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Python? Still Relevant and in Demand in the Market?
596 sats \ 10 comments \ @kepford 20 Feb devs

Due to some some org changes at my employer I may be moving to a team that uses Python heavily. I have never written Python professionally but I've dabbled. I think its used heavily in certain fields and is likely a marketable language to have on the CV. Am I correct in that summary?

Is it growing? Is it evolving? I know its alive and well but I just don't hear much about it anymore. Has it just matured like many languages over the years?

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280 sats \ 4 replies \ @SimpleStacker 20 Feb

It's the main language for anything data science, ML, or AI related.

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103 sats \ 0 replies \ @398ja 20 Feb

I'm currently learning AI, but resisting learning python. I just don't have time or enough motivation to learn a new language. Even though all the books I'm reading on the subject have examples in python, I can still read and understand the code, but I will write mine in java, using the langchain4j framework.

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30 sats \ 2 replies \ @kepford OP 20 Feb

Pfff, that's all? I actually knew that but forgot... Feel dumb now.

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61 sats \ 1 reply \ @SimpleStacker 20 Feb

But yes, highly marketable :)

Not sure what your team will be working on, but assuming it's at least somewhat ML/data related, important libraries to learn are numpy, pandas, matplotlib, and potentially sklearn

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30 sats \ 0 replies \ @kepford OP 20 Feb

Nah, its me moving to another team. May end up on a different team though.

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98 sats \ 0 replies \ @Cje95 20 Feb

Not to be that person but I staffed the House Bipartisan AI task force that released the 276 page report and Python is by far the biggest language used in the AI space. Due to how it can continue to evolve it isn’t going anywhere and is a great language to learn!

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51 sats \ 2 replies \ @itsrealfake 20 Feb

python, like javascript, has absorbed a lot of the functional fun of Lisp. What language are you coming from?

I had to go from TypeScript to Ruby, but I asked my boss to allocate significant time for a new employee to level up my Ruby skills in a pair programming way (I was fluent in TS, but definitely not in Ruby). It was one of the best/enjoyable/productive 4 months I have ever had professionally. The feature that came out of that time changed the engineering team & continues to be a benefit to the org.

Can you learn how to use the LLM to learn Python & I've been learning Rust with the help of LLMs on the ChainCode curriculum, and its been very productive.

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63 sats \ 1 reply \ @jurraca 20 Feb
python, like javascript, has absorbed a lot of the functional fun of Lisp.

imo neither python or js have not inherited much from lisp at all, curious what you mean... i went from a functional lang back to python for a project and struggled to rewire my brain to OOP.

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71 sats \ 0 replies \ @itsrealfake 20 Feb

disclaimer, I'm not proficient with Lisp. when I was learning about it, I remember thinking that a lot of the features I liked to use 'functionally' were similar to what I was reading about in the Lisp Programming book.

here's some garbage from the LLM:

Both JavaScript and Python have introduced elements of Lisp in various ways:

  • JavaScript:
    • Closures: JavaScript's closure mechanism is similar to Lisp's lexical scoping. Closures allow functions to access variables from their surrounding scope, even when called outside of that scope.
    • Higher-order functions: JavaScript functions can be passed as arguments to other functions, returned as values from functions, and stored in data structures, similar to Lisp's higher-order functions.
    • Macros: Although JavaScript does not have built-in macro support like Lisp, some libraries and frameworks, such as Sweet.js and Macros.js, provide macro-like functionality.
    • Array methods: JavaScript's array methods, such as map(), filter(), and reduce(), are similar to Lisp's sequence functions.
  • Python:
    • List comprehensions: Python's list comprehensions are similar to Lisp's mapcar function, allowing for concise creation of new lists by applying a transformation to each element of an existing list.
    • Generators: Python's generators are similar to Lisp's streams, allowing for lazy evaluation and efficient processing of large datasets.
    • Higher-order functions: Python functions can be passed as arguments to other functions, returned as values from functions, and stored in data structures, similar to Lisp's higher-order functions.
    • Macros: Although Python does not have built-in macro support like Lisp, some libraries, such as macro and pymacro, provide macro-like functionality.
    • Functional programming libraries: Libraries like toolz and cytoolz provide functional programming utilities, including functions like pipe and curry, which are inspired by Lisp.

These elements have been incorporated into JavaScript and Python to provide more expressive and flexible programming capabilities, while still maintaining their respective language syntax and semantics.

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0 sats \ 0 replies \ @398ja 20 Feb

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