Using yield to create generators in python

Generators are python functions that act like iterators. This abstraction allows you to simplify a lot of your for-loop code, implement lazy evaluation and even create more intelligent value producing iterators.

In today’s post, I’ll go through a basic usage of the yield keyword; the generator that’s created as a result and how you can interact with this function type.

Prime number example

To produce the generator, I’ve written a function that will filter through numbers picking out prime numbers. The algorithm isn’t highly optimised. It’s quite crude/brute-force in its approach, but it’ll be enough for us to understand the generator function.

import math

def primes():
	ps, cur = [2], 3
	yield 2
	while True:
		y = int(math.sqrt(cur))
		c = next((x for x in ps if x < y and (cur % x) == 0), None)

		if c == None:
			yield cur
			ps.append(cur)

		cur += 2

We’re maintaining an internal list of primes that we’ve found. When we come across a potential candidate, we try to divide it by primes that we’ve already found. To cut down on the number of divides, we only go for numbers lower than the square root of the candidate.

Note the use of yield. As we call yield, this makes another value available in the iterator. You can see that this is an iterator that doesn’t end. Well, it will end - once the integer data type overflows. If we were using a data type that wasn’t susceptible to this type of overflow, we’d only be limited by the amount of memory in the machine.

Iterating

So, we’ve created what appears to be an infinite list. Testing it out in the REPL:

>>> ps = primes()
>>> ps
<generator object primes at 0x7fa1396e8af0>
>>> ps.next()
2
>>> ps.next()
3
>>> ps.next()
5
>>> ps.next()
7
>>> ps.next()
9
>>> ps.next()
11

ps is the generator, and we’re able to call the next function on it. As we do that, we progress through the iterator. We can start to work with ps now as if it were any other iterator.

Using a list comprehension, we can find the first 10 primes:

>>> ps = primes()
>>> [ps.next() for _ in xrange(1, 10)]
[2, 3, 5, 7, 9, 11, 13, 15, 17]

Using itertools we can get all of the prime numbers under 100:

>>> import itertools
>>> list(itertools.takewhile(lambda x: x < 100, primes()))
[2, 3, 5, 7, 9, 11, 13, 15, 17, 19, 23, 25, 29, 31, 35, 37, 41, 43, 47, 49, 53, 59, 61, 67, 71, 73, 79, 83, 89, 97]

yield allows you to make generators which are the potential to create values, as opposed to the values themselves. It’s not until you start to iterate over the generator that the values start to materialise.

Exploring blocks in ruby

Ruby has a very cool feature called code blocks. Sometimes referred to as closures, code blocks are custom pieces (or blocks) of ruby code that you specify to functions that inject your code block whenever the yield keyword is used.

In today’s post, I’m just going to present a simple example and usage.

Source data

The example we’re going to use will be a Manager to Employee style relationship. A Person class is going to manage an array of Person objects that we’ll classify as staff for that person. Here’s the class definition:

class Person

	attr_reader :name, :position, :staff

	def initialize(name, position, staff=[])
		@name = name
		@position = position
		@staff = staff
	end

	def to_s
		@name + ' (' + @position + ') '
	end
end

So a Person will have a name, position and staff. Some sample data using this structure might look as follows:

bob = Person.new('Bob', 'Support Officer')
joe = Person.new('Joe', 'Support Officer')
mary = Person.new('Mary', 'Technology Director', [bob, joe])

Simple example

mary is the manager for joe and bob. Using the Array function each, we can use a code block to present each person to screen:

mary.staff.each do |p|
	puts "Mary is the manager for #{p}"
end

That’s our first code block. each will run our code block for every Person in mary’s staff array.

Another level

If we introduce ‘bill’ as the manager of the company:

bill = Person.new('Bill', 'Managing Director', [mary])

We can use each to look at Bill’s staff, which is just Mary at this stage. More interestingly, we could implement our own function on the Person class that shows all of that person’s descendants.

def descendants

	@staff.each do |s|
		yield s

		# recurse 
		s.descendants do |q|
			yield q
		end

	end

end

We’re going to call any code block specified to our descendants function for each of the staff that are managed by this Person object, but we’re also going to call each descendant’s descendants function so that we recurse down the tree.

We could augment this call slightly to also include the manager of the descendants:

def descendants

	@staff.each do |s|
		yield s

		# recurse 
		s.descendants do |q|
			yield q, s
		end

	end

end

This will supply a manager to the calling block, 1 level down from where we specify.

bill.descendants do |p, s|
	if s == nil
		puts "#{p} is managed by #{bill}"
	else
		puts "#{p} is managed by #{s}"
	end
end

This code here emits the following:

Mary (Technology Director)  is managed by Bill (Managing Director) 
Bob (Support Officer)  is managed by Mary (Technology Director) 
Joe (Support Officer)  is managed by Mary (Technology Director) 

Mary’s manager variable in the block comes through as nil as she’s a direct descendant of bill, so we handle this case in the block as opposed to in descendants.

You can specify as many parameters as you want in your yield. It’s your block’s responsibility to do something useful with them!

Other options

Within your function, you can test the block_given? property for a boolean that will determine if the calling code did or didn’t specify a block.

You can also have a parameter specified in your function &block which can be handy should you need to pass the block around.

Dissecting dmesg with awk

AWK is a programming language that deals with processing text in a sequence of pattern matching rules. It’s really handy for reducing massive amounts of text into just the information that you care about. The full user guide for AWK can be found here.

Rather than take you on a tour through the user guide, I thought today’s post might be better as a practical example. I’m going to present some useful functions with AWK using the Linux Kernel’s dmesg output as source data.

As a final note, a lot if not all of the information that I’ll present below can be transformed into a “one liner”. There’s quite a few instances of crafty AWK hackers putting these together. I just want to present some of the language.

Source data

The dmesg data is in an easy-enough format to work with. Taking the first few lines as an example:

[    0.000000] Initializing cgroup subsys cpuset
[    0.000000] Initializing cgroup subsys cpu
[    0.000000] Initializing cgroup subsys cpuacct

We see that there is an elapsed time figure surrounded with square brackets, the rest of the line is the log text. Further on through the text, we start to see the log lines prefixed with a driver name also:

[    4.871693] vboxdrv: Found 8 processor cores.
[    4.872033] vboxdrv: fAsync=0 offMin=0x19e offMax=0xcb6

Basic usage

For the purposes of today’s post, the following usage is going to be most useful to us

dmesg | awk -f our-awk-script.awk

This supplies the dmesg output to our AWK script.

Print any line with the word “failed” in it

To accomplish this task, we’re going to use a regular expression to pick out each line with “fail” in it.

/ failed / {
	print $0
}

Immediately, you can see that AWK statements take the shape of:

condition { actions }

The action here print $0 prints the whole, captured line to the console. Other variables are available to be printed such as $1, $2, and so on. These numbered variables take chunks of the captured string, split by a space character as its delimiter.

Exploring the variables

Just to take a look at those variables a little closer, we can augment our initial rule slightly to see what’s contained in those variables:

/ failed / {
	print "$0: ", $0
	print "$1: ", $1
	print "$2: ", $2
	print "$3: ", $3
	print "$4: ", $4
}

Run for one line of text matching the “failed” rule:

$0:  [    1.804314] iwlwifi 0000:03:00.0: Direct firmware load failed with error -2
$1:  [
$2:  1.804314]
$3:  iwlwifi
$4:  0000:03:00.0:

Listing out which drivers mentioned the word “failed”

AWK has a very flexible associative array type as well. We can basically reference any variable with any index we choose. For the next progression of this script, we’ll build an array of driver names with an instance count so we can just give the user a report of the which drivers were mentioned how many times.

/ failed / { 
	drivers[$3] = drivers[$3] + 1
}

END {
	for (driver in drivers) {
		print driver ":", drivers[driver]
	}	
}

$3 is giving us the driver name, so we just increment a value in the array for that driver. END is something new. It’s executed, at the end. We enumerate the array that we’ve built, printing the name of the driver and the count.

Running this, I get the following result:

nouveau: 1
nouveau:: 1
iwlwifi: 2

That’s annoying. nouveau appears in the report twice because it’s mentioned with and without a colon : character in the source text.

[    1.687503] nouveau E[     DRM] failed to create 0x80000080, -22
[    1.687631] nouveau: probe of 0000:01:00.0 failed with error -22

Adding a call to gsub to perform a simple string replacement does the trick. gsub is a part of AWK’s string functions.

/ failed / { 
	gsub(/\:/, "", $3)
	drivers[$3] = drivers[$3] + 1
}

With an output like this

nouveau: 2
iwlwifi: 2

Much better.

Just as we have an ‘END’ section above, we are also given the ability to write code in a ‘BEGIN’ section that will kick off before any of our pattern rules are executed.

Using boolean logic in conditions

AWK conditions aren’t just regular expressions, they can incorporate boolean logic from the file also. You can test any variable like a normal boolean condition. In the following example, I don’t want to count failures that come out of the iwlwifi driver.

/ failed / && $3 != "iwlwifi" { 
	gsub(/\:/, "", $3)
	drivers[$3] = drivers[$3] + 1
}

Other functions to check out

If at any time, your rule wants to bug out of the script entirely - wire up the exit call. If you just want to stop processing this line of text and move on to the next, you can use next.

Sharing files easily over HTTP with Python

Getting a quick web server up and running is really simple (if you don’t need a fully blown application server). I find this technique really useful when prototyping web sites that I only need to serve static HTML, CSS & Javascript with.

In the folder that hosts your web application, issue the following Python command:

python -m SimpleHTTPServer

After you do this, you’ll get a confirmation message that your site is available:

Serving HTTP on 0.0.0.0 port 8000 ...

And that’s it. You can read up more on this really handy utility here.

An inline assembly primer with gcc

A really handy feature of GCC is that it allows you to inter-mix assembly code with your C code.

There are so many great references on this topic already. One of the best is from Lockless however there are many, many more.

Today’s article is more of a quick reference for inlining your assembly code.

Syntax

When preparing a block of assembly to be put inline in your C code, you use the asm keyword.

asm [volatile] ( 
	assembly code
	: outputs
	: inputs
	: clobbers
)

The first parameter that is passed is the assembly code itself. It’ll be in AT&T syntax, but will also have some extra rules apply to it which will allow for the compiler to make some decisions for you. The outputs, inputs and clobbers are optional lists consisting of directives instructing the compiler how to handle inputs, outputs and what’s expected to be trashed (clobbered) in your assembly block.

A simple example usage, to add two integers and return the result might look like this:

int add(int a, int b) {
	int c;

	asm (
		"xorl	%%eax, %%eax\n\t"
		"addl	%2, %1\n\t"
		"movl 	%1, %0"
		: "=m" (c)
		: "r" (a), "r" (b)
		: "%eax"
	);

	return c;
}

Once this code is compiled, you can see what the compiler has done with it:

	asm (
   a:	8b 55 ec             	mov    edx,DWORD PTR [rbp-0x14]
   d:	8b 4d e8             	mov    ecx,DWORD PTR [rbp-0x18]
  10:	31 c0                	xor    eax,eax
  12:	01 ca                	add    edx,ecx
  14:	89 55 fc             	mov    DWORD PTR [rbp-0x4],edx
		: "=m" (c)
		: "r" (a), "r" (b)
		: "%eax"
	);

edx and ecx were chosen as our general purpose registers for inputs, so they’re loaded first-up. The addition occurs and then the result (as requested) is placed in the memory location of our output. Back in the inline code, you can see that these registers have been symbolically referenced as %1, %2, etc.

Outputs are a mix of constraints and modifiers, inputs are just constraints and clobbers list out what was modified (register-wise or other).

What about volatile?

The volatile keyword allows you to tell the compiler to not optimise away our code if it deems that it isn’t required (i.e. is has no effect on anything).

Constraints

A full description of all of these constraints can be found here.

Modifiers

A full description of all of these modifiers can be found here.

Clobbers

A full description of clobbers can be found here.