class Perceptron(object):
 
    def __init__(self, weights=None, threshold=0.5):
        self.threshold = threshold
        self.weights = weights
        self.verbose = False
 
    def output(self, input_vector):
        if self._total(input_vector) < self.threshold:
            return 0
        else:
            return 1
 
    def train(self, training_set, alpha=0.1, end_after=100):
        if self.weights is None:
            self.weights = [0 for _ in range(len(training_set.keys()[0]))]
        n = 0
        updated = True
        while(updated):
            n += 1
            updated = False
            for xv, t in training_set.items():
                y = self.output(xv)
                if(y != t):
                    self._update_weights(alpha, t, y, xv)
                    self._update_threshold(alpha, t, y)
                    updated = True
            if end_after is not None and n >= end_after:
                break
        return n
 
    def test(self, training_set):
        for xv, t in training_set.items():
            if(self.output(xv) != t):
                return False
        return True
 
    def _total(self, input_vector):
        total = 0
        for w,x in zip(self.weights, input_vector):
            total += (w * x)
        return total
 
    def _update_weights(self, alpha, t, y, xv):
        for i in range(len(self.weights)):
            self.weights[i] = (alpha * (t - y) * xv[i]) + self.weights[i]
 
    def _update_threshold(self, alpha, t, y):
        self.threshold = (alpha * (t - y) * -1) + self.threshold

nand_set = {
  (0,0): 1,
  (0,1): 1,
  (1,0): 1,
  (1,1): 0
  }
 
nn = Perceptron()
iterations = nn.train(nand_set, alpha=.2) # alpha is the learning rate
print "Trained in {0} iterations.".format(iterations)
print "Correct?", nn.test(nand_set)
print "Weights: {0}, Threshold: {1}".format(nn.weights, nn.threshold)

Trained in 9 iterations.
Correct? True
Weights: [-0.40000000000000002, -0.20000000000000001], Threshold: -0.5

nand_perceptron = Perceptron((-0.4, -0.2), -0.5)
print "Correct?", nand_perceptron.test(nand_set)

Correct? True

import asynchat
import socket
import ssl
import errno
 
class async_chat_ssl(asynchat.async_chat):
    """ Asynchronous connection with SSL support. """
 
    def connect(self, host, use_ssl=False):
        self.use_ssl = use_ssl
        if use_ssl:
            self.send = self._ssl_send
            self.recv = self._ssl_recv
        asynchat.async_chat.connect(self, host)
 
    def handle_connect(self):
        """ Initializes SSL support after the connection has been made. """
        if self.use_ssl:
            self.ssl = ssl.wrap_socket(self.socket)
            self.set_socket(self.ssl)
 
    def _ssl_send(self, data):
        """ Replacement for self.send() during SSL connections. """
        try:
            result = self.write(data)
            return result
        except ssl.SSLError, why:
            if why[0] in (asyncore.EWOULDBLOCK, errno.ESRCH):
                return 0
            else:
                raise ssl.SSLError, why
            return 0
 
    def _ssl_recv(self, buffer_size):
        """ Replacement for self.recv() during SSL connections. """
        try:
            data = self.read(buffer_size)
            if not data:
                self.handle_close()
                return ''
            return data
        except ssl.SSLError, why:
            if why[0] in (asyncore.ECONNRESET, asyncore.ENOTCONN, 
                          asyncore.ESHUTDOWN):
                self.handle_close()
                return ''
            elif why[0] == errno.ENOENT:
                # Required in order to keep it non-blocking
                return ''
            else:
                raise

connect(host, use_ssl=True)

import collections
import random
 
 
class DynamicDie(collections.defaultdict):
 
    def __init__(self):
        collections.defaultdict.__init__(self, int)
 
    def add_side(self, side):
        self[side] += 1
 
    def total_sides(self):
        return sum(self.values())
 
    def roll(self):
        random_num = random.randint(0, self.total_sides())
        total_pos = 0
        for side, qty in self.items():
            total_pos += qty
            if random_num <= total_pos:
                return side
 
 
class MarkovChain(collections.defaultdict):
    """ Yet another markov chain implementation.
        This one differs in the sense that it is able to better support
        huge amounts of data since the weighted randomization doesn't rely
        on duplicates.
    """
 
    # Sentinals 
    # Discussion here: http://stackoverflow.com/questions/1677726
    class START(object):pass
    class END(object):pass
 
    def __init__(self):
        collections.defaultdict.__init__(self, DynamicDie)
 
    def add(self, iterable):
        """ Insert an iterable (pattern) item into the markov chain.
            The order of the pattern will define more of the chain.
        """
        item1 = item2 = MarkovChain.START
        for item3 in iterable:
            self[(item1, item2)].add_side(item3)
            item1 = item2
            item2 = item3
        self[(item1, item2)].add_side(MarkovChain.END)
 
    def random_output(self, max=100):
        """ Generate a list of elements from the markov chain.
            The `max` value is in place in order to prevent excessive iteration.
        """
        output = []
        item1 = item2 = MarkovChain.START
        for i in range(max-2):
            item3 = self[(item1, item2)].roll()
            if item3 is MarkovChain.END:
                break
            output.append(item3)
            item1 = item2
            item2 = item3
        return output

import markov
chain = markov.MarkovChain()
 
# Load the dictionary into the markov chain
dictionary = "/usr/share/dict/words"
for word in open(dictionary):
    word = word.strip()
    if word != "" and not word.endswith("'s"):
        chain.add(word)
 
# Let's generate 10 random pseudowords
for i in range(10):
    print "".join(chain.random_output())

import time
 
def send_to_future(message, seconds):
    time.sleep(seconds)
    return message

import random
 
vowels = ["a", "e", "i", "o", "u"]
consonants = ['b', 'c', 'd', 'f', 'g', 'h', 'j', 'k', 'l', 'm', 'n', 'p', 'q', 
              'r', 's', 't', 'v', 'w', 'x', 'y', 'z']
 
def _vowel():
    return random.choice(vowels)
 
def _consonant():
    return random.choice(consonants)
 
def _cv():
    return _consonant() + _vowel()
 
def _cvc():
    return _cv() + _consonant()
 
def _syllable():
    return random.choice([_vowel, _cv, _cvc])()
 
def create_fake_word():
    """ This function generates a fake word by creating between two and three
        random syllables and then joining them together.
    """
    syllables = []
    for x in range(random.randint(2,3)):
        syllables.append(_syllable())
    return "".join(syllables)
 
if __name__ == "__main__":
    print create_fake_word()

hojocina
eliphaa
deaketyed
ciboa
tiuzi

# pluginmanager.py
from collections import defaultdict
 
 
plugins = defaultdict(list)
def register(*events):
    """ This decorator is to be used for registering a function as a plugin for
        a specific event or list of events. 
    """
    def registered_plugin(funct):
        for event in events:
            plugins[event].append(funct)
        return funct
    return registered_plugin
 
 
def trigger_event(event, *args, **kwargs):
    """ Call this function to trigger an event. It will run any plugins that
        have registered themselves to the event. Any additional arguments or
        keyword arguments you pass in will be passed to the plugins.
    """
    for plugin in plugins[event]:
        plugin(*args, **kwargs)
 
 
def load_plugins(config_file):
    """ This reads a config file of a list of plugins to load. It ignores
        empty lines or lines beginning with a hash mark (#). It is so plugin
        imports are more dynamic and you don't need to continue appending
        import statements to the top of a file.
    """
    with open(config_file, "r") as fh:
        for line in fh:
            line = line.strip()
            if line.startswith("#") or line == "":
                continue
            __import__(line,  globals(), locals(), [], -1)

import pluginmanager
 
@pluginmanager.register("FOO_ACTIVE")
def print_data(*args, **kwargs):
    if "data" in kwargs:
        print "Received the following: %s" % kwargs["data"]
    else:
        print "Didn't receive any data."

# Blank lines and lines starting with a hash (#) are ignored.
# So be as verbose as you want.
plugins.example

import pluginmanager
pluginmanager.load_plugins("plugins.list") # load any plugins in the list
 
# ... code ...
 
# The FOO_ACTIVE event occurs somewhere
pluginmanager.trigger_event("FOO_ACTIVE", 
                            data="this data is sent to the plugin", 
                            foo="so is this")
 
# ... code ...

import re
 
def identifier(scanner, token): return "IDENT", token
def operator(scanner, token):   return "OPERATOR", token
def digit(scanner, token):      return "DIGIT", token
def end_stmnt(scanner, token):  return "END_STATEMENT"
 
scanner = re.Scanner([
    (r"[a-zA-Z_]\w*", identifier),
    (r"\+|\-|\\|\*|\=", operator),
    (r"[0-9]+(\.[0-9]+)?", digit),
    (r";", end_stmnt),
    (r"\s+", None),
    ])
 
tokens, remainder = scanner.scan("foo = 5 * 30; bar = bar - 60;")
for token in tokens:
    print token

('IDENT', 'foo')
('OPERATOR', '=')
('DIGIT', '5')
('OPERATOR', '*')
('DIGIT', '30')
END_STATEMENT
('IDENT', 'bar')
('OPERATOR', '=')
('IDENT', 'bar')
('OPERATOR', '-')
('DIGIT', '60')
END_STATEMENT

import re
 
 
class UnknownTokenError(Exception):
    """ This exception is for use to be thrown when an unknown token is
        encountered in the token stream. It hols the line number and the
        offending token.
    """
    def __init__(self, token, lineno):
        self.token = token
        self.lineno = lineno
 
    def __str__(self):
        return "Line #%s, Found token: %s" % (self.lineno, self.token)
 
 
class _InputScanner(object):
    """ This class manages the scanning of a specific input. An instance of it is
        returned when scan() is called. It is built to be great for iteration. This is
        mainly to be used by the Lexer and ideally not directly.
    """
 
    def __init__(self, lexer, input):
        """ Put the lexer into this instance so the callbacks can reference it 
            if needed.
        """
        self._position = 0
        self.lexer = lexer
        self.input = input
 
    def __iter__(self):
        """ All of the code for iteration is controlled by the class itself.
            This and next() (or __next__() in Python 3.0) are so syntax
            like `for token in Lexer(...):` is valid and works.
        """
        return self
 
    def next(self):
        """ Used for iteration. It returns token after token until there
            are no more tokens. (change this to __next__(self) if using Py3.0)
        """
        if not self.done_scanning():
            return self.scan_next()
        raise StopIteration
 
    def done_scanning(self):
        """ A simple boolean function that returns true if scanning is
            complete and false if it isn't.
        """
        return self._position >= len(self.input)
 
    def scan_next(self):
        """ Retreive the next token from the input. If the
            flag `omit_whitespace` is set to True, then it will
            skip over the whitespace characters present.
        """
        if self.done_scanning():
            return None
        if self.lexer.omit_whitespace:
            match = self.lexer.ws_regexc.match(self.input, self._position)
            if match:
                self._position = match.end()
        match = self.lexer.regexc.match(self.input, self._position)
        if match is None:
            lineno = self.input[:self._position].count("\n") + 1
            raise UnknownTokenError(self.input[self._position], lineno)
        self._position = match.end()
        value = match.group(match.lastgroup)
        if match.lastgroup in self.lexer._callbacks:
            value = self.lexer._callbacks[match.lastgroup](self, value)
        return match.lastgroup, value
 
 
class Lexer(object):
    """ A lexical scanner. It takes in an input and a set of rules based
        on reqular expressions. It then scans the input and returns the
        tokens one-by-one. It is meant to be used through iterating.
    """
 
    def __init__(self, rules, case_sensitive=True, omit_whitespace=True):
        """ Set up the lexical scanner. Build and compile the regular expression
            and prepare the whitespace searcher.
        """
        self._callbacks = {}
        self.omit_whitespace = omit_whitespace
        self.case_sensitive = case_sensitive
        parts = []
        for name, rule in rules:
            if not isinstance(rule, str):
                rule, callback = rule
                self._callbacks[name] = callback
            parts.append("(?P<%s>%s)" % (name, rule))
        if self.case_sensitive:
            flags = re.M
        else:
            flags = re.M|re.I
        self.regexc = re.compile("|".join(parts), flags)
        self.ws_regexc = re.compile("\s*", re.MULTILINE)
 
    def scan(self, input):
        """ Return a scanner built for matching through the `input` field. 
            The scanner that it returns is built well for iterating.
        """
        return _InputScanner(self, input)

def stmnt_callback(scanner, token):
    """ This is just an example of providing a function to run the
        token through.
    """
    return ""
 
rules = [
    ("IDENTIFIER", r"[a-zA-Z_]\w*"),
    ("OPERATOR",   r"\+|\-|\\|\*|\="),
    ("DIGIT",      r"[0-9]+(\.[0-9]+)?"),
    ("END_STMNT",  (";", stmnt_callback)), 
    ]
 
lex = Lexer(rules, case_sensitive=True)
for token in lex.scan("foo = 5 * 30; bar = bar - 60;"):
    print token

('IDENTIFIER', 'foo')
('OPERATOR', '=')
('DIGIT', '5')
('OPERATOR', '*')
('DIGIT', '30')
('END_STMNT', '')
('IDENTIFIER', 'bar')
('OPERATOR', '=')
('IDENTIFIER', 'bar')
('OPERATOR', '-')
('DIGIT', '60')
('END_STMNT', '')