palkan/n_plus_one_control While Bullet is designed to detect any N+1 queries in development, N + 1 Control is designed to be used in tests. It evaluates the code under consideration several times with different scale factors to make sure that the number of DB queries behaves as expected. #3 NewRelic, AppSignal, and other APM systems These tools offer various features and integrations that can assist you in monitoring and diagnosing N+1 query problems and other performance issues in your Ruby on Rails applications. Above is the screenshot from AppSignal indicating a request with an N+1 problem. #4 PgHero https://github.com/ankane/pghero PgHero is a powerful database optimization web dashboard explicitly designed for . Founded by Andrew Kane, PgHero offers comprehensive features and insights to help users identify and resolve performance bottlenecks, ensuring their applications run efficiently and smoothly. PostgreSQL One of PgHero's standout features is its real-time dashboard, which gives users a holistic view of their database's performance metrics. This includes information on query execution times, slow queries, database locks, and more. With this dashboard, users can quickly pinpoint areas that require attention and take proactive measures to optimize their database queries and configurations. Additionally, PgHero offers historical query analysis, allowing users to track query performance over time and identify trends or anomalies. PgHero is distributed as a Rails Engine or Docker image, which seems a better option for me and can be easily added to your Rails application deployed with Kamal as an accessory. #5 Rails PG Extras https://github.com/pawurb/rails-pg-extras Of course, many of you know that Postgres stores a lot of its internal metrics and params and they are available through different views. Likewise, if you need to get information about used and not used indexes you will probably query view (You can read more about this here ). pg_stat_user_indexes https://www.postgresql.org/docs/current/monitoring-stats.html The goal of Rails PG Extras is to offer robust insights from your PostgreSQL databases. It encompasses both rake tasks and the Ruby method designed to retrieve data regarding a Postgres instance. It encompasses details such as locks, index utilization, buffer cache hit ratios, and vacuum statistics. Through the Ruby API, developers can seamlessly incorporate this tool into tasks like automated monitoring. #6 Strong Migrations https://github.com/ankane/strong_migrations Strong Migrations catches unsafe migrations in development, and while having potentially dangerous operations in migrations does not affect your application performance directly, adding index non-concurrently or adding a foreign key can slow down your application while you deploy a new release. Anyway, keeping your migrations well organized is just another way to improve your application's overall quality and improve team knowledge, this is why we have strong migrations gems in all our projects. #7 Database Validations https://github.com/toptal/database_validations Another gem that makes your codebase not only faster, but better in general is database validations. It implements two new methods for ActiveRecord: and . As you can guess they work similarly to existing active record methods, but work on a database level. Based on benchmarks included in the gem it is 2.5x times faster than active record methods. Besides it ensures real uniqueness of values and has built its Rubocop rules to force your team to use it. db_belongs_to validates_db_uniqueness_of #8 Database Consistency https://github.com/djezzzl/database_consistency Database consistency gem created by Evgeniy Demin, author of database_validations. The main goal of the project is to help you avoid various issues due to inconsistencies and inefficiencies between a database schema and application models. Lintering & Audit You probably already have Rubocop configured in your project to provide a unified code style and keep the code base in good shape. #9 RuboCop Performance https://docs.rubocop.org/rubocop-performance/cops_performance.html https://github.com/rubocop/rubocop-performance RuboCop rules can improve not only your code style but also the performance of your code. This is where rubocop-performance gem comes in place. Look at a couple of examples below for nonobvious performance improvements. Case-insensitive string comparison is faster with compared to plus . String#casecmp String#downcase == # Performance/Casecmp

# bad
str.downcase == 'abc'
str.upcase.eql? 'ABC'
'abc' == str.downcase
'ABC'.eql? str.upcase
str.downcase == str.downcase

# good
str.casecmp('ABC').zero?
'abc'.casecmp(str).zero? When working with arrays you can modify existing Array instead of creating a new intermediate array for each iteration. # Performance/ChainArrayAllocation

# bad
array = ["a", "b", "c"]
array.compact.flatten.map { |x| x.downcase }

# good
array = ["a", "b", "c"]
array.compact!
array.flatten!
array.map! { |x| x.downcase }
array #10 Fasterer https://github.com/DamirSvrtan/fasterer Another tool that can be used for automated code performance improvements is Fasterer. Fasterer is based on FastRuby idioms and can be configured to run in your https://github.com/fastruby/fast-ruby CI/CD pipeline. #11 bundler-leak https://github.com/rubymem/bundler-leak Another tool from fast-ruby that may help you is bundler-leak. It analyzes your Gemfile over the database and provides you with information on what parts of your bundle may have memory leaks. I usually have bundler-leak as a part of my CI/CD pipeline. RubyMem Data Serialization Speed in data serialization is crucial because it directly impacts the efficiency and performance of your applications. As a Ruby programmer, you understand the importance of optimizing code for better execution. When data serialization to JSON is fast, it reduces the overhead of converting data into a human-readable format, allowing your applications to transmit and receive data swiftly. As far as I know, there are two serializers that can be declared as fastest in Ruby's world. #12 Panko https://github.com/yosiat/panko_serializer Panko is inspired by ActiveModelSerializers (which is currently not in active development ), but works much faster . https://github.com/rails-api/active_model_serializers#status-of-ams https://panko.dev/docs/performance.html The performance result is achieved by four approaches: Using the C extension of OJ library Incremental serialization of Ruby arrays Type casting that does not rely on ActiveRecord Figuring out the metadata, ahead of time Of course like in any other library, there are some cons: Panko can serialize only ActiveRecord objects. #13 Alba & OJ https://github.com/okuramasafumi/alba Compared to Panko, Alba can serialize any Ruby object and do it fast by using OJ library as the backend (Alba allows you to configure different backends). #14 GraphQL Performance Tools When dealing with APIs, which I usually use when building mobile applications, you cannot preemptively optimize your queries, like you do in . There is no silver bullet that will make everything work faster, however, there is a batch of tools that may help you. GraphQL REST GraphQL Batch https://github.com/Shopify/graphql-batch ArLazyPreload https://github.com/DmitryTsepelev/ar_lazy_preload GraphQL::PersistedQueries https://github.com/DmitryTsepelev/graphql-ruby-persisted_queries GraphQL::FragmentCache https://github.com/DmitryTsepelev/graphql-ruby-fragment_cache Profiling Profiling allows you to identify bottlenecks and areas of improvement in your applications. #15 Rack Mini Profiler, Stackprof & MemoryProfiler https://github.com/MiniProfiler/rack-mini-profiler https://github.com/tmm1/stackprof https://github.com/SamSaffron/memory_profiler When I hear about profiling in Rails, I always think about Rack Mini Profiler. This Rack middleware for Ruby web applications enables real-time profiling and performance monitoring. With it can also provide flamegraphs. I especially love that it is designed to work both in production and development. stackprof By adding gem to your application bundle, you can also do memory profiling for each request directly in your browser, which is really helpful. memory_profiler Dockerfile optimization Dockerfile optimization is crucial in enhancing the overall performance and efficiency of your Ruby on Rails application. Here are some key reasons why Dockerfile optimization impacts your Rails application: : The size of your Docker container directly affects deployment times, resource consumption, and scalability. Container Size and Efficiency : Docker containers share resources with the host system. An inefficient Dockerfile can lead to excessive resource consumption, causing performance bottlenecks and potential service interruptions. Resource Utilization : Docker allows you to package your Rails application and its dependencies together. An optimized Dockerfile defines dependencies explicitly and installs only what's necessary. Dependency Management : Dockerfiles are used to create reproducible environments. An optimized Dockerfile guarantees consistency across development, staging, and production environments. Reproducibility : When your application needs to scale to handle increased traffic, the efficiency of your Docker containers becomes critical. Scalability : An optimized Dockerfile speeds up your continuous integration and continuous deployment (CI/CD) pipeline. CI/CD Pipeline Efficiency : Running containers in the cloud often incurs costs based on resource usage. By optimizing your Docker containers, you can reduce resource utilization, leading to cost savings in terms of infrastructure and cloud services. Cost Savings For me, Dockerfile optimization is not just a technical concern but a strategic one. It impacts your Ruby on Rails application's performance, scalability, security, and cost-effectiveness. The biggest question is how to measure everything stated above. There are a lot of articles dedicated to Dockerfile optimization and I will not cover everything in this article, however, I want to share one tool that I always use. #16 Dive https://github.com/wagoodman/dive Dive is a powerful console utility explicitly designed for Docker and OCI image exploration. It empowers developers and system administrators to delve deep into the intricacies of these container images. With Dive, you can examine the image layers and uncover valuable insights on optimizing and reducing the overall size of your Docker or OCI image. Furthermore, Dive can be used with your CI/CD pipelines to make sure that changes made to your Dockerfile do not affect its performance and efficiency. Caching Caching can bring a significant performance boost to your applications as well as bring a lot of pain to your life. I don’t know a better manual about caching in Rails than Rails guides: https://guides.rubyonrails.org/caching_with_rails.html #17 Dalli https://github.com/petergoldstein/dalli If you decided to use caching in Rails then probably you will end with Memcached as a cache store. In this case, don’t forget to switch to dalli memcached driver. Originally created by Mike Perham (author of Sidekiq) more than 10 years ago, it is still the best way to use Memcached from Ruby: it is fast, secure, and support complex Memcached configurations. Tests Performance Last but not the least. Your application tests (specs in my case) should be as fast as possible, long-running tests will reduce the time that you can afford on everything described above. #18 Test Prof https://github.com/test-prof/test-prof Test Prof is a collection of profilers, recipes and RuboCop rules to make your test suite run fast. Of course, this is not a silver bullet, and it requires a lot of manual work, but it gives you instruments to do this work. As for me, I use , , and in every project, even in a new one, even if the test suite is relatively fast. let_it_be before_all factory_default Conclusions It is vital to understand the significance of optimizing Rails applications for better performance. Spending time and resources on this area can lead to significant enhancements. User experience is crucial in today's competitive digital world. Optimizing Rails applications means more than just improving speed; it also means delivering a more seamless, responsive, and satisfying user experience. I have provided a thorough overview of different tools and techniques that you can utilize. Moreover, it is essential to note that Ruby and Rails are not dead or slow. Like any other technology, it is important to be diligent with your Ruby code and understand how to enhance it. Also published here.

Enhancing Rails Application Performance: 18 Essential Tools and Techniques

Github Motion to dismiss Court Filing, retrieved on January 26, 2023 is part of . You can jump to any part in this filing . This part is 24 of 26. HackerNoon’s Legal PDF Series here ARGUMENT VI. PLAINTIFFS’ PRIVACY CLAIMS AGAINST GITHUB FAIL. Plaintiffs attempt to claim that GitHub invaded their privacy (Counts VIII, IX, and X) at the same time that the overall thrust of the Complaint is a failure to publicly attribute their identity to code. The Complaint does not identify any specific privacy-related provision of any alleged contract that was violated or how; does not allege a data breach that could yield liability under the California Consumer Privacy Act (“CCPA”); and does not identify any personal data that was negligently handled nor how that occurred. As noted in Part I.B, supra, no facts in the Complaint explain how Plaintiffs were harmed by any privacy-based conduct by GitHub. Whatever privacy-based claim Plaintiffs purport to advance, at a minimum they must provide a description of the PII at issue and a plausible allegation of some conduct in connection with that PII. Plaintiffs fail to provide those basics. See Compl. ¶¶ 215-39. The Complaint uses the conclusory terms “personal data,” “personal information,” and “PII” in describing Plaintiffs’ claims, e.g., Compl. ¶¶ 220, 228-29, but never defines those terms or specifies the actual data types discussed. Similarly, the Complaint insinuates that GitHub is collecting, distributing, using, or selling such information, but does so without alleging any facts. See Compl. ¶¶ 220, 229-33, 236-37. Plaintiffs never identify which personal information is involved, how it is captured, shared, sold, or otherwise distributed, or how any of this has resulted or is likely to result in concrete injury. Plaintiffs thus fail to provide basic notice of their claims for breach of GitHub’s Privacy Policy, violation of the CCPA, or negligence, necessitating dismissal. The CCPA claim, moreover, faces a particularly demanding standard that Plaintiffs do not even attempt to satisfy. The CCPA provides a limited private right of action. See Cal. Civ. Code § 1798.150. It allows a private claim only if a consumer’s “nonencrypted or nonredacted personal information, as defined in [§ 1798.81.5(d)(1)(A)], is subject to an unauthorized access and exfiltration, theft, or disclosure as a result of the business’s violation of the duty to implement and maintain reasonable security procedures and practices appropriate to the nature of the information to protect the personal information.” It is thus § 1798.81.5(d)(1)(A)—not § 1798.140(o)(1), as Plaintiffs allege, Compl. ¶ 228—that defines personal information for purposes of a CCPA claim. That provision defines such information as last name and first name or first initial, plus one or more of a social security number, driver’s license or similar number, account number or card number with access code or password that would give access to a financial account, medical information, health insurance information, biometric data, or genetic data. See Cal. Civ. Code § 1798.81.5(d). Plaintiffs’ allegations of misuse of unspecified PII are not actionable under § 1798.150, because Plaintiffs fail to plead any facts regarding data security or theft of the specified categories of data that could support a CCPA claim. Simply parroting the language of the statute is not enough to plausibly plead a claim, see Cork v. CC-Palo Alto, Inc., 534 F. Supp. 3d 1156, 1183 (N.D. Cal. 2021), and that is particularly true here where the facts described in the Complaint regarding training a machine learning model on publicly available data appears to be far afield from the ordinary fact patterns in data breach cases. Continue Reading . Here About HackerNoon Legal PDF Series: We bring you the most important technical and insightful public domain court case filings. This court case 4:22-cv-06823-JST retrieved on September 11, 2023, from is part of the public domain. The court-created documents are works of the federal government, and under copyright law, are automatically placed in the public domain and may be shared without legal restriction. documentcloud.org

Privacy Claims Against GitHub Fail

Hey there! I would like to tell you about a framework for building user interfaces on iOS and macOS. It is very convenient to use because it employs a declarative approach to programming. With SwiftUI, you can describe what your interface should do and look like, and the framework will take care of the rest. SwiftUI, One of the key elements of SwiftUI is the use of property wrappers. These are functional elements that allow you to provide additional logic for properties. SwiftUI has five main property wrappers: @State @Binding @ObservedObject @StateObject @EnvironmentObject They will become your best friends in development. @State allows you to create properties that can be changed and, if necessary, update the interface based on these changes. For example, if you want to create a button that changes its color when pressed, you can create a @State variable to store the color and add it to the button: @State struct MyButton: View {
    @State var buttonColor = Color.blue

    var body: some View {
        Button("Press me!") {
            buttonColor = Color.red
        }
        .background(buttonColor)
    }
} @Binding allows you to use a value that It is typically used in SwiftUI to pass a value from one view to another, allowing them to interact with each other. For example, imagine we have two views - one with a text field and the other with a button. We want the text field to update when the user presses the button. To do this, we can use @Binding: @Binding is stored in one part of the code in another part of the code. struct ContentView: View {
    @State private var text = ""

    var body: some View {
        VStack {
            TextField("Enter text", text: $text)
            Button("Update text") {
                text = "New text"
            }
            SecondView(text: $text)
        }
    }
}

struct SecondView: View {
    @Binding var text: String

    var body: some View {
        Text(text)
    }
} In this example, is used to pass the value from (which is in ) to (which is in ), so when the user presses the button, the text field will update and display the new text. @Binding $text ContentView text SecondView @ObservedObject is used to mark properties that are This property wrapper subscribes to changes in the object that conforms to the and automatically updates the relevant parts of the interface if the data has changed. Here's a brief example of using : @ObservedObject observed and can change depending on external data changes. ObservableObject protocol @ObservedObject class UserData: ObservableObject {
    @Published var name = "John"
}

struct ContentView: View {
    @ObservedObject var userData = UserData()

    var body: some View {
        VStack {
            Text("Hello, \(userData.name)!")
            TextField("Enter your name", text: $userData.name)
        }
    }
} In this example, we create a class called UserData, which contains a @Published name. In the ContentView structure, we create a property called userData with the type UserData, We display the value of userData.name in a text field and output it on the screen. using @ObservedObject. When the user changes the value in the SwiftUI automatically updates the corresponding part of the interface, as the property is published and observed using This means we don't need our own code to update the interface, and we allow SwiftUI to do it for us. text field, name @Published. If you don't know, @Published is a property wrapper from the Combine framework that can be added to a class or structure property, which automatically sends notifications of any changes to the value of that property to anyone who has subscribed to it. In other words, it's a helper attribute for properties that can be tracked for changes. Note: @StateObject is a property wrapper used This means that the object is stored as long as the view exists and is destroyed along with it. Typically, using is more practical for class objects that are needed for views, not just For example: @StateObject to initialize a class object and store it in the view state in SwiftUI. @StateObject multiple one. class UserData: ObservableObject {
    @Published var name = "John"
    @Published var age = 30
}

struct ContentView: View {
    @StateObject var userData = UserData()
    
    var body: some View {
        NavigationView {
            VStack {
                Text("Name: \(userData.name)")
                Text("Age: \(userData.age)")
                
                NavigationLink(
                    destination: ProfileView(userData: userData),
                    label: {
                        Text("Edit Profile")
                    })
            }
            .navigationTitle("Home")
        }
    }
}

struct ProfileView: View {
    @ObservedObject var userData: UserData
    
    var body: some View {
        Form {
            TextField("Name", text: $userData.name)
            Stepper("Age: \(userData.age)", value: $userData.age)
        }
        .navigationTitle("Profile")
    }
} In this example, is an object of a class that contains several properties that can be used in multiple views. The class is marked as so it can be used with and . UserData ObservableObject @StateObject @ObservedObject In we create a new object using to save state between transitions between different views. In this case, displays user data, visualizes it, and contains a link to another view that can be used to edit the user data. ContentView, UserData @StateObject ContentView (ProfileView) In , we get access to the same object using to modify user data. When the user changes data, it is automatically updated in because the same object is used. ProfileView UserData @ObservedObject ContentView UserData Use @ObservedObject if you need to observe changes in a class object from one view and @StateObject if you need to save the state of a class object that affects the display of multiple views. Note: If you use @ObservedObject instead of @StateObject for an object needed in multiple views, each view will have its own instance of the object, which can lead to problems with data synchronization between views. Therefore, in this case, it is better to use @StateObject. @EnvironmentObject is a property wrapper for p It allows access to the data object from any view in the SwiftUI hierarchy that belongs to the Environment container (e.g., Scene, View, App, etc.). For example, imagine we have a task list management app. We can have a root that contains a list of tasks and the ability to create new tasks. For this, we create a separate view that displays the list of tasks and a button to add new tasks. After adding a new task, the user should be redirected to the add task screen, so we create a separate view. @EnvironmentObject assing data objects through the SwiftUI view hierarchy. ContentView TaskListView AddTaskView To pass the object to all three views, we can create its instance in , and then pass it as a parameter to both and . However, this can become a problem if we decide to add even more nested views, as we will need to pass through many intermediate views. UserManager ContentView TaskListView AddTaskView UserManager Instead of this, we can use to pass down through the view hierarchy. This way, all views that need access to can simply declare it as an and use it as needed. @EnvironmentObject UserManager UserManager @EnvironmentObject struct TaskManagerApp: App {
    @StateObject var userManager = UserManager()
    
    var body: some Scene {
        WindowGroup {
            ContentView()
                .environmentObject(userManager)
        }
    }
}

struct ContentView: View {
    var body: some View {
        NavigationView {
            TaskListView()
        }
    }
}

struct TaskListView: View {
    @EnvironmentObject var userManager: UserManager
    
    var body: some View {
        List(userManager.tasks) { task in
            TaskRow(task: task)
        }
        .navigationBarTitle("Tasks")
        .navigationBarItems(trailing:
            Button(action: {
                // Navigate to AddTaskView
            }) {
                Image(systemName: "plus")
            }
        )
    }
}

struct AddTaskView: View {
    @EnvironmentObject var userManager: UserManager
    
    var body: some View {
        // Add new task using userManager
    }
} So, now the object will be automatically passed to and via . Note that we can modify the state of in one view, and the changes will automatically be reflected in the other view. UserManager TaskListView AddTaskView @EnvironmentObject UserManager The article covered the basic SwiftUI property wrappers: @State, @Binding, @ObservedObject, @StateObject, @EnvironmentObject. These property wrappers form the foundation of working with app state in SwiftUI. Use this article as a cheat sheet to have the basic property wrappers at your fingertips, necessary for developing apps with SwiftUI. By applying this knowledge, you will be able to build more complex user interfaces with dynamically changing states and integrate data from your models into SwiftUI.

SwiftUI's 5 Main Property Wrappers and How to Use Them Effectively

SwiftUI এর 5 প্রধান সম্পত্তির মোড়ক এবং কীভাবে সেগুলি কার্যকরভাবে ব্যবহার করবেন

Die 5 wichtigsten Property Wrapper von SwiftUI und wie man sie effektiv nutzt

Los 5 contenedores de propiedades principales de SwiftUI y cómo usarlos de manera efectiva

Les 5 principaux wrappers de propriété de SwiftUI et comment les utiliser efficacement

SwiftUI के 5 मुख्य संपत्ति रैपर और उन्हें प्रभावी ढंग से कैसे उपयोग करें

SwiftUI の 5 つの主要なプロパティ ラッパーとそれらを効果的に使用する方法

SwiftUI의 5가지 주요 속성 래퍼와 이를 효과적으로 사용하는 방법

Os 5 principais wrappers de propriedade do SwiftUI e como usá-los efetivamente

SwiftUI'nin 5 Ana Özellik Paketleyicisi ve Bunların Etkili Bir Şekilde Kullanılması

5 Trình bao bọc thuộc tính chính của SwiftUI và cách sử dụng chúng hiệu quả

SwiftUI 的 5 个主要属性包装器以及如何有效地使用它们

The world of cryptocurrency transactions is fraught with uncertainties, and one of the most pressing questions is whether these transactions are truly anonymous. Specifically, is Bitcoin anonymous? Unfortunately, the answer to this question is a resounding no: Bitcoin is not entirely anonymous. But it can surely be more discreet than traditional payment methods, and there are also ways to make your transactions more private — such as using a privacy-focused cryptocurrency like Monero (XMR) or . using NOW Wallet's swap feature Why Anonymous Transactions Are Important Financial freedom is the primary reason created Bitcoin. It was an opportunity for ordinary people to participate in the global financial system on their own terms. And one of these terms is anonymity. While many may think that anonymity is a fraudster’s tool, it is actually important to the average crypto user. Satoshi First, anonymity ensures privacy and security. Anonymous transactions allow crypto users to protect their personal and financial information, thus maintaining their financial privacy. Furthermore, anonymous transactions act as an extra layer of security. It shields users’ personal information and crypto assets from malicious actors. Sometimes, these malicious actors can be governments and (their) financial institutions — and this leads to the next point. Anonymity provides a way to escape censorship. Through anonymous transactions, crypto users can evade the censorship and restrictions imposed by governments and or financial institutions. This is particularly useful for crypto individuals and businesses that operate in jurisdictions where freedom of speech is censored and financial services are limited. Finally, by ensuring user privacy and security and helping users avoid censorship, anonymous transactions increase crypto adoption. More people adopt cryptocurrencies because of their privacy and security, and this promotes financial inclusion and a decentralized financial system. Despite these benefits, no blockchain network provides complete anonymity. Even the Bitcoin network. This means that there is no anonymous . However, there are certain networks that have taken the anonymity and privacy game a notch higher than others. One such network is . Bitcoin wallet Monero Monero and How It Facilitates Anonymous Bitcoin Transactions Launched in 2014, Monero (XMR) prioritizes privacy and anonymity in its transactions. It is a fork of the Bytecoin blockchain and is based on the protocol. Its privacy and anonymity are underpinned by its ring signature technology. The technology mixes a sender’s transaction with others on the blockchain, thus making it difficult to trace the transaction’s origin. This is known as “mixing” or “tumbling.” Also, the ring signature technology allows the user to sign a message alongside other users and makes it difficult to tell who signed the transaction. CryptoNote Another privacy feature of the Monero network is stealth addresses. These are one-time addresses a user can generate for each transaction. So even if someone obtains the recipient’s address, it is impossible to see the value of the cryptocurrency sent to that address. For anonymous bitcoin transactions, the Monero network cannot directly process these transactions as a separate cryptocurrency. So what the user can do is exchange bitcoin for Monero, mix or tumble the transaction, and then exchange it back to bitcoin. An can give users access to these Monero features. Such wallets could be custodial or non-custodial, . NOW Wallet is a non-custodial, hot wallet that can help users facilitate anonymous transactions. XMR wallet hot or cold wallets The NOW Wallet Swap Feature and Anonymous Bitcoin Transactions The NOW Wallet Swap feature provides another option for anonymous transactions. Generally, NOW Wallet Swap is a feature that allows users to quickly and easily exchange their cryptocurrencies within the wallet. As a result, they do not have to go through the hassles of sending coins to an exchange, placing orders, and waiting for the transactions to be confirmed. Also, the feature allows users to send their funds to another service without revealing their cryptocurrency holdings. They can exchange or swap one crypto for another within the NOW Wallet before sending it to another recipient. Using the same cryptocurrency pair for the swap allows users to keep their transactions private. It is important to note that since NOW Wallet is , it has already been primed for privacy, security, and anonymity. No user data is collected on the wallet and funds are stored on the device. non-custodial How to Use NOW Wallet Swap In addition to privacy, NOW Wallet Swap has diverse use cases even for users who hold cryptocurrencies that are not accepted by a service. With NOW Wallet swap, the user can convert their crypto assets to the required cryptocurrency and send them to the service. Furthermore, users can swap cryptocurrencies at a predetermined exchange rate. This is called Fixed Rate Swap. This feature comes in handy when the user is looking to send a specific amount of cryptocurrency or avoid exchange rate fluctuations. to illustrate the two features explained above. Say you have ETH, but you need to send exactly 1 BTC to a network that accepts only BTC. You can convert your ETH to BTC through the NOW Wallet Swap, then use the Fixed Rate swap to send exactly 1 BTC to the network. You would not need to manually calculate the exchange rate or bother if you are actually sending more than or less than the actual value. Here is an example Send Funds to Another Service Using Swaps in NOW Wallet Step 1: Open NOW Wallet and log in to your account. Step 2: Click on the "Exchange" tab located at the bottom of the screen. Step 3: Select "To address" as the exchange type. NOW Wallet supports over 500 assets on 40+ blockchains, including Bitcoin, Ethereum, FLOKI, and SHIB. You can even select a single asset (e.g., BTC to BTC) conversion for private transactions. Step 4: Choose the pair you want to exchange. Double-check the address to ensure you're sending funds to the right recipient. Step 5: Enter the recipient's address. The exchange rate is displayed in real-time, so you'll know the exact amount of cryptocurrency you'll receive. Step 6: Review the exchange rate and confirm the transaction. The time it takes to complete an exchange depends on the amount of cryptocurrency you're exchanging and the current network traffic. Once the exchange is completed, you'll receive a notification. Step 7: Wait for the exchange to be completed. You can check the transaction details in your transaction history. Step 8: Verify that the funds have been sent to the recipient. Sending your funds to another service using swaps in NOW Wallet is straightforward and convenient. You can exchange a wide range of cryptocurrencies and send funds to anyone, anywhere, anytime. Plus, you can enjoy a high level of privacy and security, making NOW Wallet an ideal choice to use as an XMRwallet or for sending funds to another service.

Can You Send Bitcoin Anonymously? A Step-by-Step Guide for Private Crypto Transactions in NOW Wallet

¿Puedes enviar Bitcoin de forma anónima? Una guía paso a paso para transacciones criptográficas privadas en NOW Wallet

Pouvez-vous envoyer des bitcoins de manière anonyme ? Un guide étape par étape pour les transactions cryptographiques privées dans le portefeuille NOW

क्या आप गुमनाम रूप से बिटकॉइन भेज सकते हैं? नाउ वॉलेट में निजी क्रिप्टो लेनदेन के लिए चरण-दर-चरण मार्गदर्शिका

ビットコインを匿名で送信できますか? NOWウォレットでのプライベート暗号取引のステップバイステップガイド

Você pode enviar Bitcoin anonimamente? Um guia passo a passo para transações criptográficas privadas na carteira NOW

Bạn có thể gửi Bitcoin ẩn danh không? Hướng dẫn từng bước về giao dịch tiền điện tử riêng tư trong NOW Wallet

你能匿名发送比特币吗？ NOW 钱包中私人加密交易的分步指南

This story was originally published on by . ProPublica Ken Schwencke Financial technology firms at the front lines of approving loans through the Paycheck Protection Program — intended to help small businesses survive during the pandemic — lacked fraud controls, chased high fees to the detriment of some borrowers and sometimes exploited their business relationships to arrange suspect loans for the companies’ own executives. One such executive falsely claimed in loan documents to be a Black veteran and received loans through multiple business entities. These are among the findings in a by the House Select Subcommittee on the Coronavirus Crisis, which investigated the role financial technology firms, known as fintech companies, played in propagating PPP loan fraud. report released Thursday The committee referred its findings to the Department of Justice and to the Small Business Administration’s Office of Inspector General. “Even as these companies failed in their administration of the program, they nonetheless accrued massive profits from program administration fees, much of which was pocketed by the companies’ owners and executives,” said , the subcommittee’s chairman, in a statement released with the new report. Rep. James Clyburn, D-S.C. “On top of the windfall obtained by enabling others to engage in PPP fraud, some of these individuals may have augmented their ill-gotten gains by engaging in PPP fraud themselves.” Fintechs were often the front door to the PPP program: They processed huge quantities of loan applications and were hired in part to vet the documents for obvious signs of fraud before sending them on to lenders. But the vetting was often lacking. The investigation kicked off that one fintech, Kabbage, , including what claimed to be a potato farm in Palm Beach, Florida, an orange grove in Minnesota and a cattle farm on a sandbar in New Jersey. shortly after ProPublica reported approved hundreds of loans for fake farms “The illegitimacy of these purported farms,” at the time, “would have been obvious if even the bare minimum of due diligence had been conducted on the loan applications.” Clyburn wrote in a letter to Kabbage The report found that Kabbage at one point had only one full-time anti-fraud employee and considered the risk of approving fraudulent loans minimal. “A fundamental difference is the risk here is not ours — it is SBAs,” said one risk manager to his team when asked about identifying fraudulent loans, according to a company email cited in the committee’s report. Kabbage’s then- head of policy wrote that “at the end of the day, it’s the SBA’s shitty rules that created fraud, not [Kabbage].” In a statement, the company said it was proud of the role it played in supporting businesses during the pandemic. “Kabbage’s existing online lending platform was able to process the sudden flood of loan applications, in a timely manner, in the midst of a national crisis and in light of ever-changing federal lending rules,” it said. “Kabbage adhered to the applicable rules and regulations in good faith.” The statement accused the committee of reaching a predetermined conclusion and asserted that the report does a “disservice” to the American people. The House report heavily cites ProPublica’s reporting and its , as well as reporting from the Miami Herald, Bloomberg, the Project on Government Oversight and others. public database of PPP loans According to the report, fintech firms acted as “paths of least resistance” for fraudsters looking to get taxpayer-funded loans, all the while lining owners’ pockets with lucrative fees for doing so. The companies were paid for every loan paid out and were incentivized to process loans quickly without doing much due diligence. One such lender singled out in the report, Blueacorn, instructed staff to push through high-dollar loans that the company called “VIPPP” loans internally. The original fee structure for PPP loans meant that small loans netted Blueacorn and other services a few hundred dollars, while large loans would yield tens of thousands of dollars. In Slack messages obtained by the committee, Stephanie Hockridge Reis, one of the company’s founders, made clear what the priorities should be. In one message, she said “closing these monster loans will get everyone paid.” In another, referring to a $1.9 million loan as a “deal,” she wrote, “I don’t need to tell you how much Blueacorn makes off that loan alone.” She said of lower-dollar loans, “delete them, who fucking cares.” For the second round of PPP loans, the government changed the fee structure, making small loans much more lucrative to incentivize getting money to small businesses and the self-employed. But showed that those most in need were sometimes left in a lurch by companies like Blueacorn. ProPublica’s reporting from January The companies lured customers with promises of quick approval of PPP loans, and once would-be borrowers were approved, they were locked in: Federal rules prohibited them from applying for a PPP loan elsewhere. Even if the loans were approved, though, the money didn’t always make it to borrowers. A that hundreds of thousands of loans were likely canceled because of quick approvals that fell apart after additional screening. ProPublica analysis showed Blueacorn did not immediately respond to a request for comment. Its current CEO, Barry Calhoun, told ProPublica in response to questions for a past article that the SBA should have helped by allowing lenders to access more documents that would ensure the borrower was legitimate. “A few adjustments would’ve gotten rid of a lot of the lazy fraud,” Calhoun said. “Because there was so much ambiguity, it encouraged a lot of people.” , perplexed that they showed up in our database of PPP recipients despite never having received money. Scores of people wrote to ProPublica They reported receiving quick approvals in spring 2021, followed by various snafus and then a monthslong runaround from companies like Blueacorn. Eventually, the lenders working with Blueacorn and other servicers would withdraw their initial approval and no funds were paid. Terry Kilcrease contacted ProPublica after applying for a loan through Blueacorn in May 2021. After going back and forth with the company for months, he said, Blueacorn formally canceled his loan, telling him that his documentation made inconsistent claims. Kilcrease told us the application took just a few clicks to fill out, and he doesn’t remember the exact documents that were requested. “The big companies made out like fat cats, the lenders made out like fat cats, all these companies that already had plenty of money,” Kilcrease told ProPublica in a previous article. “The people like me who are struggling to get there were just completely forgotten about.” Not only did Blueacorn collect millions in PPP fees, the House report uncovered that top Blueacorn executives and received more than $650,000 in PPP loans of their own. close associates and her husband, , received nearly $300,000 — in part through , much of it processed through Blueacorn or its business partners. Hockridge Reis Nathan Reis separate companies Capital Plus, a lender that worked with Blueacorn, discovered some of these loans and requested Reis and Hockridge Reis repay over $100,000, according to the report. But the committee found that at least six more loans were listed as forgiven. Loan applications reviewed by the House committee likely would not have passed muster if more stringent controls had been in place. Reis falsely listed himself as an African American military veteran in one, according to the report. In another application, he claimed to be an independent contractor in his wife’s business, but documentation obtained by the committee shows he was never paid by that company. Finally, both Reis and Hockridge Reis answered “no” to a question about whether they owned other businesses on multiple PPP loan applications for multiple businesses. The report cites these inconsistencies and indicators of potential fraud as meriting further investigation by the SBA’s Office of Inspector General, as well as the DOJ. A lawyer for Reis and Hockridge, who have both left Blueacorn, did not reply to a request for comment. According to public records, Reis relocated to San Juan, Puerto Rico, following his work at Blueacorn. In a video obtained by the subcommittee and viewed by ProPublica, he shows off a thick roll of cash in a bar last year, and in another video he and his wife are shown on a balcony of a luxury beachfront apartment. According to , Reis started a new company, a lending service consultancy named Lender Service Consultants LLC. The address for the company is a different three-story luxury apartment. It sold for $2.3 million in 2020 and features a plunge pool and two koi ponds. corporate records Photo by on Alexander Grey Unsplash

Were Fintechs Engaging in Fraud? The House Committee Thinks So

$SHIB: My Journey Through the Deepest Recesses & High Command of a $10 Billion Decentralized Army

In TypeScript, you might have noticed that you can declare custom types in two different ways. One is with the keyword, and the other is with the keyword. As such, you may find yourself wondering why there are two ways to do one thing - and you're not alone. I already covered how to use interfaces and - but let's look a little bit more into how they differ. interface type types 1. Interfaces extend syntax is different to types If we define a type in TypeScript, it is not extendable after the fact. For example, consider this custom type I just made up: type user = {
    name: string,
    age: number
} If, after its been defined, I suddenly realise I want to add an address too, I can do this using the following syntax: type userWithAddress = user & {
    address: string
} With interfaces, we can do the same, but the syntax remains slightly different: interface user {
    name: string;
    age: number;
}
interface userWithAddress extends user {
    address: string
} Now contains all the properties of , plus one additional property - that being . userWithAddress user address between these two ways of extending types is how they handle conflicts. For example, if you extend an interface and mention a property that has already been defined, an error will be thrown. For example, : The only difference this will not work interface user {
    name: string;
}
interface newUser extends user {
    name: number;
} Meanwhile, with , you can do this: type type user = {
    name: string
}

type newUser = user & {
    name: number
} While this will not throw an error, it may result in some unexpected results - so you should avoid it where necessary. For example, above, the property is reduced to type - since a type can be both and at the same time. :) name never never string number 2. Interfaces can be merged - types cannot Along the same lines, cannot be merged, while can if you declare them multiple times. For example, if we have a type, we can't do something like this: types interfaces type cat = {
    name: string
}
type cat = {
    color: string
} In fact, . Meanwhile, with , we can do that - and it'll merge both declarations. So the example below will create a type called with both and properties: the above code will throw an error interface cat name color interface cat {
    name: string;
}
interface cat {
    color: string;
} 3. Interfaces cannot extend a primitive While we can create a type that can be an alias for a primitive type like , cannot do this. For example, if you want to create a type called , which is always of type string, we can do it like this: string interface myName type myName = string; Here, becomes an alias for - so we can write instead of , essentially, anywhere. Meanwhile, does not have this ability. The following cannot and will not work: myName string myName string interface interface myName extends string {
    
} 4. Types can create unions, while interfaces cannot We can create union types with the keyword, but we can't do that with an interface. For example, here, can be a or : type userId string number type userId = string | number Meanwhile, the above cannot be achieved with an , since the interface defines the shape or type of an object. interface 5. Classes can implement interfaces, but not types If you are using classes in your TypeScript code, they can implement interfaces, but not types. That means the class has to conform to the interface itself. If you define a , you cannot use it with a class. For example: type interface user {
    name: string;
    age: number;
}

class createUser implements user {
  name = "John";
  age = 143;
} This makes quite handy if you decide to use classes in your TypeScript code - but as we know, a lot of TypeScript code tends to be functional rather than code based. So this benefit will depend on your codebase. interface Conclusion As you can see, the main differences between and kind of depend on the circumstances you use them in. Almost all the features of are available in , which means you might find yourself more frequently going to . Typically, though, it tends to be based on preference or what works best in your codebase (i.e., using the additional feature of ). type interface interface type type implement interface In any case, rest assured that it isn't as confusing as you might first think - with both and effectively being two ways to do the same thing! interface type Also published here.

TypeScript Interfaces and Types: A Comparison

Quite often in my practice, I see people use fields with a small and limited number of available options. varchar Let's check out today what field data type is better and will be the best approach for your project. Let's imagine us designing a database for a CMS. Just pretend we don't have any of them available at every corner, and we need to create the best example. To begin with our database, we will start with the main table post. I'm now omitting the field because this is our blog, and we don't have any plans to add additional authors except for us ;) author CREATE TABLE post (
    id         INT          NOT NULL AUTO_INCREMENT,
    title      VARCHAR(255) NOT NULL,
    status     ENUM ('archived', 'deleted', 'draft', 'published') DEFAULT 'draft',
    content    TEXT         NOT NULL,
    created_at DATETIME     NOT NULL                              DEFAULT CURRENT_TIMESTAMP,
    updated_at DATETIME     NOT NULL                              DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (id),
    KEY (status)
)
    ENGINE = InnoDB; I can imagine three ways how to describe the field. status The first one is in the example above. status VARCHAR(255) NOT NULL default 'draft' The next one will be enum: status ENUM ('archived', 'deleted', 'draft', 'published') DEFAULT 'draft', And the last one is an integer: status TINYINT(1) UNSIGNED NOT NULL DEFAULT '0' Let us compare these three variants in terms of performance, easiness to use, and support for feature changes. Setting initial scores for each option. varchar_score = 0
enum_score = 0
integer_score = 0 Usability for developers/humans Varchar and enum approaches look pretty much the same for a human eye. On the other hand, the integer is not human-readable. Then you see status=1, you have no way to say what status is just by looking into the database, and you have to keep the mapping between numbers and words in your code. Updating the scores: varchar_score += 1
enum_score +=1 Sorting and querying. Internally, MySQL uses numbers and null to store values of enums. Internal value DisplayedValue null null 0 '' 1 'archived' 2 'deleted' 3 'draft' 4 'published' And now imagine your enum like that: enum('draft', 'published', 'deleted', 'archived') Ordering of the data will work based on internal representation - first will go values with next - , , and . This behavior is confusing the first time until you realize the reason for that. The correct order of options in the enum should match your expected sorting behavior. draft deleted draft published For alphabetic sorting, it should be like this: ENUM ('archived', 'deleted', 'draft', 'published') Considering that, it looks like enums might bring some problems to beginners. But you simply have to keep in mind that enum is just an integer under the hood. Space consumption Tinyint takes 1 byte. The same story with enum - it also takes 1 byte of storage. Technically, both of them might be extended to 2 bytes, but I cannot imagine a real-life case where you will need more than 255 options. For varchar, it's a bit more complicated. It will depend on the character set. For example, will take one byte per character, and can require up to four bytes per character. Plus one byte to record the length of the string. latin1 utf8mb4 The set of statuses , , , and will take from 6 to 10 bytes in the character set. archived deleted draft published latin1 The final amount of storage will depend on the distribution of the values, but anyway, varchar will take much more space. Also, you should consider not only the storage size for the data but the storage size for the indexes. And indexes for varchar will take more space as well. enum_score += 1
integer_score +=1 Database migrations This case is pretty simple. For varchar and integers, you don't need to change the schema to add a new possible option. On the other hand, adding a new option to an enum will require changes to the schema. And depending on how you are going to do it - it might lead to database downtime, which is not acceptable. varchar_score += 1
integer_score +=1 Query performance To make some experiments let's spin up the MySQL database inside the Docker container and compare the results. docker run --name blog_mysql -e MYSQL_ROOT_PASSWORD=secret -e MYSQL_DATABASE=blog -d mysql:8
docker exec -it blog_mysql mysql -u root -psecret blog Creating three very similar tables. The only difference will be in the field. status CREATE TABLE post_enum (
    id         INT          NOT NULL AUTO_INCREMENT,
    title      VARCHAR(255) NOT NULL,
    status     ENUM ('archived', 'deleted', 'draft', 'published') DEFAULT 'draft',
    content    TEXT         NOT NULL,
    created_at DATETIME     NOT NULL                              DEFAULT CURRENT_TIMESTAMP,
    updated_at DATETIME     NOT NULL                              DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (id),
    KEY (status)
)
    ENGINE = InnoDB
    COLLATE utf8_bin;
    
    
CREATE TABLE post_varchar (
    id         INT          NOT NULL AUTO_INCREMENT,
    title      VARCHAR(255) NOT NULL,
    status     VARCHAR(10)           DEFAULT 'draft',
    content    TEXT         NOT NULL,
    created_at DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (id),
    KEY (status)
)
    ENGINE = InnoDB
    COLLATE utf8_bin;

CREATE TABLE post_int (
    id         INT          NOT NULL AUTO_INCREMENT,
    title      VARCHAR(255) NOT NULL,
    status     TINYINT(1)   NOT NULL DEFAULT 0,
    content    TEXT         NOT NULL,
    created_at DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
    updated_at DATETIME     NOT NULL DEFAULT CURRENT_TIMESTAMP,
    PRIMARY KEY (id),
    KEY (status)
)
    ENGINE = InnoDB
    COLLATE utf8_bin;

SHOW TABLES; +----------------+
| Tables_in_blog |
+----------------+
| post_enum      |
| post_int       |
| post_varchar   |
+----------------+ Let's have some fun, shall we? Not many people are doing MySQL procedures, but let's try some. DROP PROCEDURE IF EXISTS add_post_varchar;
DROP PROCEDURE IF EXISTS add_post_enum;
DROP PROCEDURE IF EXISTS add_post_int; DELIMITER $$

CREATE PROCEDURE add_post_varchar(number_of_posts INT)
BEGIN
    DECLARE loop_counter INT UNSIGNED DEFAULT 0;
    DECLARE post_content TEXT DEFAULT 'Lorem Ipsum is simply dummy text of the printing and typesetting industry.';
    DECLARE post_title VARCHAR(255) DEFAULT 'Lorem Ipsum';

    WHILE loop_counter < number_of_posts
        DO
            INSERT
            INTO
                post_varchar (title, status, content)
            SELECT
                post_title,
                ELT(0.5 + RAND() * 4, 'archived', 'deleted', 'draft', 'published'),
                post_content;

            SET loop_counter = loop_counter + 1;
        END WHILE;
END $$

CREATE PROCEDURE add_post_enum(number_of_posts INT)
BEGIN
    DECLARE loop_counter INT UNSIGNED DEFAULT 0;
    DECLARE post_content TEXT DEFAULT 'Lorem Ipsum is simply dummy text of the printing and typesetting industry.';
    DECLARE post_title VARCHAR(255) DEFAULT 'Lorem Ipsum';

    WHILE loop_counter < number_of_posts
        DO
            INSERT
            INTO
                post_enum (title, status, content)
            SELECT
                post_title,
                ELT(0.5 + RAND() * 4, 'archived', 'deleted', 'draft', 'published'),
                post_content;

            SET loop_counter = loop_counter + 1;
        END WHILE;
END $$
CREATE PROCEDURE add_post_int(number_of_posts INT)
BEGIN
    DECLARE loop_counter INT UNSIGNED DEFAULT 0;
    DECLARE post_content TEXT DEFAULT 'Lorem Ipsum is simply dummy text of the printing and typesetting industry.';
    DECLARE post_title VARCHAR(255) DEFAULT 'Lorem Ipsum';

    WHILE loop_counter < number_of_posts
        DO
            INSERT
            INTO
                post_int (title, status, content)
            SELECT
                post_title,
                ELT(0.5 + RAND() * 4, '1', '2', '3', '4'),
                post_content;

            SET loop_counter = loop_counter + 1;
        END WHILE;
END $$

DELIMITER ; And create 200 000 records in each table. call add_post_int(200000);
call add_post_enum(200000);
call add_post_varchar(200000); SELECT COUNT(*), status FROM post_enum GROUP BY status
UNION
SELECT COUNT(*), status FROM post_int GROUP BY status
UNION
SELECT count(*), status FROM post_varchar GROUP BY status; +----------+-----------+
| COUNT(*) | status    |
+----------+-----------+
|    50058 | archived  |
|    50229 | deleted   |
|    50273 | draft     |
|    49440 | published |
|    50123 | 1         |
|    49848 | 2         |
|    49642 | 3         |
|    50387 | 4         |
|    49885 | archived  |
|    49974 | deleted   |
|    50060 | draft     |
|    50081 | published |
+----------+-----------+ Now we have almost even distribution. Let's run some queries. First, enable profiling: SET profiling=1; Next run queries which will use only the index to obtain the data and will not go to the heap. SELECT SQL_NO_CACHE COUNT(*), status FROM post_enum GROUP BY status;
SELECT SQL_NO_CACHE COUNT(*), status FROM post_varchar GROUP BY status;
SELECT SQL_NO_CACHE COUNT(*), status FROM post_int GROUP BY status; And finally, let's check our performance. Query_ID Duration Query 1 0.05163150 SELECT SQL_NO_CACHE COUNT(*), status FROM post_enum GROUP BY status 2 0.05172150 SELECT SQL_NO_CACHE COUNT(*), status FROM post_varchar GROUP BY status 3 0.05893025 SELECT SQL_NO_CACHE COUNT(*), status FROM post_int GROUP BY status Every scenario works at the same speed. Updating the scores: varchar_score += 1
enum_score += 1
integer_score += 1 Conclusion Our final scores are: Option Score integer_score 3 varchar_score 3 enum_score 3 Turns out all our scores are the same. I didn't expect it to be so in the beginning. Honestly, I expect enums to win this battle. But enums have some specific behavior in sorting, which is not a big deal if you know your tools, but it might confuse a beginner. Enums have advantages in being human-friendly and taking less space. Considering all of that, I'd recommend using enums for options like this. And may the fast queries be with you ;)

What Is the Difference Between Enum, Varchar and Int Data Types in MySQL

Introduction Modern Information Security can be difficult to understand. Terms like “attack”, “exploit” and “vulnerability” might be self-explanatory but what do pentest, EDR and DAST mean? Why is it important to assign testing scopes? This is a continuation of this article. Modern Information Security Explained Through Violence Some person can throw a brick on your head from the top floor. This is an . attack To do this, he will go to the construction site, climb to the highest floor, pick up a brick, aim and throw it down. This is an exploit. Your head is not designed to hit bricks with a given weight and acceleration. This is a vulnerability. You remove all the bricks from the construction site, exclude the presence of any person on it, and, just in case, also the upper floors. This is security. You put on a helmet to somehow reduce the consequences of hitting a brick. This is . anti-virus / EDR In your safety rules, everyone is prescribed to wear helmets. But the staff walked without helmets, and continue to walk. This is . paper security The foreman is still alive, that person is throwing bricks in all directions, and the watchman is already pushing the red button. This is a security analyzer. You hire two foremen so that in the event of the death of one of them, the work will not stop. This is formal fault tolerance. You hire as many foremen as you have bricks at a construction site plus one more. This is the actual fault tolerance. You buy a device that throws bricks in all directions, like tennis balls. This is DAST. Some person made his way to the construction site, climbed to the upper floors, killed the foreman with a brick, and now joyfully demands to pay him a reward for this. This is a bug-hunter. You buy a virtual simulator that does everything the same as DAST but without building the construction. This is SAST. You buy a feedback module between the throwing device and the construction simulator. This is IAST. You were crazy about buying and turned to a third-party company for help. The company invites you to purchase the latest concrete mixer from a renowned vendor to solve the problem with bricks. You don’t care how a concrete mixer and bricks are connected, but you still buy. Now, not only bricks can fall from your upper floors, but also a concrete mixer, which makes the problem of bricks not so significant. This is the involvement of an integrator. You hired an expert to check the possibility of entering the construction site, climbing up to the upper floors, and dropping bricks on the heads of staff. This is a . pentester The pentester was not only able to kill the foreman with a brick in ten different ways, but he also destroyed the whole object, burned the equipment, and forced the watchmen to kill each other. This is an who was not assigned a in time. experienced pentester testing scope You did everything conceivable and inconceivable so that the fallen brick would not kill anyone, the object could not be destroyed, the equipment could not be burned, and also security belts for watchmen, to be sure. The very next day, the foreman is fallen off from a brake system of the concrete mixer. This is the reality of modern information security. https://bit.ly/3Goglsf Final Thoughts Thank you, readers hope you all liked it. This article was first published here.

Explaining Info-Sec in Layman's Terms [Part II]

Explicando Info-Sec en términos sencillos [Parte II]

Expliquer Info-Sec en termes simples [Partie II]

आम आदमी की शर्तों में जानकारी-सेक की व्याख्या [भाग II]

情報セキュリティを分かりやすく解説【後編】

Explicando Info-Sec em termos leigos [Parte II]

Giải thích Thông tin-Sec trong Điều khoản của Cư sĩ [Phần II]

用外行术语解释 Info-Sec [第二部分]

Existential crisis, internal strife, self-destruction, whatever you choose to call it, the upshot is that the decentralized web (Web 3.0) is poised to take on mature responsibilities in its infancy. Web 3.0 and public distributed ledger technologies wrestle against multiple trillion-dollar companies and unicorns with barely two trillion dollars in market capitalization; Do we call the cops? Is the chase for decentralization in circles like a maze with no outlets? Hold up! Wait for a second! What did we expect? the internet , and had to (web 2.0) was once a bubble, had its crisis set up protocols for interoperability and synchronization. Maybe the best way to build is to experiment, trial and error, rinse and repeat. In the case of the decentralized web, there is a lot to fix, standards to set up, and chaos to settle. In this publication, I overview the web3.0 chaos and significant transformations that could lead to building a truly decentralized internet. : “Blockchains” are used throughout this publication to refer to distributed ledger technologies generally. Note Interoperability: The Architectural Chaos - Vitalik Buterin. The future will be multi-chain, but it will not be cross-chain: there are fundamental limits to the security of bridges that hop across multiple "zones of sovereignty" is the ability of different blockchains to interact and share value and information. Blockchain interoperability Imagine transferring Ethereum from the Ethereum network to a Cardano user, who would receive either Cardano or Ethereum on the Cardano blockchain; interoperability is in action. It’s not just about currencies but also about data and information. Numerous blockchains are built for different reasons to suit various individuals’ and requirements; as more users get on board, blockchains move closer to their maximum throughput and get congested. Multi-technology interoperability between web3.0 and web2.0 technologies must be established for blockchain technology to be deployed at scale. Interoperability is just as important now as it was in the early days of the internet, before webpages used HTTP to connect between web browsers and servers, SMTP to send emails, and POSIX, the standard that enhances application portability. A connected ecosystem would unlock value across technologies and enable individuals and communities to trust and use blockchains extensively with less complexity. There’s so much value to be unlocked if blockchains become interoperable, such as: increased network value. increased agnosticism and decentralization. better user experience and flexibility. Numerous blockchain projects embrace interoperability, such as the Octopus network, Cosmos, Polkadot, Aion, and many others; also, there’s the Blockchain Interoperability Alliance, an organization set up to foster blockchain interoperability. Open-source: The Structural Chaos - fission. If you're treating the built-on-open-source-contributors global blockchain as something you pay gas fees to, you don't fully understand the network of code AND people you are involved with Open-source software is distributed under a license permitting concerned entities to use, modify, and distribute the program and its source code. Open-source technologies such as programming languages (PHP, Go, Javascript), libraries (ReactJS, Tensorflow, GPT3), operating systems (Android, Linux, BSD), and a slew of other technologies and projects power most of the world’s technology infrastructure. If Blockchain and Web3.0 are going to be adopted, full transparency is essential right from the project's development to launch to the project's demise. This contributes to many factors, including decent decentralization, robust growth, and contributor economies. Decentralization without open source is a one plus one that equals 0.1,  easily insignificant. Opensource patents and laws can protect intellectual property as the contributors desire. A completely open-sourced innovative project is more likely to be sustainable and receive contributions and community support over time, which also steers it in a community-defined direction. Open source projects should also be governed in a decentralized fashion, employing structures like DAOs to ensure the project is steered in the direction of the community’s desires. Economics & Incentives: The Financial Chaos - Andre Cronje. I wrote it once before; I’ll repeat it here. In crypto, you vote with your money. If you keep voting for low energy scams, rich quick schemes, or low effort forks, you will only get more of those One of the most delicate composites of the decentralized web is the token economy's creators and owners. This has sprung up questions concerning the spread of participant values, as seen in , and promised by protocols that eventually crash and return “ afterwards. cases of overpriced digital art increased scams, the bizarre APYs This site can’t be reached” The world’s economy operates on ponzinomics; we have come to terms with that; however, we could build better this time by relying on mathematics, building sustainably, and designing better token economics systems that are reversible and renewable for more extended periods. While Web3.0 aims to fully decentralize the internet such that no party gets to control the internet like web2.0 is greatly influenced by the , an outlook on the situation see venture capitals as majority stakeholders in many protocols. fortune 500 companies Why is this important for adoption? since blockchains and web3.0 are deemed low-budget alternatives, they have to offer better UX than existing technologies and economies; the impact matters! Also, the token economy would be more potent if regulated, especially by the government with the values of the crypto economy; but that’s an issue we are not prepared to debate. The After Rant The current state of the decentralized web isn't appealing. It seems like a temporary hype or the latest scam. However, the same was acclaimed in the early days of the internet; in essence,  maybe web3.0 needs time. As Web3.0 gets all the time it needs to thrive or get cancelled, we must criticize intending to build to perfection or at least a decentralized web with a better user experience. Nonetheless, Web3.0  needs to be open-sourced, interoperable, and economically sustainable to thrive. - OECD 2019 Sometimes called a “silent” or a “quiet” revolution, decentralization is among the most significant reforms of the past 50 years.

Here's How to Build a Decentralized Internet

He aquí cómo construir una Internet descentralizada

Written by Dmytro Shtapauk, Business Process Architect of Techstack No one likes doing extra work, and I have to say, it’s fair. This is the reason why startups or small teams often choose to ignore processes and jump in accomplishing high-priority tasks first. Test documentation is sacrificed in this case because its contents seem obvious to a small team of founders plus one or two testers, and writing it down is viewed as a waste of time. Time goes by; new team members join the team. The founders take on new responsibilities and have limited time to share expertise. After many pivots, they can hardly remember what they did; even more, they may lose test cases or other useful resources that could save time and effort. What seemed a reasonable sacrifice at the start turned into a bottleneck. Running a software product requires strategic thinking By introducing test documentation early, you save many hours of rework and eliminate bugs that could leak to production. In this infographic, I’ve gathered some math to define the maturity of your QA process. If you find out that you’re doing well, there we go—your team is doing great! If you find any of the metrics out of the bounds, don’t worry — below you can read about the possible problems and find a solution. You can always get back to my article about that benefit both founders and the team. how to write a test plan and a test strategy 5 Things That May Mean You Need a Test Plan and Test Strategy: an Infographic Working in QA means thinking ahead and preventing problems. You may need someone to or discuss how your product can benefit from QA automation or improved processes. exchange thoughts about your QA practices

Developing a Test Plan and Test Strategy for Your Business

Let's cover the list data structure and why it's so wonderful. In case you missed it, here are the previous parts of the series Python for Beginners, Part 1: How to Download and Install Python Python for Beginners, Part 2: Hello World Exercise Python for Beginners, Part 3: The Turtle Module Python for Beginners, Part 4: Interactive Shell vs. Script Python for Beginners, Part 5: Variables Python for Beginners, Part 6: Strings Python for Beginners, Part 7: Fun Fun Functions Python for Beginners, Part 8: Function Arguments Python for Beginners, Part 9: Loops Python for Beginners, Part 10: Primitive Data Python for Beginners, Part 11: String Slicing Transcript 0:00 Hey guys, what's up? 0:01 So in the last video I talked about string slicing. 0:06 In this video I'm gonna talk about lists, okay? 0:08 Lists of things and what the heck are lists. 0:11 Lists are awesome. 0:12 However, in the last video I left you guys with a question. 0:16 I said, take this, 0:20 right, and parse it. 0:21 And basically XBox 360, pull that out, 0:25 save it in a variable like product. 0:27 Pull this out, save it in a variable like price. 0:30 And save this in a variable like condition. 0:32 Right, so when you have your Excel sheet open, 0:35 it looks really nice, it'll look like this. 0:43 My solution, I'm gonna do it in a different way 0:47 because if you try to use it as index, this is the solution. 0:50 So you can pause the video, think about how it works. 0:53 That's how you'll pull the 150 0:55 and using the same logic, you'll pull the New. 0:57 However, index is a very ugly method to use 1:01 for getting, parsing the string. 1:04 What I want to show you guys is this method called find. 1:07 Okay, that's a very nice method. 1:09 Let's say we take the data, and I do data.find 1:14 and find, it shows you the bottom what it takes in 1:17 as the function, it takes in the substring 1:21 and then it takes in optional arguments, like start and n. 1:26 So I'm gonna say data.find 1:29 and I'll give it 1:30 substring pite. 1:33 What a substring means is that, that's something 1:37 that exists in the original string. 1:41 For example, 1:44 I have to give find, 1:45 the function find or the method find, 1:47 I have to give it something that exists within this. 1:50 If I gave it something that doesn't exist within it 1:52 like banana, 1:54 it would say negative one, 1:56 like I didn't find anything. 1:58 But if I gave it a pite, you can see that it finds a nine. 2:04 And another thing you can give it is how you solve... 2:09 Is you can give it where to start from, okay? 2:12 So I can say, for example, 2:15 start looking after ten 2:19 or look for pite, 2:21 but I want you to start at string nine, 2:24 okay? 2:25 Or I want you to start at string ten, alright? 2:29 And now it finds a pite at location 15. 2:32 So if I do data, and if you count it up, 2:35 you'll see that this is the pite 2:37 and it is at indeed at location 15. 2:39 If I do data(15), you'll see that 2:41 it gives you back that pite. 2:45 Right? 2:47 Okay, so by getting that second pite, 2:51 now you can get the value in between the first pite 2:54 and the second pite by saying something like, 2:59 start from finding the first pite 3:03 and then go up to 3:06 finding the second pite. 3:10 Right? 3:11 So I can say, finding, 3:14 or start from, 3:17 or look for pite. 3:19 And then start from ten, for example, right? 3:24 And this gives you this guy here. 3:26 And just to make sure we don't 3:27 include the pite in the first one 3:29 we can just start from plus one with that. 3:31 Okay? 3:32 So that gives you in between the first and the second pite 3:34 you get probably like 150. 3:36 Okay, so, 3:38 the reason why I went even more in depth in strings 3:41 even when the video called lists 3:43 is because a lot of what you learn from strings 3:47 is applicable to lists, okay? 3:49 So, let's take a list and call it groceries. 3:54 And I will have apple, and I foreshadowed this 3:57 for you guys a little bit... 3:59 Banana--and you can also have integers. 4:01 Although usually you try to 4:02 put the same kind of thing in the list. 4:06 But sure, let's put five in there and six in there 4:09 and then oranges or something, okay? 4:12 Cool. 4:13 Now, if I wanna 4:15 take this list 4:17 and I wanna get the first element and the second element, 4:19 if it was just a string, 4:22 right? 4:22 Like the reason why lists are useful is 'cause 4:24 you can use it to store multiple variables. 4:29 Like for example, if you wanted to use variables 4:31 to store this, aww shh-- 4:34 It would be a little... 4:38 It would be weird. 4:39 'Cause you will say groceries, zero is equal to apple. 4:43 You would say... 4:51 Groceries of one are banana. 4:53 And so then when you do groceries of zero, 4:55 you get back apple. 4:57 And when you do groceries of one, 5:00 you get back banana. 5:02 But lists make it, make that thing, 5:05 for you in a really easy way, okay? 5:09 So now, if I do groceries and if I do groceries of zero, 5:14 I get back apple, okay? 5:16 And if I do groceries of one, I get back banana. 5:19 Because apple is in the zero position. 5:22 Banana is in the first position. 5:25 This is in the second, third, fourth position, okay? 5:30 So lists make it really nice for you. 5:33 Imagine if you were trying to store data for a race. 5:36 So like, four of your friends ran really fast 5:40 and you wanted to record who came first, who came second. 5:43 So you can save 5:46 race is equal to 5:49 like John came first, and then Bob came second, 5:53 and then, you know, whatever, like Timothy came in third, 5:59 uh, Timothy is pretty slow. (laughs) 6:03 So we can say like, okay, who came in first? 6:07 We can ask that question. 6:08 We get back John. 6:09 We can say, who came in second? 6:11 We get back Bob. 6:12 And I can say, who came in third? 6:14 Or I can say who came in last? 6:17 That negative one gets you the last element. 6:19 And this answers all my questions. 6:22 So just like how were able to slice strings, 6:26 we're able to slice 6:28 lists, okay? 6:30 But notice, lists is nicer for elements. 6:33 So for example, 6:35 XBox 360 and all this stuff, 6:38 I'll show you guys a really cool trick you can do with lists 6:41 to break that up into pieces. 6:43 So like for example, 6:46 if I gave you a string like this, right, 6:48 what is going on? 6:50 Notice that there are a lot of spaces in between, right? 6:52 Let's just replace those spaces, 6:54 just so it's more visual, 6:56 let's replace those space with that, 6:59 and let's say we want to get the what part separately, 7:02 is part separately, going part separately, 7:04 and on part separately, 7:07 without having any of the dashes in the middle. 7:10 There's a method we can use called .split, okay? 7:14 And we can pass to .split what we want to split by. 7:19 So I can say something like this, 7:21 I want to split by the dashes, okay? 7:23 So check it out, now I got what is going on, right? 7:27 This is a list 7:30 of strings. 7:31 Now the data complexity is getting a little bit higher, 7:34 it's a list containing strings inside of it. 7:39 Okay, so, I can call this like, 7:43 you know, 7:46 greeting or something, it doesn't matter, 7:48 and if I do greeting, I can say 7:50 What's the first word of greeting? 7:53 What's the second word? 7:58 Whoops. 8:02 Greeting, right, what's the second word? 8:05 And for example, I can say what's the last word? 8:09 And it'll give me what is going on, 8:11 on being the last word, right? 8:13 Now, I can also do string slicing just like 8:17 how I can do in strings. 8:19 So I have start, I have stop, 8:22 and I have step. 8:24 So if I take the race one again, 8:27 I can say go from zero all the way to the end. 8:31 I can say the same way, like this, 8:35 this is like optional, right? 8:38 It starts with zero and it ends at zero, 8:40 or ends at the last one by default. 8:43 If I wanna get from John to Bob, 8:46 I can say like give me the 8:47 first two... 8:50 first two contestants of the race. 8:53 And it will give me John and Bob. 8:55 Or I'll say give me everybody but the last guy 8:58 so I can ask that question to my list, just like that. 9:04 Okay, now to answer your guys' question 9:06 of how to reverse the string, 9:08 it's the same you can reverse the list as well. 9:12 So, lemme show you guys. 9:14 There are a couple of different ways, 9:15 but I'm gonna show you guys the nicest, the fanciest way. 9:20 So let's take this list 9:23 and I wanna step by... 9:26 Sorry, I wanna start at the default, which is zero. 9:29 I don't have to write zero, 9:30 but I'll just write it for you guys. 9:32 I want to go all the way to the end 9:34 and I don't have to write this, okay? 9:36 So I'll just leave it blank here. 9:39 And for the last part, for step, 9:42 instead of saying step by one, 9:44 which will just give me the whole thing. 9:47 Instead of saying give me every other element, 9:49 so like give me John and then Timothy 9:52 I will say 9:55 step by negative one. 9:57 So check this out, 10:00 let's remove 10:03 this, 10:05 right? 10:06 And let's remove that guy, and let's do that, 10:09 and you will see how it steps. 10:14 It just reversed the list. 10:17 If we have 10:18 the same string, like 10:20 let's say we have data I can do the same way and 10:25 reverse everything in data. 10:28 So you can see XBox 360 and New and 150 10:31 are all written backwards, okay? 10:35 So that's how you would like reverse something. 10:38 Now I want to talk about 10:43 split again, 10:44 and I want to talk about one very important method 10:48 called a pen for a list. 10:50 One of the most commonly used things 10:53 that any programmer does in any language, okay? 10:57 So split is like Java, Cs, everybody uses that. 11:01 It just might not be called split. 11:02 And the same thing in Python, everybody uses split 11:05 and the next method I'm about to show you, pen. 11:07 Very common for all the games you make, 11:10 for everything that you do, it's going to be like 11:11 one of the most common thing you use, 11:13 especially a pen, so pay attention. 11:15 So I'm gonna show you 11:18 the method called 11:20 the split, okay? 11:22 So I've shown you a little bit of that already. 11:23 So let's say I take data and I wanna break it up, 11:27 right, product, price, condition. 11:31 Very easy way to do it, very easy way to do it split. 11:33 So let's use data.split, 11:36 and I wanna say split by 11:39 pite. 11:41 Boom, look at that. 11:42 How nice is that, right? 11:44 It automatically just split it by that 11:46 and you can store that in 11:50 details or something. 11:52 And now if I do details of zero, 11:57 and I can set that equal to product. 12:00 So now if I do product, I get that. 12:03 I can say 12:05 price is equal to 12:07 details 12:09 of one 12:10 and I can say condition 12:13 is equal to details 12:14 of two. 12:16 Okay, price, condition, 12:19 boom, 12:20 okay? 12:21 So that was like some really nice ways to get this done. 12:24 In the next video I will talk about a pen. 12:27 So stay tuned.

Python for Beginners, Part 12: Lists of Things

In 2021, hosted the first-ever awards!! HackerNoon Startup of the Year The goal of this campaign was to give recognition to the hardworking startups who pulled through the pandemic -- growing and thriving (despite all of the challenges). More than 44,000 startups were nominated all across the globe! They were selected from over 4,553 cities, with a total number of * cough * “4 billion” votes. Insane, right? To see who is a winner in each respective city, visit and pick a city. The name at the top of the list is the winner. (Compromised awards are under review. Cities with tie votes will be updated to have two winners!) startups.hackernoon.com The will announce the winners per region in their respective cities. Startups Winners Announcement series Here are the winners in the : Asia region Top Startup Cities in East Asia Seoul The Startup of the Year in is with 377 votes! Seoul dable Central is the Startup of the Year! It came out ahead with 121 votes. UpNow Central Sheung Wan came out as the Startup of the Year in with 154 votes. Votee Sheung Wan Tokyo The Startup of the Year in is with 41 votes! Tokyo ACES Wan Chai The Startup of the Year in is with 54 votes! Wan Chai Zetl Osaka, Japan In , is the winner! Osaka Nanophoton Taiwan came out as the Startup of the Year in ! Tico Taiwan Dongcheng, China In , is declared the Startup of the Year! Dongcheng Waiju Taipei came out as the Startup of the Year in ! Tico Taipei Akasaka In , is the winner! Akasaka WAKUWAKU Chuo In , is declared the Startup of the Year! Chuo GO-NET Ginza came out as the Startup of the Year in ! Netyear Ginza Kanazawa In , is the winner! Kanazawa Granzella Minami-aoyama In , is declared the Startup of the Year! Minami-aoyama Tokyo6 Entertainment Shibuya came out as the Startup of the Year in ! Hupro Japan Shibuya Toranomon In , is the winner! Toranomon Small Worlds Toshima In , is declared the Startup of the Year! Toshima Altplus Guangzhou, China came out as the Startup of the Year in ! Leyaoyao Guangzhou Hong Kong, Hong Kong In , is declared the Startup of the Year! Hong Kong Episode Six Kunming In , is the winner! Kunming Green A Sapporo In , is declared the Startup of the Year! Sapporo Polar Star Space Shirokanedai came out as the Startup of the Year in ! Nupp1 Shirokanedai Wuhan In , is the winner! Wuhan CSICEE Baoan, China In , is declared the Startup of the Year! Baoan Jumper Baoshan, China In , is declared the Startup of the Year! Baoshan Renren Games Chengdu, China came out as the Startup of the Year in ! Ju You Xi Chengdu Fujisawa, Japan In , is the winner! Fujisawa Scohia Pharma Fukuoka, Japan In , is declared the Startup of the Year! Fukuoka Kyulux Haidian, China came out as the Startup of the Year in ! 51vv Haidian Hongkou, China In , is the winner! Hongkou Kidstone Jiading, China In , is declared the Startup of the Year! Jiading IMRobotic Kawasaki, Japan came out as the Startup of the Year in ! QD Laser, Inc. Kawasaki Kyoto, Japan In , is declared the Startup of the Year! Kyoto Hacarus Minato, Japan In , is the winner! Minato Visionary Fun Nagoya, Japan came out as the Startup of the Year in ! Prodrone Nagoya Ningbo, China The winner in is . Ningbo OlymTech Corporation Aomori In , is declared the Startup of the Year! Aomori Forte Japan Bandai-cho In , is the winner. Bandai-cho Delta-Fly Pharm Changchun In , the Startup of the Year is . Changchun Kaidi Animation Fuchu In , is declared the Startup of the Year! Fuchu TMS Fukuoka-shi The winner in is . Fukuoka-shi SkyDisc Fukushima In , the Startup of the Year is . Fukushima Matsuri Technologies Gotanda In , is the winner. Gotanda Basset Hachioji In , is declared the Startup of the Year! Hachioji Adriakaim Harbin The winner in is J . Harbin oining Technology Iwaki In , is the winner. Iwaki Tao Engineering Izumo In , the Startup of the Year is . Izumo PuREC Kagoshima In , is declared the Startup of the Year! Kagoshima Farmers Support Kamakura In , the Startup of the Year is . Kamakura KAYAC Kami-meguro The winner in is . Kami-meguro Buzzreach Kanagawa In , is the winner. Kanagawa LoiLo Kashiwa In , the Startup of the Year is . Kashiwa Intelligent Surfaces Kita In , is declared the Startup of the Year! Kita Ax Robotix Kobe The winner in is . Kobe Coconomi Koriyama In , the Startup of the Year is . Koriyama Tocoton Kumamoto In , is the winner. Kumamoto Bloom Technology Kunitachi In , is declared the Startup of the Year! Kunitachi Trys Liaocheng The winner in is . Liaocheng Jinzheng Animation Minami In , is declared the Startup of the Year! Minami ATLAB Miyazaki In , is the winner. Miyazaki Caster Nagano In , is declared the Startup of the Year! Nagano Precision Forestry Nagaoka The winner in is . Nagaoka Plant Form Nihombashi-hamacho In , the Startup of the Year is . Nihombashi-hamacho Shizen Energy Niigata In , is declared the Startup of the Year! Niigata UniBio Japan Nishi-shinagawa In , is the winner. Nishi-shinagawa Play Heart Okayama In , is the winner! Okayama Arch Farm Okinawa In , is declared the Startup of the Year! Okinawa BlogNinja Otemachi In , the Startup of the Year is . Otemachi beBit, Inc Qingdao Shi In , is the winner! Qingdao Shi Manyoubang Quanzhou In , is declared the Startup of the Year! Quanzhou KungFu Animation Group Roppongi The winner in is . Roppongi Holo-X Saitama In , the Startup of the Year is . Saitama GameTector Sendai In , is the winner! Sendai Sendai Smart Machines Setagaya In , is declared the Startup of the Year! Setagaya Skyestate Shenzhen In , the Startup of the Year is . Shenzhen Aiator Shinjuku In , is declared the Startup of the Year! Shinjuku Scalar Shizuoka In , is the winner! Shizuoka PiPhotonics Sumida The winner in is . Sumida Holotch Tachikawa In , the Startup of the Year is . Tachikawa PlusOne Takamatsu In , is declared the Startup of the Year! Takamatsu Ken Robotec Tokushima In , is the winner! Tokushima DennoKotsu Toyonaka In , the Startup of the Year is . Toyonaka FISH BIOTECH Tsukuba In , is declared the Startup of the Year! Tsukuba WARPSPACE Wakayama In , the Startup of the Year is . Wakayama 4D Sensor Xiangzhou In , is the winner! Xiangzhou ALLiN Edutech Group Xianyang The winner in is . Xianyang TONLY Xiaoshan In , is declared the Startup of the Year! Xiaoshan GONGHUI Yamaguchi In , the Startup of the Year is . Yamaguchi Archis Yangpu The winner in is . Yangpu Tmxmall Yau Tsim Mong In , is the winner! Yau Tsim Mong Airnugget Yeoksamdong In , the Startup of the Year is . Yeoksamdong WizSchool Yichang In , is declared the Startup of the Year! Yichang Hubei Kento Electronic Yokohama In , is the winner! Yokohama Next Innovation Yubei In , the Startup of the Year is . Yubei Ophiux Network Yueqing The winner in is . Yueqing Yueqing Easythink Media Zhuhai In , is the winner! Zhuhai Aijuba Hongo In , the Startup of the Year is . Hongo Smile Robotics, Inc Admiralty In , is declared the Startup of the Year! Admiralty BUNCH Southern In , the Startup of the Year is . Southern Retykle Yongdungpo In , is the winner! Yongdungpo Push News Taichung In , is declared the Startup of the Year! Taichung Wondercise Cyberport, Hong Kong In , the Startup of the Year is . Cyberport Animoca Brands Hefei, China In , is the winner! Hefei Tsinglink New Territories, Hong Kong The winner in is . New Territories, Hong Kong Zeek Dezhou In , the Startup of the Year is . Dezhou Dezhou Baji Kitakyushu In , is declared the Startup of the Year! Kitakyushu Reif Seongnam In , is the winner! Seongnam EOFlow Yanshi In , the Startup of the Year is . Yanshi CASI Vision Top Startup Cities in South Asia Hyderabad, India The Startup of the Year in is with 962 votes Hyderabad Quixy Lahore, Pakistan is the Startup of the Year! It came out ahead with 186 votes. SmartWindows Lahore Bangalore, India When it comes to , is the Startup of the Year with 210 votes! Bangalore vBridge Hub Pune, India couldn’t be beaten for Startup of the Year in , it won with 129 votes! InfraCloud Pune Jaipur, India The Startup of the Year in is with 166 votes Jaipur Emizen Tech Lucknow, India is the Startup of the Year! It came out ahead with 279 votes. Keeros Superfoods Lucknow Noida, India came out as the Startup of the Year in with 156 votes! Bagisto Noida Mumbai, India When it comes to , is the Startup of the Year with 96 votes! Mumbai Sequretek Sylhet couldn’t be beaten for Startup of the Year in , it won with 122 votes! DataXpie Sylhet Mylapore, India In , is the winner! Mylapore Yalimart Goa, India In , the Startup of the Year is Goa Filter Coffee Delhi, India In , is declared the Startup of the Year! Delhi EkAnek Networks Karachi, Pakistan The winner in is Karachi Bykea Ahmedabad, India In , is the winner Ahmedabad MageComp Dhaka, Bangladesh The winner in is Dhaka SOLshare Islamabad, Pakistan In Islamabad, is declared the Startup of the Year! TAG Gurgaon, India In , the Startup of the Year is Gurgaon ixigo Bengaluru, India In , is the winner! Bengaluru Prakshep Private Limited Haryana, India couldn’t be beaten for Startup of the Year in ! Footprints Childcare Haryana Kolkata, India In , is the winner! Kolkata Wow! Momo New Delhi, India In , is declared the Startup of the Year! New Delhi Rusk Media Indore, India The winner in is Indore Chattar Patar Kormangala In , is the winner Kormangala Sanctum Technologies Ghaziabad came out as the Startup of the Year in Craftfurnish.com Ghaziabad! Mohali In , the Startup of the Year is Mohali DataKund Mysore The Startup of the Year in is Mysore Excelsoft Karnal came out as the Startup of the Year in ! Dunar Karnal Kolhapur In , is the winner! Kolhapur Zanvar Group Patiya In , the Startup of the Year is Patiya Kloud Project Kathmandu In , is declared the Startup of the Year! Kathmandu Vairav Technology Bangalore City, India In is the winner! Bangalore City, PagarBook Ernakulam The winner in is Ernakulam Epixel Solutions Colombo, Sri Lanka couldn’t be beaten for Startup in the Year in MAs Foods Colombo Andheri, India When it comes to , is the Startup of the Year! Andheri DoorMint Kanpur, India came out as the Startup of the Year in ! ServiceWalaa Kanpur Faisalabad In , is the winner! Faisalabad DigiKhata Nasik The Startup of the Year in is Nasik Sahyadri Farms Patna came out as the Startup of the Year in ! Asvin Tech Patna Chennai, India In , is the winner! Chennai Agnikul Cosmos Faridabad, India In , is declared the Startup of the Year! Faridabad UClean Panjim, India The winner in is Panjim TempoGO Ranchi, India In , is the winner Ranchi Osam Dairy Surat, India In , is declared the Startup of the Year! Surat Wishbook Thane, India In , is the winner! Thane Delight Foods Trivandrum, India came out as the Startup of the Year in ! GenRobotic Trivandrum Vijayawada, India In , the Startup of the Year is Vijayawada Eruvaka Technologies Visakhapatnam, India In , Ltd is declared the Startup of the Year! Visakhapatnam Greenline Labs Pvt Ahmadabad In , is the winner! Ahmadabad KiwiQA Services Bandra came out as the Startup of the Year in ! Car Club Bandra Bombay In , is the winner! Bombay Locobuddy Mobile Technology (Sportobuddy) Cochin In , the Startup of the Year is Cochin Tuttifrutti Interactive Gandhinagar In , is declared the Startup of the Year! Gandhinagar Kroop AI Guwahati In , the Startup of the Year is Guwahati GNRC Hospitals Jamshedpur In , is declared the Startup of the Year! Jamshedpur Intelliber Kabul The winner in is Kabul Miracle Shop (Vocinno Technology) Karur In , is the winner Karur Karur Vysya Bank Kochi The winner in is Kochi BestDoc Kozhikode In , is declared the Startup of the Year! Kozhikode OfficeKit HR Ludhiana In , the Startup of the Year is Ludhiana Trendy Beat Network Madhapur In , is the winner! Madhapur Head Digital Works Mangalore When it comes to , is the Startup of the Year Mangalore Hangyo Nagpur came out as the Startup of the Year in ! UPrudence Agro Nagpur Rawalpindi The Startup of the Year in is Rawalpindi Pro Options Marketing Rishikesh came out as the Startup of the Year in ! Descatuk Rishikesh Secunderabad couldn’t be beaten for Startup of the Year in Prakriti Biosystems Engineering Secunderabad Tirupur In , is the winner! Tirupur Tubeknit Fashions Udupi The winner in is Udupi Krishitantra Top Startup Cities in Southeast Asia Singapore, Singapore The Startup of the Year in is with 6556 votes! Singapore Cake DeFi Hanoi, Vietnam is the Startup of the Year! It came out ahead with 683 votes. DeFi For You Hanoi Kuala Lumpur, Malaysia came out as the Startup of the Year in with 109 votes! Trambellir Kuala Lumpur Pasig, Philippines When it comes to , . is the Startup of the Year with 110 votes! Pasig Quickreach Inc Bangkok, Thailand couldn’t be beaten for Startup in the Year in , it won with 60 votes! Perception Codes Bangkok Johor Bahru In , the Startup of the Year is . Johor Bahru AGR1 Bandung, Indonesia In , is declared the Startup of the Year! Bandung Prosa Portugal The winner in is . Portugal SCEMAI Tangerang, Indonesia In , is the winner Tangerang Yummy Corp Jakarta, Indonesia In , is the winner! Jakarta Tokocrypto Dki Jakarta, Indonesia In , is declared the Startup of the Year! Dki Jakarta Limakilo Bangkok Metropolis In , is the winner! Bangkok Meticuly Medan The winner in is ! Medan DIKA Manila, Philippines In , is declared the Startup of the Year! Manila PawnHero Phnom Penh, Cambodia In , the Startup of the Year is Phnom Penh vKirirom Bali In , is the winner! Bali Radius App Penang When it comes to , is the Startup of the Year Penang EasyParcel Surabaya came out as the Startup of the Year in ! Super Surabaya Setiabudi, Indonesia The Startup of the Year in is Setiabudi Chilibeli Cebu City came out as the Startup of the Year in MiCab Cebu City! Jawa couldn’t be beaten for Startup in the Year in DAUR Jawa Ho Chi Minh City, Vietnam In , is the winner! Ho Chi Minh City Pharmacity Selangor, Malaysia is the Startup of the Year! BabyDash Selangor Jakarta Pusat, Indonesia In , is the winner! Jakarta Pusat StickEarn Semarang When it comes to , is the Startup of the Year! Semarang Food Bear Petaling Jaya, Malaysia The winner in is . Petaling Jaya Deemples Kebayoran Baru, Indonesia couldn’t be beaten for Startup in the Year in ! Yogrt Kebayoran Baru Kuningan The winner in is . Kuningan Prinzio Bukit Merah came out as the Startup of the Year in ! DC Alliance Bukit Merah Huai Khwang In , the Startup of the Year is . Huai Khwang AppMan Co.,Ltd Kuta In , is declared the Startup of the Year! Kuta Gringgo Mandaluyong came out ahead as the Startup of the Year! Work Inspire Mandaluyong Midview City In , is the winner! Midview City BioMers Phuket The Startup of the Year in is ! Phuket Sapahn Yangon, Myanmar The winner in is . Yangon Wave Money Denpasar When it comes to , is the Startup of the Year! Denpasar Revasi Nakhon Ratchasima, Thailand The winner in is . Nakhon Ratchasima Siam Lottery co., Ltd Taguig, Philippines In , is the winner! Taguig PayMongo Bogor came out as the Startup of the Year in ! TIRANYX Bogor Senai, Malaysia won as the Startup of the Year. Nutrition Technologies Senai Bekasi Kota couldn’t be beaten for Startup in the Year in ! 8villages Bekasi Kota Top Startup Cities in Middle East Tel Aviv, Israel The Startup of the Year in is with 1,065 votes! Tel Aviv hyro Beirut, Lebanon is the Startup of the Year! It came out ahead with 1,276 votes. Hovi Digital Lab Beirut Riyadh, Saudi Arabia With 350 votes, came out as the Startup of the Year in ! Flicron Riyadh Tel Aviv-yafo, Israel When it comes to , is the Startup of the Year with 167 votes! Tel Aviv-yafo Cymbio Haifa, Israel couldn’t be beaten for Startup in the Year in , it won with 183 votes! Pico Haifa Amman, Jordan In , with 141 votes, is the winner! Amman Edexy Dubai, United Arab Emirates In , the Startup of the Year is with 74 votes. Dubai Ziina Doha, Qatar In , is declared the Startup of the Year! Doha SkipCash Tehran, Iran The winner in is . BeyondBoard AR Tehran Jerusalem, Israel In , is the winner! Jerusalem SolidBlock Rishon Le Zion The Startup of the Year in is ! Rishon Le Zion Passparto Ness Ziona, Israel is the Startup of the Year! Soapy Ness Ziona Kuwait, Kuwait came out as the Startup of the Year in ! Brapper Shop Kuwait Manama, Bahrain couldn’t be beaten for Startup in the Year in ! Doctori Manama Lod, Israel is the winner in ! Phinergy Lod Agudat Israel, Israel When it comes to is the Startup of the Year with [vote ] votes! Agudat Israel, Aqaurius Engines Beersheba, Israel In , the Startup of the Year is . Beersheba Visual Estate Ltd Giv'atayim, Israel In , is declared the Startup of the Year! Giv'atayim WSC Sports Modi'in, Israel The winner in is . Modi'in Loginno Nazareth, Israel In , is the winner! Nazareth AR Guide In Medical Ramat Gan, Israel The Startup of the Year in is . Ramat Gan Datos Health Baghdad When it comes to , is the Startup of the Year! Baghdad Mishwar Khobar In , the Startup of the Year is . Khobar Garage Misgav couldn’t be beaten for Startup in the Year in ! Eden Shield Misgav Sharjah came out as the Startup of the Year in ! Bookends Sharjah Affula In , the Startup of the Year is . Affula eMotion Technologies Bene Beraq, Israel In , is the winner Bene Beraq Reflectiz Caesarea, Israel In , the Startup of the Year is . Caesarea CardiacSense Dubayy In , is declared the Startup of the Year! Dubayy North Ladder Muscat couldn’t be beaten for Startup in the Year in ! iLab Marine Muscat Tirat Carmel In , the Startup of the Year is . Tirat Carmel PassCall Advanced Technologies Hod Hasharon, Israel The winner in is . Hod Hasharon Idomoo Holon, Israel came out ahead as the Startup of the Year! OptimalPlus Holon Jeddah, Saudi Arabia When it comes to , is the Startup of the Year! Jeddah Arabian Combustion Technologies Ramat Hasharon, Israel is the Startup of the Year! Lumen Ramat Hasharon Al Khobar came out as the Startup of the Year in ! Swyft Al Khobar Bet Shemesh In , is the winner! Bet Shemesh Degania Medical Binyamina When it comes to , is the Startup of the Year! Binyamina OncoHost Makkah In , the Startup of the Year is Makkah Scimagine Or Akiva Last but not least, couldn’t be beaten for Startup in the Year in the city of ! WMT Or Akiva More Information: If you’re a winner, please answer ! If you’re a reader, participant, just a curious individual, consider answering one of our interviews . this interview here Read the FAQs about or . Startups here here To see all of the winners you may visit , pick any city and view the name that appears at the top. this site If you’re interested in partnering with us, we invite you to look through some of these or reach out to our business department. unique sponsorship options Perhaps creating your very own tickles your fancy or maybe you have a whole new idea for how we can partner! writing contest Thank you to all of our sponsors! We truly appreciate your contribution to the tech world and thus the future! The Startups Awards are sponsored by: , , , , , , , , , , Blockster Brex FreeCodeCamp LaunchDarkly Coil Udacity Udemy Vercel Asia Pacific Transgender Network Bybit Everscale Network The post was written by Kushal Tamrakar and Valerie Ejegi, edited by Hang Ngo. If you have any questions or concerns or would like to report a discrepancy please email ellen@hackernoon.com.

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