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Given the technical sophistication of our always-on interconnected world it might surprise you to learn that the first general-purpose programming language did not arise with Charles Babbage’s difference engine or the delightfully pre-Victorian Ada Lovelace but instead came into existence in Germany as recently as 1945, well within living memory.
Plankalkül, as it was known, had features we would recognize today such as branches and loops. It was sophisticated enough that its inventor, Konrad Zuse, designed a chess program with it. It’s odd how often chess crops up as a problem to solve programmatically. Zuse might have enjoyed greater recognition as a household name were it not for the fact his algorithmic genius was blossoming in the midst of a global war.
In the 76 years since Zuse produced that first programming language at least 700 more have come into existence.
Today there is a vast mixture of ways to pass instructions to a computer in the form of a program. Some are natural evolutions of earlier members of a similar language such as that of C and C++. Some are extremely specialized like the Transputer-focused Occam, while others are intensely esoteric and arguably intended as a practical joke such as “Whitespace” whose instructions are composed entirely of spaces, tab, and linefeed characters.
Nestling comfortably in the oeuvre of practical, stable and usefully general-purpose programming languages are two that have stood the test of time: Object Pascal (Delphi) and Python.
Object Pascal was the original name of the object-oriented programming language used in the software product Delphi that offers an integrated development environment (IDE) designed to enable rapid application development (RAD) of a broad range of software.
The Object Pascal language evolved as an extension of the original Pascal language. This object-enhanced version of Pascal was developed by Apple Computer and came into being in consultation with Pascal's inventor Niklaus Wirth in the mid-1980s.
Apple’s particular flavor of Object Pascal was used extensively for their Mac operating systems and applications. The language was sufficiently abstract and “high level” that it could simplify the development of complex applications and yet retain sufficient “low level” power to allow widespread adoption as the primary language of choice for Apple’s Macintosh software.
One of the Object Pascal implementations was later refined with a series of extensions by the Borland Software Corporation culminating in February 1995 with the release of version 1.0 of its Delphi language and IDE.
Delphi quickly became wildly popular and soon established itself as the dominant implementation of object orientated Pascal. As a result of this broad market recognition the names Object Pascal and Delphi often appear interchangeably.
The modern programming community refers to both the Delphi flavor of the Object Pascal language and the integrated development environment – the code editor, compiler, and debugger - as ‘Delphi,’ and we will refer to it as Delphi for the remainder of this article.
From 2015 to date, Delphi has been owned and distributed by Embarcadero, based in Austin, Texas.
There was definitely something special about the 1980s and 90s. While Pascal was evolving into Object Pascal and Delphi was readying itself to reveal its low-code, visually driven design, another programming giant was emerging. This new language was called Python and it proved to be every bit of a game changer as its 90s contemporary, Delphi.
Python is a general-purpose interpreted programming language designed by Guido van Rossum in the 1980s as a successor to his ABC programming language. Its official release took place in 1991 with the name Python 0.9.0.
Today Python enjoys wide recognition as one of the most popular programming languages in the world.
Delphi and Python share an emergence in the same time frame and both continue to evolve to take on new advances in technology, incorporate new programming paradigms and techniques, and adapt to advances in computing hardware and operating systems.
Let’s take a look at how they differ and how their relative strengths complement each other as well as ways they can actually work in harmony to augment their respective capabilities into a combined strength greater than the two halves.
Overall, Delphi has more diverse features than Python, lending it more commercial relevance than its counterpart, particularly for the end-user consumer and business-to-business market sectors.
Delphi’s ‘platform native’, fully compiled code applications are quicker, more secure, and resistant to casual interference. Additionally, Delphi supports a wider range of execution platforms, particularly for mobile devices.
Python benefits from its open-source nature and a correspondingly lower cost of entry which have helped it gain widespread adoption.
Programming languages require the conversion of the human readable source code into raw machine instructions which can be executed by the computer.
With Delphi, this conversion takes place directly within its integrated editor environment where the compiler produces fully compiled applications ready to execute without further pre-processing and, typically, no further support components or installable runtimes.
Python takes an approach where the code requires a runtime interpreter installed on the end user’s own computer to accomplish the conversion when One wishes to execute a program or application written with it.
The runtime interpretation is fast but it’s still no match for programs which are already pre-compiled and as a result, programs written in Delphi run significantly faster than Python apps.
Python programs are delivered either as plain text files or as partially pre-compiled modules. Both of these forms are easily examined – in the case of the text source files anyone can view them without any special tools at all.
In many internal business and home scenarios it might not be a problem for the Python program’s source code to be easily open to examination and in fact can be a significant advantage for the types of use case where a user needs or wishes to customize the behavior or outcomes of the Python program.
Generally, for a commercial program aimed at generating a profit and targeted at a home user or business market the internal workings of the program are considered ‘intellectual property’ and are closely guarded from being revealed.
For scenarios involving security or valuable private items such as access keys and tokens it can often be absolutely essential to make sure the source code of the program maintains its unadulterated integrity – and of the two, only Delphi could ensure the highest confidence in that uncompromised fidelity.
The balance between ease of modification and the mitigation of that modification being an unauthorized thing such as the actions of a hacker plays heavily into which of the two, Delphi or Python, best fits the requirements of the desired solution.
Delphi is a statically typed programming language, while Python is a dynamically typed one.
This means that Delphi's code is ‘type-checked’ at compile-time, but for Python, this happens at runtime.
The Delphi IDE combined with the static typing helps identify potential problems in the code before the program’s use by the end-user.
Code execution is often faster with static typing because of the elimination of the need for the variable types to be identified and checked as the program runs allowing for optimizations which are impossible with Python’s runtime interpretation.
Some developers may still prefer the dynamic typing nature of Python as it offers some benefits for less restrictive code structures.
Both languages take slightly different approaches to how the actual code is laid out, but perhaps the one major difference is in how Python and Delphi code blocks are indented.
For code indentation, Python requires rigid consistency since it forms part of the syntax of the language.
For instance, in Python 3, if you initially use tabs for indentation instead of spaces, you must maintain this throughout your code. The level of ‘whitespace’ indentation is intrinsic to the operation of the Python program’s code.
By contrast, in Delphi programs, the form of indentation and the number of spaces or tabs have no relevance or direct impact on the syntax of the code.
Finally, while Python's code is case-sensitive, Delphi's code is not, which helps Delphi developers avoid several forms of case-related bugs which can be challenging to diagnose and fix. It’s fair to say the case sensitivity of Python can be a major frustration for novice Python developers.
Delphi is extremely versatile when it comes to the range of platforms it can target. It allows development of Windows, macOS, Linux, iOS, and Android applications from a Windows environment.
Python runtime interpreters are widely available for most platforms.
Frequently used IDEs for Python include Pycharm, Visual Studio Code, and PyScripter and they are available on a greater range of platforms for the initial development of the actual code.
However, unlike Delphi (and RAD Studio) those Python-compatible IDEs cannot generate native applications for Android and iOS though there may be third-party solutions to package up Python code for use on those platforms.
Python is an open-source language that allows it to be openly and freely examined, used, modified and distributed without charge.
Delphi’s compiler and IDE is commercially closed source; however the Delphi runtime library’s source code is provided with the product and can also be freely examined and used as a learning resource or adapted to provide additional functionality.
Delphi offers a free Community Edition that allows the creation of open-source projects and there are pricing schemes for academic and research institutions.
Python's interpretation step can result in more significant memory usage and higher battery drainage on mobile devices.
Delphi has a much lower memory overhead beyond the initial size of the executable package. Python programs, the .py text files, frequently start very small since the overall size is only truly realized with the running in-memory image of the Python program after interpretation. This overall larger size is mainly made up from an expansion of that small text file of instructions into a tokenized form which then gets converted into actual in-memory ‘real’ code.
Delphi's excellent GUI design tools allow the developer to ‘draw’ and layout the screens of their application without the need for any additional prototyping or wireframe tool to make rapid development and accurate adherence to a customer’s visual design documents possible.
These tools are integrated into the development environment, implying zero time wastage as there is no switching or load time involved.
With the help of these tools, the time to produce prototypes is drastically shortened and often completely avoided altogether.
Python is largely a code-only development experience where the program is typed as text into an editor or IDE in long-form.
Delphi's ecosystem is more business-centric, with many experts playing a role in enriching its features and spreading its functionality. On the other hand, Python's ecosystem is more driven towards a broad spectrum of both amateurs, hobbyists and IT professionals. While this makes Python more open and inclusive to novice and intermediate developers, high-level support for large-scale projects may be limited.
Python programs tend to be ‘back-end’ server applications in the private and commercial business server utilitarian space and rarely target the mass-market end-user, regular business, and home computer users.
Delphi has numerous commercial partners from all over the world, especially in Europe.
These include reseller partners helping its spread across many industries and business verticals.
In addition, there are several consulting, training, and technology partners whose assistance is available in understanding, improving, scaling products and projects making use of Delphi.
The training aspect is powerful, accessible in various formats, including webinars, live online sessions, and even in-person classroom-style arrangements.
There is an abundance of third-party Delphi components (including a rich collection of free ones) to allow developers to add robust functionality to their applications, often without requiring them to write additional code to achieve enhanced or new functionality even for complex solutions.
Lastly, Delphi offers various libraries targeting the specific needs of different enterprises and developers.
On the other hand, Python has a superb package manager called The Python Package Index (PyPI), which consists of an extensive collection of software.
There are millions of files in the Python Package Index, and it has over half a million users.
Whether you are using Delphi or Python there is a rich wealth of help, examples and enhancements available – one of the advantages of both language’s longevity and firmly established user bases.
In general, most developers seem to consider both Delphi and Python easy to use. However, it may be easier for those transitioning from other statically typed languages to pick up Delphi. Overall, the purpose of usage governs One's comfort level in opting for one or the other of these languages.
So let's dive into it.
Delphi is more geared towards native (x86/x64) desktop and mobile (ARM) applications. It offers quick and easy development of Graphical User Interface (GUI) apps with interactive buttons, menus, and icons.
Delphi is also the far superior choice for database development. It can access all major databases, including Oracle and SQL Server, with little or no need for additional libraries and large support library downloads.
Python is popular when it comes to dealing with large datasets and statistical number crunching.
This specialization has rightly made it a darling of the data science world.
And there are numerous Python Analytical Libraries that considerably ease the lives of people working with data.
And Python, being a scripting language, performs well when directed at one or more relatively small-scale ad-hoc or “quick and dirty” coding activities.
Of course, this makes it directly relevant to many industries, businesses, and individual users, hence its popularity.
Delphi has something of the upper hand when dealing with large-scale applications due to its quick prototyping, commercial support, and fast development.
It is common for Delphi applications to be able to run for many years, transitioning through many operating system upgrades and security patches, continuing to operate as designed and unaffected.
This is not the case for Python programs and other languages such as C#, which are highly susceptible to such changes in their running environment.
So, perhaps the most critical factor relevant to Delphi's enterprise-level usage and broad adoption is this very little need for code maintenance.
Python has particular strengths in interfacing with some APIs, especially some AI and machine learning API as a service systems.
The good news is you don’t always have to make a choice between Delphi and Python – a system called Python4Delphi exists which allows Delphi programs to host and run Python scripts and for Python programs to benefit from the speed and power of the Delphi compiler and Delphi’s extraordinarily strong graphical user interface and design capabilities.
Of the many hundreds of programming languages out there, Delphi and Python are amongst the ones that have managed to be strongly relevant and widely used for decades.
Delphi stands out with more platforms supported natively and incredible speed, security, and efficiency when comparing features and performance.
Python is beloved within the data science community and is excellent for finding small-scale solutions while Delphi has stronger large-scale commercial relevance, particularly for GUI and mobile app development.
Even then, you don’t have to pick between these two grown-up programming siblings, you can combine the best of both should you wish and really have the dream team at your fingertips.