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Project from Hell (2008)

projectfailures.wordpress.com

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Re: Project from Hell (2008)

#151

Post by collyw »

tigershark wrote: post #66
desertrider12 wrote: post #48

Earlier quoted context omitted.

C++ is only "fast" because people who care about performance use it and a lot of people who are good at compilers work on gcc/intel/llvm. If the LLVM team decided to spend 5 years making python "fast", I bet they could make it benchmark just as well as C++.

No, It’s not possible to optimise Python like c++ because of the characteristics of the language. Plenty of very good people are working on Python optimisation and it’s still painfully slow and will always be.

I have been using Python for a while now, and its rarely that the language is too slow (I have encountered it on one problem). A lot of Python is for web programming where you optimize the database and set up caching to improve performance. If you want to do some heavy number crunching Numpy is apparently not far of C in terms of performance.

Obviously its a case of the correct tool for the job and depends heavily on the type of software you are writing, but in most cases its a different type of optimization that is needed for Python code.

Re: Project from Hell (2008)

#152

Post by collyw »

emmelaich wrote: post #124
woliveirajr wrote: post #116

> The tool that was finally chosen is a disaster with a graphical user interface, an abomination coming directly from Sweden. Ohh, which versioning software comes from Sweden and is so bad? Got curious about this one.

Maybe ClearCase? Centralised, with access through a versioning filesystem. Performance would strongly depend on the power of the server and a bunch of other things. Also, apparently builds are done centrally. A get the shivers just thinking about it. https://en.wikipedia.org/wiki/Rational_ClearCase See also these two links. https://www.daedtech.com/how-rational-clear-case-stole-my-in... https://stackoverflow.com/ques…

Clearcase was fucking awful when I had to use it. My install was so fucked I needed a whole new Windows reinstall.

Re: Project from Hell (2008)

#153

Post by Mandatum »

toomanybeersies wrote: post #137
Mandatum wrote: post #127

Earlier quoted context omitted.

That's incorrect unless you're a company contracting to an organisation, in which case you signed a contract saying you're going to stay and do X for period of time, and if they have to stop and scramble because you left without the contracting being breached - you're liable. Which is fair and universal. Employees on the other hand have NEVER been docked pay in New Zealand and you are in NO way legally obligated to t…

You can if you've specifically written it into the contract and made sure the employee is aware of the clause: https://www.employment.govt.nz/hours-and-wages/pay/deduction... (Recovering money owed if employee leaves without working out notice) I'm not sure if it's ever been in any of my contracts, but it is apparently an option.

That's only in the case where you're over-paid, or paid up-front - in which case you've been paid for a month, and if leaving in 2 weeks you'd only be paid for the time you worked.

Very different to being liable for finding a new hire.

The employment court of New Zealand is very favourable to employees. Even if something was contractually obligated - it can easily be null and void by the court if they deem it unreasonably overreaching by the employer.

Re: Project from Hell (2008)

#154

Post by igouy »

collyw wrote: post #151
tigershark wrote: post #66

Earlier quoted context omitted.

No, It’s not possible to optimise Python like c++ because of the characteristics of the language. Plenty of very good people are working on Python optimisation and it’s still painfully slow and will always be.

I have been using Python for a while now, and its rarely that the language is too slow (I have encountered it on one problem). A lot of Python is for web programming where you optimize the database and set up caching to improve performance. If you want to do some heavy number crunching Numpy is apparently not far of C in terms of performance. Obviously its a case of the correct tool for the job and depends heavily on…

> …too slow…

No language implementation is "too slow" if performance doesn't matter.

> … Numpy is apparently not far of C in terms of performance

As-fast-as C when it is C (or Fortran or assembler…) :-)

Re: Project from Hell (2008)

#155

Post by igouy »

msla wrote: post #77
tigershark wrote: post #69

Earlier quoted context omitted.

That is only a very specific benchmark and as that post said the result is so strange probably because of the changes in the C trigonometric functions lib that slowed down a lot to increase precision.

The point, however, is that if the difference is down to library code, the language itself isn't imposing a penalty. That is what is counter-intuitive here.

What's "counter-intuitive" about that?

As-fast-as C when it is C (or Fortran or assembler…)

Re: Project from Hell (2008)

#156

Post by kabdib »

ww520 wrote: post #108
kabdib wrote: post #107

I think I've used the source code control system mentioned in the article. It was indeed a pile of garbage. Took a couple days of training in it, and the folks running the class kept telling us not to use certain checkboxes and features of the UI "or bad stuff will happen".

Just curious. What is it?

It's been nearly 20 years and hard to remember. I think it was called Continuus, but that they changed their name. A sibling comment refers to 'Synergy' and that sounds right.

Just another proof that if a product involves the word "Synergy" in its marketing, you should run away fast.

Re: Project from Hell (2008)

#157

Post by collyw »

igouy wrote: post #154
collyw wrote: post #151

Earlier quoted context omitted.

I have been using Python for a while now, and its rarely that the language is too slow (I have encountered it on one problem). A lot of Python is for web programming where you optimize the database and set up caching to improve performance. If you want to do some heavy number crunching Numpy is apparently not far of C in terms of performance. Obviously its a case of the correct tool for the job and depends heavily on…

> …too slow… No language implementation is "too slow" if performance doesn't matter. > … Numpy is apparently not far of C in terms of performance As-fast-as C when it is C (or Fortran or assembler…) :-)

Numpy is a Python library, not a C library. By your reasoning Python is C.
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