20 Must-Follow Guidelines For Python Developers

The article contains a compiled list of 20 guidelines that all Python coders should attempt to follow.

Each guideline is further supported with a suitable code snippet.

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blog_number = 1
my_blog = f'This is my blog number: {blog_number}'
This will return This is my blog number: 1
import io
file = io.open("my_file", mode="r", encoding="utf-8")
file = open('my_file', 'w')try:
file.write('this is a fintechexplained blog')
# using with statement
with open('my_file', 'w') as file:
file.write('this is a fintechexplained blog')
class MyNewException(Exception):
raise MyNewException
#critical code section
except ValueError as err:
#handle error
def get_result(input):
if input == 'a':
return True
elif input == 'b':
return False

#default case

Understanding Must-Know Front Office Trading Lingo, Stock Market, Trades, Bonds, Shares, Bid-Ask Spread

This article is written for the readers who want to understand the terminology that is used in the trading world.

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Article Aim

My aim is to explain the most common phrases and trading terminology in this article.

The goal is to explain each term in a way that can prepare us for the subsequent terms in the article.

This article provides a high-level overview of the trading keywords. My aim is to keep the article simple and straight-forward.

I will explain the terms with questions and answers.

1. Is the stock market bullish or bearish today?

Let’s start with the first key terms: stock market, bullish and bearish.

  • The stock market is where the traders buy/sell shares (stocks). …

The Must-Know Python 3.9 Features

The latest Python 3.9.0 final version is out on the Monday, 2020–10–05

Just like most of the Python fans, I am super excited to explore and use the latest features. This article will provide an overview of the must-know features of Python 3.9.

This is again an exciting time for the Python programmers.

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Image By Author

I read through the Python 3.9 release notes and the associated discussions. Based on the information, I wanted to write a comprehensive guide so everyone can get a glimpse of the features along with their detailed workings.

Before I begin, I have to say, I am very excited to explore version 3.9 as some of the features are definitely going to be used in my applications. …

Guidelines & Idioms When Using Multiple Processes In Python

One of the quickest and safest techniques to scale up the application is to launch multiple Python processes in an application. This also helps us by-pass the famous GIL issue.

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Guidelines for multiple Python processes

The challenge of launching multiple processes is that it can cause unintended problems if the application is not designed appropriately.

I have written 12 top guidelines that I recommend everyone to follow. This article aims to outline the programming guidelines for multiple processing programming.

I recommend this article to everyone who is/or intends in using the Python programming language.

If you want to understand the Python programming language from the beginner to an advanced level then I highly recommend the article…

Learn How To Use Python Synchronisation Primitives

Most of the enterprise-level high-performant computationally-intensive applications are concurrent and parallel in nature. The advanced features of concurrency and parallelism are usually used to enhance the performance of an application.

One of the biggest challenges in the concurrent and parallel applications is to be able to share the data between threads, asyncio routines, and/or processes.

This is where we can use the synchronization primitives. This article will aim to explain what they are and when to use them.

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Synchronisation Primitives

Article Aim

This article will help us understand what Python Synchronisation Primitives are which can be used to share the data between processes/threads/tasks.

I will start by providing a brief overview of concurrency and parallelism concepts in general. I will then provide an overview of the basic synchronisation primitives along with the information on when to use them. …

Outlining the steps to download news from Google via Python code

All successful projects revolve around clean data. Google is by far the best search engine. Furthermore, Google News is a fantastic source that combines news from various media and publishers.

I will demonstrate how we can build data sets for data science projects by using news from Google News. I wanted to be able to fetch Google News via Python code so that I can get the latest news daily without any manual intervention.

This article will demonstrate the steps that are required to retrieve google news for our chosen topics, words, and locations via Python code.

I will present two methodologies that can be utilized to get news from Google News. …

Introducing Expert Data Scientists Skills Along With The Best Practices & Successful Data Science Project Steps

Data Science is a hot topic nowadays. Organizations consider data scientists to be the Crème de la crème. Everyone in the industry is talking about the potential of data science and what data scientists can bring in their BigTech and FinTech organizations. It’s attractive to be a data scientist.

This article will outline everything we need to know to become an expert in the Data Science field.

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A topic on Expert Data Scientists. Image by author

During tough times, data scientists are required even more because it’s crucial to be able to work on projects that cut costs and generate revenue. …

Learn What Signaling Is And How To Generate Signals In Your Python Application

Operating systems use signals to communicate with the processes. There is not a lot of content on Python signals on Medium, even though they are heavily used in enterprise-level applications. This article will demonstrate what signals are and how they can be used in Python applications.

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Article focuses on the signal library

This article will focus on signal driven programming. Signaling is used in a large number of Python packages such as Django, Flask, FastAPI etc.

The signaling concept is widely used in a number of enterprise-level industry applications and is a must-know topic for all programmers who want to become an expert in Python programing language. …

Learn How To Boost Performance Of Frequent Long-Running Operations In Python

Caching is an important concept to understand for every Python programmer.

In a nutshell, the concept of caching revolves around utilising programming techniques to store data in a temporary location instead of retrieving it from the source each time.

Subsequently, caching can provide an application performance boost as it is faster to access data from the temporary location than it is to fetch the data from the source each time, such as from database, web service, etc.

This article aims to explain how caching works in Python.

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This is an advanced level topic for Python developers and I recommend it to everyone who is/or intends in using the Python programming language. …

Explaining How To Detect & Resolve Performance Bottlenecks

No one wants a slow data science application. Not when it is required to be consumed by high-demanding users who expect a quick turn around.

Profiling is one of those concepts that every Python programmer must be familiar with. It is required to become an expert in the programming field. This is an advanced level topic for Python developers and I recommend it to everyone who is/or intends in using the Python programming language.

We can learn the Python library and understand how to create objects and modules, but the true Python experts emerge when they encounter and fix tough technical issues. …


Farhad Malik

My personal blog, aiming to explain complex mathematical, financial and technological concepts in simple terms. Contact: FarhadMalik84@googlemail.com

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