5 ms·

I don't want to disparage the pragmatic value of the features on your list, but they all pale in comparison to the one true killer feature for fast development

I don't want to disparage the pragmatic value of the features on your list, but they all pale in comparison to the one true killer feature for fast development cycles: a REPL.

gowld 6y ago
REPL == eval.
- mumblemumble 6y ago
  eval is useful for making a repl, but there are languages with a repl and no eval (Haskell comes to mind), and there are languages like PHP that have eval but no (built-in) repl.
millstone 6y ago
Agreed, how'd I miss that!
war1025 6y ago
> the one true killer feature for fast development cycles: a REPL. I've been a python dev for about a decade. I do use the REPL a couple times a week, but I wouldn't really call it "essential". How do people use it that makes it so valuable? Usually I just use it when trying to figure out how to parse some text or check what methods or properties are available on an object. Really nothing that I couldn't do in a test suite or the code itself.
- deleted 6y ago
  [deleted]
- xapata 6y ago
  If you're not writing your code in a design that lets you run parts of it every few minutes (or more frequently), you're missing out. Best way to avoid bugs in your module: don't put them in there. Find out in the REPL before you put code in the .py file. Also, it's more important the more data-dependent your code is.
  - SPBS 6y ago
    Tests also have the advantage of input automation. They have the disadvantage that you can't poke around at the environment once they're done (unless you drop into a debugger).
    - lukeschlather 6y ago
      I've found this is more and more the primary way I use the Python repl - I invoke pytest and tell it to drop me into the debugger if there's an error.
    - xapata 6y ago
      I usually have a test data set and run my module against it in IPython. So input is automated to some extent. If I'm analyzing the output, it can be helpful to quickly adjust charts and graphs. I'm now in the process of building distribution tests into my test suite, but it's not clear how to track everything. I need data sources essentially kept under version control, but which are generally too big for git.
  - mantap 6y ago
    Python has a lot of REPLs, which one in particular do you mean?
    - xapata 6y ago
      My personal choices are IPython and Jupyter, depending on whether I'm making plots. If you choose Jupyter, though, I caution that you should be careful you don't switch entirely away from modules and test suites. Jupyter can be too easy in a way.
      - war1025 6y ago
        This sounds quite a bit different from the sort of development work I do. I can see how a REPL would be really useful when working with data, but for building out a webserver or desktop application, it doesn't have nearly as much value.
ncmncm 6y ago
Funny, that. I see the REPL as a trap. (IDEs, too, for other reasons.) REPLs are a trap because they give you the illusion of progress while mostly just wasting your time. I am used to writing 2000 lines of code and having it run (mostly) correctly the first time. In C++, in my case. Otherwise my experience is like the author's. Types are not mainly for error checking. I demand they earn their keep as part of the solution, and they do.
- mantap 6y ago
  It depends a lot on what the program is doing. Writing 2000 lines of C++ that interface with other C++ libraries and having it work first time is something I can understand. But if you have to consume untyped input (such as parsing text), or produce untyped output (such as an image) then the value of a Notebook/REPL really shines.
greggman3 6y ago
I'd love to see a video of someone developing via the REPL that somehow let me "get it". I've never written code for which I've found the REPL that useful so either my domain is not conducive to REPL usage or I need a good tutorial or example to see what I missing and how to change my approach. Any suggested videos or articles? though i suspect a video would be better for this type of thing

I don't want to disparage the pragmatic value of the features on your list, but they all pale in comparison to the one true killer feature for fast development cycles: a REPL.

gowld 6y ago

REPL == eval.

mumblemumble 6y ago
eval is useful for making a repl, but there are languages with a repl and no eval (Haskell comes to mind), and there are languages like PHP that have eval but no (built-in) repl.

millstone 6y ago

Agreed, how'd I miss that!

war1025 6y ago

> the one true killer feature for fast development cycles: a REPL. I've been a python dev for about a decade. I do use the REPL a couple times a week, but I wouldn't really call it "essential". How do people use it that makes it so valuable? Usually I just use it when trying to figure out how to parse some text or check what methods or properties are available on an object. Really nothing that I couldn't do in a test suite or the code itself.

deleted 6y ago
[deleted]
xapata 6y ago
If you're not writing your code in a design that lets you run parts of it every few minutes (or more frequently), you're missing out. Best way to avoid bugs in your module: don't put them in there. Find out in the REPL before you put code in the .py file. Also, it's more important the more data-dependent your code is.
- SPBS 6y ago
  Tests also have the advantage of input automation. They have the disadvantage that you can't poke around at the environment once they're done (unless you drop into a debugger).
  - lukeschlather 6y ago
    I've found this is more and more the primary way I use the Python repl - I invoke pytest and tell it to drop me into the debugger if there's an error.
  - xapata 6y ago
    I usually have a test data set and run my module against it in IPython. So input is automated to some extent. If I'm analyzing the output, it can be helpful to quickly adjust charts and graphs. I'm now in the process of building distribution tests into my test suite, but it's not clear how to track everything. I need data sources essentially kept under version control, but which are generally too big for git.
- mantap 6y ago
  Python has a lot of REPLs, which one in particular do you mean?
  - xapata 6y ago
    My personal choices are IPython and Jupyter, depending on whether I'm making plots. If you choose Jupyter, though, I caution that you should be careful you don't switch entirely away from modules and test suites. Jupyter can be too easy in a way.
    - war1025 6y ago
      This sounds quite a bit different from the sort of development work I do. I can see how a REPL would be really useful when working with data, but for building out a webserver or desktop application, it doesn't have nearly as much value.

ncmncm 6y ago

Funny, that. I see the REPL as a trap. (IDEs, too, for other reasons.) REPLs are a trap because they give you the illusion of progress while mostly just wasting your time. I am used to writing 2000 lines of code and having it run (mostly) correctly the first time. In C++, in my case. Otherwise my experience is like the author's. Types are not mainly for error checking. I demand they earn their keep as part of the solution, and they do.

mantap 6y ago
It depends a lot on what the program is doing. Writing 2000 lines of C++ that interface with other C++ libraries and having it work first time is something I can understand. But if you have to consume untyped input (such as parsing text), or produce untyped output (such as an image) then the value of a Notebook/REPL really shines.

greggman3 6y ago

I'd love to see a video of someone developing via the REPL that somehow let me "get it". I've never written code for which I've found the REPL that useful so either my domain is not conducive to REPL usage or I need a good tutorial or example to see what I missing and how to change my approach. Any suggested videos or articles? though i suspect a video would be better for this type of thing