[Functional Programming In JavaScript: How To Improve Your JavaScript Programs Using Functional Techn
Laurice Whack
Functional Programming in JavaScript teaches JavaScript developers functional techniques that will improve extensibility, modularity, reusability, testability, and performance. Through concrete examples and jargon-free explanations, this book teaches you how to apply functional programming to real-life development tasks
In complex web applications, the low-level details of your JavaScript code can obscure the workings of the system as a whole. As a coding style, functional programming (FP) promotes loosely coupled relationships among the components of your application, making the big picture easier to design, communicate, and maintain.
Functional Programming In JavaScript: How To Improve Your JavaScript Programs Using Functional Techn
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Functional Programming in JavaScript teaches you techniques to improve your web applications: their extensibility, modularity, reusability, and testability, as well as their performance. This easy-to-read book uses concrete examples and clear explanations to show you how to use functional programming in real life. If you're new to functional programming, you'll appreciate this guide's many insightful comparisons to imperative or object-oriented programming that help you understand functional design. By the end, you'll think about application design in a fresh new way, and you may even grow to appreciate monads!
In the solution we are also using ["Title"] and ["imdbRating"], which are in the original array, but we are adding them into our function, not pulling them from the original array, as the instructions ask us to do. So this solution does not comply with the instructions.
This article gives a brief introduction to the concept and usage of callback functions in the JavaScript programming language. Functions are Objects The first thing we need to know is that in Javascript, functions are first-class objects. As such, we...
this function can be written with implicit return, and you do this by not using the graph parenthesis that indetify the function body and not using the return keyword
with implicit return you put the value to return immediately to the right of the arrow
if you want to return an object with implicit return you need to make sure that the graph parenthesis are not mistaken for those delimiting the function body, so you wrap the value to return in round parenthesis
map will return an array where each element is the returned value from the callback when the element at that index in the original array is passed in: [func(arr[0]), func(arr[1]), ... , func(arr[arr.length - 1])]
we are not adding those, we are creating a new object that has only those two properties - the original object has many more properties, so we are actually extracting just those two properties from there.
in the definition of the method, which for these methods is already present in the language.
here two challenges in which you need to write the logic of the methods yourself:
-algorithms-and-data-structures/functional-programming/implement-the-filter-method-on-a-prototype
-algorithms-and-data-structures/functional-programming/implement-map-on-a-prototype
I thought that the map method was iterating over the items in an array in the same way that a loop would - one-by-one. If so, then we should be able to use the push method, just like with a loop, right?
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We all know that real production code is not as simple as these examples, so in reality, our code base gets cluttered with a lot of boilerplate checks for the presence of a value before attempting to do some operation using it. I am a functional programming fan, although I never tell anyone that it is better than other paradigms (like OOP). Instead, I encourage developers to learn this paradigm and then find ways to combine it with OOP, taking the best of both words, and creating a powerful combination.
1- map: It takes a function, and if the value exists, applies that function on the value and returns a new value inside the same Maybe container (although a new instance). If the value is not there, it will just return a Maybe wrapping undefined.
We are not going to use a function to curry our functions here, instead, we will curry them manually, you can find such function in libraries like ramda. Bear in mind that in production code, you will want to use a function to curry your functions for you (instead of doing it manually), although you should know that the curry function and default parameters do not play nicely if combined together. If you used such function, it would look like this:
Noticed that the add function used above is the curried version. The pipe function reads top to bottom (or left to right), if you feel more comfortable reading bottom to top (or right to left), then the function you want to use is compose, it does the same that pipe, but starting with the bottom/right most function. You could implement compose like this (basically using reduceRight instead of reduce):
There are several JavaScript libraries that provide you with the functional constructs you need to write functional programs, some of the most famous ones are ramda, underscorejs, lodash and folktale. I encourage you to take a look at them, and use them (instead of using your own implementations) whenever feasible and possible.
Hence I spent the last three months figuring out how to improve my coding interview skills and eventually received offers from big tech companies like Google, Facebook, Airbnb, Lyft, Dropbox and more.
Many of the algorithmic concepts tested in coding interviews are not what I usually use at work, where I am a Front End Engineer (web). Naturally, I have forgotten quite a bit about these algorithms and data structures, which I learned mostly during my freshmen and sophomore years of college.
I used to think that being able to think, code, and communicate simultaneously was an impossible feat, until I realized that most people are just not good at coding interviews when they first start out. Interviewing is a skill that you can get better at by studying, preparing, and practicing for it.
My recent job search has led me on a journey to improve my coding interview skills. Front End Engineers like to rant about how the current hiring process is broken because technical interviews can include skills not related to front-end development. For example, writing a maze solving algorithm and merging two sorted lists of numbers. As a Front End Engineer myself, I can empathize with them.
Front end is a specialized domain where engineers have to care about many issues related to browser compatibilities, the Document Object Model, JavaScript performance, CSS layouts, and so on. It is uncommon for front-end engineers to implement some of the complex algorithms tested in interviews.
From my experience as an interviewer, most candidates pick Python or Java. Other languages commonly selected include JavaScript, Ruby, and C++. I would absolutely avoid lower-level languages like C or Go, simply because they lack standard library functions and data structures.
One of the top reasons I recommend Python is that it uses consistent APIs that operate on different data structures, such as len(), for ... in ... and slicing notation on sequences (strings, lists, and tuples). Getting the last element in a sequence is arr[-1] , and reversing it is simply arr[::-1]. You can achieve a lot with minimal syntax in Python.
Java is a decent choice too. But because you will have to constantly declare types in your code, it means entering extra keystrokes. This will slow down the speed at which you code and type. This issue will be more apparent when you have to write on a whiteboard during on-site interviews.
The reasons for choosing or not choosing C++ are similar to Java. Ultimately, Python, Java, and C++ are decent choices. If you have been using Java for a while, and do not have time to become familiar with another language, I recommend sticking to Java instead of picking up Python from scratch. This helps you to avoid having to use one language for work and another one for interviews. Most of the time, the bottleneck is in the thinking and not the writing.
If you need to use a data structure that the language does not support, such as a queue or heap in JavaScript, ask the interviewer if you can assume that you have a data structure that implements certain methods with specified time complexities. If the implementation of that data structure is not crucial to solving the problem, the interviewer will usually allow it.
If you have been out of college for some time, it is highly advisable to review the CS fundamentals. I prefer to review it as I practice. I scan through my notes from college and revise the various algorithms as I work on the algorithm problems from LeetCode and Cracking the Coding Interview.
Practice and solve algorithm questions in your chosen language. While Cracking the Coding Interview is a good resource, I prefer solving problems by typing code, letting it run, and getting instant feedback.
There are various Online Judges, such as LeetCode, HackerRank, and CodeForces for you to practice questions online and to get used to the language. From my experience, LeetCode questions are most similar to the questions asked in interviews. HackerRank and CodeForces questions are more similar to questions in competitive programming.
After completing a question on LeetCode, I usually add the time and space complexities of the written code as comments above the function body. I use the comments to remind myself to communicate the analysis of the algorithm after I have completed the implementation.
Learn about and be familiar with the common pitfalls and caveats of the language. If you point them out during the interview and avoid falling into them, you will earn bonus points and impress the interviewer, regardless of whether the interviewer is familiar with the language or not.
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