I'm developing a roguelike in Lua for iOS and OSX. Pretty new to Lua and discovered to my dismay how nonrandom math.random is on my platform. I already had already setup my calls for random numbers set up through a function:
function rollD(max)
return math.random(max)
end
So I found a fantastic answer in response to this post which turns out I think will solve my problem (it's pretty critical for a roguelike that the game be different each time) But in order to make the following tweaked function:
function rollD(max)
return srandom(seedobj,1,max)
end
work, I had to make:
local seedobj = { seed = -232343 }
from Donati's Knuth adaptation not be local anymore, and then actually modified it to use (os.time()*-1). This actually works perfectly so far and my (very rudimentary) roguelike is rolling up random bad guys and dungeons just like I want it to. But I worry when things work right...
With a high number of calls to srandom (probably upwards of a thousand calls per level) am I going to take some kind of performance hit by having seedobj be global? I would like to think that, because it's nested in the table, that seed is a reference and that I'm worrying for nothing. But otherwise: is there a way I should modify this function so I can call it more efficiently?
Accessing a global variable in Lua is like accessing a table field. If seedobj is global the following code:
function rollD(max)
return srandom(seedobj,1,max)
end
in Lua 5.2 is equivalent to:
function rollD(max)
return srandom(_ENV.seedobj,1,max)
end
or in Lua 5.1 is (roughly) equivalent to
function rollD(max)
return srandom(_G.seedobj,1,max)
end
Where _ENV is the variable holding the current environment table and _G is the variable holding the global table.
Therefore whenever you call rollD you incur a small performance penalty for that indirect access, compared to a local variable. In general this penalty is significant or not depending on the complexity of the other operations performed when you call rollD.
In your specific case that penalty is unlikely to be noticeable, since the srandom implementation already performs much more intensive computations (among which some table accesses as well).
Related
There is a very peculiar slow down in Julia. When running, for example, a for loop by calling a function
function TestFunc(num)
for i=1:num
end
end
It is MUCH faster than when I just run a for loop for the exact same num ...
for i=1:num
end
The slow down isn't marginal either, it is magnitudes slower, the following image shows me running it.
For Loop Code
In some of my other code, the opposite actually happens but I just feel like I am missing something fundamental about the way Julia runs. How do I keep my code optimal and why do these differences exist?
Anything you can write outside a function, you can write inside a function. So just like in C, you can write
function main()
print("Hello World\n")
end
main()
So just pretend it is a C program and write your stuff inside the main() function.
Why is it so slow outside a function, it is because any variable inside a function is protected from being changed by another thread or task. So for a for loop in the global scope must check its variables for its type everytime it is access by the for loop, just in case it was change by another thread or task. All these checking is slowing it down FOR SAFETY.
The first Performance Law of Julia is
Global is slow
The performance tips in the Julia Documentation says
A global variable might have its value, and therefore its type, change at any point. This makes it difficult for the compiler to optimize code using global variables. Variables should be local, or passed as arguments to functions, whenever possible.
Any code that is performance critical or being benchmarked should be inside a function.
I have a function that does a find/replace on text files, and it has worked well for some time. Until I needed to process a 12 million line file.
My initial code used Get-Content and Write-Content, and with the massive file it was going to take hours to process, not to mention the memory implications of loading 12 million lines into RAM.
So, I wrote a little test script to compare that approach vs Stream Reader/Writer. And Streaming looked like it was going to be a massive performance improvement, dropping processing to 30 seconds. I then added a .Replace() on each line, and total processing time only went up to maybe a minute. All good. So then I went to implement it in my real code, and performance has tanked again. That code is a PS1 that loads a number of PSM1 files. The function to do the find replace is in one of those PSM1 files, and that code calls functions in another PSM1. The test script was everything in a single small PS1.
Given that my test script didn't use a function call at all, I tested that first, so there is a function in the PS1 that gets called 12 million times from the loop in the same PS1. No real performance impact.
So, my thought then was that calling a function in one PSM1 that then calls a function in another PSM1 (12 million times) might be the issue. So I made a dummy function (which just returns the passed string, as if no replacement was needed) in the same PSM1 as the loop. And that is orders of magnitude slower.
I have not tested this with everything in the PS1, mostly because these functions are needed in three different scripts with very different argument requirements, so implementing it with Modules really made a lot of sense logistically, and changing that would be a massive undertaking.
That said, is there a known performance hit when calling a function that lives in a Module? I was under the impression that once the Modules are loaded, it's basically the same as if it was all in a single PS1, but perhaps not? FWIW, I am not using NameSpaces. All of my functions just have function name prefix on the noun side to avoid conflicts.
I also can't really post minimally functional code very easily since that's in a single file that doesn't exhibit the behavior. If there is no obvious answer to someone I guess my next step is to implement the test script with some modules, but that's not really apples to apples either, since my real modules are rather large.
To add a little context: When the function (in a PSM1) does not call a function and simply sets $writeLine = $originalLine total time is 15 seconds.
When doing an actual find and replace inline (no call to a function) like this $writeLine = $originalLine.Replace($replace, $with) total processing time is 16 seconds.
When calling a function in the same PSM1 that just returns the original string total time is 17 minutes.
But again, when it's all in a PS1 file with no modules, calling a function has minimal impact. So it certainly seems like calling a function in a PSM1, even from a function in that same PSM1, has a massive performance overhead.
And more context:
I moved the replace function in the test script into a Module. No appreciable change. So I moved the main code, including the loop, into a function in that module, and called it from the main script. Again, no real change. Both took around 15 seconds.
So, it's not something innate in Modules. That then begs the question, what could I be doing in my other modules that would trigger this behavior? This modules are 3000-10,000 lines of code, so there is a lot going on. Hopefully someone has some insight as to best practices with modules to mitigate this. And hopefully it's not "Don't use big modules". ;)
Final update:
It seems it IS a function of how big the module is. I deleted all the other functions in the Module that contains the loop, and performance is fine, 17 seconds. So, basically even as of PS5.0, the implementation of modules is pretty useless for anything large. Rather disconcerting. I wonder if the same would be true if all the functions where in a single file, and PowerShell performance with large files with lots of functions is just bad? Anyone have any experience down this road?
I'm relatively new to software development, and I'm on my way to completing my first app for the iPhone.
While learning Swift, I learned that I could add functions outside the class definition, and have it accessible across all views. After a while, I found myself making many global functions for setting app preferences (registering defaults, UIAppearance, etc).
Is this bad practice? The only alternate way I could think of was creating a custom class to encapsulate them, but then the class itself wouldn't serve any purpose and I'd have to think of ways to passing it around views.
Global functions: good (IMHO anyway, though some disagree)
Global state: bad (fairly universally agreed upon)
By which I mean, it’s probably a good practice to break up your code to create lots of small utility functions, to make them general, and to re-use them. So long as they are “pure functions”
For example, suppose you find yourself checking if all the entries in an array have a certain property. You might write a for loop over the array checking them. You might even re-use the standard reduce to do it. Or you could write a re-useable function, all, that takes a closure that checks an element, and runs it against every element in the array. It’s nice and clear when you’re reading code that goes let allAboveGround = all(sprites) { $0.position.y > 0 } rather than a for…in loop that does the same thing. You can also write a separate unit test specifically for your all function, and be confident it works correctly, rather than a much more involved test for a function that includes embedded in it a version of all amongst other business logic.
Breaking up your code into smaller functions can also help avoid needing to use var so much. For example, in the above example you would probably need a var to track the result of your looping but the result of the all function can be assigned using let. Favoring immutable variables declared with let can help make your program easier to reason about and debug.
What you shouldn’t do, as #drewag points out in his answer, is write functions that change global variables (or access singletons which amount to the same thing). Any global function you write should operate only on their inputs and produce the exact same results every time regardless of when they are called. Global functions that mutate global state (i.e. make changes to global variables (or change values of variables passed to them as arguments by reference) can be incredibly confusing to debug due to unexpected side-effects they might cause.
There is one downside to writing pure global functions,* which is that you end up “polluting the namespace” – that is, you have all these functions lying around that might have specific relevance to a particular part of your program, but accessible everywhere. To be honest, for a medium-sized application, with well-written generic functions named sensibly, this is probably not an issue. If a function is purely of use to a specific struct or class, maybe make it a static method. If your project really is getting too big, you could perhaps factor out your most general functions into a separate framework, though this is quite a big overhead/learning exercise (and Swift frameworks aren’t entirely fully-baked yet), so if you are just starting out so I’d suggest leaving this for now until you get more confident.
* edit: ok two downsides – member functions are more discoverable (via autocomplete when you hit .)
Updated after discussion with #AirspeedVelocity
Global functions can be ok and they really aren't much different than having type methods or even instance methods on a custom type that is not actually intended to contain state.
The entire thing comes down mostly to personal preference. Here are some pros and cons.
Cons:
They sometimes can cause unintended side effects. That is they can change some global state that you or the caller forgets about causing hard to track down bugs. As long as you are careful about not using global variables and ensure that your function always returns the same result with the same input regardless of the state of the rest of the system, you can mostly ignore this con.
They make code that uses them difficult to test which is important once you start unit testing (which is a definite good policy in most circumstances). It is hard to test because you can't mock out the implementation of a global function easily. For example, to change the value of a global setting. Instead your test will start to depend on your other class that sets this global setting. Being able to inject a setting into your class instead of having to fake out a global function is generally preferable.
They sometimes hint at poor code organization. All of your code should be separable into small, single purpose, logical units. This ensures your code will remain understandable as your code base grows in size and age. The exception to this is truly universal functions that have very high level and reusable concepts. For example, a function that lets you test all of the elements in a sequence. You can also still separate global functions into logical units by separating them into well named files.
Pros:
High level global functions can be very easy to test. However, you cannot ignore the need to still test their logic where they are used because your unit test should not be written with knowledge of how your code is actually implemented.
Easily accessible. It can often be a pain to inject many types into another class (pass objects into an initializer and probably store it as a property). Global functions can often remove this boiler plate code (even if it has the trade off of being less flexible and less testable).
In the end, every code architecture decision is a balance of trade offs each time you go to use it.
I have a Framework.swift that contains a set of common global functions like local(str:String) to get rid of the 2nd parameter from NSLocalize. Also there are a number of alert functions internally using local and with varying number of parameters which makes use of NSAlert as modal dialogs more easy.
So for that purpose global functions are good. They are bad habit when it comes to information hiding where you would expose internal class knowledge to some global functionality.
I have a chunk of lua code that I'd like to be able to (selectively) ignore. I don't have the option of not reading it in and sometimes I'd like it to be processed, sometimes not, so I can't just comment it out (that is, there's a whole bunch of blocks of code and I either have the option of reading none of them or reading all of them). I came up with two ways to implement this (there may well be more - I'm very much a beginner): either enclose the code in a function and then call or not call the function (and once I'm sure I'm passed the point where I would call the function, I can set it to nil to free up the memory) or enclose the code in an if ... end block. The former has slight advantages in that there are several of these blocks and using the former method makes it easier for one block to load another even if the main program didn't request it, but the latter seems the more efficient. However, not knowing much, I don't know if the efficiency saving is worth it.
So how much more efficient is:
if false then
-- a few hundred lines
end
than
throwaway = function ()
-- a few hundred lines
end
throwaway = nil -- to ensure that both methods leave me in the same state after garbage collection
?
If it depends a lot on the lua implementation, how big would the "few hundred lines" need to be to reliably spot the difference, and what sort of stuff should it include to best test (the main use of the blocks is to define a load of possibly useful functions)?
Lua's not smart enough to dump the code for the function, so you're not going to save any memory.
In terms of speed, you're talking about a different of nanoseconds which happens once per program execution. It's harming your efficiency to worry about this, which has virtually no relevance to actual performance. Write the code that you feel expresses your intent most clearly, without trying to be clever. If you run into performance issues, it's going to be a million miles away from this decision.
If you want to save memory, which is understandable on a mobile platform, you could put your conditional code in it's own module and never load it at all of not needed (if your framework supports it; e.g. MOAI does, Corona doesn't).
If there is really a lot of unused code, you can define it as a collection of Strings and loadstring() it when needed. Storing functions as strings will reduce the initial compile time, however of most functions the string representation probably takes up more memory than it's compiled form and what you save when compiling is probably not significant before a few thousand lines... Just saying.
If you put this code in a table, you could compile it transparently through a metatable for minimal performance impact on repeated calls.
Example code
local code_uncompiled = {
f = [=[
local x, y = ...;
return x+y;
]=]
}
code = setmetatable({}, {
__index = function(self, k)
self[k] = assert(loadstring(code_uncompiled[k]));
return self[k];
end
});
local ff = code.f; -- code of x gets compiled here
ff = code.f; -- no compilation here
for i=1, 1000 do
print( ff(2*i, -i) ); -- no compilation here either
print( code.f(2*i, -i) ); -- no compile either, but table access (slower)
end
The beauty of it is that this compiles as needed and you don't really have to waste another thought on it, it's just like storing a function in a table and allows for a lot of flexibility.
Another advantage of this solution is that when the amount of dynamically loaded code gets out of hand, you could transparently change it to load code from external files on demand through the __index function of the metatable. Also, you can mix compiled and uncompiled code by populating the "code" table with "real" functions.
Try the one that makes the code more legible to you first. If it runs fast enough on your target machine, use that.
If it doesn't run fast enough, try the other one.
lua can ignore multiple lines by:
function dostuff()
blabla
faaaaa
--[[
ignore this
and this
maybe this
this as well
]]--
end
There are always several ways to do the same thing in Mathematica. For example, when adapting WReach's solution for my recent problem I used Condition:
ClearAll[ff];
SetAttributes[ff, HoldAllComplete];
ff[expr_] /; (Unset[done]; True) :=
Internal`WithLocalSettings[Null, done = f[expr],
AbortProtect[If[! ValueQ[done], Print["Interrupt!"]]; Unset[done]]]
However, we can do the same thing with Block:
ClearAll[ff];
SetAttributes[ff, HoldAllComplete];
ff[expr_] :=
Block[{done},
Internal`WithLocalSettings[Null, done = f[expr],
AbortProtect[If[! ValueQ[done], Print["Interrupt!"]]]]]
Or with Module:
ClearAll[ff];
SetAttributes[ff, HoldAllComplete];
ff[expr_] :=
Module[{done},
Internal`WithLocalSettings[Null, done = f[expr],
AbortProtect[If[! ValueQ[done], Print["Interrupt!"]]]]]
Probably there are several other ways to do the same. Which way is the most efficient from the point of view of memory and CPU use (f may return very large arrays of data - but may return very small)?
Both Module and Block are quite efficient, so the overhead induced by them is only noticable when the body of a function whose variables you localize does very little. There are two major reasons for the overhead: scoping construct overhead (scoping constructs must analyze the code they enclose to resolve possible name conflicts and bind variables - this takes place for both Module and Block), and the overhead of creation and destruction of new symbols in a symbol table (only for Module). For this reason, Block is somewhat faster. To see how much faster, you can do a simple experiment:
In[14]:=
Clear[f,fm,fb,fmp];
f[x_]:=x;
fm[x_]:=Module[{xl = x},xl];
fb[x_]:=Block[{xl = x},xl];
Module[{xl},fmp[x_]:= xl=x]
We defined here 4 functions, with the simplest body possible - just return the argument, possibly assigned to a local variable. We can expect the effect to be most pronounced here, since the body does very little.
In[19]:= f/#Range[100000];//Timing
Out[19]= {0.063,Null}
In[20]:= fm/#Range[100000];//Timing
Out[20]= {0.343,Null}
In[21]:= fb/#Range[100000];//Timing
Out[21]= {0.172,Null}
In[22]:= fmp/#Range[100000];//Timing
Out[22]= {0.109,Null}
From these timings, we see that Block is about twice faster than Module, but that the version that uses persistent variable created by Module in the last function only once, is about twice more efficient than Block, and almost as fast as a simple function invokation (because persistent variable is only created once, and there is no scoping overhead when applying the function).
For real functions, and most of the time, the overhead of either Module or Block should not matter, so I'd use whatever is safer (usually, Module). If it does matter, one option is to use persistent local variables created by Module only once. If even this overhead is significant, I'd reconsider the design - since then obviously your function does too little.There are cases when Block is more beneficial, for example when you want to be sure that all the memory used by local variables will be automatically released (this is particularly relevant for local variables with DownValues, since they are not always garbage - collected when created by Module). Another reason to use Block is when you expect a possibility of interrupts such as exceptions or aborts, and want the local variables to automatically be reset (which Block does). By using Block, however, you risk name collisions, since it binds variables dynamically rather than lexically.
So, to summarize: in most cases, my suggestion is this: if you feel that your function has serious memory or run-time inefficiency, look elsewhere - it is very rare for scoping constructs to be the major bottleneck. Exceptions would include not garbage-collected Module variables with accumulated data, very light-weight functions used very frequently, and functions which operate on very efficient low-level structures such as packed arrays and sparse arrays, where symbolic scoping overhead may be comparable to the time it takes a function to process its data, since the body is very efficient and uses fast functions that by-pass the main evaluator.
EDIT
By combining Block and Module in the fashion suggested here:
Module[{xl}, fmbp[x_] := Block[{xl = x}, xl]]
you can have the best of both worlds: a function as fast as Block - scoped one and as safe as the one that uses Module.