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Python's strength is its simplified coding style. People who use these frameworks are not software engineers who want to deal with object passing mechanics in e

Python's strength is its simplified coding style. People who use these frameworks are not software engineers who want to deal with object passing mechanics in excruciating detail. There are software engineers to do just that. So until something beats Python in simplified writing style or Python becomes incredibly slow, it won't be easy to supplant.

yahyaheee 6y ago
There are a lot of people who are somewhere in between these groups and providing a language that goes up and down the stack well would be super useful. I agree it needs to be as simple as python on the high level though, or the data science end of the spectrum will just never adopt it.
- Cullinet 6y ago
  foreign function interop ideally at the system (or intermediate) level does so much. before getting distracted by dot net and mono, I feel I have to lay the blame (and my nineties) at the feet of CORBA and the Object Management Group. Seriously though, what was the OMG but a UNIX consortium trying to break the hold of DEC and VMS over the most complex critical systems..
- hnews_account_1 6y ago
  That is currently a non issue since software is lagging hardware. So you can join 2 systems together fairly inefficiently and still make a go of it. Sure, a good language for people down the stack can topple python from the top, but it won't be easy. It'd be far easier if we were approaching software limits on current hardware and needed to pull everything into one language and system to make it work together.
  - yahyaheee 6y ago
    Its useful for ML in that it requires so much optimization, that being about to drop down in the same language is incredibly handy. For ML software isn't lagging hardware its the other way around.
tharne 6y ago
This 100%. A lot of people working with code are folks who code as a means to an end rather than as a craft unto itself, and these folks are important because they often have expertise in a domain other than software engineering. Python hits a sweet spot in terms of power and ease-of-learning/ease-of-use that makes it incredibly well-suited to these types of users.
- Cullinet 6y ago
  I see this reflected as in the DBASE - *gres impedance. ~ the one end Ashton Tate delivering a shallow learning curve declarative language for semi referential data that SOHO novices can create applications with, and at the other, Stonebraker wanting to put the neatness that pure client computing enabled (dedicated cpu time and architecture leading to multimedia inexpensively) together with large system semantics [0] long before capabilities, a curse I believe was academic grant seeking behaviour in origin. I seriously keep seeing the results of driving forces individually uniquely capable in project conditions which are very difficult to reconcile with the ultimate purpose software is used for. like, before Jim Keller quit Intel, he gave a talk explaining how Tesla was founded on a unique case where reductions to silicon were optimal for CAFÉ and that's a rare case, and how he couldn't see the 22 people in the audience he knew can tune the full performance out of modern silicon software instructions. (probably that should have called out his imminent departure considering the proliferating instruction set at Intel and his unusual call out to a success he thought worthy of mention). it used to be academia thinking about small systems applications and development, eg the Edinburgh AI group up to the 80s and Carl Hewitt thinking about how to make "next use unknown" a good thing in PLANNER. But certainly lately academic prowess has adhered to scale and the apparent needs of the largest computing users. If there's a impedance mismatch here I think it has evolved from putting the solo developer in the employ of hyperscalers without any thought about the effects of that situation. [0] personally I remember the talk preceded the walk by some 20 years or so) and simultaneously take on the big iron boys at IBM. Oracle drove it's ugly polluting truck thru the middle and created a empire that we're still far from superannuating (not replacing, in the view of this guy seriously targeting openVMS 9.3 with the ability to have workstations join the cluster and run transactions across the system and db against the same native transaction manager and define time series objects using FORTRAN and make the cursor over the resulting blobs addressable from DEC BASIC inside user applications including Excel soon to be patched to the VMS TM via SRV-IO via a switch on the same NIC. All very much old functionality becoming the new. if I'm allowed to write about it, I will probably emphasise just how much innovative design has been enabled by expensive licensing and recount my memories of how nothing ever cropped up to address comparable needs in the FOSS world despite the foundations resting upon some of the most well documented CS and being wonderfully unencumbered by IP inhibitors due to the passing of time.
open-source-ux 6y ago
"Python's strength is its simplified coding style" Anyone familiar with Python is unlikely to struggle with the syntax of Julia or with reading straightforward Julia code. In fact, I'd argue that Julia is easier to learn than Python in many aspects. Python is now a large language, not the small, simple language of years past. Of course, in both languages (Julia and Python) you can ignore complex features. But what Python also gives you is abundant examples and solutions to problems that are easily found on the Web. In contrast, new(ish) programming languages suffer from a lack of libraries, examples and tutorials that slows down momentum.
- hnews_account_1 6y ago
  Yes. First mover advantage and network effects. It is difficult to topple the leader even if your own product is somehow way better.

yahyaheee 6y ago

There are a lot of people who are somewhere in between these groups and providing a language that goes up and down the stack well would be super useful. I agree it needs to be as simple as python on the high level though, or the data science end of the spectrum will just never adopt it.

Cullinet 6y ago
foreign function interop ideally at the system (or intermediate) level does so much. before getting distracted by dot net and mono, I feel I have to lay the blame (and my nineties) at the feet of CORBA and the Object Management Group. Seriously though, what was the OMG but a UNIX consortium trying to break the hold of DEC and VMS over the most complex critical systems..
hnews_account_1 6y ago
That is currently a non issue since software is lagging hardware. So you can join 2 systems together fairly inefficiently and still make a go of it. Sure, a good language for people down the stack can topple python from the top, but it won't be easy. It'd be far easier if we were approaching software limits on current hardware and needed to pull everything into one language and system to make it work together.
- yahyaheee 6y ago
  Its useful for ML in that it requires so much optimization, that being about to drop down in the same language is incredibly handy. For ML software isn't lagging hardware its the other way around.

tharne 6y ago

This 100%. A lot of people working with code are folks who code as a means to an end rather than as a craft unto itself, and these folks are important because they often have expertise in a domain other than software engineering. Python hits a sweet spot in terms of power and ease-of-learning/ease-of-use that makes it incredibly well-suited to these types of users.

Cullinet 6y ago
I see this reflected as in the DBASE - *gres impedance. ~ the one end Ashton Tate delivering a shallow learning curve declarative language for semi referential data that SOHO novices can create applications with, and at the other, Stonebraker wanting to put the neatness that pure client computing enabled (dedicated cpu time and architecture leading to multimedia inexpensively) together with large system semantics [0] long before capabilities, a curse I believe was academic grant seeking behaviour in origin. I seriously keep seeing the results of driving forces individually uniquely capable in project conditions which are very difficult to reconcile with the ultimate purpose software is used for. like, before Jim Keller quit Intel, he gave a talk explaining how Tesla was founded on a unique case where reductions to silicon were optimal for CAFÉ and that's a rare case, and how he couldn't see the 22 people in the audience he knew can tune the full performance out of modern silicon software instructions. (probably that should have called out his imminent departure considering the proliferating instruction set at Intel and his unusual call out to a success he thought worthy of mention). it used to be academia thinking about small systems applications and development, eg the Edinburgh AI group up to the 80s and Carl Hewitt thinking about how to make "next use unknown" a good thing in PLANNER. But certainly lately academic prowess has adhered to scale and the apparent needs of the largest computing users. If there's a impedance mismatch here I think it has evolved from putting the solo developer in the employ of hyperscalers without any thought about the effects of that situation. [0] personally I remember the talk preceded the walk by some 20 years or so) and simultaneously take on the big iron boys at IBM. Oracle drove it's ugly polluting truck thru the middle and created a empire that we're still far from superannuating (not replacing, in the view of this guy seriously targeting openVMS 9.3 with the ability to have workstations join the cluster and run transactions across the system and db against the same native transaction manager and define time series objects using FORTRAN and make the cursor over the resulting blobs addressable from DEC BASIC inside user applications including Excel soon to be patched to the VMS TM via SRV-IO via a switch on the same NIC. All very much old functionality becoming the new. if I'm allowed to write about it, I will probably emphasise just how much innovative design has been enabled by expensive licensing and recount my memories of how nothing ever cropped up to address comparable needs in the FOSS world despite the foundations resting upon some of the most well documented CS and being wonderfully unencumbered by IP inhibitors due to the passing of time.

open-source-ux 6y ago

"Python's strength is its simplified coding style" Anyone familiar with Python is unlikely to struggle with the syntax of Julia or with reading straightforward Julia code. In fact, I'd argue that Julia is easier to learn than Python in many aspects. Python is now a large language, not the small, simple language of years past. Of course, in both languages (Julia and Python) you can ignore complex features. But what Python also gives you is abundant examples and solutions to problems that are easily found on the Web. In contrast, new(ish) programming languages suffer from a lack of libraries, examples and tutorials that slows down momentum.

hnews_account_1 6y ago
Yes. First mover advantage and network effects. It is difficult to topple the leader even if your own product is somehow way better.