The first module of the Certificate of Advanced Studies in Translation Technology and AI at the University of Zurich begins with Computer Assisted Translation (CAT) and basic programming, with Python being the preferred programming language.
The European Master in Translation and Interpreting Technology also appears to favor Python as the preferred programming language in three modules. Even the Master of Arts in Translation and Localization Management offered by the Middlebury Institute of International Studies in Monterey actually begins with two introductory courses in programming with Python.
Many other courses and degrees use Python or Python-based toolkits in their programs. So what makes Python seem like the programming language of choice for translation studies?
Friendly and ubiquitous
Middlebury’s course descriptions indicate that Python is “the easiest programming language to learn”, adding that it allows linguists “to program using easy-to-understand techniques that build on each other.”
It’s pretty much spot on. Being high-level and general-purpose, Python is relatively more user-friendly than most other programming languages.
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High-level languages use structures that are easy to read and more human-readable, unlike low-level languages which run directly on a computer’s processor. Being high level also means that Python is more portable – it can be used on many different computers without needing a lot of modifications, which further increases usability.
Meanwhile, general-purpose languages like Python are, as implied, meant to be used on almost anything and everything. Python is simple in its syntax, so it’s easy and natural to learn, with its written code easy to read, understand, share, and maintain (again, compared to most other programming languages).
After its premiere in 1991, Python – named after British comedy troupe Monty Python – immediately rose to popularity, surpassing more established programming languages. Today, it consistently ranks first through third in the TIOBE Index, a ranking of the most popular and widely used programming languages.
Due to its popularity, Python’s user base has continually created new libraries, toolkits, and custom software packages that other Python programmers can use without writing their own code. This makes it even more useful for beginners and general applications.
As of this writing, the Python Package Index, an official software repository for Python, has over 300,000 projects that anyone can use.
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Why Python for Translation Technology Studies?
The short answer is that Python, with its ease of use and popularity, has been widely used in computational linguistics; and, more recently, machine learning, which now powers contemporary natural language processing (NLP) and machine translation (MT).
In recent years, several scientific papers have examined and discussed the choice of Python as the programming language for linguistic students.
A 2019 article stated, “Python is available for free and easy to learn, which is extremely important to our linguistics students who are usually unsure of themselves when it comes to thinking.[ing] on programming.
The author, Assistant Professor Lesia Ivashkevych of the National Technical University of Ukraine, explained that Python can solve “really complicated tasks” and is “widely used in science in general and in computational linguistics in particular, and there is many learning resources that are intended for linguists.
Ivashkevych’s article, which appeared in the third edition of the peer-reviewed journal Advanced Linguistics, also noted that “the syntax of Python is similar to that of English, and it is easy to understand the code already. writing”.
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It is true that other programming languages, such as C, are also widely used for coding NLP and MT applications. But in the context of students learning to code, Python seems to have the edge.
Used in over 25 countries
As Python and Python software projects are widely used in machine learning and hence in NLP and TA applications, very popular toolkits such as Natural Language Toolkit (NLTK) have sprung up. This has strengthened Python as the go-to programming language for students learning to code applications for natural language and translation technologies.
The NLTK, as the Toolkit website states, is a “platform for creating Python programs to work with human language data.” It offers built-in support for more than 100 corpora and lexical resources, such as WordNet, and is currently used in 89 courses around the world and in more than 40 universities and institutions in 25 countries.
Long story short: in terms of computational linguistics, NLP, and AT, Python is a must-have and is the most popular programming language for student linguists.
