I’ve been playing around with Julia lately and have been enjoying it. I have come from python and as a learning exercise was looking at re-writing some code I had written to do least significant bit embedding.
I’m wondering if my re-write below is the best way to write a more complicated generator or if there are better or more efficient ways to implement one.
Apologies if I’ve just missed something obvious.
Original python code below:
def bit_generator(s):
for x in s:
a = ord(x)
i = 0
while i < 7:
yield a & 1
a = a >> 1 # bit shifting embeds character backwards
i += 1
# signify end with 14 zeros (double ascii null)
for x in xrange(14):
yield 0
Julia equivalent (without the nulls at the end). This is where I missed yield as I ended up creating two generators to achieve the same - I could have easily just missed something here, but this is what I came up with.
type OrdGenerator
s::String
end
Base.start(x::OrdGenerator) = 1
Base.done(x::OrdGenerator, state) = length(x.s) == state - 1
Base.next(x::OrdGenerator, state) = Int8(x.s[state]), state + 1
type BitGenerator
b::Int8
end
Base.start(x::BitGenerator) = 1
Base.done(x::BitGenerator, state) = state > 7
function Base.next(x::BitGenerator, state)
a = x.b & 1
x.b = x.b >> 1
a, state + 1
end
s = "word? w"
println("$s : length = $(length(s))")
for (i, x) in enumerate(OrdGenerator(s))
println("$i: $x | $(bin(x))")
for (j, bit) in enumerate(BitGenerator(x))
println(" $j: $bit")
end
end
I think my attempt above does use the iterator interface - happy that I’ve used the best method to create one.
After seeing your response and thinking about this a bit more, my main issue was probably more around the fact that I had to create two generators to achieve what I wanted as there was a nested while under the for.
I ended up working out that you can create a type for the state variable that has an accumulator, which works (see code below), but I’m still wondering if this approach is reasonable or what other people do?
Also, by “more complicated generator”, I really meant anything that couldn’t be easily achieved in something like a list comprehension.
type Generator
s::String
end
type State
i::Int64
index_bit::Int8
acc::Int8
end
Base.start(x::Generator) = State(1, 0, 0)
Base.done(x::Generator, state::State) = (length(x.s), 7) == (state.i, state.index_bit)
function Base.next(x::Generator, state::State)
if state.index_bit == 0
state = State(state.i, state.index_bit + 1, Int8(x.s[state.i]))
elseif state.index_bit == 7
state = State(state.i + 1, 1, Int8(x.s[state.i + 1]))
else
state = State(state.i, state.index_bit + 1, state.acc >> 1)
end
println("$(state.acc & 1) | $state")
state.acc & 1, state
end
s = "here"
for (i, x) in enumerate(Generator(s)) end
I had looked at Tasks but as they were used in parallel computing, I thought they might be overkill for what I was doing.
I tried to create a generator using Channels (running Julia v0.5.2) this morning with no luck. I had success with the Tasks equivalent:
bit_generator(s::String) = Task() do
for x in s
a = Int8(x[1])
i = 0
while i < 7
produce(a & 1)
a = a >> 1
i += 1
end
end
for x in 1:14
produce(0)
end
end
for bit in bit_generator("text")
@printf("%d", bit)
end
My Channels attempt was essentially replacing as per below:
Tasks() do -> Channels() do c
produce(y) -> push!(c, y)
but I get the following error.
MethodError: Cannot `convert` an object of type ##45#46{String} to an object of type Channel{T}
This may have arisen from a call to the constructor Channel{T}(...),
since type constructors fall back to convert methods.
in anonymous at ./<missing>:?
I also looking for a way to define a generator using Channel
Generator1() = Channel() do c
i = 1
while(true)
push!(c, i)
i = i + 1
end
end
function Generator2()
c = Channel{Int}(1)
i = 1
while(true)
push!(c, i)
i = i + 1
end
end
# println(Generator1())
for i in Generator1()
@show i
sleep(1)
end
My issue is that I don’t like Generator1 to be a Channel of Any I’d prefer it to return a Channel of Int.
I tried to implement such an idea in Generator2 but nothing is displayed on console.
Generator1() = Channel(ctype=Int) do c
i = 1
while(true)
push!(c, i)
i = i + 1
end
end
The above code is calling this constructor Channel(func::Function; ctype=Any, csize=0, taskref=nothing). The first argument comes from the do syntax and the rest of the arguments can be used normally.
Depends on your performance requirements. For the highest performance, create a type that implements the iteration protocol. If your performance demands aren’t that stringent then a channel is a fine way to go as well.
struct PSerie
p
end
function Base.iterate(ps::PSerie, itr=(0,1,0))
s,n,y = itr
if y == 1; @goto y1 end
while true
s += 1.0/(n^ps.p)
return s,(s,n,1)
@label y1
n += 1
end
end
p_serie(n) = (x for x in PSerie(n))
then run
using Base.Iterators: take
[take(p_serie(2),10)...]
Thanks for the example. What I am interested in: Is there anyone here
who doesn’t think the Python code is easier and clearer?
ffevotte> ‘If you’re willing to import additional packages’.
Honestly, no. This is such an elementary and frequent task that
I think Base should provide it. Do I remember correctly that this
worked in version 0.6?
I don’t think this is a good example of that. It’s true that your solution closely resembles the original yielding python code, but for Julia developers used to Julia style iterators (and who don’t have the Python code to compare to), I think that style of iterator may be confusing. Compare your suggestion:
function Base.iterate(ps::PSerie, itr=(0,1,0))
s,n,y = itr
if y == 1; @goto y1 end
while true
s += 1.0/(n^ps.p)
return s,(s,n,1)
@label y1
n += 1
end
end
To the equivalent Julia style iterator:
function Base.iterate(ps::PSerie, (s,n) = (0,1))
s += 1 / (n^ps.p)
s, (s, n+1)
end
I’m not sure I agree anymore. I used to use generators all the time when choosing in Python, and I definitely missed this functionality when I first started working on Julia. But I can honestly say in the past year of doing basically everything in Julia, it just hasn’t been an issue.
Secondly, it’s an example. so it was kept simple deliberately.
I like a lot generators too but for any functions that will have two yields or more you will got an irreducible control flow graph that you won’t be able to recode with a generator. Your solution will won’t work for two yields or more. The goto one will.
For a single case yield, use generator. They’re great
IMO, the goto solution is not more readable than the two line iterator I posted. My initial reaction is “why is there a while loop in an iterator, there must be something wrong here”. Of course, it depends on what you’re used to. Someone used to yielding iterators might find it easier to read.
Could you give an example of such a function? Perhaps there’s an alternative way to do it.
