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All Samples(248669)  |  Call(242594)  |  Derive(6068)  |  Import(7)
list() -> new empty list
list(iterable) -> new list initialized from iterable's items

src/p/y/pysam-0.7.7/tests/example.py   pysam(Download)
print "###################"
# check different ways to iterate
print len(list(samfile.fetch()))
print len(list(samfile.fetch( "chr1", 10, 200 )))
print len(list(samfile.fetch( region="chr1:10-200" )))
print len(list(samfile.fetch( "chr1" )))
print len(list(samfile.fetch( region="chr1")))

src/h/u/hunch-sample-app-HEAD/django/contrib/messages/tests/base.py   hunch-sample-app(Download)
 
        storage.add(constants.INFO, 'Test message 3')
        list(storage)   # Simulates a read
        storage.update(response)
 
    def test_existing_read_add_update(self):
        storage = self.get_existing_storage()
        response = self.get_response()
 
        list(storage)   # Simulates a read
        user = User.objects.create_user('test', 'test@example.com', 'test')
        self.client.login(username='test', password='test')
        settings.INSTALLED_APPS = list(settings.INSTALLED_APPS)
        settings.INSTALLED_APPS.remove(
            'django.contrib.messages',
        )
        settings.MIDDLEWARE_CLASSES = list(settings.MIDDLEWARE_CLASSES)

src/m/o/modern-python-example-HEAD/lib/python2.7/site-packages/logilab/astng/test/unittest_inference.py   modern-python-example(Download)
        a1 = astng.locals['A'][0]
        a2 = astng.locals['A'][1]
        a2_ancestors = list(a2.ancestors())
        self.failUnlessEqual(len(a2_ancestors), 1)
        self.failUnless(a2_ancestors[0] is a1)
        a1 = astng.locals['A'][0]
        a2 = astng.locals['A'][1]
        a2_ancestors = list(a2.ancestors())
        self.failUnlessEqual(len(a2_ancestors), 2)
        self.failUnless(a2_ancestors[0] is astng.locals['B'][0])
        astng = builder.string_build(code, __name__, __file__)
        node = get_name_node(astng, 'help', -1)
        infered = list(node.infer())
        self.failUnlessEqual(len(infered), 1, infered)
        self.assertIsInstance(infered[0], Instance)
        astng = builder.string_build(code, __name__, __file__)
        node = get_name_node(astng, 'open', -1)
        infered = list(node.infer())
        self.failUnlessEqual(len(infered), 1)
        self.assertIsInstance(infered[0], nodes.Function)
        '''
        astng = builder.string_build(code, __name__, __file__)
        infered = list(astng.igetattr('un'))
        self.failUnlessEqual(len(infered), 1)
        self.assertIsInstance(infered[0], nodes.Const)

src/d/j/django-admin-report-HEAD/example/lib/reportlab/platypus/tables.py   django-admin-report(Download)
                    setattr(self,a,getattr(parent,a))
        if cmds:
            commands = commands + list(cmds)
        self._cmds = commands
        self._opts={}
        and assign some best-guess values."""
 
        W = list(self._argW) # _calc_pc(self._argW,availWidth)
        verbose = 0
        totalDefined = 0.0
        percentDefined = 0
        percentTotal = 0
        numberUndefined = 0
        numberGreedyUndefined = 0
        for w in W:
        elementWidth = self._elementWidth
        for colNo in xrange(self._ncols):
            w = W[colNo]
            if w is None or w=='*' or _endswith(w,'%'):
                siz = 1
            effectiveRemaining = remaining
            for colNo, minimum in minimums.items():
                w = W[colNo]
                if _endswith(w,'%'):
                    desired = (float(w[:-1])/percentTotal)*availWidth

src/p/y/pyaaf-HEAD/example/qt_aafmodel.py   pyaaf(Download)
        elif isinstance(item, aaf.storage.ContentStorage):
            l = []
            l.append(DummyItem(list(item.composition_mobs()),"CompositionMobs"))
            l.append(DummyItem(list(item.master_mobs()),"MasterMobs"))
            #l.append(DummyItem(list(item.GetSourceMobs()),"SourceMobs"))
        elif isinstance(item, aaf.dictionary.Dictionary):
            l = []
            l.append(DummyItem(list(item.class_defs()), 'ClassDefs'))
            l.append(DummyItem(list(item.codec_defs()), 'CodecDefs'))
            l.append(DummyItem(list(item.container_defs()), 'ContainerDefs'))

src/n/e/networkx-HEAD/examples/subclass/printgraph.py   networkx(Download)
    print(G.edges(data=True))
    G.remove_edge(0,1)
    G.add_edges_from(list(zip(list(range(0o3)),list(range(1,4)))),weight=10)
    print(G.edges(data=True))
    G.remove_edges_from(list(zip(list(range(0o3)),list(range(1,4)))))

src/a/d/adder-HEAD/samples/web/w.py   adder(Download)
            _adder__0023_003cgensym_002dscratch_0020_002350_003e=_adder_head_002d1596213198(_adder_cs_002d1588635523)
            _adder__0023_003cgensym_002dscratch_0020_002351_003e=_adder_head_002d1596213198(_adder__0023_003cgensym_002dscratch_0020_002350_003e)
            _adder__0023_003cgensym_002dscratch_0020_002352_003e=adder.common.Symbol('begin')
            _adder__0023_003cgensym_002dscratch_0020_002353_003e=[_adder__0023_003cgensym_002dscratch_0020_002352_003e]
            _adder__0023_003cgensym_002dscratch_0020_002354_003e=_adder_head_002d1596213198(_adder_cs_002d1588635523)
    _adder__0023_003cgensym_002dscratch_0020_002364_003e=adder.common.Symbol('lambda')
    _adder__0023_003cgensym_002dscratch_0020_002365_003e=adder.common.Symbol('obj')
    _adder__0023_003cgensym_002dscratch_0020_002366_003e=[_adder__0023_003cgensym_002dscratch_0020_002365_003e]
    _adder__0023_003cgensym_002dscratch_0020_002367_003e=adder.common.Symbol('.')
    _adder__0023_003cgensym_002dscratch_0020_002368_003e=adder.common.Symbol('obj')
        else:
            _adder__0023_003cgensym_002dscratch_0020_0023100_003e=adder.common.Symbol('defvar')
            _adder__0023_003cgensym_002dscratch_0020_0023101_003e=[_adder__0023_003cgensym_002dscratch_0020_0023100_003e, _adder_def_002d1581057848]
            _adder__0023_003cgensym_002dif_0020_002399_003e=_adder__0023_003cgensym_002dscratch_0020_0023101_003e
        return _adder__0023_003cgensym_002dif_0020_002399_003e
            _adder__0023_003cgensym_002dscratch_0020_0023111_003e=_adder_head_002d1596213198(_adder_def_002d1574562698)
            _adder__0023_003cgensym_002dif_0020_0023112_003e=_adder__0023_003cgensym_002dscratch_0020_0023111_003e
        else:
            _adder__0023_003cgensym_002dif_0020_0023112_003e=_adder_def_002d1574562698
        return _adder__0023_003cgensym_002dif_0020_0023112_003e

src/h/o/hortonworks-sandbox-HEAD/desktop/core/ext-py/processing/examples/ex_pool.py   hortonworks-sandbox(Download)
 
    t = time.time()
    C = list(pool.imap(pow3, xrange(N), chunksize=N//8))
    print '\tlist(pool.imap(pow3, xrange(%d), chunksize=%d)):\n\t\t%s' \
          ' seconds' % (N, N//8, time.time() - t)
 
    assert A == B == C, (len(A), len(B), len(C))
 
    t = time.time()
    C = list(pool.imap(noop, L, chunksize=len(L)//8))
    print '\tlist(pool.imap(noop, L, chunksize=%d)):\n\t\t%s seconds' % \
          (len(L)//8, time.time() - t)
 
    assert A == B == C, (len(A), len(B), len(C))

src/q/s/QSTK-0.2.7/Examples/FeatureSearch/functions.py   QSTK(Download)
def sequentialForwardSelection(naFeatTrain,naFeatTest,lFeatures,classLabelIndex):
	lSelectedFeatures = list()
	lRemainingFeatures = lFeatures[:]
	lCorrCoef = list();
	while len(lRemainingFeatures) > 0:
def sequentialBackwardSelection(naFeatTrain,naFeatTest,lFeatures,classLabelIndex):
	lSelectedFeatures = lFeatures[:]
	lCorrCoef = list()
	lRemovedFeatures = list()
	while len(lSelectedFeatures) > 0:
	maxlCorrCoef = max(lCorrCoef)
	maxlCorrCoefIndex = lCorrCoef.index(maxlCorrCoef)
	lBestSet = list(set(lFeatures) - set(lRemovedFeatures[0:maxlCorrCoefIndex+1]))
	sys.stdout.write('best feature set is ' + str(lBestSet+[classLabelIndex]) + '\n')
	sys.stdout.write('corr coef = ' + str(maxlCorrCoef))

src/c/o/coopr.pyomo-3.5/coopr/pyomo/tests/examples/pmedian2.py   coopr.pyomo(Download)
def pyomo_preprocess(**kwds):
    print( "PREPROCESSING %s"%(sorted(list(kwds.keys()))) )
 
def pyomo_create_model(**kwds):
    print( "CREATING MODEL %s"%(sorted(list(kwds.keys()))) )
    return pmedian.model
 
def pyomo_print_model(**kwds):
    print( "PRINTING MODEL %s"%(sorted(list(kwds.keys()))) )
def pyomo_print_instance(**kwds):
    print( "PRINTING INSTANCE %s"%(sorted(list(kwds.keys()))) )
 
def pyomo_save_instance(**kwds):
    print( "SAVE INSTANCE %s"%(sorted(list(kwds.keys()))) )

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