Computers work by a set of instructions which are written by human beings. The collection of instructions is referred to as programming. Computer programming is, therefore, a set of guidelines a machine is supposed to execute. The two core elements of programming are data and interpretation of instructions. When writing computer instructions, People use various kinds of languages. These are referred to like computer programming languages. This article explores some of the tiring things that we keep on hearing about Python programming. However, when you Learn Python Programming, you will acknowledge that they don't have any weight.
Weakly Typed Members
Python is a weakly-typed language meaning that its safety is low. Whereas a strongly-typed programming language checks the kind of variables before operating, a weakly-typed language does not. The casts in a strong language typed language are explicit, but a weakly typed language has implicit casts.
Although the pro-python evangelists keep saying that the language is dynamic, the complexity of a codebase may overwhelm the developer and hurt their productivity. Besides, the overhead costs associated with dynamically typed languages are high. Due to this weakness, many developers spend lots of time and energy to infer the kinds of boilerplate code manually.
Another weakness of Python that its evangelists overlook has to do with multiple errors that are revealed at runtime. These mistakes may not be discovered at the stage of testing but during runtime. Strongly-typed programming languages verify that they offer error-free software. For instance, the strongly-typed languages use type-checking compilers that provide an elevated level of safety and security, which minimizes mistakes during runtime.
In case you're writing a serious code, minimizing error should be one of your priorities. The lack of security in Python should concern any programmer writing a critical code. Python has come up with various strategies like the use of Jedi, pytype, and others to offset the, but many programmers don't use them. This is because the libraries, as mentioned earlier, don't belong to the standard toolchain and require much time and effort to update.
Although proponents of python market it as a dynamically-typed programming language, its level of security is low, given the fact that errors are likely to occur during runtime. The words used to describe it are meant to market it as the best language. Yet many people who understand the Python are tired of big words that are used to describe the language like dynamically-typed language that doesn't add any value in the security of the language.
The Global Interpreter Lock
Modern software has numerous threads and multicore. Additionally, the current programming language requires concurrency primitives. Python ships are, however, limited as they can only run on one thread. This is because Python runs on the Global Interpreter Lock (GIL). When computers had one core, this was no problem. However, times have changed, and the current machines are developed with numerous processors. At this point, the use of GIL doesn't augur well between CPU processors and concurrent programs.
People keep saying that Python is a quick programming language. However, in reality, Python is in terms of multi-thread and concurrency aspects. Additionally, Python is slow when performing different tasks, including computational and I/O tasks. The programming language also is handicapped in terms of invocation overhead.
Because of its slowness, Python is not ideal for real-time processing that can modify vast volumes of data across multiple computers.
The never-ending divide between Python and Python 3
A schism has emerged between python 2 and python 3 supporters. Most developers started with python 2 but as time went by, python 3 emerged. The developers on python 2 may want to upgrade to the new python 3 which has lots of tools in its library. However, developers have realized that some computers do not support the installation of Python 3 programs. This has seen to the emergence of two camps within the python development projects.
In some organizations, two camps have emerged that are either pro-python 2 or pro-python 3. Although small companies can choose a specific version of Python that supports their projects, the big institutions have witnessed the emergence of two python camps. Because machines installed with python 2 can't accept the Python 3 codes, bridging the two factions is almost impossible.
Python has a limitation in writing code either backward or forwards. This weakness frustrates many developers working on python projects.
Encapsulation and packaging
In Python, abstractions are leaky, and the code is accessible to anybody from wherever they're. Some of the classes may contain members that may be risky if executed outside their defined boundaries. There are two kinds of members including 'protected' and those regarded as 'private'. Because Python lacks a privacy model, the interpreter may choose to mangle and shield namespaces if they apply inheritance. The mangled class members are still accessible.
You may find the above state of affairs disturbing, especially if you come from a Java background. Java and C/C++ have modifiers that encapsulate information, make it possible to access data, and facilitate actions on the data.
Python is a messy system
Most developers find it messy constructing and importing python dependencies. You may never accomplish your plans for building a serious software program using Python. Because the Program always messes up the application of specific aspects like numby library, you may never use the best modules like MATLAB, Octave, and others.
Python is a slow programming language
In case you require a quick programming language, you should never select Python as it's lax compared to other languages like C and C++. The main theories behind Python's slowness include its Global Interpreter Locker; Python is an interpreted language, and Program is dynamically typed.
Mobile application and development
Python is not the best language in mobile apps and development. The Program lacks the robustness that is critical in any language applied in mobile computing. Most mobile application programs like Carbonnelle may not be constructed on Python.
It's clear that at the time of its inception, Python didn't have Android and iOS on their mind. To offset the weakness, Python has come up with programs like Kivy and BeeWare that are mobile-friendly. However, the programs mentioned above are still weak compared to other mobile application programs like Java, Swift and others.
In case you've tasks that require expansive memory, Python may not assist you. Python also consumes tons of memories because of its flexibility with various data-types.
Python is poor in Enterprise Development
Due to its weak and primitive database layer, it's challenging to access Python's database. This means that the Program can't be applied in sophisticated legacy data for specific enterprises. This makes the Program not suitable for enterprises that require smooth interaction for advanced legacy data.
Python also lacks support tools like GUI equipment, multiprocessor aid, and commercial access points. These weaknesses make Python unsuitable language for enterprise development.
Despite some people hailing Python as the best programming language, it has different weaknesses that many don't know. Although the evangelists of Python keep heaping praises to the programming language, it has its fair share of flaws including:
• Poor utilization of memory
• Weak in enterprise development
• Weakly typed language