Author: Armin Rigo <ar...@tunes.org>
Branch:
Changeset: r50126:6d5002ae61ff
Date: 2011-12-04 13:23 +0100
http://bitbucket.org/pypy/pypy/changeset/6d5002ae61ff/
Log: backout d5a684ab8934: the approach does not really work at all. User
code can really expect that after "import itertools", the itertools
module is the built-in one. For example it behaves differently when
reload() is called. Major mess.
diff --git a/lib_pypy/_itertools.py b/lib_pypy/_itertools.py
deleted file mode 100644
--- a/lib_pypy/_itertools.py
+++ /dev/null
@@ -1,670 +0,0 @@
-# Note that PyPy contains also a built-in implementation of 'itertools';
-# when translated with default options, this one is not used.
-
-"""Functional tools for creating and using iterators.
-
-Infinite iterators:
-count([n]) --> n, n+1, n+2, ...
-cycle(p) --> p0, p1, ... plast, p0, p1, ...
-repeat(elem [,n]) --> elem, elem, elem, ... endlessly or up to n times
-
-Iterators terminating on the shortest input sequence:
-izip(p, q, ...) --> (p[0], q[0]), (p[1], q[1]), ...
-ifilter(pred, seq) --> elements of seq where pred(elem) is True
-ifilterfalse(pred, seq) --> elements of seq where pred(elem) is False
-islice(seq, [start,] stop [, step]) --> elements from
- seq[start:stop:step]
-imap(fun, p, q, ...) --> fun(p0, q0), fun(p1, q1), ...
-starmap(fun, seq) --> fun(*seq[0]), fun(*seq[1]), ...
-tee(it, n=2) --> (it1, it2 , ... itn) splits one iterator into n
-chain(p, q, ...) --> p0, p1, ... plast, q0, q1, ...
-takewhile(pred, seq) --> seq[0], seq[1], until pred fails
-dropwhile(pred, seq) --> seq[n], seq[n+1], starting when pred fails
-groupby(iterable[, keyfunc]) --> sub-iterators grouped by value of keyfunc(v)
-"""
-
-__all__ = ['chain', 'count', 'cycle', 'dropwhile', 'groupby', 'ifilter',
- 'ifilterfalse', 'imap', 'islice', 'izip', 'repeat', 'starmap',
- 'takewhile', 'tee', 'compress', 'product']
-
-try: from __pypy__ import builtinify
-except ImportError: builtinify = lambda f: f
-
-
-class chain(object):
- """Make an iterator that returns elements from the first iterable
- until it is exhausted, then proceeds to the next iterable, until
- all of the iterables are exhausted. Used for treating consecutive
- sequences as a single sequence.
-
- Equivalent to :
-
- def chain(*iterables):
- for it in iterables:
- for element in it:
- yield element
- """
- def __init__(self, *iterables):
- self._iterables_iter = iter(map(iter, iterables))
- # little trick for the first chain.next() call
- self._cur_iterable_iter = iter([])
-
- def __iter__(self):
- return self
-
- def next(self):
- while True:
- try:
- return self._cur_iterable_iter.next()
- except StopIteration:
- self._cur_iterable_iter = self._iterables_iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._cur_iterable_iter))
-
-
-class compress(object):
- def __init__(self, data, selectors):
- self.data = iter(data)
- self.selectors = iter(selectors)
-
- def __iter__(self):
- return self
-
- def next(self):
- while True:
- next_item = self.data.next()
- next_selector = self.selectors.next()
- if bool(next_selector):
- return next_item
-
-
-class count(object):
- """Make an iterator that returns consecutive integers starting
- with n. If not specified n defaults to zero. Does not currently
- support python long integers. Often used as an argument to imap()
- to generate consecutive data points. Also, used with izip() to
- add sequence numbers.
-
- Equivalent to :
-
- def count(n=0):
- if not isinstance(n, int):
- raise TypeError("%s is not a regular integer" % n)
- while True:
- yield n
- n += 1
- """
- def __init__(self, n=0):
- if not isinstance(n, int):
- raise TypeError('%s is not a regular integer' % n)
- self.times = n-1
-
- def __iter__(self):
- return self
-
- def next(self):
- self.times += 1
- return self.times
-
- def __repr__(self):
- return 'count(%d)' % (self.times + 1)
-
-
-
-class cycle(object):
- """Make an iterator returning elements from the iterable and
- saving a copy of each. When the iterable is exhausted, return
- elements from the saved copy. Repeats indefinitely.
-
- Equivalent to :
-
- def cycle(iterable):
- saved = []
- for element in iterable:
- yield element
- saved.append(element)
- while saved:
- for element in saved:
- yield element
- """
- def __init__(self, iterable):
- self._cur_iter = iter(iterable)
- self._saved = []
- self._must_save = True
-
- def __iter__(self):
- return self
-
- def next(self):
- # XXX Could probably be improved
- try:
- next_elt = self._cur_iter.next()
- if self._must_save:
- self._saved.append(next_elt)
- except StopIteration:
- self._cur_iter = iter(self._saved)
- next_elt = self._cur_iter.next()
- self._must_save = False
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._cur_iter))
- return next_elt
-
-
-class dropwhile(object):
- """Make an iterator that drops elements from the iterable as long
- as the predicate is true; afterwards, returns every
- element. Note, the iterator does not produce any output until the
- predicate is true, so it may have a lengthy start-up time.
-
- Equivalent to :
-
- def dropwhile(predicate, iterable):
- iterable = iter(iterable)
- for x in iterable:
- if not predicate(x):
- yield x
- break
- for x in iterable:
- yield x
- """
- def __init__(self, predicate, iterable):
- self._predicate = predicate
- self._iter = iter(iterable)
- self._dropped = False
-
- def __iter__(self):
- return self
-
- def next(self):
- try:
- value = self._iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._iter))
- if self._dropped:
- return value
- while self._predicate(value):
- value = self._iter.next()
- self._dropped = True
- return value
-
-class groupby(object):
- """Make an iterator that returns consecutive keys and groups from the
- iterable. The key is a function computing a key value for each
- element. If not specified or is None, key defaults to an identity
- function and returns the element unchanged. Generally, the
- iterable needs to already be sorted on the same key function.
-
- The returned group is itself an iterator that shares the
- underlying iterable with groupby(). Because the source is shared,
- when the groupby object is advanced, the previous group is no
- longer visible. So, if that data is needed later, it should be
- stored as a list:
-
- groups = []
- uniquekeys = []
- for k, g in groupby(data, keyfunc):
- groups.append(list(g)) # Store group iterator as a list
- uniquekeys.append(k)
- """
- def __init__(self, iterable, key=None):
- if key is None:
- key = lambda x: x
- self.keyfunc = key
- self.it = iter(iterable)
- self.tgtkey = self.currkey = self.currvalue = xrange(0)
-
- def __iter__(self):
- return self
-
- def next(self):
- while self.currkey == self.tgtkey:
- try:
- self.currvalue = self.it.next() # Exit on StopIteration
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self.it))
- self.currkey = self.keyfunc(self.currvalue)
- self.tgtkey = self.currkey
- return (self.currkey, self._grouper(self.tgtkey))
-
- def _grouper(self, tgtkey):
- while self.currkey == tgtkey:
- yield self.currvalue
- self.currvalue = self.it.next() # Exit on StopIteration
- self.currkey = self.keyfunc(self.currvalue)
-
-
-
-class _ifilter_base(object):
- """base class for ifilter and ifilterflase"""
- def __init__(self, predicate, iterable):
- # Make sure iterable *IS* iterable
- self._iter = iter(iterable)
- if predicate is None:
- self._predicate = bool
- else:
- self._predicate = predicate
-
- def __iter__(self):
- return self
-
-class ifilter(_ifilter_base):
- """Make an iterator that filters elements from iterable returning
- only those for which the predicate is True. If predicate is
- None, return the items that are true.
-
- Equivalent to :
-
- def ifilter:
- if predicate is None:
- predicate = bool
- for x in iterable:
- if predicate(x):
- yield x
- """
- def next(self):
- try:
- next_elt = self._iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._iter))
- while True:
- if self._predicate(next_elt):
- return next_elt
- next_elt = self._iter.next()
-
-class ifilterfalse(_ifilter_base):
- """Make an iterator that filters elements from iterable returning
- only those for which the predicate is False. If predicate is
- None, return the items that are false.
-
- Equivalent to :
-
- def ifilterfalse(predicate, iterable):
- if predicate is None:
- predicate = bool
- for x in iterable:
- if not predicate(x):
- yield x
- """
- def next(self):
- try:
- next_elt = self._iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._iter))
- while True:
- if not self._predicate(next_elt):
- return next_elt
- next_elt = self._iter.next()
-
-
-
-
-class imap(object):
- """Make an iterator that computes the function using arguments
- from each of the iterables. If function is set to None, then
- imap() returns the arguments as a tuple. Like map() but stops
- when the shortest iterable is exhausted instead of filling in
- None for shorter iterables. The reason for the difference is that
- infinite iterator arguments are typically an error for map()
- (because the output is fully evaluated) but represent a common
- and useful way of supplying arguments to imap().
-
- Equivalent to :
-
- def imap(function, *iterables):
- iterables = map(iter, iterables)
- while True:
- args = [i.next() for i in iterables]
- if function is None:
- yield tuple(args)
- else:
- yield function(*args)
-
- """
- def __init__(self, function, iterable, *other_iterables):
- self._func = function
- self._iters = map(iter, (iterable, ) + other_iterables)
-
- def __iter__(self):
- return self
-
- def next(self):
- try:
- args = [it.next() for it in self._iters]
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (it))
- if self._func is None:
- return tuple(args)
- else:
- return self._func(*args)
-
-
-
-class islice(object):
- """Make an iterator that returns selected elements from the
- iterable. If start is non-zero, then elements from the iterable
- are skipped until start is reached. Afterward, elements are
- returned consecutively unless step is set higher than one which
- results in items being skipped. If stop is None, then iteration
- continues until the iterator is exhausted, if at all; otherwise,
- it stops at the specified position. Unlike regular slicing,
- islice() does not support negative values for start, stop, or
- step. Can be used to extract related fields from data where the
- internal structure has been flattened (for example, a multi-line
- report may list a name field on every third line).
- """
- def __init__(self, iterable, *args):
- s = slice(*args)
- self.start, self.stop, self.step = s.start or 0, s.stop, s.step
- if not isinstance(self.start, (int, long)):
- raise ValueError("Start argument must be an integer")
- if self.stop is not None and not isinstance(self.stop, (int,long)):
- raise ValueError("Stop argument must be an integer or None")
- if self.step is None:
- self.step = 1
- if self.start<0 or (self.stop is not None and self.stop<0
- ) or self.step<=0:
- raise ValueError, "indices for islice() must be positive"
- self.it = iter(iterable)
- self.donext = None
- self.cnt = 0
-
- def __iter__(self):
- return self
-
- def next(self):
- if self.donext is None:
- try:
- self.donext = self.it.next
- except AttributeError:
- raise TypeError
- nextindex = self.start
- if self.stop is not None and nextindex >= self.stop:
- raise StopIteration
- while self.cnt <= nextindex:
- nextitem = self.donext()
- self.cnt += 1
- self.start += self.step
- return nextitem
-
-class izip(object):
- """Make an iterator that aggregates elements from each of the
- iterables. Like zip() except that it returns an iterator instead
- of a list. Used for lock-step iteration over several iterables at
- a time.
-
- Equivalent to :
-
- def izip(*iterables):
- iterables = map(iter, iterables)
- while iterables:
- result = [i.next() for i in iterables]
- yield tuple(result)
- """
- def __init__(self, *iterables):
- self._iterators = map(iter, iterables)
- self._result = [None] * len(self._iterators)
-
- def __iter__(self):
- return self
-
- def next(self):
- if not self._iterators:
- raise StopIteration()
- try:
- return tuple([i.next() for i in self._iterators])
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % (i))
-
-
-class product(object):
-
- def __init__(self, *args, **kw):
- if len(kw) > 1:
- raise TypeError("product() takes at most 1 argument (%d given)" %
- len(kw))
- self.repeat = kw.get('repeat', 1)
- self.gears = [x for x in args] * self.repeat
- self.num_gears = len(self.gears)
- # initialization of indicies to loop over
- self.indicies = [(0, len(self.gears[x]))
- for x in range(0, self.num_gears)]
- self.cont = True
-
- def roll_gears(self):
- # Starting from the end of the gear indicies work to the front
- # incrementing the gear until the limit is reached. When the limit
- # is reached carry operation to the next gear
- should_carry = True
- for n in range(0, self.num_gears):
- nth_gear = self.num_gears - n - 1
- if should_carry:
- count, lim = self.indicies[nth_gear]
- count += 1
- if count == lim and nth_gear == 0:
- self.cont = False
- if count == lim:
- should_carry = True
- count = 0
- else:
- should_carry = False
- self.indicies[nth_gear] = (count, lim)
- else:
- break
-
- def __iter__(self):
- return self
-
- def next(self):
- if not self.cont:
- raise StopIteration
- l = []
- for x in range(0, self.num_gears):
- index, limit = self.indicies[x]
- l.append(self.gears[x][index])
- self.roll_gears()
- return tuple(l)
-
-
-class repeat(object):
- """Make an iterator that returns object over and over again.
- Runs indefinitely unless the times argument is specified. Used
- as argument to imap() for invariant parameters to the called
- function. Also used with izip() to create an invariant part of a
- tuple record.
-
- Equivalent to :
-
- def repeat(object, times=None):
- if times is None:
- while True:
- yield object
- else:
- for i in xrange(times):
- yield object
- """
- def __init__(self, obj, times=None):
- self._obj = obj
- if times is not None:
- xrange(times) # Raise a TypeError
- if times < 0:
- times = 0
- self._times = times
-
- def __iter__(self):
- return self
-
- def next(self):
- # next() *need* to decrement self._times when consumed
- if self._times is not None:
- if self._times <= 0:
- raise StopIteration()
- self._times -= 1
- return self._obj
-
- def __repr__(self):
- if self._times is not None:
- return 'repeat(%r, %r)' % (self._obj, self._times)
- else:
- return 'repeat(%r)' % (self._obj,)
-
- def __len__(self):
- if self._times == -1 or self._times is None:
- raise TypeError("len() of uniszed object")
- return self._times
-
-
-class starmap(object):
- """Make an iterator that computes the function using arguments
- tuples obtained from the iterable. Used instead of imap() when
- argument parameters are already grouped in tuples from a single
- iterable (the data has been ``pre-zipped''). The difference
- between imap() and starmap() parallels the distinction between
- function(a,b) and function(*c).
-
- Equivalent to :
-
- def starmap(function, iterable):
- iterable = iter(iterable)
- while True:
- yield function(*iterable.next())
- """
- def __init__(self, function, iterable):
- self._func = function
- self._iter = iter(iterable)
-
- def __iter__(self):
- return self
-
- def next(self):
- # CPython raises a TypeError when the iterator doesn't return a tuple
- try:
- t = self._iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % self._iter)
- if not isinstance(t, tuple):
- raise TypeError("iterator must return a tuple")
- return self._func(*t)
-
-
-
-class takewhile(object):
- """Make an iterator that returns elements from the iterable as
- long as the predicate is true.
-
- Equivalent to :
-
- def takewhile(predicate, iterable):
- for x in iterable:
- if predicate(x):
- yield x
- else:
- break
- """
- def __init__(self, predicate, iterable):
- self._predicate = predicate
- self._iter = iter(iterable)
-
- def __iter__(self):
- return self
-
- def next(self):
- try:
- value = self._iter.next()
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % \
- (self._iter))
- if not self._predicate(value):
- raise StopIteration()
- return value
-
-
-class TeeData(object):
- """Holds cached values for TeeObjects"""
- def __init__(self, iterator):
- self.data = []
- self._iter = iterator
-
- def __getitem__(self, i):
- # iterates until 'i' if not done yet
- while i>= len(self.data):
- try:
- self.data.append( self._iter.next() )
- except AttributeError:
- # CPython raises a TypeError when next() is not defined
- raise TypeError('%s has no next() method' % self._iter)
- return self.data[i]
-
-
-class TeeObject(object):
- """Iterables / Iterators as returned by the tee() function"""
- def __init__(self, iterable=None, tee_data=None):
- if tee_data:
- self.tee_data = tee_data
- self.pos = 0
- # <=> Copy constructor
- elif isinstance(iterable, TeeObject):
- self.tee_data = iterable.tee_data
- self.pos = iterable.pos
- else:
- self.tee_data = TeeData(iter(iterable))
- self.pos = 0
-
- def next(self):
- data = self.tee_data[self.pos]
- self.pos += 1
- return data
-
- def __iter__(self):
- return self
-
-
-@builtinify
-def tee(iterable, n=2):
- """Return n independent iterators from a single iterable.
- Note : once tee() has made a split, the original iterable
- should not be used anywhere else; otherwise, the iterable could get
- advanced without the tee objects being informed.
-
- Note : this member of the toolkit may require significant auxiliary
- storage (depending on how much temporary data needs to be stored).
- In general, if one iterator is going to use most or all of the
- data before the other iterator, it is faster to use list() instead
- of tee()
-
- Equivalent to :
-
- def tee(iterable, n=2):
- def gen(next, data={}, cnt=[0]):
- for i in count():
- if i == cnt[0]:
- item = data[i] = next()
- cnt[0] += 1
- else:
- item = data.pop(i)
- yield item
- it = iter(iterable)
- return tuple([gen(it.next) for i in range(n)])
- """
- if isinstance(iterable, TeeObject):
- # a,b = tee(range(10)) ; c,d = tee(a) ; self.assert_(a is c)
- return tuple([iterable] +
- [TeeObject(tee_data=iterable.tee_data) for i in xrange(n-1)])
- tee_data = TeeData(iter(iterable))
- return tuple([TeeObject(tee_data=tee_data) for i in xrange(n)])
diff --git a/lib_pypy/itertools.py b/lib_pypy/itertools.py
new file mode 100644
--- /dev/null
+++ b/lib_pypy/itertools.py
@@ -0,0 +1,670 @@
+# Note that PyPy contains also a built-in module 'itertools' which will
+# hide this one if compiled in.
+
+"""Functional tools for creating and using iterators.
+
+Infinite iterators:
+count([n]) --> n, n+1, n+2, ...
+cycle(p) --> p0, p1, ... plast, p0, p1, ...
+repeat(elem [,n]) --> elem, elem, elem, ... endlessly or up to n times
+
+Iterators terminating on the shortest input sequence:
+izip(p, q, ...) --> (p[0], q[0]), (p[1], q[1]), ...
+ifilter(pred, seq) --> elements of seq where pred(elem) is True
+ifilterfalse(pred, seq) --> elements of seq where pred(elem) is False
+islice(seq, [start,] stop [, step]) --> elements from
+ seq[start:stop:step]
+imap(fun, p, q, ...) --> fun(p0, q0), fun(p1, q1), ...
+starmap(fun, seq) --> fun(*seq[0]), fun(*seq[1]), ...
+tee(it, n=2) --> (it1, it2 , ... itn) splits one iterator into n
+chain(p, q, ...) --> p0, p1, ... plast, q0, q1, ...
+takewhile(pred, seq) --> seq[0], seq[1], until pred fails
+dropwhile(pred, seq) --> seq[n], seq[n+1], starting when pred fails
+groupby(iterable[, keyfunc]) --> sub-iterators grouped by value of keyfunc(v)
+"""
+
+__all__ = ['chain', 'count', 'cycle', 'dropwhile', 'groupby', 'ifilter',
+ 'ifilterfalse', 'imap', 'islice', 'izip', 'repeat', 'starmap',
+ 'takewhile', 'tee', 'compress', 'product']
+
+try: from __pypy__ import builtinify
+except ImportError: builtinify = lambda f: f
+
+
+class chain(object):
+ """Make an iterator that returns elements from the first iterable
+ until it is exhausted, then proceeds to the next iterable, until
+ all of the iterables are exhausted. Used for treating consecutive
+ sequences as a single sequence.
+
+ Equivalent to :
+
+ def chain(*iterables):
+ for it in iterables:
+ for element in it:
+ yield element
+ """
+ def __init__(self, *iterables):
+ self._iterables_iter = iter(map(iter, iterables))
+ # little trick for the first chain.next() call
+ self._cur_iterable_iter = iter([])
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ while True:
+ try:
+ return self._cur_iterable_iter.next()
+ except StopIteration:
+ self._cur_iterable_iter = self._iterables_iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._cur_iterable_iter))
+
+
+class compress(object):
+ def __init__(self, data, selectors):
+ self.data = iter(data)
+ self.selectors = iter(selectors)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ while True:
+ next_item = self.data.next()
+ next_selector = self.selectors.next()
+ if bool(next_selector):
+ return next_item
+
+
+class count(object):
+ """Make an iterator that returns consecutive integers starting
+ with n. If not specified n defaults to zero. Does not currently
+ support python long integers. Often used as an argument to imap()
+ to generate consecutive data points. Also, used with izip() to
+ add sequence numbers.
+
+ Equivalent to :
+
+ def count(n=0):
+ if not isinstance(n, int):
+ raise TypeError("%s is not a regular integer" % n)
+ while True:
+ yield n
+ n += 1
+ """
+ def __init__(self, n=0):
+ if not isinstance(n, int):
+ raise TypeError('%s is not a regular integer' % n)
+ self.times = n-1
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ self.times += 1
+ return self.times
+
+ def __repr__(self):
+ return 'count(%d)' % (self.times + 1)
+
+
+
+class cycle(object):
+ """Make an iterator returning elements from the iterable and
+ saving a copy of each. When the iterable is exhausted, return
+ elements from the saved copy. Repeats indefinitely.
+
+ Equivalent to :
+
+ def cycle(iterable):
+ saved = []
+ for element in iterable:
+ yield element
+ saved.append(element)
+ while saved:
+ for element in saved:
+ yield element
+ """
+ def __init__(self, iterable):
+ self._cur_iter = iter(iterable)
+ self._saved = []
+ self._must_save = True
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ # XXX Could probably be improved
+ try:
+ next_elt = self._cur_iter.next()
+ if self._must_save:
+ self._saved.append(next_elt)
+ except StopIteration:
+ self._cur_iter = iter(self._saved)
+ next_elt = self._cur_iter.next()
+ self._must_save = False
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._cur_iter))
+ return next_elt
+
+
+class dropwhile(object):
+ """Make an iterator that drops elements from the iterable as long
+ as the predicate is true; afterwards, returns every
+ element. Note, the iterator does not produce any output until the
+ predicate is true, so it may have a lengthy start-up time.
+
+ Equivalent to :
+
+ def dropwhile(predicate, iterable):
+ iterable = iter(iterable)
+ for x in iterable:
+ if not predicate(x):
+ yield x
+ break
+ for x in iterable:
+ yield x
+ """
+ def __init__(self, predicate, iterable):
+ self._predicate = predicate
+ self._iter = iter(iterable)
+ self._dropped = False
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ try:
+ value = self._iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._iter))
+ if self._dropped:
+ return value
+ while self._predicate(value):
+ value = self._iter.next()
+ self._dropped = True
+ return value
+
+class groupby(object):
+ """Make an iterator that returns consecutive keys and groups from the
+ iterable. The key is a function computing a key value for each
+ element. If not specified or is None, key defaults to an identity
+ function and returns the element unchanged. Generally, the
+ iterable needs to already be sorted on the same key function.
+
+ The returned group is itself an iterator that shares the
+ underlying iterable with groupby(). Because the source is shared,
+ when the groupby object is advanced, the previous group is no
+ longer visible. So, if that data is needed later, it should be
+ stored as a list:
+
+ groups = []
+ uniquekeys = []
+ for k, g in groupby(data, keyfunc):
+ groups.append(list(g)) # Store group iterator as a list
+ uniquekeys.append(k)
+ """
+ def __init__(self, iterable, key=None):
+ if key is None:
+ key = lambda x: x
+ self.keyfunc = key
+ self.it = iter(iterable)
+ self.tgtkey = self.currkey = self.currvalue = xrange(0)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ while self.currkey == self.tgtkey:
+ try:
+ self.currvalue = self.it.next() # Exit on StopIteration
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self.it))
+ self.currkey = self.keyfunc(self.currvalue)
+ self.tgtkey = self.currkey
+ return (self.currkey, self._grouper(self.tgtkey))
+
+ def _grouper(self, tgtkey):
+ while self.currkey == tgtkey:
+ yield self.currvalue
+ self.currvalue = self.it.next() # Exit on StopIteration
+ self.currkey = self.keyfunc(self.currvalue)
+
+
+
+class _ifilter_base(object):
+ """base class for ifilter and ifilterflase"""
+ def __init__(self, predicate, iterable):
+ # Make sure iterable *IS* iterable
+ self._iter = iter(iterable)
+ if predicate is None:
+ self._predicate = bool
+ else:
+ self._predicate = predicate
+
+ def __iter__(self):
+ return self
+
+class ifilter(_ifilter_base):
+ """Make an iterator that filters elements from iterable returning
+ only those for which the predicate is True. If predicate is
+ None, return the items that are true.
+
+ Equivalent to :
+
+ def ifilter:
+ if predicate is None:
+ predicate = bool
+ for x in iterable:
+ if predicate(x):
+ yield x
+ """
+ def next(self):
+ try:
+ next_elt = self._iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._iter))
+ while True:
+ if self._predicate(next_elt):
+ return next_elt
+ next_elt = self._iter.next()
+
+class ifilterfalse(_ifilter_base):
+ """Make an iterator that filters elements from iterable returning
+ only those for which the predicate is False. If predicate is
+ None, return the items that are false.
+
+ Equivalent to :
+
+ def ifilterfalse(predicate, iterable):
+ if predicate is None:
+ predicate = bool
+ for x in iterable:
+ if not predicate(x):
+ yield x
+ """
+ def next(self):
+ try:
+ next_elt = self._iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._iter))
+ while True:
+ if not self._predicate(next_elt):
+ return next_elt
+ next_elt = self._iter.next()
+
+
+
+
+class imap(object):
+ """Make an iterator that computes the function using arguments
+ from each of the iterables. If function is set to None, then
+ imap() returns the arguments as a tuple. Like map() but stops
+ when the shortest iterable is exhausted instead of filling in
+ None for shorter iterables. The reason for the difference is that
+ infinite iterator arguments are typically an error for map()
+ (because the output is fully evaluated) but represent a common
+ and useful way of supplying arguments to imap().
+
+ Equivalent to :
+
+ def imap(function, *iterables):
+ iterables = map(iter, iterables)
+ while True:
+ args = [i.next() for i in iterables]
+ if function is None:
+ yield tuple(args)
+ else:
+ yield function(*args)
+
+ """
+ def __init__(self, function, iterable, *other_iterables):
+ self._func = function
+ self._iters = map(iter, (iterable, ) + other_iterables)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ try:
+ args = [it.next() for it in self._iters]
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (it))
+ if self._func is None:
+ return tuple(args)
+ else:
+ return self._func(*args)
+
+
+
+class islice(object):
+ """Make an iterator that returns selected elements from the
+ iterable. If start is non-zero, then elements from the iterable
+ are skipped until start is reached. Afterward, elements are
+ returned consecutively unless step is set higher than one which
+ results in items being skipped. If stop is None, then iteration
+ continues until the iterator is exhausted, if at all; otherwise,
+ it stops at the specified position. Unlike regular slicing,
+ islice() does not support negative values for start, stop, or
+ step. Can be used to extract related fields from data where the
+ internal structure has been flattened (for example, a multi-line
+ report may list a name field on every third line).
+ """
+ def __init__(self, iterable, *args):
+ s = slice(*args)
+ self.start, self.stop, self.step = s.start or 0, s.stop, s.step
+ if not isinstance(self.start, (int, long)):
+ raise ValueError("Start argument must be an integer")
+ if self.stop is not None and not isinstance(self.stop, (int,long)):
+ raise ValueError("Stop argument must be an integer or None")
+ if self.step is None:
+ self.step = 1
+ if self.start<0 or (self.stop is not None and self.stop<0
+ ) or self.step<=0:
+ raise ValueError, "indices for islice() must be positive"
+ self.it = iter(iterable)
+ self.donext = None
+ self.cnt = 0
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ if self.donext is None:
+ try:
+ self.donext = self.it.next
+ except AttributeError:
+ raise TypeError
+ nextindex = self.start
+ if self.stop is not None and nextindex >= self.stop:
+ raise StopIteration
+ while self.cnt <= nextindex:
+ nextitem = self.donext()
+ self.cnt += 1
+ self.start += self.step
+ return nextitem
+
+class izip(object):
+ """Make an iterator that aggregates elements from each of the
+ iterables. Like zip() except that it returns an iterator instead
+ of a list. Used for lock-step iteration over several iterables at
+ a time.
+
+ Equivalent to :
+
+ def izip(*iterables):
+ iterables = map(iter, iterables)
+ while iterables:
+ result = [i.next() for i in iterables]
+ yield tuple(result)
+ """
+ def __init__(self, *iterables):
+ self._iterators = map(iter, iterables)
+ self._result = [None] * len(self._iterators)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ if not self._iterators:
+ raise StopIteration()
+ try:
+ return tuple([i.next() for i in self._iterators])
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % (i))
+
+
+class product(object):
+
+ def __init__(self, *args, **kw):
+ if len(kw) > 1:
+ raise TypeError("product() takes at most 1 argument (%d given)" %
+ len(kw))
+ self.repeat = kw.get('repeat', 1)
+ self.gears = [x for x in args] * self.repeat
+ self.num_gears = len(self.gears)
+ # initialization of indicies to loop over
+ self.indicies = [(0, len(self.gears[x]))
+ for x in range(0, self.num_gears)]
+ self.cont = True
+
+ def roll_gears(self):
+ # Starting from the end of the gear indicies work to the front
+ # incrementing the gear until the limit is reached. When the limit
+ # is reached carry operation to the next gear
+ should_carry = True
+ for n in range(0, self.num_gears):
+ nth_gear = self.num_gears - n - 1
+ if should_carry:
+ count, lim = self.indicies[nth_gear]
+ count += 1
+ if count == lim and nth_gear == 0:
+ self.cont = False
+ if count == lim:
+ should_carry = True
+ count = 0
+ else:
+ should_carry = False
+ self.indicies[nth_gear] = (count, lim)
+ else:
+ break
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ if not self.cont:
+ raise StopIteration
+ l = []
+ for x in range(0, self.num_gears):
+ index, limit = self.indicies[x]
+ l.append(self.gears[x][index])
+ self.roll_gears()
+ return tuple(l)
+
+
+class repeat(object):
+ """Make an iterator that returns object over and over again.
+ Runs indefinitely unless the times argument is specified. Used
+ as argument to imap() for invariant parameters to the called
+ function. Also used with izip() to create an invariant part of a
+ tuple record.
+
+ Equivalent to :
+
+ def repeat(object, times=None):
+ if times is None:
+ while True:
+ yield object
+ else:
+ for i in xrange(times):
+ yield object
+ """
+ def __init__(self, obj, times=None):
+ self._obj = obj
+ if times is not None:
+ xrange(times) # Raise a TypeError
+ if times < 0:
+ times = 0
+ self._times = times
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ # next() *need* to decrement self._times when consumed
+ if self._times is not None:
+ if self._times <= 0:
+ raise StopIteration()
+ self._times -= 1
+ return self._obj
+
+ def __repr__(self):
+ if self._times is not None:
+ return 'repeat(%r, %r)' % (self._obj, self._times)
+ else:
+ return 'repeat(%r)' % (self._obj,)
+
+ def __len__(self):
+ if self._times == -1 or self._times is None:
+ raise TypeError("len() of uniszed object")
+ return self._times
+
+
+class starmap(object):
+ """Make an iterator that computes the function using arguments
+ tuples obtained from the iterable. Used instead of imap() when
+ argument parameters are already grouped in tuples from a single
+ iterable (the data has been ``pre-zipped''). The difference
+ between imap() and starmap() parallels the distinction between
+ function(a,b) and function(*c).
+
+ Equivalent to :
+
+ def starmap(function, iterable):
+ iterable = iter(iterable)
+ while True:
+ yield function(*iterable.next())
+ """
+ def __init__(self, function, iterable):
+ self._func = function
+ self._iter = iter(iterable)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ # CPython raises a TypeError when the iterator doesn't return a tuple
+ try:
+ t = self._iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % self._iter)
+ if not isinstance(t, tuple):
+ raise TypeError("iterator must return a tuple")
+ return self._func(*t)
+
+
+
+class takewhile(object):
+ """Make an iterator that returns elements from the iterable as
+ long as the predicate is true.
+
+ Equivalent to :
+
+ def takewhile(predicate, iterable):
+ for x in iterable:
+ if predicate(x):
+ yield x
+ else:
+ break
+ """
+ def __init__(self, predicate, iterable):
+ self._predicate = predicate
+ self._iter = iter(iterable)
+
+ def __iter__(self):
+ return self
+
+ def next(self):
+ try:
+ value = self._iter.next()
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % \
+ (self._iter))
+ if not self._predicate(value):
+ raise StopIteration()
+ return value
+
+
+class TeeData(object):
+ """Holds cached values for TeeObjects"""
+ def __init__(self, iterator):
+ self.data = []
+ self._iter = iterator
+
+ def __getitem__(self, i):
+ # iterates until 'i' if not done yet
+ while i>= len(self.data):
+ try:
+ self.data.append( self._iter.next() )
+ except AttributeError:
+ # CPython raises a TypeError when next() is not defined
+ raise TypeError('%s has no next() method' % self._iter)
+ return self.data[i]
+
+
+class TeeObject(object):
+ """Iterables / Iterators as returned by the tee() function"""
+ def __init__(self, iterable=None, tee_data=None):
+ if tee_data:
+ self.tee_data = tee_data
+ self.pos = 0
+ # <=> Copy constructor
+ elif isinstance(iterable, TeeObject):
+ self.tee_data = iterable.tee_data
+ self.pos = iterable.pos
+ else:
+ self.tee_data = TeeData(iter(iterable))
+ self.pos = 0
+
+ def next(self):
+ data = self.tee_data[self.pos]
+ self.pos += 1
+ return data
+
+ def __iter__(self):
+ return self
+
+
+@builtinify
+def tee(iterable, n=2):
+ """Return n independent iterators from a single iterable.
+ Note : once tee() has made a split, the original iterable
+ should not be used anywhere else; otherwise, the iterable could get
+ advanced without the tee objects being informed.
+
+ Note : this member of the toolkit may require significant auxiliary
+ storage (depending on how much temporary data needs to be stored).
+ In general, if one iterator is going to use most or all of the
+ data before the other iterator, it is faster to use list() instead
+ of tee()
+
+ Equivalent to :
+
+ def tee(iterable, n=2):
+ def gen(next, data={}, cnt=[0]):
+ for i in count():
+ if i == cnt[0]:
+ item = data[i] = next()
+ cnt[0] += 1
+ else:
+ item = data.pop(i)
+ yield item
+ it = iter(iterable)
+ return tuple([gen(it.next) for i in range(n)])
+ """
+ if isinstance(iterable, TeeObject):
+ # a,b = tee(range(10)) ; c,d = tee(a) ; self.assert_(a is c)
+ return tuple([iterable] +
+ [TeeObject(tee_data=iterable.tee_data) for i in xrange(n-1)])
+ tee_data = TeeData(iter(iterable))
+ return tuple([TeeObject(tee_data=tee_data) for i in xrange(n)])
diff --git a/pypy/module/itertools/__init__.py
b/pypy/module/itertools/__init__.py
--- a/pypy/module/itertools/__init__.py
+++ b/pypy/module/itertools/__init__.py
@@ -23,7 +23,6 @@
dropwhile(pred, seq) --> seq[n], seq[n+1], starting when pred fails
groupby(iterable[, keyfunc]) --> sub-iterators grouped by value of
keyfunc(v)
"""
- applevel_name = '__builtin_itertools'
interpleveldefs = {
'chain' : 'interp_itertools.W_Chain',
_______________________________________________
pypy-commit mailing list
pypy-commit@python.org
http://mail.python.org/mailman/listinfo/pypy-commit
