Python types.FunctionType方法代碼示例

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def run_test(work_type: FunctionType, job_sets: Sequence, trials: int,
             pool_class: type, worker_count: int) -> Mapping:
    pool = pool_class(worker_count)
    if work_type == 'compute':
        test_func = pool.run_compute_test
    elif work_type == 'network':
        test_func = pool.run_network_test
    else:
        raise Exception("Invalid work type: {}".format(work_type))
    results = map(
        lambda jobs: test_func(jobs, trials, show_progress=True),
        tqdm(job_sets, desc=pool_class.__name__),
    )
    summarized_results = list(map(summarize_test, results))
    pool.destroy_pool()
    return summarized_results 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def validate_error_func(self):
        if self.error_func:
            if isinstance(self.error_func,types.FunctionType):
                ismethod = 0
            elif isinstance(self.error_func, types.MethodType):
                ismethod = 1
            else:
                self.log.error("'p_error' defined, but is not a function or method")
                self.error = 1
                return

            eline = func_code(self.error_func).co_firstlineno
            efile = func_code(self.error_func).co_filename
            module = inspect.getmodule(self.error_func)
            self.modules[module] = 1

            argcount = func_code(self.error_func).co_argcount - ismethod
            if argcount != 1:
                self.log.error("%s:%d: p_error() requires 1 argument",efile,eline)
                self.error = 1

    # Get the tokens map 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def get_pfunctions(self):
        p_functions = []
        for name, item in self.pdict.items():
            if not name.startswith('p_'): continue
            if name == 'p_error': continue
            if isinstance(item,(types.FunctionType,types.MethodType)):
                line = func_code(item).co_firstlineno
                module = inspect.getmodule(item)
                p_functions.append((line,module,name,item.__doc__))

        # Sort all of the actions by line number
        p_functions.sort()
        self.pfuncs = p_functions


    # Validate all of the p_functions 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def default(self, o):
        if types.FunctionType == type(o):
            return o.__name__
        # sets become lists
        if isinstance(o, set):
            return list(o)
        # date times become strings
        if isinstance(o, datetime):
            return o.isoformat()
        if isinstance(o, decimal.Decimal):
            return float(o)
        if isinstance(o, type):
            return str(o)
        if isinstance(o, Exception):
            return str(o)
        if isinstance(o, set):
            return str(o, 'utf-8')
        if isinstance(o, bytes):
            return str(o, 'utf-8')
        
        return json.JSONEncoder.default(self, o) 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def always_seq(edge, reset):
    callinfo = _getCallInfo()
    sigargs = []
    if not isinstance(edge, _WaiterList):
        raise AlwaysSeqError(_error.EdgeType)
    edge.sig._read = True
    edge.sig._used = True
    sigargs.append(edge.sig)
    if reset is not None:
        if not isinstance(reset, ResetSignal):
            raise AlwaysSeqError(_error.ResetType)
        reset._read = True
        reset._used = True
        sigargs.append(reset)
    sigdict = _get_sigdict(sigargs, callinfo.symdict)

    def _always_seq_decorator(func):
        if not isinstance(func, FunctionType):
            raise AlwaysSeqError(_error.ArgType)
        if _isGenFunc(func):
            raise AlwaysSeqError(_error.ArgType)
        if func.__code__.co_argcount > 0:
            raise AlwaysSeqError(_error.NrOfArgs)
        return _AlwaysSeq(func, edge, reset, callinfo=callinfo, sigdict=sigdict)
    return _always_seq_decorator 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def always(*args):
    callinfo = _getCallInfo()
    sigargs = []
    for arg in args:
        if isinstance(arg, _Signal):
            arg._read = True
            arg._used = True
            sigargs.append(arg)
        elif isinstance(arg, _WaiterList):
            arg.sig._read = True
            arg.sig._used = True
            sigargs.append(arg.sig)
        elif not isinstance(arg, delay):
            raise AlwaysError(_error.DecArgType)
    sigdict = _get_sigdict(sigargs, callinfo.symdict)

    def _always_decorator(func):
        if not isinstance(func, FunctionType):
            raise AlwaysError(_error.ArgType)
        if _isGenFunc(func):
            raise AlwaysError(_error.ArgType)
        if func.__code__.co_argcount > 0:
            raise AlwaysError(_error.NrOfArgs)
        return _Always(func, args, callinfo=callinfo, sigdict=sigdict)
    return _always_decorator 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def save_pypy_builtin_func(self, obj):
        """Save pypy equivalent of builtin functions.

        PyPy does not have the concept of builtin-functions. Instead,
        builtin-functions are simple function instances, but with a
        builtin-code attribute.
        Most of the time, builtin functions should be pickled by attribute. But
        PyPy has flaky support for __qualname__, so some builtin functions such
        as float.__new__ will be classified as dynamic. For this reason only,
        we created this special routine. Because builtin-functions are not
        expected to have closure or globals, there is no additional hack
        (compared the one already implemented in pickle) to protect ourselves
        from reference cycles. A simple (reconstructor, newargs, obj.__dict__)
        tuple is save_reduced.

        Note also that PyPy improved their support for __qualname__ in v3.6, so
        this routing should be removed when cloudpickle supports only PyPy 3.6
        and later.
        """
        rv = (types.FunctionType, (obj.__code__, {}, obj.__name__,
                                   obj.__defaults__, obj.__closure__),
              obj.__dict__)
        self.save_reduce(*rv, obj=obj) 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def _make_skel_func(code, cell_count, base_globals=None):
    """ Creates a skeleton function object that contains just the provided
        code and the correct number of cells in func_closure.  All other
        func attributes (e.g. func_globals) are empty.
    """
    # This is backward-compatibility code: for cloudpickle versions between
    # 0.5.4 and 0.7, base_globals could be a string or None. base_globals
    # should now always be a dictionary.
    if base_globals is None or isinstance(base_globals, str):
        base_globals = {}

    base_globals['__builtins__'] = __builtins__

    closure = (
        tuple(_make_empty_cell() for _ in range(cell_count))
        if cell_count >= 0 else
        None
    )
    return types.FunctionType(code, base_globals, None, None, closure) 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def getCommands(cls):
        excludes = [
            'opened',
            'closed',
            'received_message',
            'exec_command',
            'getCommands'
        ]
        out = []
        m = [x for x, y in cls.__dict__.items() if type(y) == FunctionType]
        for method in m:
            if method.startswith("_" + cls.__name__):
                continue
            if method in excludes:
                continue
            if method.startswith("__"):
                continue
            out.append(method)
        out.sort()
        return out 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def get_module_functions(modules):
  """Finds functions that do not have implemented derivatives.

  Args:
    modules: A list of Python modules. Functions contained in these modules
        will be checked for membership in 'implemented', and if not found,
        will be added to an 'unimplemented' set
    implemented: A Python object containing implemented derivatives. A function
        should be checkable for membership using the `fn in implemented` syntax.

  Returns:
    module_fns: A set of functions, builtins or ufuncs in `modules`.
  """
  module_fns = set()
  for module in modules:
    for key in dir(module):
      attr = getattr(module, key)
      if isinstance(
          attr, (types.BuiltinFunctionType, types.FunctionType, numpy.ufunc)):
        module_fns.add(attr)
  return module_fns 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def with_temp_path(filename=None):
    """Decorator version of ``IOBase.temp_path``"""
    arg_fn = None
    if isinstance(filename, types.FunctionType):
        # Decorator was used without calling, so `filename' is actually the decorated function
        arg_fn = filename
        filename = None

    def decorator(fn):
        @functools.wraps(fn)
        def inner(self, *args, **kwargs):
            with self.temp_path(filename) as tmp_path:
                return fn(self, tmp_path, *args, **kwargs)
        return inner
    if arg_fn is not None:
        return decorator(arg_fn)
    else:
        return decorator 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def validate_error_func(self):
        if self.error_func:
            if isinstance(self.error_func, types.FunctionType):
                ismethod = 0
            elif isinstance(self.error_func, types.MethodType):
                ismethod = 1
            else:
                self.log.error("'p_error' defined, but is not a function or method")
                self.error = True
                return

            eline = self.error_func.__code__.co_firstlineno
            efile = self.error_func.__code__.co_filename
            module = inspect.getmodule(self.error_func)
            self.modules.add(module)

            argcount = self.error_func.__code__.co_argcount - ismethod
            if argcount != 1:
                self.log.error('%s:%d: p_error() requires 1 argument', efile, eline)
                self.error = True

    # Get the tokens map 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def get_pfunctions(self):
        p_functions = []
        for name, item in self.pdict.items():
            if not name.startswith('p_') or name == 'p_error':
                continue
            if isinstance(item, (types.FunctionType, types.MethodType)):
                line = getattr(item, 'co_firstlineno', item.__code__.co_firstlineno)
                module = inspect.getmodule(item)
                p_functions.append((line, module, name, item.__doc__))

        # Sort all of the actions by line number; make sure to stringify
        # modules to make them sortable, since `line` may not uniquely sort all
        # p functions
        p_functions.sort(key=lambda p_function: (
            p_function[0],
            str(p_function[1]),
            p_function[2],
            p_function[3]))
        self.pfuncs = p_functions

    # Validate all of the p_functions 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def __new__(mcs, name, bases, attrs):
    """Automatically wraps all methods of subclasses of RecipeApi with
    @infer_composite_step. This allows defer_results to work as intended without
    manually decorating every method.
    """
    wrap = lambda f: infer_composite_step(f) if f else f
    for attr in attrs:
      if attr in RecipeApiMeta.WHITELIST:
        continue
      val = attrs[attr]
      if isinstance(val, types.FunctionType):
        attrs[attr] = wrap(val)
      elif isinstance(val, property):
        attrs[attr] = property(
          wrap(val.fget),
          wrap(val.fset),
          wrap(val.fdel),
          val.__doc__)
    return super(RecipeApiMeta, mcs).__new__(mcs, name, bases, attrs) 

# 需要導入模塊: import types [as 別名]
# 或者: from types import FunctionType [as 別名]
def string_function(module: [str, ModuleType], func: str, *args, **kwargs):
    """根據字符串方法名來進行調用模塊方法

    :param module: 模塊名
    :param func: 模塊中的方法名字
    :param args: 方法裏麵的參數值
    :param kwargs: 方法裏麵的參數值
    :return: 返回一個返回值
    """
    if isinstance(module, ModuleType):
        if hasattr(module, func):
            func_or_var = getattr(module, func)
            if isinstance(func_or_var, FunctionType):
                return func_or_var(*args, **kwargs)
            else:
                return func_or_var
        else:
            print(f'{func}不是一個方法')
    elif isinstance(module, str):
        m = __import__(module)
        return string_function(m, func, *args, **kwargs)
    else:
        print(f'{module}不是一個模塊')
    return None