My dad was in the military. I can’t count the number of times he said these words to me

Over the recent years, there has been a lot of advancements in this area, but these newly added libraries aren’t even close to their strong competitors like Kotlin, Swift and Java.Although Python dominates the fields of Data Science and Machine Learning, and, to some extent, Scientific and Mathematical computing, it does have its share of disadvantages when compared to newer languages like Julia, Swift and Java.It’ll take me a while to reap the fruits of this income stream (i.e., live off of it, all or in part), but it would also take me a while (probably much longer) to see the benefits of real estate price appreciation. Because, again, I need someplace to live. Being house rich would not work for me.

Ever since Python was released in the early 1990s, it has generated a lot of hype. Sure, it took the programming community at least 2 decades to appreciate its existence, but since then, it has far surpassed C, C#, Java and even Javascript in popularity.


1*V8UCZJ_7hMc5Axm_PZKZqQ.jpegThe more I look back on how long I spent in pain, the more I realize that I really did believe my pain was the result of some moral failing, like if only I wasn’t so lazy or weak, I’d have learned to straighten it out (literally). “One of the greatest difficulties we have is that posture like many other qualities of the body is also associated with character,” Gilman says.Yet another reason for Python’s versatility is its heavy usage by enterprises (FAANG included) as well as countless smaller ventures. Today, you’ll find a Python package for pretty much anything you can think of — for scientific computing, you’ve got Numpy, Sklearn for Machine Learning and Caer (my Computer Vision package) for Computer Vision.
I’m presently obsessed with economic psychology. The branch of psychology that “deals with decisions (individual or interactive), preferences, judgments, and factors influencing these, as well as the consequences of judgments and decisions for economics and society.”
The language, at its very core, emphasised extensively on code readability. With its concise and expressive syntax, it allowed developers to express ideas and concepts without writing tons of lines code (as would be the case in lower-level languages like C or Java). Its simplicity a given, Python seamlessly integrates with other programming languages (like offloading CPU-intensive tasks to C/C++), making it an added bonus to polyglot developers.

I’d rather take the money I have left — after ensuring I’m cash secure — and invest it in dividend-paying stocks. This is where I choose to invest a bulk of my money. Not in a house. I’ll forgo the appreciation we see in frothy housing markets in favor of the aforementioned cash security. I’ll opt for the power of compounding and the exponentially growing income stream this style of stock market investing brings.
One of the major reasons for Python’s slowness is the presence of GIL (Global Interpreter Lock) which allows only one thread to execute at a time. While this boosts the performance of single threading, it places a limitation on parallelism where developers have to implement multiprocessing programs as opposed to multi-threaded ones, to improve speeds.This article is for informational purposes only. It should not be considered Financial or Legal Advice. Not all information will be accurate. Consult a financial professional before making any major financial decisions.When objects go out of scope, Python has automatic garbage collections. It aims to remove a lot of the complexities involved in memory management that C and C++ involve. Owing to the flexibility (or lack thereof) of specifying data types, the amount of memory Python consumes can quickly explode.Among the major reasons why Python is “slow”, it really boils down to 2 — Python is interpreted as opposed to compiled, ultimately leading to slower execution times; and the fact that it is dynamically typed (data types of variables are automatically inferred by Python during execution).I keep more than ample cash on hand in an emergency and other funds, so I feel cash secure. I would never spend — or invest — this money on a mortgage down payment. Money sitting in home equity would feel so far away from me. And, practically, it is. If I needed the cash, I couldn’t access it because I need a place to live. (Don’t tell me to take out a home equity loan!).

Take, for example, TensorFlow, a Machine Learning library available in Python. These libraries were actually written in C++ and made available in Python, sort of forming a Python “wrapper” around the C++ implementation. The same goes for Numpy and, to an extent, even Caer.1*DuC__vD9r59ErqhDAnDdeQ.jpegThis is probably a no-brainer. Speed is generally considered to be one of the key focuses of a developer and will probably continue to be for an unforeseeable amount of time.


One of the main driving points behind Python’s meteoric growth was how easy it was to learn and how powerful it was to use, making it extremely appealing to beginners and even those who shied away from programming because of the hard, unfamiliar syntax of languages like C/C++.




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