在编程中,变量可以分为全局变量和局部变量。
全局变量指的是可以在本程序的任何地方进行调用,而不局限于只能在某个函数体内部进行调用。
对应的,局部变量只可以在当前函数体或者当前模块中进行调用,无法在其他函数体或者模块中进行调用。

在函数func中定义一个局部变量 a ,如果在函数func外调用就会报错

def func():
    a = 5
    print ('这是在函数func内调用的,a是一个局部变量,a=%s'%a)
func()
print(a)

这是在函数func内调用的,a是一个局部变量,a=5


NameErrorTraceback (most recent call last)
<ipython-input-2-14122dcadd6a> in <module>()
      3     print ('这是在函数func内调用的,a是一个局部变量,a=%s'%a)
      4 func()
----> 5 print(a)

NameError: name 'a' is not defined

现在我们定义一个全局变量 b ,无论在函数体内还是在函数体外调用都没有问题

b = 5
l = []
def func2():
    print ('这是在函数func2内调用的,b是一个全局变量,如果没有在函数体内重新赋值,则调用的是全局变量b b=%s'%b)
    l.append(1)
    print ('对于全局变量的修改,也可以在函数体内进行 l = %s'%l)
func2()
print(l)

这是在函数func2内调用的,b是一个全局变量,如果没有在函数体内重新赋值,则调用的是全局变量b b=5
对于全局变量的修改,也可以在函数体内进行 l = [1]
[1]

c = 1
def func3():
#     global c   # 如果声明是全局变量,那么重新赋值直接作用于全局变量
    c = 2
    print ('这是在函数func3内调用的,c 是一个全局变量,在函数体内被重新赋值,赋值后调用的是函数体内的局部变量  c=%s'%c)
func3()
print('在函数体外调用的是全局变量 c = %s'%c)

这是在函数func3内调用的,c 是一个全局变量,在函数体内被重新赋值,赋值后调用的是函数体内的局部变量  c=2
在函数体外调用的是全局变量 c = 1

# 直接调用会报错
def a():
    X = 5
a()
def b():
    print(X)
b()


NameErrorTraceback (most recent call last)
<ipython-input-5-dee1ce8dd41b> in <module>()
      5 def b():
      6     print(X)
----> 7 b()

<ipython-input-5-dee1ce8dd41b> in b()
      4 a()
      5 def b():
----> 6     print(X)
      7 b()

NameError: global name 'X' is not defined

# 可以使用 globals 在函数体中声名这是一个全局变量
def a():
    global X
    X = 5
a()
def b():
    print(X)
b()

5

# 查看当前级别下的局部变量
def test():
    a = 1
    b = 2
    print locals()
test()

{'a': 1, 'b': 2}

# 查看全局变量
def test():
    a = 1
    b = 2
    print globals()
test()

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          u'ytick.minor.size': 2.0,
          u'ytick.minor.visible': False,
          u'ytick.minor.width': 0.6,
          u'ytick.right': False}), 'IndexDateFormatter': <class 'matplotlib.dates.IndexDateFormatter'>, 'MO': MO, 'asscalar': <function asscalar at 0x7f90f67a2758>, 'LogLocator': <class 'matplotlib.ticker.LogLocator'>, 'binomial': <built-in method binomial of mtrand.RandomState object at 0x7f90f5c4d390>, 'broken_barh': <function broken_barh at 0x7f90e490e488>, 'poisson': <built-in method poisson of mtrand.RandomState object at 0x7f90f5c4d390>, 'HourLocator': <class 'matplotlib.dates.HourLocator'>, 'less_equal': <ufunc 'less_equal'>, 'l1norm': <function l1norm at 0x7f90ec5658c0>, 'BUFSIZE': 8192, 'sci': <function sci at 0x7f90e4906cf8>, 'ginput': <function ginput at 0x7f90e490a578>, 'FR': FR, 'shuffle': <built-in method shuffle of mtrand.RandomState object at 0x7f90f5c4d390>, 'RAISE': 2, 'csingle': <type 'numpy.complex64'>, 'dtype': <type 'numpy.dtype'>, 'unsignedinteger': <type 'numpy.unsignedinteger'>, 'fftshift': <function fftshift at 0x7f90f6518230>, 'fastCopyAndTranspose': <built-in function _fastCopyAndTranspose>, 'num2date': <function num2date at 0x7f9142a91668>, 'silent_list': <class 'matplotlib.cbook.silent_list'>, 'bitwise_and': <ufunc 'bitwise_and'>, 'uintc': <type 'numpy.uint32'>, 'TH': TH, 'Line2D': <class 'matplotlib.lines.Line2D'>, 'select': <function select at 0x7f90f6743398>, 'ticklabel_format': <function ticklabel_format at 0x7f90e490fd70>, 'deg2rad': <ufunc 'deg2rad'>, 'plot': <function plot at 0x7f90e490f0c8>, 'nditer': <type 'numpy.nditer'>, 'eye': <function eye at 0x7f90f67346e0>, 'figure': <function figure at 0x7f90e4906e60>, 'kron': <function kron at 0x7f90f6758c80>, 'newbuffer': <built-in function newbuffer>, 'quiverkey': <function quiverkey at 0x7f90e490f2a8>, 'axhspan': <function axhspan at 0x7f90e490e230>, 'busday_offset': <built-in function busday_offset>, 'xticks': <function xticks at 0x7f90e490c500>, 'standard_gamma': <built-in method standard_gamma of mtrand.RandomState object at 0x7f90f5c4d390>, 'lstsq': <function lstsq at 0x7f90f676ed70>, 'print_function': _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 65536), 'MAXDIMS': 32, 'clabel': <function clabel at 0x7f90e490e5f0>, 'setxor1d': <function setxor1d at 0x7f90f64f2320>, 'rk4': <function rk4 at 0x7f90ec565320>, 'fftfreq': <function fftfreq at 0x7f90f65182a8>, 'ifft2': <function ifft2 at 0x7f90f6518a28>, 'longdouble': <type 'numpy.float128'>, 'vlines': <function vlines at 0x7f90e490f938>, 'zeros_like': <function zeros_like at 0x7f9145607f50>, 'blackman': <function blackman at 0x7f90f6743a28>, 'int_asbuffer': <built-in function int_asbuffer>, 'uint8': <type 'numpy.uint8'>, 'flag': <function flag at 0x7f90e49101b8>, 'nanmean': <function nanmean at 0x7f90f6751ed8>, 'linspace': <function linspace at 0x7f90f69ee230>, 'hold': <function hold at 0x7f90e490a8c0>, 'mirr': <function mirr at 0x7f90f650e320>, 'uint64': <type 'numpy.uint64'>, 'autumn': <function autumn at 0x7f90e490cf50>, 'ma': <module 'numpy.ma' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/ma/__init__.pyc'>, 'func2': <function func2 at 0x7f9142a9d758>, 'f': <built-in method f of mtrand.RandomState object at 0x7f90f5c4d390>, 'hist2d': <function hist2d at 0x7f90e490eb18>, 'Text': <class 'matplotlib.text.Text'>, 'isneginf': <function isneginf at 0x7f90f67a2398>, 'true_divide': <ufunc 'true_divide'>, 'det': <function det at 0x7f90f676e050>, 'SU': SU, 'DateLocator': <class 'matplotlib.dates.DateLocator'>, '_i8': u'# \u67e5\u770b\u5168\u5c40\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print globals()\ntest()  ', 'SA': SA, 'finfo': <class 'numpy.core.getlimits.finfo'>, 'scatter': <function scatter at 0x7f90e490f320>, 'Out': {}, 'Normalize': <class 'matplotlib.colors.Normalize'>, 'spy': <function spy at 0x7f90e490ced8>, 'MinuteLocator': <class 'matplotlib.dates.MinuteLocator'>, 'quiver': <function quiver at 0x7f90e490f230>, 'triu_indices': <function triu_indices at 0x7f90f6734c08>, 'subplot2grid': <function subplot2grid at 0x7f90e490ad70>, 'int_': <type 'numpy.int64'>, 'get_sparse_matrix': <function get_sparse_matrix at 0x7f90ec565488>, 'setp': <function setp at 0x7f90e4906de8>, 'add_newdoc': <function add_newdoc at 0x7f90f67472a8>, 'seterrcall': <function seterrcall at 0x7f9145629398>, 'sample': <built-in method random_sample of mtrand.RandomState object at 0x7f90f5c4d390>, 'logical_or': <ufunc 'logical_or'>, 'minimum': <ufunc 'minimum'>, 'WRAP': 1, 'tan': <ufunc 'tan'>, 'rms_flat': <function rms_flat at 0x7f90ec565848>, 'eigvalsh': <function eigvalsh at 0x7f90f676e578>, 'pink': <function pink at 0x7f90e4910410>, 'winter': <function winter at 0x7f90e49105f0>, 'gcf': <function gcf at 0x7f90e4906f50>, 'gci': <function gci at 0x7f90e4906b18>, 'csd': <function csd at 0x7f90e490e758>, 'RRuleLocator': <class 'matplotlib.dates.RRuleLocator'>, 'six': <module 'six' from '/opt/conda/envs/python2/lib/python2.7/site-packages/six.pyc'>, 'polymul': <function polymul at 0x7f90f64f02a8>, 'hot': <function hot at 0x7f90e49102a8>, 'minorticks_off': <function minorticks_off at 0x7f90e490c668>, 'get_ipython': <bound method ZMQInteractiveShell.get_ipython of <ipykernel.zmqshell.ZMQInteractiveShell object at 0x7f90ee917750>>, 'FuncFormatter': <class 'matplotlib.ticker.FuncFormatter'>, 'get_figlabels': <function get_figlabels at 0x7f90e490a140>, 'tile': <function tile at 0x7f90f6758cf8>, 'array_str': <function array_str at 0x7f9145627aa0>, 'axis': <function axis at 0x7f90e490c1b8>, 'iterable': <function iterable at 0x7f90f673b050>, 'pinv': <function pinv at 0x7f90f676e140>, 'LogFormatter': <class 'matplotlib.ticker.LogFormatter'>, 'gca': <function gca at 0x7f90e490ac08>, 'product': <function product at 0x7f91456262a8>, 'int16': <type 'numpy.int16'>, 's_': <numpy.lib.index_tricks.IndexExpression object at 0x7f90f674e4d0>, 'mat': <function asmatrix at 0x7f90f67478c0>, 'fv': <function fv at 0x7f90f650eb90>, 'arccos': <ufunc 'arccos'>, 'docstring': <module 'matplotlib.docstring' from '/opt/conda/envs/python2/lib/python2.7/site-packages/matplotlib/docstring.pyc'>, 'ifftn': <function ifftn at 0x7f90f6518938>, 'asanyarray': <function asanyarray at 0x7f9145607b90>, 'uint': <type 'numpy.uint64'>, 'negative_binomial': <built-in method negative_binomial of mtrand.RandomState object at 0x7f90f5c4d390>, 'npv': <function npv at 0x7f90f650e410>, 'colormaps': <function colormaps at 0x7f90e490c938>, 'types': <module 'types' from '/opt/conda/envs/python2/lib/python2.7/types.pyc'>, 'flatnonzero': <function flatnonzero at 0x7f91456078c0>, 'a': <function a at 0x7f90e456f0c8>, 'amin': <function amin at 0x7f91456266e0>, 'correlate': <function correlate at 0x7f91456077d0>, 'getfigs': <function getfigs at 0x7f9148fcdc08>, 'fromstring': <built-in function fromstring>, 'pylab_setup': <function pylab_setup at 0x7f90e48f75f0>, 'left_shift': <ufunc 'left_shift'>, 'TickHelper': <class 'matplotlib.ticker.TickHelper'>, 'subplots': <function subplots at 0x7f90e490acf8>, 'searchsorted': <function searchsorted at 0x7f914560ecf8>, 'barbs': <function barbs at 0x7f90e490fa28>, 'int64': <type 'numpy.int64'>, 'gamma': <built-in method gamma of mtrand.RandomState object at 0x7f90f5c4d390>, 'array_repr': <function array_repr at 0x7f9145627488>, '__': '', 'GridSpec': <class 'matplotlib.gridspec.GridSpec'>, 'get_array_wrap': <function get_array_wrap at 0x7f90f6758c08>, 'xlim': <function xlim at 0x7f90e490c320>, 'rand': <built-in method rand of mtrand.RandomState object at 0x7f90f5c4d390>, 'MONTHLY': 1, 'over': <function over at 0x7f90e490aaa0>, 'intersect1d': <function intersect1d at 0x7f90f64f22a8>, 'cosh': <ufunc 'cosh'>, 'window_none': <function window_none at 0x7f90ec561140>, 'can_cast': <built-in function can_cast>, 'ppmt': <function ppmt at 0x7f90f650e7d0>, 'cumsum': <function cumsum at 0x7f9145626500>, 'ravel': <function ravel at 0x7f914560ef50>, 'roots': <function roots at 0x7f90f676eed8>, 'Widget': <class 'matplotlib.widgets.Widget'>, 'outer': <function outer at 0x7f91456076e0>, 'intc': <type 'numpy.int32'>, 'num2epoch': <function num2epoch at 0x7f913b7cd398>, 'fix': <function fix at 0x7f90f67a21b8>, 'stineman_interp': <function stineman_interp at 0x7f90ec56b230>, 'busday_count': <built-in function busday_count>, 'cla': <function cla at 0x7f90e490faa0>, 'timedelta64': <type 'numpy.timedelta64'>, 'strpdate2num': <class 'matplotlib.dates.strpdate2num'>, 'standard_exponential': <built-in method standard_exponential of mtrand.RandomState object at 0x7f90f5c4d390>, 'subplot_tool': <function subplot_tool at 0x7f90e490af50>, 'choose': <function choose at 0x7f914560e410>, '_i': u'# \u67e5\u770b\u5f53\u524d\u7ea7\u522b\u4e0b\u7684\u5c40\u90e8\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print locals()\ntest()  ', 'FPE_INVALID': 8, 'recfromcsv': <function recfromcsv at 0x7f90f650e1b8>, 'fill_diagonal': <function fill_diagonal at 0x7f90f6751140>, 'cool': <function cool at 0x7f90e49100c8>, 'get_fignums': <function get_fignums at 0x7f90e490a0c8>, 'exception_to_str': <function exception_to_str at 0x7f9142eb31b8>, 'SECONDLY': 6, 'logaddexp2': <ufunc 'logaddexp2'>, 'greater': <ufunc 'greater'>, 'suptitle': <function suptitle at 0x7f90e490a6e0>, 'get_backend': <function get_backend at 0x7f9142ae5e60>, 'drange': <function drange at 0x7f9142a916e0>, 'number': <type 'numpy.number'>, 'polyint': <function polyint at 0x7f90f676ef50>, 'qr': <function qr at 0x7f90f676e668>, 'arctan2': <ufunc 'arctan2'>, 'Arrow': <class 'matplotlib.patches.Arrow'>, 'datetime64': <type 'numpy.datetime64'>, 'complexfloating': <type 'numpy.complexfloating'>, 'is_numlike': <function is_numlike at 0x7f9142eadf50>, 'ndindex': <class 'numpy.lib.index_tricks.ndindex'>, 'ctypeslib': <module 'numpy.ctypeslib' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/ctypeslib.pyc'>, 'waitforbuttonpress': <function waitforbuttonpress at 0x7f90e490a5f0>, 'PZERO': 0.0, 'array_equiv': <function array_equiv at 0x7f9145629140>, 'MonthLocator': <class 'matplotlib.dates.MonthLocator'>, 'asfarray': <function asfarray at 0x7f90f67a2140>, 'nanmedian': <function nanmedian at 0x7f90f6758140>, 'radians': <ufunc 'radians'>, 'sin': <ufunc 'sin'>, 'fliplr': <function fliplr at 0x7f90f6734578>, 'alen': <function alen at 0x7f9145626758>, 'recarray': <class 'numpy.core.records.recarray'>, 'modf': <ufunc 'modf'>, 'unpackbits': <built-in function unpackbits>, 'bone': <function bone at 0x7f90e4910050>, 'mean': <function mean at 0x7f9145626b18>, 'longlong': <type 'numpy.int64'>, 'poly_below': <function poly_below at 0x7f90ec56b500>, 'square': <ufunc 'square'>, 'isvector': <function isvector at 0x7f90ec565cf8>, 'ogrid': <numpy.lib.index_tricks.nd_grid object at 0x7f90f674e250>, 'median': <function median at 0x7f90f6747050>, 'nanargmin': <function nanargmin at 0x7f90f6751d70>, 'r_': <numpy.lib.index_tricks.RClass object at 0x7f90f674e2d0>, 'hanning': <function hanning at 0x7f90f6743b18>, 'connect': <function connect at 0x7f90e490a2a8>, 'str_': <type 'numpy.string_'>, 'margins': <function margins at 0x7f90e490fed8>, 'allclose': <function allclose at 0x7f9145627f50>, 'extract': <function extract at 0x7f90f6743500>, 'float16': <type 'numpy.float16'>, 'uninstall_repl_displayhook': <function uninstall_repl_displayhook at 0x7f90e49066e0>, 'ulonglong': <type 'numpy.uint64'>, 'matrix': <class 'numpy.matrixlib.defmatrix.matrix'>, 'asarray': <function asarray at 0x7f9145607c08>, 'True_': True, 'IndexLocator': <class 'matplotlib.ticker.IndexLocator'>, 'streamplot': <function streamplot at 0x7f90e490f668>, 'void': <type 'numpy.void'>, 'rc': <function rc at 0x7f90e4906b90>, 'rec': <module 'numpy.core.records' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/core/records.pyc'>, 'arange': <built-in function arange>, 'datetime_as_string': <built-in function datetime_as_string>, 'plotting': <function plotting at 0x7f90e490c7d0>, 'math': <module 'math' from '/opt/conda/envs/python2/lib/python2.7/lib-dynload/math.so'>, 'get_cmap': <function get_cmap at 0x7f90ec5380c8>, 'log2': <ufunc 'log2'>, 'date2num': <function date2num at 0x7f9142a91500>, '__builtins__': {'bytearray': <type 'bytearray'>, 'IndexError': <type 'exceptions.IndexError'>, 'all': <built-in function all>, 'help': Type help() for interactive help, or help(object) for help about object., 'vars': <built-in function vars>, 'SyntaxError': <type 'exceptions.SyntaxError'>, 'get_locked_shares': <function get_locked_shares at 0x7f90ee905f50>, 'get_all_securities': <function get_all_securities at 0x7f90ee905b18>, 'unicode': <type 'unicode'>, 'UnicodeDecodeError': <type 'exceptions.UnicodeDecodeError'>, 'memoryview': <type 'memoryview'>, 'query': <function query at 0x7f91321a5140>, 'isinstance': <built-in function isinstance>, 'get_industry': <function get_industry at 0x7f90ee905a28>, 'indicator': <class 'jqdata.fundamentals_tables_gen.FinancialIndicator'>, 'copyright': Copyright (c) 2001-2015 Python Software Foundation.
All Rights Reserved.

Copyright (c) 2000 BeOpen.com.
All Rights Reserved.

Copyright (c) 1995-2001 Corporation for National Research Initiatives.
All Rights Reserved.

Copyright (c) 1991-1995 Stichting Mathematisch Centrum, Amsterdam.
All Rights Reserved., 'NameError': <type 'exceptions.NameError'>, 'BytesWarning': <type 'exceptions.BytesWarning'>, 'dict': <type 'dict'>, 'get_bars': <function get_bars at 0x7f90ee905668>, 'input': <function <lambda> at 0x7f90e4910a28>, 'oct': <built-in function oct>, 'bin': <built-in function bin>, 'SystemExit': <type 'exceptions.SystemExit'>, 'StandardError': <type 'exceptions.StandardError'>, 'format': <built-in function format>, 'income': <class 'jqdata.fundamentals_tables_gen.IncomeStatement'>, 'repr': <built-in function repr>, 'normalize_code': <function normalize_code at 0x7f90ee905d70>, 'get_fundamentals': <function get_fundamentals at 0x7f90ee9057d0>, 'sorted': <built-in function sorted>, 'False': False, 'RuntimeWarning': <type 'exceptions.RuntimeWarning'>, 'list': <type 'list'>, 'iter': <built-in function iter>, 'reload': <built-in function reload>, 'get_index_weights': <function get_index_weights at 0x7f90ee905938>, 'Warning': <type 'exceptions.Warning'>, '__package__': None, 'get_index_stocks': <function get_index_stocks at 0x7f90ee9058c0>, 'round': <built-in function round>, 'dir': <built-in function dir>, 'cmp': <built-in function cmp>, 'set': <type 'set'>, 'bytes': <type 'str'>, 'reduce': <built-in function reduce>, 'security_indicator': <class 'jqdata.fundamentals_tables_gen.SecurityIndicatorAcc'>, 'intern': <built-in function intern>, 'issubclass': <built-in function issubclass>, 'cash_flow': <class 'jqdata.fundamentals_tables_gen.CashFlowStatement'>, 'get_backtest': <function get_backtest at 0x7f90ee9041b8>, 'Ellipsis': Ellipsis, 'write_file': <function write_file at 0x7f90ee9042a8>, 'EOFError': <type 'exceptions.EOFError'>, 'balance': <class 'jqdata.fundamentals_tables_gen.BalanceSheet'>, 'locals': <built-in function locals>, 'BufferError': <type 'exceptions.BufferError'>, 'slice': <type 'slice'>, 'FloatingPointError': <type 'exceptions.FloatingPointError'>, 'sum': <built-in function sum>, 'get_extras': <function get_extras at 0x7f90ee905758>, 'getattr': <built-in function getattr>, 'abs': <built-in function abs>, 'print': <built-in function print>, 'True': True, 'insurance_indicator': <class 'jqdata.fundamentals_tables_gen.InsuranceIndicatorAcc'>, 'FutureWarning': <type 'exceptions.FutureWarning'>, 'calc_factors': <function calc_factors at 0x7f90ee904050>, 'ImportWarning': <type 'exceptions.ImportWarning'>, 'None': None, 'hash': <built-in function hash>, 'ReferenceError': <type 'exceptions.ReferenceError'>, 'len': <built-in function len>, 'credits':     Thanks to CWI, CNRI, BeOpen.com, Zope Corporation and a cast of thousands
    for supporting Python development.  See www.python.org for more information., 'frozenset': <type 'frozenset'>, '__name__': '__builtin__', 'ord': <built-in function ord>, 'super': <type 'super'>, 'log': <logging.Logger object at 0x7f90ee903710>, 'TypeError': <type 'exceptions.TypeError'>, 'bank_indicator': <class 'jqdata.fundamentals_tables_gen.BankIndicatorAcc'>, 'license': Type license() to see the full license text, 'KeyboardInterrupt': <type 'exceptions.KeyboardInterrupt'>, 'get_fundamentals_continuously': <function get_fundamentals_continuously at 0x7f90ee905848>, 'UserWarning': <type 'exceptions.UserWarning'>, 'filter': <built-in function filter>, 'range': <built-in function range>, 'staticmethod': <type 'staticmethod'>, 'SystemError': <type 'exceptions.SystemError'>, 'BaseException': <type 'exceptions.BaseException'>, 'get_concept_stocks': <function get_concept_stocks at 0x7f90ee905aa0>, 'pow': <built-in function pow>, 'RuntimeError': <type 'exceptions.RuntimeError'>, 'float': <type 'float'>, 'MemoryError': <type 'exceptions.MemoryError'>, 'StopIteration': <type 'exceptions.StopIteration'>, 'globals': <built-in function globals>, 'divmod': <built-in function divmod>, 'enumerate': <type 'enumerate'>, 'apply': <built-in function apply>, 'LookupError': <type 'exceptions.LookupError'>, 'open': <built-in function open>, 'get_billboard_list': <function get_billboard_list at 0x7f90ee905ed8>, 'basestring': <type 'basestring'>, 'UnicodeError': <type 'exceptions.UnicodeError'>, 'zip': <built-in function zip>, 'hex': <built-in function hex>, 'get_marginsec_stocks': <function get_marginsec_stocks at 0x7f90ee905cf8>, 'long': <type 'long'>, 'next': <built-in function next>, 'ImportError': <type 'exceptions.ImportError'>, 'chr': <built-in function chr>, 'xrange': <type 'xrange'>, 'type': <type 'type'>, '__doc__': "Built-in functions, exceptions, and other objects.\n\nNoteworthy: None is the `nil' object; Ellipsis represents `...' in slices.", 'Exception': <type 'exceptions.Exception'>, '__IPYTHON__': True, 'tuple': <type 'tuple'>, 'fundamentals': <module 'jqdata.apis.db' from '/opt/conda/envs/python2/lib/python2.7/site-packages/jqdata/apis/db.pyc'>, 'UnicodeTranslateError': <type 'exceptions.UnicodeTranslateError'>, 'reversed': <type 'reversed'>, 'UnicodeEncodeError': <type 'exceptions.UnicodeEncodeError'>, 'IOError': <type 'exceptions.IOError'>, 'valuation': <class 'jqdata.fundamentals_tables_gen.StockValuation'>, 'create_backtest': <function create_backtest at 0x7f90ee9040c8>, 'hasattr': <built-in function hasattr>, 'delattr': <built-in function delattr>, 'get_dominant_future': <function get_dominant_future at 0x7f90ee905de8>, 'setattr': <built-in function setattr>, 'raw_input': <bound method IPythonKernel.raw_input of <ipykernel.ipkernel.IPythonKernel object at 0x7f90ee92e410>>, 'SyntaxWarning': <type 'exceptions.SyntaxWarning'>, 'compile': <built-in function compile>, 'ArithmeticError': <type 'exceptions.ArithmeticError'>, 'str': <type 'str'>, 'read_file': <function read_file at 0x7f90ee904230>, 'property': <type 'property'>, 'dreload': <function _dreload at 0x7f90ec6c4d70>, 'display': <function display at 0x7f914a8cc848>, 'history': <function history at 0x7f90ee905578>, 'GeneratorExit': <type 'exceptions.GeneratorExit'>, 'int': <type 'int'>, '__import__': <built-in function __import__>, 'get_industry_stocks': <function get_industry_stocks at 0x7f90ee9059b0>, 'KeyError': <type 'exceptions.KeyError'>, 'coerce': <built-in function coerce>, 'PendingDeprecationWarning': <type 'exceptions.PendingDeprecationWarning'>, 'get_price': <function get_price at 0x7f90ee905500>, 'file': <type 'file'>, 'EnvironmentError': <type 'exceptions.EnvironmentError'>, 'unichr': <built-in function unichr>, 'get_security_info': <function get_security_info at 0x7f90ee905b90>, 'id': <built-in function id>, 'OSError': <type 'exceptions.OSError'>, 'DeprecationWarning': <type 'exceptions.DeprecationWarning'>, 'get_future_contracts': <function get_future_contracts at 0x7f90ee905e60>, 'min': <built-in function min>, 'UnicodeWarning': <type 'exceptions.UnicodeWarning'>, 'get_ticks': <function get_ticks at 0x7f90ee9056e0>, 'execfile': <built-in function execfile>, 'any': <built-in function any>, 'complex': <type 'complex'>, 'bool': <type 'bool'>, 'get_ipython': <bound method ZMQInteractiveShell.get_ipython of <ipykernel.zmqshell.ZMQInteractiveShell object at 0x7f90ee917750>>, 'get_margincash_stocks': <function get_margincash_stocks at 0x7f90ee905c80>, 'attribute_history': <function attribute_history at 0x7f90ee9055f0>, 'ValueError': <type 'exceptions.ValueError'>, 'NotImplemented': NotImplemented, 'map': <built-in function map>, 'buffer': <type 'buffer'>, 'max': <built-in function max>, 'object': <type 'object'>, 'TabError': <type 'exceptions.TabError'>, 'callable': <built-in function callable>, 'ZeroDivisionError': <type 'exceptions.ZeroDivisionError'>, 'eval': <built-in function eval>, '__debug__': True, 'IndentationError': <type 'exceptions.IndentationError'>, 'AssertionError': <type 'exceptions.AssertionError'>, 'classmethod': <type 'classmethod'>, 'get_fund_info': <function get_fund_info at 0x7f90ee905c08>, 'UnboundLocalError': <type 'exceptions.UnboundLocalError'>, 'NotImplementedError': <type 'exceptions.NotImplementedError'>, 'AttributeError': <type 'exceptions.AttributeError'>, 'OverflowError': <type 'exceptions.OverflowError'>}, 'rec_join': <function rec_join at 0x7f90ec566140>, 'acorr': <function acorr at 0x7f90e490e050>, 'cumproduct': <function cumproduct at 0x7f9145626578>, 'diagonal': <function diagonal at 0x7f914560ee60>, 'atleast_1d': <function atleast_1d at 0x7f90f69eec08>, 'meshgrid': <function meshgrid at 0x7f90f6747320>, 'eventplot': <function eventplot at 0x7f90e490e848>, 'column_stack': <function column_stack at 0x7f90f67587d0>, 'put': <function put at 0x7f914560e230>, '___': '', 'remainder': <ufunc 'remainder'>, 'isreal': <function isreal at 0x7f90f67a2488>, 'get_scale_docs': <function get_scale_docs at 0x7f90e4989140>, 'row_stack': <function vstack at 0x7f90f69eed70>, 'expm1': <ufunc 'expm1'>, 'deprecated': <function deprecated at 0x7f9142ea98c0>, 'insert': <function insert at 0x7f90f6747410>, 'semilogx': <function semilogx at 0x7f90e490f398>, 'semilogy': <function semilogy at 0x7f90e490f410>, 'ndfromtxt': <function ndfromtxt at 0x7f90f650e050>, 'place': <function place at 0x7f90f6743668>, 'DataSource': <class 'numpy.lib._datasource.DataSource'>, 'newaxis': None, 'yticks': <function yticks at 0x7f90e490c578>, 'epoch2num': <function epoch2num at 0x7f913b7cd320>, 'signedinteger': <type 'numpy.signedinteger'>, 'ndim': <function ndim at 0x7f91456268c0>, 'copper': <function copper at 0x7f90e4910140>, 'irfft': <function irfft at 0x7f90f6518578>, 'ranf': <built-in method random_sample of mtrand.RandomState object at 0x7f90f5c4d390>, 'subplots_adjust': <function subplots_adjust at 0x7f90e490aed8>, 'rint': <ufunc 'rint'>, 'fill_between': <function fill_between at 0x7f90e490e938>, 'Axes': <class 'matplotlib.axes._axes.Axes'>, 'MaxNLocator': <class 'matplotlib.ticker.MaxNLocator'>, 'rank': <function rank at 0x7f9145626938>, 'little_endian': True, 'ldexp': <ufunc 'ldexp'>, 'lognormal': <built-in method lognormal of mtrand.RandomState object at 0x7f90f5c4d390>, 'lookfor': <function lookfor at 0x7f90f673b8c0>, 'hfft': <function hfft at 0x7f90f65185f0>, 'array': <built-in function array>, 'vsplit': <function vsplit at 0x7f90f6758aa0>, 'common_type': <function common_type at 0x7f90f67a2848>, 'size': <function size at 0x7f91456269b0>, 'logical_xor': <ufunc 'logical_xor'>, 'geterrcall': <function geterrcall at 0x7f9145629410>, 'figimage': <function figimage at 0x7f90e490a758>, 'jet': <function jet at 0x7f90e4910398>, 'figaspect': <function figaspect at 0x7f90e48f10c8>, 'sometrue': <function sometrue at 0x7f9145626320>, 'exp2': <ufunc 'exp2'>, 'imshow': <function imshow at 0x7f90e490ec80>, 'axhline': <function axhline at 0x7f90e490e1b8>, 'bool8': <type 'numpy.bool_'>, 'logaddexp': <ufunc 'logaddexp'>, 'msort': <function msort at 0x7f90f6743ed8>, 'alltrue': <function alltrue at 0x7f9145626398>, 'zeros': <built-in function zeros>, 'inferno': <function inferno at 0x7f90e49106e0>, 'pcolor': <function pcolor at 0x7f90e490ee60>, 'mintypecode': <function mintypecode at 0x7f90f67a2410>, 'triplot': <function triplot at 0x7f90e490f848>, 'subplot': <function subplot at 0x7f90e490ac80>, 'nansum': <function nansum at 0x7f90f6751e60>, 'bool_': <type 'numpy.bool_'>, 'inexact': <type 'numpy.inexact'>, 'nanpercentile': <function nanpercentile at 0x7f90f67581b8>, 'broadcast': <type 'numpy.broadcast'>, 'copyto': <built-in function copyto>, 'short': <type 'numpy.int16'>, 'arctanh': <ufunc 'arctanh'>, 'rfft': <function rfft at 0x7f9146120398>, 'typecodes': {'All': '?bhilqpBHILQPefdgFDGSUVOMm', 'Complex': 'FDG', 'AllFloat': 'efdgFDG', 'Integer': 'bhilqp', 'UnsignedInteger': 'BHILQP', 'Float': 'efdg', 'Character': 'c', 'Datetime': 'Mm', 'AllInteger': 'bBhHiIlLqQpP'}, 'locator_params': <function locator_params at 0x7f90e490fde8>, 'savetxt': <function savetxt at 0x7f90f6509e60>, 'copy': <function copy at 0x7f90f67435f0>, 'False_': False, 'std': <function std at 0x7f9145626b90>, 'segments_intersect': <function segments_intersect at 0x7f90ec5655f0>, 'not_equal': <ufunc 'not_equal'>, 'fromfunction': <function fromfunction at 0x7f9145627c08>, 'greater_equal': <ufunc 'greater_equal'>, 'tril_indices_from': <function tril_indices_from at 0x7f90f6734b90>, 'double': <type 'numpy.float64'>, 'require': <function require at 0x7f9145607a28>, 'rate': <function rate at 0x7f90f650e5f0>, 'LogFormatterExponent': <class 'matplotlib.ticker.LogFormatterExponent'>, '_iii': u'# \u76f4\u63a5\u8c03\u7528\u4f1a\u62a5\u9519\ndef a():\n    X = 5\na()\ndef b():\n    print(X)\nb()', 'xlabel': <function xlabel at 0x7f90e490c230>, 'nested_iters': <built-in function nested_iters>, 'getbuffer': <built-in function getbuffer>, 'xcorr': <function xcorr at 0x7f90e490f9b0>, 'slogdet': <function slogdet at 0x7f90f676e0c8>, 'clip': <function clip at 0x7f91456261b8>, 'tripcolor': <function tripcolor at 0x7f90e490f7d0>, 'half': <type 'numpy.float16'>, 'savez_compressed': <function savez_compressed at 0x7f90f6509c08>, 'tricontour': <function tricontour at 0x7f90e490f6e0>, 'isinteractive': <function isinteractive at 0x7f90e4906938>, 'eigvals': <function eigvals at 0x7f90f676e5f0>, 'seed': <built-in method seed of mtrand.RandomState object at 0x7f90f5c4d390>, 'triu_indices_from': <function triu_indices_from at 0x7f90f6734c80>, 'conjugate': <ufunc 'conjugate'>, 'clim': <function clim at 0x7f90e490caa0>, 'ylim': <function ylim at 0x7f90e490c398>, 'draw_all': <bound method type.draw_all of <class 'matplotlib._pylab_helpers.Gcf'>>, 'asfortranarray': <function asfortranarray at 0x7f9145607aa0>, 'binary_repr': <function binary_repr at 0x7f9145627cf8>, 'angle': <function angle at 0x7f90f6743320>, 'randint': <built-in method randint of mtrand.RandomState object at 0x7f90f5c4d390>, '_i7': u'# \u67e5\u770b\u5f53\u524d\u7ea7\u522b\u4e0b\u7684\u5c40\u90e8\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print locals()\ntest()  ', '_i6': u'# \u53ef\u4ee5\u4f7f\u7528 globals \u5728\u51fd\u6570\u4f53\u4e2d\u58f0\u540d\u8fd9\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf\ndef a():\n    global X\n    X = 5\na()\ndef b():\n    print(X)\nb()', '_i5': u'# \u76f4\u63a5\u8c03\u7528\u4f1a\u62a5\u9519\ndef a():\n    X = 5\na()\ndef b():\n    print(X)\nb()', 'linalg': <module 'numpy.linalg' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/linalg/__init__.pyc'>, 'apply_over_axes': <function apply_over_axes at 0x7f90f67586e0>, '_i2': u"def func():\n    a = 5\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func\u5185\u8c03\u7528\u7684,a\u662f\u4e00\u4e2a\u5c40\u90e8\u53d8\u91cf,a=%s'%a)\nfunc()\nprint(a)", '_i1': u'\u5728\u7f16\u7a0b\u4e2d,\u53d8\u91cf\u53ef\u4ee5\u5206\u4e3a\u5168\u5c40\u53d8\u91cf\u548c\u5c40\u90e8\u53d8\u91cf\u3002  \n\u5168\u5c40\u53d8\u91cf\u6307\u7684\u662f\u53ef\u4ee5\u5728\u672c\u7a0b\u5e8f\u7684\u4efb\u4f55\u5730\u65b9\u8fdb\u884c\u8c03\u7528,\u800c\u4e0d\u5c40\u9650\u4e8e\u53ea\u80fd\u5728\u67d0\u4e2a\u51fd\u6570\u4f53\u5185\u90e8\u8fdb\u884c\u8c03\u7528\u3002  \n\u5bf9\u5e94\u7684,\u5c40\u90e8\u53d8\u91cf\u53ea\u53ef\u4ee5\u5728\u5f53\u524d\u51fd\u6570\u4f53\u6216\u8005\u5f53\u524d\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528,\u65e0\u6cd5\u5728\u5176\u4ed6\u51fd\u6570\u4f53\u6216\u8005\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528\u3002', 'figlegend': <function figlegend at 0x7f90e490a488>, 'ERR_LOG': 5, 'right_shift': <ufunc 'right_shift'>, 'take': <function take at 0x7f914560e578>, 'set_state': <built-in method set_state of mtrand.RandomState object at 0x7f90f5c4d390>, 'demean': <function demean at 0x7f90ec5612a8>, 'FixedFormatter': <class 'matplotlib.ticker.FixedFormatter'>, 'boxplot': <function boxplot at 0x7f90e490e500>, 'SecondLocator': <class 'matplotlib.dates.SecondLocator'>, 'logseries': <built-in method logseries of mtrand.RandomState object at 0x7f90f5c4d390>, 'byte_bounds': <function byte_bounds at 0x7f90f673bc08>, 'trace': <function trace at 0x7f914560eed8>, 'warnings': <module 'warnings' from '/opt/conda/envs/python2/lib/python2.7/warnings.pyc'>, 'any': <function any at 0x7f9145626410>, 'Button': <class 'matplotlib.widgets.Button'>, 'may_share_memory': <built-in function may_share_memory>, 'compress': <function compress at 0x7f9145626140>, 'isnan': <ufunc 'isnan'>, 'histogramdd': <function histogramdd at 0x7f90f6734f50>, 'beta': <built-in method beta of mtrand.RandomState object at 0x7f90f5c4d390>, 'flatiter': <type 'numpy.flatiter'>, 'amap': <function amap at 0x7f90ec5657d0>, 'multiply': <ufunc 'multiply'>, 'np': <module 'numpy' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/__init__.pyc'>, 'mask_indices': <function mask_indices at 0x7f90f6734aa0>, 'detrend_none': <function detrend_none at 0x7f90ec561398>, 'amax': <function amax at 0x7f9145626668>, 'logical_not': <ufunc 'logical_not'>, 'average': <function average at 0x7f90f6734de8>, 'partition': <function partition at 0x7f914560e140>, 'nbytes': {<type 'numpy.void'>: 0, <type 'numpy.int64'>: 8, <type 'numpy.uint64'>: 8, <type 'numpy.datetime64'>: 8, <type 'numpy.object_'>: 8, <type 'numpy.int8'>: 1, <type 'numpy.uint8'>: 1, <type 'numpy.float16'>: 2, <type 'numpy.timedelta64'>: 8, <type 'numpy.bool_'>: 1, <type 'numpy.int16'>: 2, <type 'numpy.uint16'>: 2, <type 'numpy.float32'>: 4, <type 'numpy.complex64'>: 8, <type 'numpy.string_'>: 0, <type 'numpy.int32'>: 4, <type 'numpy.uint32'>: 4, <type 'numpy.float64'>: 8, <type 'numpy.complex128'>: 16, <type 'numpy.unicode_'>: 0, <type 'numpy.int64'>: 8, <type 'numpy.uint64'>: 8, <type 'numpy.float128'>: 16, <type 'numpy.complex256'>: 32}, 'exp': <ufunc 'exp'>, '_ih': ['', u'\u5728\u7f16\u7a0b\u4e2d,\u53d8\u91cf\u53ef\u4ee5\u5206\u4e3a\u5168\u5c40\u53d8\u91cf\u548c\u5c40\u90e8\u53d8\u91cf\u3002  \n\u5168\u5c40\u53d8\u91cf\u6307\u7684\u662f\u53ef\u4ee5\u5728\u672c\u7a0b\u5e8f\u7684\u4efb\u4f55\u5730\u65b9\u8fdb\u884c\u8c03\u7528,\u800c\u4e0d\u5c40\u9650\u4e8e\u53ea\u80fd\u5728\u67d0\u4e2a\u51fd\u6570\u4f53\u5185\u90e8\u8fdb\u884c\u8c03\u7528\u3002  \n\u5bf9\u5e94\u7684,\u5c40\u90e8\u53d8\u91cf\u53ea\u53ef\u4ee5\u5728\u5f53\u524d\u51fd\u6570\u4f53\u6216\u8005\u5f53\u524d\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528,\u65e0\u6cd5\u5728\u5176\u4ed6\u51fd\u6570\u4f53\u6216\u8005\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528\u3002', u"def func():\n    a = 5\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func\u5185\u8c03\u7528\u7684,a\u662f\u4e00\u4e2a\u5c40\u90e8\u53d8\u91cf,a=%s'%a)\nfunc()\nprint(a)", u"b = 5\nl = []\ndef func2():\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func2\u5185\u8c03\u7528\u7684,b\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5982\u679c\u6ca1\u6709\u5728\u51fd\u6570\u4f53\u5185\u91cd\u65b0\u8d4b\u503c,\u5219\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cfb b=%s'%b)\n    l.append(1)\n    print ('\u5bf9\u4e8e\u5168\u5c40\u53d8\u91cf\u7684\u4fee\u6539,\u4e5f\u53ef\u4ee5\u5728\u51fd\u6570\u4f53\u5185\u8fdb\u884c l = %s'%l)\nfunc2()\nprint(l)", u"c = 1\ndef func3():\n#     global c   # \u5982\u679c\u58f0\u660e\u662f\u5168\u5c40\u53d8\u91cf,\u90a3\u4e48\u91cd\u65b0\u8d4b\u503c\u76f4\u63a5\u4f5c\u7528\u4e8e\u5168\u5c40\u53d8\u91cf\n    c = 2\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func3\u5185\u8c03\u7528\u7684,c \u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5728\u51fd\u6570\u4f53\u5185\u88ab\u91cd\u65b0\u8d4b\u503c,\u8d4b\u503c\u540e\u8c03\u7528\u7684\u662f\u51fd\u6570\u4f53\u5185\u7684\u5c40\u90e8\u53d8\u91cf  c=%s'%c)\nfunc3()\nprint('\u5728\u51fd\u6570\u4f53\u5916\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cf c = %s'%c)", u'# \u76f4\u63a5\u8c03\u7528\u4f1a\u62a5\u9519\ndef a():\n    X = 5\na()\ndef b():\n    print(X)\nb()', u'# \u53ef\u4ee5\u4f7f\u7528 globals \u5728\u51fd\u6570\u4f53\u4e2d\u58f0\u540d\u8fd9\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf\ndef a():\n    global X\n    X = 5\na()\ndef b():\n    print(X)\nb()', u'# \u67e5\u770b\u5f53\u524d\u7ea7\u522b\u4e0b\u7684\u5c40\u90e8\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print locals()\ntest()  ', u'# \u67e5\u770b\u5168\u5c40\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print globals()\ntest()  '], 'axvspan': <function axvspan at 0x7f90e490e320>, 'rollaxis': <function rollaxis at 0x7f9145607488>, 'dot': <built-in function dot>, 'int0': <type 'numpy.int64'>, 'pylab': <module 'matplotlib.pylab' from '/opt/conda/envs/python2/lib/python2.7/site-packages/matplotlib/pylab.pyc'>, 'WE': WE, 'longfloat': <type 'numpy.float128'>, 'draw_if_interactive': <function wrapper at 0x7f90e4910b18>, 'show': <function show at 0x7f90e49068c0>, 'alterdot': <built-in function alterdot>, 'text': <function text at 0x7f90e490fc80>, 'random': <module 'numpy.random' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/random/__init__.pyc'>, 'random_integers': <built-in method random_integers of mtrand.RandomState object at 0x7f90f5c4d390>, 'datetime': <module 'datetime' from '/opt/conda/envs/python2/lib/python2.7/lib-dynload/datetime.so'>, 'get_plot_commands': <function get_plot_commands at 0x7f90e490c848>, 'stackplot': <function stackplot at 0x7f90e490f500>, 'rot90': <function rot90 at 0x7f90f6734668>, 'find': <function find at 0x7f90ec561de8>, 'FigureCanvasBase': <class 'matplotlib.backend_bases.FigureCanvasBase'>, 'randn': <built-in method randn of mtrand.RandomState object at 0x7f90f5c4d390>, 'savefig': <function savefig at 0x7f90e490a500>, 'title': <function title at 0x7f90e490c140>, 'FPE_UNDERFLOW': 4, 'frexp': <ufunc 'frexp'>, 'errstate': <class 'numpy.core.numeric.errstate'>, 'PolarAxes': <class 'matplotlib.projections.polar.PolarAxes'>, 'nanmin': <function nanmin at 0x7f90f6751c80>, 'DAILY': 3, 'center_matrix': <function center_matrix at 0x7f90ec5652a8>, 'SHIFT_OVERFLOW': 3, 'dsplit': <function dsplit at 0x7f90f6758b18>, 'infty': inf, 'plotfile': <function plotfile at 0x7f90e490cd70>, 'ModuleDeprecationWarning': <class 'numpy.ModuleDeprecationWarning'>, 'get': <function getp at 0x7f90ec66a140>, 'ispower2': <function ispower2 at 0x7f90ec565c80>, 'NZERO': -0.0, 'ceil': <ufunc 'ceil'>, 'ones': <function ones at 0x7f9145607ed8>, 'add_newdoc_ufunc': <built-in function add_newdoc_ufunc>, 'X': 5, 'geometric': <built-in method geometric of mtrand.RandomState object at 0x7f90f5c4d390>, 'ihfft': <function ihfft at 0x7f90f65187d0>, 'gray': <function gray at 0x7f90e4910230>, 'using_mklfft': False, 'bar': <function bar at 0x7f90e490e398>, 'ediff1d': <function ediff1d at 0x7f90f64f21b8>, 'ioff': <function ioff at 0x7f90e49069b0>, 'geterr': <function geterr at 0x7f9145629230>, 'convolve': <function convolve at 0x7f9145607758>, 'nan_to_num': <function nan_to_num at 0x7f90f67a2668>, 'logistic': <built-in method logistic of mtrand.RandomState object at 0x7f90f5c4d390>, 'weibull': <built-in method weibull of mtrand.RandomState object at 0x7f90f5c4d390>, 'cycler': <function cycler at 0x7f9142b52ed8>, 'where': <built-in function where>, 'rcParamsDefault': RcParams({u'_internal.classic_mode': False,
          u'agg.path.chunksize': 0,
          u'animation.avconv_args': [],
          u'animation.avconv_path': u'avconv',
          u'animation.bitrate': -1,
          u'animation.codec': u'h264',
          u'animation.convert_args': [],
          u'animation.convert_path': u'convert',
          u'animation.ffmpeg_args': [],
          u'animation.ffmpeg_path': u'ffmpeg',
          u'animation.frame_format': u'png',
          u'animation.html': u'none',
          u'animation.mencoder_args': [],
          u'animation.mencoder_path': u'mencoder',
          u'animation.writer': u'ffmpeg',
          u'axes.autolimit_mode': u'data',
          u'axes.axisbelow': u'line',
          u'axes.edgecolor': u'k',
          u'axes.facecolor': u'w',
          u'axes.formatter.limits': [-7, 7],
          u'axes.formatter.offset_threshold': 4,
          u'axes.formatter.use_locale': False,
          u'axes.formatter.use_mathtext': False,
          u'axes.formatter.useoffset': True,
          u'axes.grid': False,
          u'axes.grid.axis': u'both',
          u'axes.grid.which': u'major',
          u'axes.hold': None,
          u'axes.labelcolor': u'k',
          u'axes.labelpad': 4.0,
          u'axes.labelsize': u'medium',
          u'axes.labelweight': u'normal',
          u'axes.linewidth': 0.8,
          u'axes.prop_cycle': cycler(u'color', [u'#1f77b4', u'#ff7f0e', u'#2ca02c', u'#d62728', u'#9467bd', u'#8c564b', u'#e377c2', u'#7f7f7f', u'#bcbd22', u'#17becf']),
          u'axes.spines.bottom': True,
          u'axes.spines.left': True,
          u'axes.spines.right': True,
          u'axes.spines.top': True,
          u'axes.titlepad': 6.0,
          u'axes.titlesize': u'large',
          u'axes.titleweight': u'normal',
          u'axes.unicode_minus': True,
          u'axes.xmargin': 0.05,
          u'axes.ymargin': 0.05,
          u'axes3d.grid': True,
          u'backend': u'agg',
          u'backend.qt4': u'PyQt4',
          u'backend.qt5': u'PyQt5',
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          u'boxplot.bootstrap': None,
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'numpy.uint8'>: 'UInt8', 'I': 'UInt32', '?': 'Bool', 'Void0': <type 'numpy.void'>, <type 'numpy.uint16'>: 'UInt16', 'G': 'Complex128', 'O': 'Object0', 'UInt8': <type 'numpy.uint8'>, 'S': 'String0', <type 'numpy.uint32'>: 'UInt32', 'UInt64': <type 'numpy.uint64'>, 'g': 'Float128', <type 'numpy.uint64'>: 'UInt64', 'Float16': <type 'numpy.float16'>, <type 'numpy.uint64'>: 'UInt64', 'Bool': <type 'numpy.bool_'>, 'u8': <type 'numpy.uint64'>, 'u4': <type 'numpy.uint32'>, <type 'numpy.float16'>: 'Float16', 'Unicode0': <type 'numpy.unicode_'>, 'u1': <type 'numpy.uint8'>, 'u2': <type 'numpy.uint16'>, 'Datetime64': <type 'numpy.datetime64'>, 'Int8': <type 'numpy.int8'>, 'B': 'UInt8', <type 'numpy.float32'>: 'Float32', 'F': 'Complex32', 'c8': 'Complex32', 'Int64': <type 'numpy.int64'>, <type 'numpy.int64'>: 'Int64', 'Complex32': <type 'numpy.complex64'>, 'V': 'Void0', <type 'numpy.float64'>: 'Float64', 'b': 'Int8', 'f': 'Float32', 'm8': 'Timedelta64', <type 'numpy.float128'>: 'Float128', 'f16': 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0x7f90e490cc80>, 'vdot': <built-in function vdot>, 'bincount': <built-in function bincount>, 'copysign': <ufunc 'copysign'>, 'sctypes': {'int': [<type 'numpy.int8'>, <type 'numpy.int16'>, <type 'numpy.int32'>, <type 'numpy.int64'>], 'float': [<type 'numpy.float16'>, <type 'numpy.float32'>, <type 'numpy.float64'>, <type 'numpy.float128'>], 'uint': [<type 'numpy.uint8'>, <type 'numpy.uint16'>, <type 'numpy.uint32'>, <type 'numpy.uint64'>], 'complex': [<type 'numpy.complex64'>, <type 'numpy.complex128'>, <type 'numpy.complex256'>], 'others': [<type 'bool'>, <type 'object'>, <type 'str'>, <type 'unicode'>, <type 'numpy.void'>]}, 'transpose': <function transpose at 0x7f914560e1b8>, 'style': <module 'matplotlib.style' from '/opt/conda/envs/python2/lib/python2.7/site-packages/matplotlib/style/__init__.pyc'>, 'detrend_linear': <function detrend_linear at 0x7f90ec561410>, 'corrcoef': <function corrcoef at 0x7f90f67439b0>, 'fromregex': <function fromregex at 0x7f90f6509ed8>, 'fmod': <ufunc 'fmod'>, 'vector_lengths': <function vector_lengths at 0x7f90ec56b7d0>, 'vectorize': <class 'numpy.lib.function_base.vectorize'>, 'AutoLocator': <class 'matplotlib.ticker.AutoLocator'>, 'isrealobj': <function isrealobj at 0x7f90f67a2578>, 'trim_zeros': <function trim_zeros at 0x7f90f6743140>, 'WEEKLY': 2, 'cos': <ufunc 'cos'>, 'detrend': <function detrend at 0x7f90ec561230>, 'log1p': <ufunc 'log1p'>, 'DateFormatter': <class 'matplotlib.dates.DateFormatter'>, 'equal': <ufunc 'equal'>, 'display': <function display at 0x7f914a8cc848>, 'Locator': <class 'matplotlib.ticker.Locator'>, 'LinAlgError': <class 'numpy.linalg.linalg.LinAlgError'>, 'float_': <type 'numpy.float64'>, 'deprecate': <function deprecate at 0x7f90f673be60>, 'vander': <function vander at 0x7f90f67349b0>, 'geterrobj': <built-in function geterrobj>, 'interactive': <function interactive at 0x7f9142ae5ed8>, 'clf': <function clf at 0x7f90e490a398>, 'wald': <built-in method wald of mtrand.RandomState object at 0x7f90f5c4d390>, 'fromiter': <built-in function fromiter>, 'prctile_rank': <function prctile_rank at 0x7f90ec565230>, 'cm': <module 'matplotlib.cm' from '/opt/conda/envs/python2/lib/python2.7/site-packages/matplotlib/cm.pyc'>, 'tril': <function tril at 0x7f90f67348c0>, 'solve': <function solve at 0x7f90f676e8c0>, 'poly': <function poly at 0x7f90f675c6e0>, 'loglog': <function loglog at 0x7f90e490ecf8>, 'bitwise_or': <ufunc 'bitwise_or'>, 'figtext': <function figtext at 0x7f90e490a668>, 'norm_flat': <function norm_flat at 0x7f90ec5659b0>, '_i3': u"b = 5\nl = []\ndef func2():\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func2\u5185\u8c03\u7528\u7684,b\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5982\u679c\u6ca1\u6709\u5728\u51fd\u6570\u4f53\u5185\u91cd\u65b0\u8d4b\u503c,\u5219\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cfb b=%s'%b)\n    l.append(1)\n    print ('\u5bf9\u4e8e\u5168\u5c40\u53d8\u91cf\u7684\u4fee\u6539,\u4e5f\u53ef\u4ee5\u5728\u51fd\u6570\u4f53\u5185\u8fdb\u884c l = %s'%l)\nfunc2()\nprint(l)", 'tricontourf': <function tricontourf at 0x7f90e490f758>, 'table': <function table at 0x7f90e490fc08>, 'cohere': <function cohere at 0x7f90e490e578>, 'normpdf': <function normpdf at 0x7f90ec561d70>, 'set_printoptions': <function set_printoptions at 0x7f9145626cf8>, 'xkcd': <function xkcd at 0x7f90e4906d70>, 'quit': <IPython.core.autocall.ZMQExitAutocall object at 0x7f90ec6c2a10>, 'get_include': <function get_include at 0x7f90f673bf50>, 'pv': <function pv at 0x7f90f650e6e0>, 'tensordot': <function tensordot at 0x7f91456075f0>, 'piecewise': <function piecewise at 0x7f90f6734cf8>, 'rfftn': <function rfftn at 0x7f90f6518aa0>, 'invert': <ufunc 'invert'>, 'UFUNC_PYVALS_NAME': 'UFUNC_PYVALS', 'fftpack_lite': <module 'numpy.fft.fftpack_lite' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/fft/fftpack_lite.so'>, 'sinc': <function sinc at 0x7f90f6743e60>, 'SHIFT_INVALID': 9, 'ubyte': <type 'numpy.uint8'>, 'c_': <numpy.lib.index_tricks.CClass object at 0x7f90f674e390>, 'matrix_rank': <function matrix_rank at 0x7f90f676e230>, 'degrees': <ufunc 'degrees'>, 'switch_backend': <function switch_backend at 0x7f90e49067d0>, 'numpy': <module 'numpy' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/__init__.pyc'>, '__doc__': 'Automatically created module for IPython interactive environment', 'empty': <built-in function empty>, 'VisibleDeprecationWarning': <class 'numpy.VisibleDeprecationWarning'>, 'find_common_type': <function find_common_type at 0x7f914724e6e0>, 'random_sample': <built-in method random_sample of mtrand.RandomState object at 0x7f90f5c4d390>, 'longest_ones': <function longest_ones at 0x7f90ec561ed8>, 'irfft2': <function irfft2 at 0x7f90f6518668>, 'arcsin': <ufunc 'arcsin'>, 'sctypeNA': {<type 'numpy.void'>: 'Void0', 'Int32': <type 'numpy.int32'>, 'Complex64': <type 'numpy.complex128'>, <type 'numpy.int8'>: 'Int8', 'c16': 'Complex64', <type 'numpy.int16'>: 'Int16', 'D': 'Complex64', 'H': 'UInt16', 'L': 'UInt64', <type 'numpy.int32'>: 'Int32', 'd': 'Float64', 'h': 'Int16', 'l': 'Int64', <type 'numpy.int64'>: 'Int64', 'c32': 'Complex128', 'Timedelta64': <type 'numpy.timedelta64'>, 'b1': 'Bool', 'M8': 'Datetime64', 'String0': <type 'numpy.string_'>, <type 'numpy.uint8'>: 'UInt8', 'I': 'UInt32', '?': 'Bool', 'Void0': <type 'numpy.void'>, <type 'numpy.uint16'>: 'UInt16', 'G': 'Complex128', 'O': 'Object0', 'UInt8': <type 'numpy.uint8'>, 'S': 'String0', <type 'numpy.uint32'>: 'UInt32', 'UInt64': <type 'numpy.uint64'>, 'g': 'Float128', <type 'numpy.uint64'>: 'UInt64', 'Float16': <type 'numpy.float16'>, <type 'numpy.uint64'>: 'UInt64', 'Bool': <type 'numpy.bool_'>, 'u8': <type 'numpy.uint64'>, 'u4': <type 'numpy.uint32'>, <type 'numpy.float16'>: 'Float16', 'Unicode0': <type 'numpy.unicode_'>, 'u1': <type 'numpy.uint8'>, 'u2': <type 'numpy.uint16'>, 'Datetime64': <type 'numpy.datetime64'>, 'Int8': <type 'numpy.int8'>, 'B': 'UInt8', <type 'numpy.float32'>: 'Float32', 'F': 'Complex32', 'c8': 'Complex32', 'Int64': <type 'numpy.int64'>, <type 'numpy.int64'>: 'Int64', 'Complex32': <type 'numpy.complex64'>, 'V': 'Void0', <type 'numpy.float64'>: 'Float64', 'b': 'Int8', 'f': 'Float32', 'm8': 'Timedelta64', <type 'numpy.float128'>: 'Float128', 'f16': 'Float128', 'UInt32': <type 'numpy.uint32'>, 'f2': 'Float16', 'f4': 'Float32', 'f8': 'Float64', 'Complex128': <type 'numpy.complex256'>, <type 'numpy.datetime64'>: 'Datetime64', 'Object0': <type 'numpy.object_'>, 'Int16': <type 'numpy.int16'>, <type 'numpy.object_'>: 'Object0', 'Float64': <type 'numpy.float64'>, <type 'numpy.timedelta64'>: 'Timedelta64', 'UInt16': <type 'numpy.uint16'>, 'Float32': <type 'numpy.float32'>, <type 'numpy.bool_'>: 'Bool', 'i8': <type 'numpy.int64'>, <type 'numpy.complex64'>: 'Complex32', 'i1': <type 'numpy.int8'>, 'i2': <type 'numpy.int16'>, 'M': 'Datetime64', 'i4': <type 'numpy.int32'>, 'Q': 'UInt64', 'U': 'Unicode0', <type 'numpy.string_'>: 'String0', <type 'numpy.complex128'>: 'Complex64', 'e': 'Float16', 'i': 'Int32', 'm': 'Timedelta64', 'q': 'Int64', <type 'numpy.unicode_'>: 'Unicode0', 'Float128': <type 'numpy.float128'>, <type 'numpy.complex256'>: 'Complex128'}, 'imag': <function imag at 0x7f90f67a2230>, 'sctype2char': <function sctype2char at 0x7f91455fdde8>, 'singlecomplex': <type 'numpy.complex64'>, 'SHIFT_DIVIDEBYZERO': 0, 'sort': <function sort at 0x7f914560e050>, 'bytes': <type 'str'>, 'func': <function func at 0x7f90e45a70c8>, 'csv2rec': <function csv2rec at 0x7f90ec566230>, 'MachAr': <class 'numpy.core.machar.MachAr'>, 'apply_along_axis': <function apply_along_axis at 0x7f90f6758668>, 'new_figure_manager': <function new_figure_manager at 0x7f90e48f7c08>, 'tight_layout': <function tight_layout at 0x7f90e490c050>, 'reciprocal': <ufunc 'reciprocal'>, 'tanh': <ufunc 'tanh'>, 'dstack': <function dstack at 0x7f90f6758848>, 'float64': <type 'numpy.float64'>, 'angle_spectrum': <function angle_spectrum at 0x7f90e490e0c8>, 'colorbar': <function colorbar at 0x7f90e490ca28>, 'cast': {<type 'numpy.void'>: <function <lambda> at 0x7f91455fde60>, <type 'numpy.int64'>: <function <lambda> at 0x7f91455fded8>, <type 'numpy.uint64'>: <function <lambda> at 0x7f91455fdf50>, <type 'numpy.datetime64'>: <function <lambda> at 0x7f9145603050>, <type 'numpy.object_'>: <function <lambda> at 0x7f91456030c8>, <type 'numpy.int8'>: <function <lambda> at 0x7f9145603140>, <type 'numpy.uint8'>: <function <lambda> at 0x7f91456031b8>, <type 'numpy.float16'>: <function <lambda> at 0x7f9145603230>, <type 'numpy.timedelta64'>: <function <lambda> at 0x7f91456032a8>, <type 'numpy.bool_'>: <function <lambda> at 0x7f9145603320>, <type 'numpy.int16'>: <function <lambda> at 0x7f9145603398>, <type 'numpy.uint16'>: <function <lambda> at 0x7f9145603410>, <type 'numpy.float32'>: <function <lambda> at 0x7f9145603488>, <type 'numpy.complex64'>: <function <lambda> at 0x7f9145603500>, <type 'numpy.string_'>: <function <lambda> at 0x7f9145603578>, <type 'numpy.int32'>: <function <lambda> at 0x7f91456035f0>, <type 'numpy.uint32'>: <function <lambda> at 0x7f9145603668>, <type 'numpy.float64'>: <function <lambda> at 0x7f91456036e0>, <type 'numpy.complex128'>: <function <lambda> at 0x7f9145603758>, <type 'numpy.unicode_'>: <function <lambda> at 0x7f91456037d0>, <type 'numpy.int64'>: <function <lambda> at 0x7f9145603848>, <type 'numpy.uint64'>: <function <lambda> at 0x7f91456038c0>, <type 'numpy.float128'>: <function <lambda> at 0x7f9145603938>, <type 'numpy.complex256'>: <function <lambda> at 0x7f91456039b0>}, 'gumbel': <built-in method gumbel of mtrand.RandomState object at 0x7f90f5c4d390>, 'rfft2': <function rfft2 at 0x7f90f6518b18>, 'eig': <function eig at 0x7f90f676e488>, 'packbits': <built-in function packbits>, 'issctype': <function issctype at 0x7f91455fdaa0>, 'mgrid': <numpy.lib.index_tricks.nd_grid object at 0x7f90f674e150>, 'Slider': <class 'matplotlib.widgets.Slider'>, 'vonmises': <built-in method vonmises of mtrand.RandomState object at 0x7f90f5c4d390>, 'ushort': <type 'numpy.uint16'>, 'Polygon': <class 'matplotlib.patches.Polygon'>, 'complex256': <type 'numpy.complex256'>, 'empty_like': <built-in function empty_like>, 'unicode_literals': _Feature((2, 6, 0, 'alpha', 2), (3, 0, 0, 'alpha', 0), 131072), 'einsum': <built-in function einsum>, 'signbit': <ufunc 'signbit'>, 'cond': <function cond at 0x7f90f676e2a8>, 'chisquare': <built-in method chisquare of mtrand.RandomState object at 0x7f90f5c4d390>, 'conj': <ufunc 'conjugate'>, 'asmatrix': <function asmatrix at 0x7f90f67478c0>, 'floating': <type 'numpy.floating'>, 'setdiff1d': <function setdiff1d at 0x7f90f64f2488>, 'bitwise_xor': <ufunc 'bitwise_xor'>, 'WeekdayLocator': <class 'matplotlib.dates.WeekdayLocator'>, 'fabs': <ufunc 'fabs'>, 'cumprod': <function cumprod at 0x7f9145626848>, 'generic': <type 'numpy.generic'>, 'reshape': <function reshape at 0x7f914560e500>, 'NaN': nan, 'cross': <function cross at 0x7f9145607398>, 'sqrt': <ufunc 'sqrt'>, 'show_config': <function show at 0x7f9146120410>, 'longcomplex': <type 'numpy.complex256'>, 'poly_between': <function poly_between at 0x7f90ec56b578>, 'pad': <function pad at 0x7f90f651d410>, 'split': <function split at 0x7f90f67589b0>, 'getp': <function getp at 0x7f90ec66a140>, 'floor_divide': <ufunc 'floor_divide'>, '__version__': '1.9.3', 'format_parser': <class numpy.core.records.format_parser at 0x7f90f69ea188>, 'nextafter': <ufunc 'nextafter'>, 'exponential': <built-in method exponential of mtrand.RandomState object at 0x7f90f5c4d390>, 'dedent': <function dedent at 0x7f9142eaff50>, 'polyval': <function polyval at 0x7f90f64f0140>, 'SubplotTool': <class 'matplotlib.widgets.SubplotTool'>, 'flipud': <function flipud at 0x7f90f67345f0>, 'i0': <function i0 at 0x7f90f6743d70>, 'permutation': <built-in method permutation of mtrand.RandomState object at 0x7f90f5c4d390>, 'disconnect': <function disconnect at 0x7f90e490a320>, 'iscomplexobj': <function iscomplexobj at 0x7f90f67a2500>, 'sys': <module 'sys' (built-in)>, 'ion': <function ion at 0x7f90e4906a28>, 'array2string': <function array2string at 0x7f9145627140>, 'ComplexWarning': <class 'numpy.core.numeric.ComplexWarning'>, 'mafromtxt': <function mafromtxt at 0x7f90f650e0c8>, 'bartlett': <function bartlett at 0x7f90f6743aa0>, 'polydiv': <function polydiv at 0x7f90f64f0320>, 'histogram2d': <function histogram2d at 0x7f90f6734a28>, 'identity': <function identity at 0x7f9145627ed8>, 'safe_eval': <function safe_eval at 0x7f90f673b6e0>, 'ifft': <function ifft at 0x7f9146120c80>, 'cov': <function cov at 0x7f90f6743758>, 'Figure': <class 'matplotlib.figure.Figure'>, 'byte': <type 'numpy.int8'>, 'Tester': <class 'numpy.testing.nosetester.NoseTester'>, 'trapz': <function trapz at 0x7f90f6747230>, 'PINF': inf, 'rec_drop_fields': <function rec_drop_fields at 0x7f90ec565ed8>, 'recfromtxt': <function recfromtxt at 0x7f90f650e140>, 'add_newdocs': <module 'numpy.add_newdocs' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/add_newdocs.pyc'>, 'In': ['', u'\u5728\u7f16\u7a0b\u4e2d,\u53d8\u91cf\u53ef\u4ee5\u5206\u4e3a\u5168\u5c40\u53d8\u91cf\u548c\u5c40\u90e8\u53d8\u91cf\u3002  \n\u5168\u5c40\u53d8\u91cf\u6307\u7684\u662f\u53ef\u4ee5\u5728\u672c\u7a0b\u5e8f\u7684\u4efb\u4f55\u5730\u65b9\u8fdb\u884c\u8c03\u7528,\u800c\u4e0d\u5c40\u9650\u4e8e\u53ea\u80fd\u5728\u67d0\u4e2a\u51fd\u6570\u4f53\u5185\u90e8\u8fdb\u884c\u8c03\u7528\u3002  \n\u5bf9\u5e94\u7684,\u5c40\u90e8\u53d8\u91cf\u53ea\u53ef\u4ee5\u5728\u5f53\u524d\u51fd\u6570\u4f53\u6216\u8005\u5f53\u524d\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528,\u65e0\u6cd5\u5728\u5176\u4ed6\u51fd\u6570\u4f53\u6216\u8005\u6a21\u5757\u4e2d\u8fdb\u884c\u8c03\u7528\u3002', u"def func():\n    a = 5\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func\u5185\u8c03\u7528\u7684,a\u662f\u4e00\u4e2a\u5c40\u90e8\u53d8\u91cf,a=%s'%a)\nfunc()\nprint(a)", u"b = 5\nl = []\ndef func2():\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func2\u5185\u8c03\u7528\u7684,b\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5982\u679c\u6ca1\u6709\u5728\u51fd\u6570\u4f53\u5185\u91cd\u65b0\u8d4b\u503c,\u5219\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cfb b=%s'%b)\n    l.append(1)\n    print ('\u5bf9\u4e8e\u5168\u5c40\u53d8\u91cf\u7684\u4fee\u6539,\u4e5f\u53ef\u4ee5\u5728\u51fd\u6570\u4f53\u5185\u8fdb\u884c l = %s'%l)\nfunc2()\nprint(l)", u"c = 1\ndef func3():\n#     global c   # \u5982\u679c\u58f0\u660e\u662f\u5168\u5c40\u53d8\u91cf,\u90a3\u4e48\u91cd\u65b0\u8d4b\u503c\u76f4\u63a5\u4f5c\u7528\u4e8e\u5168\u5c40\u53d8\u91cf\n    c = 2\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func3\u5185\u8c03\u7528\u7684,c \u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5728\u51fd\u6570\u4f53\u5185\u88ab\u91cd\u65b0\u8d4b\u503c,\u8d4b\u503c\u540e\u8c03\u7528\u7684\u662f\u51fd\u6570\u4f53\u5185\u7684\u5c40\u90e8\u53d8\u91cf  c=%s'%c)\nfunc3()\nprint('\u5728\u51fd\u6570\u4f53\u5916\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cf c = %s'%c)", u'# \u76f4\u63a5\u8c03\u7528\u4f1a\u62a5\u9519\ndef a():\n    X = 5\na()\ndef b():\n    print(X)\nb()', u'# \u53ef\u4ee5\u4f7f\u7528 globals \u5728\u51fd\u6570\u4f53\u4e2d\u58f0\u540d\u8fd9\u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf\ndef a():\n    global X\n    X = 5\na()\ndef b():\n    print(X)\nb()', u'# \u67e5\u770b\u5f53\u524d\u7ea7\u522b\u4e0b\u7684\u5c40\u90e8\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print locals()\ntest()  ', u'# \u67e5\u770b\u5168\u5c40\u53d8\u91cf\ndef test():\n    a = 1\n    b = 2\n    print globals()\ntest()  '], 'ipmt': <function ipmt at 0x7f90f650e938>, 'object_': <type 'numpy.object_'>, 'RankWarning': <class 'numpy.lib.polynomial.RankWarning'>, 'ascontiguousarray': <function ascontiguousarray at 0x7f9145607b18>, 'summer': <function summer at 0x7f90e4910578>, '_i4': u"c = 1\ndef func3():\n#     global c   # \u5982\u679c\u58f0\u660e\u662f\u5168\u5c40\u53d8\u91cf,\u90a3\u4e48\u91cd\u65b0\u8d4b\u503c\u76f4\u63a5\u4f5c\u7528\u4e8e\u5168\u5c40\u53d8\u91cf\n    c = 2\n    print ('\u8fd9\u662f\u5728\u51fd\u6570func3\u5185\u8c03\u7528\u7684,c \u662f\u4e00\u4e2a\u5168\u5c40\u53d8\u91cf,\u5728\u51fd\u6570\u4f53\u5185\u88ab\u91cd\u65b0\u8d4b\u503c,\u8d4b\u503c\u540e\u8c03\u7528\u7684\u662f\u51fd\u6570\u4f53\u5185\u7684\u5c40\u90e8\u53d8\u91cf  c=%s'%c)\nfunc3()\nprint('\u5728\u51fd\u6570\u4f53\u5916\u8c03\u7528\u7684\u662f\u5168\u5c40\u53d8\u91cf c = %s'%c)", 'hexbin': <function hexbin at 0x7f90e490ea28>, 'absolute': <ufunc 'absolute'>, 'less': <ufunc 'less'>, 'putmask': <built-in function putmask>, 'UFUNC_BUFSIZE_DEFAULT': 8192, 'get_state': <built-in method get_state of mtrand.RandomState object at 0x7f90f5c4d390>, 'NAN': nan, 'absolute_import': _Feature((2, 5, 0, 'alpha', 1), (3, 0, 0, 'alpha', 0), 16384), 'typeDict': {0: <type 'numpy.bool_'>, 1: <type 'numpy.int8'>, 2: <type 'numpy.uint8'>, 3: <type 'numpy.int16'>, 4: <type 'numpy.uint16'>, 5: <type 'numpy.int32'>, 6: <type 'numpy.uint32'>, 7: <type 'numpy.int64'>, 8: <type 'numpy.uint64'>, 9: <type 'numpy.int64'>, 10: <type 'numpy.uint64'>, 11: <type 'numpy.float32'>, 12: <type 'numpy.float64'>, 13: <type 'numpy.float128'>, 14: <type 'numpy.complex64'>, 15: <type 'numpy.complex128'>, 16: <type 'numpy.complex256'>, 17: <type 'numpy.object_'>, 18: <type 'numpy.string_'>, 19: <type 'numpy.unicode_'>, 20: <type 'numpy.void'>, 21: <type 'numpy.datetime64'>, 'unicode': <type 'numpy.unicode_'>, 23: <type 'numpy.float16'>, 'cfloat': <type 'numpy.complex128'>, 'longfloat': <type 'numpy.float128'>, 'Int32': <type 'numpy.int32'>, 'Complex64': <type 'numpy.complex128'>, 'unicode_': <type 'numpy.unicode_'>, 'complex': <type 'numpy.complex128'>, 'timedelta64': <type 'numpy.timedelta64'>, 'uint16': <type 'numpy.uint16'>, 'c16': <type 'numpy.complex128'>, 'float32': <type 'numpy.float32'>, 'complex256': <type 'numpy.complex256'>, 'D': <type 'numpy.complex128'>, 'H': <type 'numpy.uint16'>, 'void': <type 'numpy.void'>, 'unicode0': <type 'numpy.unicode_'>, 'L': <type 'numpy.uint64'>, 'P': <type 'numpy.uint64'>, 'half': <type 'numpy.float16'>, 'void0': <type 'numpy.void'>, 'd': <type 'numpy.float64'>, 'h': <type 'numpy.int16'>, 'l': <type 'numpy.int64'>, 'p': <type 'numpy.int64'>, 'c32': <type 'numpy.complex256'>, 22: <type 'numpy.timedelta64'>, 'O8': <type 'numpy.object_'>, 'Timedelta64': <type 'numpy.timedelta64'>, 'object0': <type 'numpy.object_'>, 'b1': <type 'numpy.bool_'>, 'float128': <type 'numpy.float128'>, 'M8': <type 'numpy.datetime64'>, 'String0': <type 'numpy.string_'>, 'float16': <type 'numpy.float16'>, 'ulonglong': <type 'numpy.uint64'>, 'i1': <type 'numpy.int8'>, 'uint32': <type 'numpy.uint32'>, '?': <type 'numpy.bool_'>, 'Void0': <type 'numpy.void'>, 'complex64': <type 'numpy.complex64'>, 'G': <type 'numpy.complex256'>, 'O': <type 'numpy.object_'>, 'UInt8': <type 'numpy.uint8'>, 'S': <type 'numpy.string_'>, 'byte': <type 'numpy.int8'>, 'UInt64': <type 'numpy.uint64'>, 'g': <type 'numpy.float128'>, 'float64': <type 'numpy.float64'>, 'ushort': <type 'numpy.uint16'>, 'float_': <type 'numpy.float64'>, 'uint': <type 'numpy.uint64'>, 'object_': <type 'numpy.object_'>, 'Float16': <type 'numpy.float16'>, 'complex_': <type 'numpy.complex128'>, 'Unicode0': <type 'numpy.unicode_'>, 'uintp': <type 'numpy.uint64'>, 'intc': <type 'numpy.int32'>, 'csingle': <type 'numpy.complex64'>, 'datetime64': <type 'numpy.datetime64'>, 'float': <type 'numpy.float64'>, 'bool8': <type 'numpy.bool_'>, 'Bool': <type 'numpy.bool_'>, 'intp': <type 'numpy.int64'>, 'uintc': <type 'numpy.uint32'>, 'bytes_': <type 'numpy.string_'>, 'u8': <type 'numpy.uint64'>, 'u4': <type 'numpy.uint32'>, 'int_': <type 'numpy.int64'>, 'cdouble': <type 'numpy.complex128'>, 'u1': <type 'numpy.uint8'>, 'complex128': <type 'numpy.complex128'>, 'u2': <type 'numpy.uint16'>, 'f8': <type 'numpy.float64'>, 'Datetime64': <type 'numpy.datetime64'>, 'ubyte': <type 'numpy.uint8'>, 'm8': <type 'numpy.timedelta64'>, 'B': <type 'numpy.uint8'>, 'uint0': <type 'numpy.uint64'>, 'F': <type 'numpy.complex64'>, 'bool_': <type 'numpy.bool_'>, 'uint8': <type 'numpy.uint8'>, 'c8': <type 'numpy.complex64'>, 'Int64': <type 'numpy.int64'>, 'Int8': <type 'numpy.int8'>, 'Complex32': <type 'numpy.complex64'>, 'V': <type 'numpy.void'>, 'int8': <type 'numpy.int8'>, 'uint64': <type 'numpy.uint64'>, 'b': <type 'numpy.int8'>, 'f': <type 'numpy.float32'>, 'double': <type 'numpy.float64'>, 'UInt32': <type 'numpy.uint32'>, 'clongdouble': <type 'numpy.complex256'>, 'str': <type 'numpy.string_'>, 'f16': <type 'numpy.float128'>, 'f2': <type 'numpy.float16'>, 'f4': <type 'numpy.float32'>, 'int32': <type 'numpy.int32'>, 'int': <type 'numpy.int64'>, 'longdouble': <type 'numpy.float128'>, 'Complex128': <type 'numpy.complex256'>, 'single': <type 'numpy.float32'>, 'string': <type 'numpy.string_'>, 'q': <type 'numpy.int64'>, 'Int16': <type 'numpy.int16'>, 'Float64': <type 'numpy.float64'>, 'longcomplex': <type 'numpy.complex256'>, 'UInt16': <type 'numpy.uint16'>, 'bool': <type 'numpy.bool_'>, 'Float32': <type 'numpy.float32'>, 'string0': <type 'numpy.string_'>, 'longlong': <type 'numpy.int64'>, 'i8': <type 'numpy.int64'>, 'int16': <type 'numpy.int16'>, 'str_': <type 'numpy.string_'>, 'I': <type 'numpy.uint32'>, 'object': <type 'numpy.object_'>, 'M': <type 'numpy.datetime64'>, 'i4': <type 'numpy.int32'>, 'singlecomplex': <type 'numpy.complex64'>, 'Q': <type 'numpy.uint64'>, 'string_': <type 'numpy.string_'>, 'U': <type 'numpy.unicode_'>, 'a': <type 'numpy.string_'>, 'short': <type 'numpy.int16'>, 'e': <type 'numpy.float16'>, 'i': <type 'numpy.int32'>, 'clongfloat': <type 'numpy.complex256'>, 'm': <type 'numpy.timedelta64'>, 'Object0': <type 'numpy.object_'>, 'int64': <type 'numpy.int64'>, 'Float128': <type 'numpy.float128'>, 'i2': <type 'numpy.int16'>, 'int0': <type 'numpy.int64'>}, 'shape': <function shape at 0x7f91456260c8>, 'setbufsize': <function setbufsize at 0x7f91456292a8>, 'cfloat': <type 'numpy.complex128'>, 'divide': <ufunc 'divide'>, 'detrend_mean': <function detrend_mean at 0x7f90ec561320>, 'isscalar': <function isscalar at 0x7f9145627c80>, 'standard_normal': <built-in method standard_normal of mtrand.RandomState object at 0x7f90f5c4d390>, 'get_current_fig_manager': <function get_current_fig_manager at 0x7f90e490a1b8>, 'character': <type 'numpy.character'>, 'bench': <bound method NoseTester.test of <numpy.testing.nosetester.NoseTester object at 0x7f90f676c990>>, 'source': <function source at 0x7f90f673b938>, 'add': <ufunc 'add'>, 'uint16': <type 'numpy.uint16'>, 'hlines': <function hlines at 0x7f90e490ec08>, 'ufunc': <type 'numpy.ufunc'>, 'save': <function save at 0x7f90f65090c8>, 'plasma': <function plasma at 0x7f90e4910758>, 'Annotation': <class 'matplotlib.text.Annotation'>, 'float32': <type 'numpy.float32'>, 'real': <function real at 0x7f90f67a20c8>, 'int32': <type 'numpy.int32'>, 'path_length': <function path_length at 0x7f90ec56b8c0>, 'tril_indices': <function tril_indices at 0x7f90f6734b18>, 'around': <function around at 0x7f9145626a28>, 'cbook': <module 'matplotlib.cbook' from '/opt/conda/envs/python2/lib/python2.7/site-packages/matplotlib/cbook.pyc'>, 'lexsort': <built-in function lexsort>, 'get_scale_names': <function get_scale_names at 0x7f90e49dfb18>, 'complex_': <type 'numpy.complex128'>, 'load': <function load at 0x7f90f65097d0>, 'psd': <function psd at 0x7f90e490f1b8>, 'datestr2num': <function datestr2num at 0x7f9142a912a8>, 'xscale': <function xscale at 0x7f90e490c410>, 'unicode0': <type 'numpy.unicode_'>, 'grid': <function grid at 0x7f90e490fb18>, 'issubclass_': <function issubclass_ at 0x7f91455fdb90>, 'atleast_3d': <function atleast_3d at 0x7f90f69eecf8>, 'nper': <function nper at 0x7f90f650e9b0>, 'integer': <type 'numpy.integer'>, 'unique': <function unique at 0x7f90f64f2230>, 'mod': <ufunc 'remainder'>, '_sh': <module 'IPython.core.shadowns' from '/opt/conda/envs/python2/lib/python2.7/site-packages/IPython/core/shadowns.pyc'>, 'bitwise_not': <ufunc 'invert'>, 'plot_date': <function plot_date at 0x7f90e490f140>, 'laplace': <built-in method laplace of mtrand.RandomState object at 0x7f90f5c4d390>, 'getbufsize': <function getbufsize at 0x7f9145629320>, 'isfortran': <function isfortran at 0x7f91456079b0>, 'get_printoptions': <function get_printoptions at 0x7f9145626de8>, 'asarray_chkfinite': <function asarray_chkfinite at 0x7f90f6734d70>, 'pcolormesh': <function pcolormesh at 0x7f90e490eed8>, 'string0': <type 'numpy.string_'>, 'barh': <function barh at 0x7f90e490e410>, 'sign': <ufunc 'sign'>, '_dh': [u'/home/jquser'], 'findobj': <function findobj at 0x7f90e4906848>, 'spring': <function spring at 0x7f90e4910500>, 'in1d': <function in1d at 0x7f90f64f2398>, 'NullLocator': <class 'matplotlib.ticker.NullLocator'>, 'real_if_close': <function real_if_close at 0x7f90f67a26e0>, 'l': [1], 'rcdefaults': <function rcdefaults at 0x7f90e4906c80>, 'magma': <function magma at 0x7f90e4910668>, 'hypot': <ufunc 'hypot'>, 'logical_and': <ufunc 'logical_and'>, 'rrule': <class 'dateutil.rrule.rrule'>, 'diff': <function diff at 0x7f90f6743488>, 'diagflat': <function diagflat at 0x7f90f67347d0>, 'float128': <type 'numpy.float128'>, 'matshow': <function matshow at 0x7f90e490cb90>, 'isfinite': <ufunc 'isfinite'>, 'MINUTELY': 5, 'nonzero': <function nonzero at 0x7f9145626050>, 'kaiser': <function kaiser at 0x7f90f6743de8>, 'ifftshift': <function ifftshift at 0x7f90f6518398>, 'uint0': <type 'numpy.uint64'>, 'inside_poly': <function inside_poly at 0x7f90ec56b2a8>, 'normal': <built-in method normal of mtrand.RandomState object at 0x7f90f5c4d390>, 'flatten': <function flatten at 0x7f9142eaf230>, 'is_closed_polygon': <function is_closed_polygon at 0x7f90ec56b5f0>, 'polysub': <function polysub at 0x7f90f64f0230>, 'exit': <IPython.core.autocall.ZMQExitAutocall object at 0x7f90ec6c2a10>, 'Rectangle': <class 'matplotlib.patches.Rectangle'>, 'fromfile': <built-in function fromfile>, 'prod': <function prod at 0x7f91456267d0>, 'nanmax': <function nanmax at 0x7f90f6751cf8>, 'LinearLocator': <class 'matplotlib.ticker.LinearLocator'>, 'tensorinv': <function tensorinv at 0x7f90f676e848>, 'who': <function who at 0x7f90f673bb90>, 'dist_point_to_segment': <function dist_point_to_segment at 0x7f90ec565578>, 'power': <ufunc 'power'>, 'array_split': <function array_split at 0x7f90f6758938>, 'c': 1, 'zipf': <built-in method zipf of mtrand.RandomState object at 0x7f90f5c4d390>, 'stem': <function stem at 0x7f90e490f578>, 'step': <function step at 0x7f90e490f5f0>, 'percentile': <function percentile at 0x7f90f6747140>, 'hsv': <function hsv at 0x7f90e4910320>, 'FPE_DIVIDEBYZERO': 1, '__name__': '__main__', 'subtract': <ufunc 'subtract'>, '_': '', 'mx2num': <function mx2num at 0x7f913b7cd410>, 'frompyfunc': <built-in function frompyfunc>, 'multinomial': <built-in method multinomial of mtrand.RandomState object at 0x7f90f5c4d390>, 'frombuffer': <built-in function frombuffer>, 'iscomplex': <function iscomplex at 0x7f90f67a2050>, 'Artist': <class 'matplotlib.artist.Artist'>, 'fill_betweenx': <function fill_betweenx at 0x7f90e490e9b0>, 'multivariate_normal': <built-in method multivariate_normal of mtrand.RandomState object at 0x7f90f5c4d390>, 'add_docstring': <built-in function add_docstring>, 'argsort': <function argsort at 0x7f914560eb90>, 'relativedelta': <class 'dateutil.relativedelta.relativedelta'>, 'fmin': <ufunc 'fmin'>, 'loadtxt': <function loadtxt at 0x7f90f6509d70>, 'bytes_': <type 'numpy.string_'>, 'ones_like': <function ones_like at 0x7f9145607de8>, 'ScalarFormatter': <class 'matplotlib.ticker.ScalarFormatter'>, 'is_busday': <built-in function is_busday>, 'arcsinh': <ufunc 'arcsinh'>, 'CLIP': 0, 'exp_safe': <function exp_safe at 0x7f90ec565758>, '__builtin__': <module '__builtin__' (built-in)>, 'negative': <ufunc 'negative'>, 'annotate': <function annotate at 0x7f90e490fcf8>, 'ndenumerate': <class 'numpy.lib.index_tricks.ndenumerate'>, 'intp': <type 'numpy.int64'>, 'standard_cauchy': <built-in method standard_cauchy of mtrand.RandomState object at 0x7f90f5c4d390>, 'standard_t': <built-in method standard_t of mtrand.RandomState object at 0x7f90f5c4d390>, 'HOURLY': 4, 'arrow': <function arrow at 0x7f90e490e140>, 'Infinity': inf, 'log': <ufunc 'log'>, 'cdouble': <type 'numpy.complex128'>, 'complex128': <type 'numpy.complex128'>, 'tick_params': <function tick_params at 0x7f90e490fe60>, 'round_': <function round_ at 0x7f9145626aa0>, 'broadcast_arrays': <function broadcast_arrays at 0x7f90f674fb18>, 'inner': <built-in function inner>, 'var': <function var at 0x7f9145626c08>, 'slopes': <function slopes at 0x7f90ec56b1b8>, 'log10': <ufunc 'log10'>, 'hypergeometric': <built-in method hypergeometric of mtrand.RandomState object at 0x7f90f5c4d390>, 'uintp': <type 'numpy.uint64'>, 'unwrap': <function unwrap at 0x7f90f6743230>, 'interp': <function interp at 0x7f90f6743410>, 'triangular': <built-in method triangular of mtrand.RandomState object at 0x7f90f5c4d390>, 'noncentral_chisquare': <built-in method noncentral_chisquare of mtrand.RandomState object at 0x7f90f5c4d390>, 'histogram': <function histogram at 0x7f90f6734ed8>, 'issubdtype': <function issubdtype at 0x7f91455fdc80>, 'maximum_sctype': <function maximum_sctype at 0x7f91455fd9b0>, 'flexible': <type 'numpy.flexible'>, 'e': 2.718281828459045, 'squeeze': <function squeeze at 0x7f914560ede8>, 'int8': <type 'numpy.int8'>, 'cholesky': <function cholesky at 0x7f90f676e6e0>, 'info': <function info at 0x7f90f673b9b0>, 'seterr': <function seterr at 0x7f91456291b8>, 'argmin': <function argmin at 0x7f914560ec80>, 'fignum_exists': <function fignum_exists at 0x7f90e490a050>, 'genfromtxt': <function genfromtxt at 0x7f90f6509f50>, 'rec_append_fields': <function rec_append_fields at 0x7f90ec565e60>, 'maximum': <ufunc 'maximum'>, 'record': <class 'numpy.core.records.record'>, 'obj2sctype': <function obj2sctype at 0x7f91455fdb18>, 'clongdouble': <type 'numpy.complex256'>, 'sum': <function sum at 0x7f9145626230>, 'euler_gamma': 0.5772156649015329, 'arccosh': <ufunc 'arccosh'>, '_oh': {}, 'delete': <function delete at 0x7f90f6747398>, 'YEARLY': 0, 'digitize': <built-in function digitize>, 'clongfloat': <type 'numpy.complex256'>, 'yscale': <function yscale at 0x7f90e490c488>, 'inv': <function inv at 0x7f90f676e7d0>, 'specgram': <function specgram at 0x7f90e490f488>, 'pie': <function pie at 0x7f90e490f050>, 'char': <module 'numpy.core.defchararray' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/core/defchararray.pyc'>, 'single': <type 'numpy.float32'>, 'isposinf': <function isposinf at 0x7f90f67a2320>, 'set_cmap': <function set_cmap at 0x7f90e490cb18>, 'hsplit': <function hsplit at 0x7f90f6758a28>, 'ScalarType': (<type 'int'>, <type 'float'>, <type 'complex'>, <type 'long'>, <type 'bool'>, <type 'str'>, <type 'unicode'>, <type 'buffer'>, <type 'numpy.void'>, <type 'numpy.int64'>, <type 'numpy.uint64'>, <type 'numpy.datetime64'>, <type 'numpy.object_'>, <type 'numpy.int8'>, <type 'numpy.uint8'>, <type 'numpy.float16'>, <type 'numpy.timedelta64'>, <type 'numpy.bool_'>, <type 'numpy.int16'>, <type 'numpy.uint16'>, <type 'numpy.float32'>, <type 'numpy.complex64'>, <type 'numpy.string_'>, <type 'numpy.int32'>, <type 'numpy.uint32'>, <type 'numpy.float64'>, <type 'numpy.complex128'>, <type 'numpy.unicode_'>, <type 'numpy.int64'>, <type 'numpy.uint64'>, <type 'numpy.float128'>, <type 'numpy.complex256'>), 'noncentral_f': <built-in method noncentral_f of mtrand.RandomState object at 0x7f90f5c4d390>, 'triu': <function triu at 0x7f90f6734938>, 'inf': inf, 'fill': <function fill at 0x7f90e490e8c0>, 'expand_dims': <function expand_dims at 0x7f90f6758758>, 'pareto': <built-in method pareto of mtrand.RandomState object at 0x7f90f5c4d390>, 'logspace': <function logspace at 0x7f90f69ee2a8>, 'floor': <ufunc 'floor'>, 'polyadd': <function polyadd at 0x7f90f64f01b8>, 'TU': TU, 'nan': nan, 'fft': <module 'numpy.fft' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/fft/__init__.pyc'>, 'emath': <module 'numpy.lib.scimath' from '/opt/conda/envs/python2/lib/python2.7/site-packages/numpy/lib/scimath.pyc'>, 'arctan': <ufunc 'arctan'>, 'bmat': <function bmat at 0x7f90f674f938>, 'unravel_index': <built-in function unravel_index>, 'prism': <function prism at 0x7f90e4910488>, 'isclose': <function isclose at 0x7f9145629050>, 'ERR_DEFAULT': 521, 'magnitude_spectrum': <function magnitude_spectrum at 0x7f90e490ed70>, 'test': <function test at 0x7f90e456f230>, 'pi': 3.141592653589793, 'register_cmap': <function register_cmap at 0x7f90ec538050>, 'roll': <function roll at 0x7f9145607500>, 'figsize': <function figsize at 0x7f9148fcdc80>, 'compare_chararrays': <built-in function compare_chararrays>, 'polar': <function polar at 0x7f90e490ccf8>, 'draw': <function draw at 0x7f90e490a410>, 'repeat': <function repeat at 0x7f914560e398>, 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学习笔记-python的变量

吃瓜群众小王发表于：5 月 10 日 06：15回复(1)

什么是全局变量?

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