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Should today’s developers worry about AI code generators taking their jobs? Dec 11, 2022 Book review: Clojure for the Brave and True Oct 2, 2022 Stop Shakespearizing Sep 16, 2022 Using GNU Make with JavaScript and Node.js to build AWS Lambda functions Sep 4, 2022 Monolithic repository vs a monolith Aug 23, 2022 Scripting languages are tools for tying APIs together, not building complex systems Jun 8, 2022 Good developers can pick up new programming languages Jun 3, 2022 Java is no longer relevant May 29, 2022 Automation and coding tools for pet projects on the Apple hardware May 28, 2022 There is no such thing as one grand unified full-stack programming language May 27, 2022 Most terrifying professional artifact May 14, 2022 TypeScript is a productivity problem in and of itself Apr 20, 2022 Tools of the craft Dec 18, 2021 Node.js and Lambda deployment size restrictions Mar 1, 2021 What programming language to use for a brand new project? Feb 18, 2020 Using Markov Chain Generator to create Donald Trump's state of union speech Jan 20, 2019 The religion of JavaScript Nov 26, 2018 Let’s talk cloud neutrality Sep 17, 2018 TypeScript starts where JavaScript leaves off Aug 2, 2017 Node.js is a perfect enterprise application platform Jul 30, 2017 Singletons in TypeScript Jul 16, 2017 Copyright in the 21st century or how "IT Gurus of Atlanta" plagiarized my and other's articles Mar 21, 2017 Collaborative work in the cloud: what I learned teaching my daughter how to code Dec 10, 2016 Amazon Alexa is eating the retailers alive Jun 22, 2016 What can we learn from the last week's salesforce.com outage ? May 15, 2016 JEE in the cloud era: building application servers Apr 22, 2016 JavaScript as the language of the cloud Feb 20, 2016 In memory of Ed Yourdon Jan 23, 2016 Top Ten Differences Between ActiveMQ and Amazon SQS Sep 5, 2015 We Live in a Mobile Device Notification Hell Aug 22, 2015 What Every College Computer Science Freshman Should Know Aug 14, 2015 Ten Questions to Consider Before Choosing Cassandra Aug 8, 2015 The Three Myths About JavaScript Simplicity Jul 10, 2015 Book Review: "Shop Class As Soulcraft" By Matthew B. Crawford Jul 5, 2015 Big Data is not all about Hadoop May 30, 2015 Smart IT Departments Own Their Business API and Take Ownership of Data Governance May 13, 2015 Guaranteeing Delivery of Messages with AWS SQS May 9, 2015 Where AWS Elastic BeanStalk Could be Better Mar 3, 2015 Why I am Tempted to Replace Cassandra With DynamoDB Nov 13, 2014 How We Overcomplicated Web Design Oct 8, 2014 Docker can fundamentally change how you think of server deployments Aug 26, 2014 Cassandra: Lessons Learned Jun 6, 2014 Things I wish Apache Cassandra was better at Feb 12, 2014 "Hello, World!" Using Apache Thrift Feb 24, 2013 Have computers become too complicated for teaching ? Jan 1, 2013 Java, Linux and UNIX: How much things have progressed Dec 7, 2010

Scripting languages are tools for tying APIs together, not building complex systems

June 8, 2022

There are two general categories of programming languages: compiled, and interpreted.



A program written in a compiled language must first be converted into native machine code to run. This step is called compilation.



A program written in an interpreted language does not need to be converted into native code. The interpreter parses the program and executes it in real-time. It is possible to use the interpreter interactively as a calculator or debugger.



In some cases, the interpreter may store the program in the form of intermediate code in memory and compile parts of it into native code in-real-time in a process called Just-in-time Compilation.



The interpreter may save the intermediate bytecode for faster loading times during future execution as an optimization. Python, for example, saves *.pyc files with compiled bytecode of the imported modules. 



Similarly, though technically a compiled language, Java produces *.class files with bytecode. Java is not a strictly interpreted language and is outside of this post's scope.



An interpreted language is typically a higher-level language. It may explicitly represent data structures, such as lists, tuples, and dictionaries (maps). It may also have higher-level abstractions over algorithms. It does not have to be loosely typed, though most interpreted languages are.



Under most circumstances, a program written in an interpreted language is slower than compiled. However, program performance needs to be balanced against developer productivity. The very purpose of an interpreted language is to hide complex algorithms from the developer and make programs available to run immediately after every change. A program being executed is in the same language that it is written in.



To paraphrase Mel Conway, an interpreted language is an application language, not algorithm (aka platform ) language. Interpreted languages are best used as a "glue" that ties algorithms and APIs together — not to implement algorithms.



There is a reason why many modern interpreted languages are also referred to as "scripting." Scripting is automating existing APIs and algorithms and combining them into new APIs and algorithms. Scripting is about controlling or orchestrating existing tools, APIs, and algorithms.








A reader may rightfully ask, "Oleg, what are you getting at?"



What makes me think of these things early in the mornings is the proliferation of JavaScript as an enterprise application language. I believe using JS as a hammer to solve every problem will hound enterprise IT for decades.



JavaScript is an interpreted scripting language. It's a tool for tying things together — DOM objects on a web page and APIs.



I love JavaScript as a tool for quickly building simple apps that tie cloud APIs together.



I'm not too fond of JavaScript for the religion it cultivates among its fans who are in denial about its limitations and feel the need to use it to solve every problem, however inappropriate it might be for the task.