Terminology: output is silenced, not disabled.

IPython/core/magic.py

@@ -1,757 +1,757 b''
 # encoding: utf-8
 """Magic functions for InteractiveShell.
 """
 
 #-----------------------------------------------------------------------------
 #  Copyright (C) 2001 Janko Hauser <[e-mail]> and
 #  Copyright (C) 2001 Fernando Perez <[e-mail]>
 #  Copyright (C) 2008 The IPython Development Team
 
 #  Distributed under the terms of the BSD License.  The full license is in
 #  the file COPYING, distributed as part of this software.
 #-----------------------------------------------------------------------------
 
 import os
 import re
 import sys
 from getopt import getopt, GetoptError
 
 from traitlets.config.configurable import Configurable
 from . import oinspect
 from .error import UsageError
 from .inputtransformer2 import ESC_MAGIC, ESC_MAGIC2
 from ..utils.ipstruct import Struct
 from ..utils.process import arg_split
 from ..utils.text import dedent
 from traitlets import Bool, Dict, Instance, observe
 from logging import error
 
 #-----------------------------------------------------------------------------
 # Globals
 #-----------------------------------------------------------------------------
 
 # A dict we'll use for each class that has magics, used as temporary storage to
 # pass information between the @line/cell_magic method decorators and the
 # @magics_class class decorator, because the method decorators have no
 # access to the class when they run.  See for more details:
 # http://stackoverflow.com/questions/2366713/can-a-python-decorator-of-an-instance-method-access-the-class
 
 magics = dict(line={}, cell={})
 
 magic_kinds = ('line', 'cell')
 magic_spec = ('line', 'cell', 'line_cell')
 magic_escapes = dict(line=ESC_MAGIC, cell=ESC_MAGIC2)
 
 #-----------------------------------------------------------------------------
 # Utility classes and functions
 #-----------------------------------------------------------------------------
 
 class Bunch: pass
 
 
 def on_off(tag):
     """Return an ON/OFF string for a 1/0 input. Simple utility function."""
     return ['OFF','ON'][tag]
 
 
 def compress_dhist(dh):
     """Compress a directory history into a new one with at most 20 entries.
 
     Return a new list made from the first and last 10 elements of dhist after
     removal of duplicates.
     """
     head, tail = dh[:-10], dh[-10:]
 
     newhead = []
     done = set()
     for h in head:
         if h in done:
             continue
         newhead.append(h)
         done.add(h)
 
     return newhead + tail
 
 
 def needs_local_scope(func):
     """Decorator to mark magic functions which need to local scope to run."""
     func.needs_local_scope = True
     return func
 
 #-----------------------------------------------------------------------------
 # Class and method decorators for registering magics
 #-----------------------------------------------------------------------------
 
 def magics_class(cls):
     """Class decorator for all subclasses of the main Magics class.
 
     Any class that subclasses Magics *must* also apply this decorator, to
     ensure that all the methods that have been decorated as line/cell magics
     get correctly registered in the class instance.  This is necessary because
     when method decorators run, the class does not exist yet, so they
     temporarily store their information into a module global.  Application of
     this class decorator copies that global data to the class instance and
     clears the global.
 
     Obviously, this mechanism is not thread-safe, which means that the
     *creation* of subclasses of Magic should only be done in a single-thread
     context.  Instantiation of the classes has no restrictions.  Given that
     these classes are typically created at IPython startup time and before user
     application code becomes active, in practice this should not pose any
     problems.
     """
     cls.registered = True
     cls.magics = dict(line = magics['line'],
                       cell = magics['cell'])
     magics['line'] = {}
     magics['cell'] = {}
     return cls
 
 
 def record_magic(dct, magic_kind, magic_name, func):
     """Utility function to store a function as a magic of a specific kind.
 
     Parameters
     ----------
     dct : dict
         A dictionary with 'line' and 'cell' subdicts.
     magic_kind : str
         Kind of magic to be stored.
     magic_name : str
         Key to store the magic as.
     func : function
         Callable object to store.
     """
     if magic_kind == 'line_cell':
         dct['line'][magic_name] = dct['cell'][magic_name] = func
     else:
         dct[magic_kind][magic_name] = func
 
 
 def validate_type(magic_kind):
     """Ensure that the given magic_kind is valid.
 
     Check that the given magic_kind is one of the accepted spec types (stored
     in the global `magic_spec`), raise ValueError otherwise.
     """
     if magic_kind not in magic_spec:
         raise ValueError('magic_kind must be one of %s, %s given' %
                          magic_kinds, magic_kind)
 
 
 # The docstrings for the decorator below will be fairly similar for the two
 # types (method and function), so we generate them here once and reuse the
 # templates below.
 _docstring_template = \
 """Decorate the given {0} as {1} magic.
 
 The decorator can be used with or without arguments, as follows.
 
 i) without arguments: it will create a {1} magic named as the {0} being
 decorated::
 
     @deco
     def foo(...)
 
 will create a {1} magic named `foo`.
 
 ii) with one string argument: which will be used as the actual name of the
 resulting magic::
 
     @deco('bar')
     def foo(...)
 
 will create a {1} magic named `bar`.
 
 To register a class magic use ``Interactiveshell.register_magic(class or instance)``.
 """
 
 # These two are decorator factories.  While they are conceptually very similar,
 # there are enough differences in the details that it's simpler to have them
 # written as completely standalone functions rather than trying to share code
 # and make a single one with convoluted logic.
 
 def _method_magic_marker(magic_kind):
     """Decorator factory for methods in Magics subclasses.
     """
 
     validate_type(magic_kind)
 
     # This is a closure to capture the magic_kind.  We could also use a class,
     # but it's overkill for just that one bit of state.
     def magic_deco(arg):
         if callable(arg):
             # "Naked" decorator call (just @foo, no args)
             func = arg
             name = func.__name__
             retval = arg
             record_magic(magics, magic_kind, name, name)
         elif isinstance(arg, str):
             # Decorator called with arguments (@foo('bar'))
             name = arg
             def mark(func, *a, **kw):
                 record_magic(magics, magic_kind, name, func.__name__)
                 return func
             retval = mark
         else:
             raise TypeError("Decorator can only be called with "
                             "string or function")
         return retval
 
     # Ensure the resulting decorator has a usable docstring
     magic_deco.__doc__ = _docstring_template.format('method', magic_kind)
     return magic_deco
 
 
 def _function_magic_marker(magic_kind):
     """Decorator factory for standalone functions.
     """
     validate_type(magic_kind)
     
     # This is a closure to capture the magic_kind.  We could also use a class,
     # but it's overkill for just that one bit of state.
     def magic_deco(arg):
         # Find get_ipython() in the caller's namespace
         caller = sys._getframe(1)
         for ns in ['f_locals', 'f_globals', 'f_builtins']:
             get_ipython = getattr(caller, ns).get('get_ipython')
             if get_ipython is not None:
                 break
         else:
             raise NameError('Decorator can only run in context where '
                             '`get_ipython` exists')
 
         ip = get_ipython()
 
         if callable(arg):
             # "Naked" decorator call (just @foo, no args)
             func = arg
             name = func.__name__
             ip.register_magic_function(func, magic_kind, name)
             retval = arg
         elif isinstance(arg, str):
             # Decorator called with arguments (@foo('bar'))
             name = arg
             def mark(func, *a, **kw):
                 ip.register_magic_function(func, magic_kind, name)
                 return func
             retval = mark
         else:
             raise TypeError("Decorator can only be called with "
                              "string or function")
         return retval
 
     # Ensure the resulting decorator has a usable docstring
     ds = _docstring_template.format('function', magic_kind)
 
     ds += dedent("""
     Note: this decorator can only be used in a context where IPython is already
     active, so that the `get_ipython()` call succeeds.  You can therefore use
     it in your startup files loaded after IPython initializes, but *not* in the
     IPython configuration file itself, which is executed before IPython is
     fully up and running.  Any file located in the `startup` subdirectory of
     your configuration profile will be OK in this sense.
     """)
     
     magic_deco.__doc__ = ds
     return magic_deco
 
 
 MAGIC_NO_VAR_EXPAND_ATTR = "_ipython_magic_no_var_expand"
-MAGIC_OUTPUT_CAN_BE_DISABLED = "_ipython_magic_output_can_be_disabled"
+MAGIC_OUTPUT_CAN_BE_SILENCED = "_ipython_magic_output_can_be_silenced"
 
 
 def no_var_expand(magic_func):
     """Mark a magic function as not needing variable expansion
 
     By default, IPython interprets `{a}` or `$a` in the line passed to magics
     as variables that should be interpolated from the interactive namespace
     before passing the line to the magic function.
     This is not always desirable, e.g. when the magic executes Python code
     (%timeit, %time, etc.).
     Decorate magics with `@no_var_expand` to opt-out of variable expansion.
 
     .. versionadded:: 7.3
     """
     setattr(magic_func, MAGIC_NO_VAR_EXPAND_ATTR, True)
     return magic_func
 
 
-def output_can_be_disabled(magic_func):
-    """Mark a magic function so its output may be disabled.
+def output_can_be_silenced(magic_func):
+    """Mark a magic function so its output may be silenced.
 
-    The output is disabled if the Python expression used as a parameter of
+    The output is silenced if the Python expression used as a parameter of
     the magic ends in a semicolon, not counting a Python comment that can
-    follows it.
+    follow it.
     """
-    setattr(magic_func, MAGIC_OUTPUT_CAN_BE_DISABLED, True)
+    setattr(magic_func, MAGIC_OUTPUT_CAN_BE_SILENCED, True)
     return magic_func
 
 # Create the actual decorators for public use
 
 # These three are used to decorate methods in class definitions
 line_magic = _method_magic_marker('line')
 cell_magic = _method_magic_marker('cell')
 line_cell_magic = _method_magic_marker('line_cell')
 
 # These three decorate standalone functions and perform the decoration
 # immediately.  They can only run where get_ipython() works
 register_line_magic = _function_magic_marker('line')
 register_cell_magic = _function_magic_marker('cell')
 register_line_cell_magic = _function_magic_marker('line_cell')
 
 #-----------------------------------------------------------------------------
 # Core Magic classes
 #-----------------------------------------------------------------------------
 
 class MagicsManager(Configurable):
     """Object that handles all magic-related functionality for IPython.
     """
     # Non-configurable class attributes
 
     # A two-level dict, first keyed by magic type, then by magic function, and
     # holding the actual callable object as value.  This is the dict used for
     # magic function dispatch
     magics = Dict()
     lazy_magics = Dict(
         help="""
     Mapping from magic names to modules to load.
 
     This can be used in IPython/IPykernel configuration to declare lazy magics
     that will only be imported/registered on first use.
 
     For example::
 
         c.MagicsManager.lazy_magics = {
           "my_magic": "slow.to.import",
           "my_other_magic": "also.slow",
         }
 
     On first invocation of `%my_magic`, `%%my_magic`, `%%my_other_magic` or
     `%%my_other_magic`, the corresponding module will be loaded as an ipython
     extensions as if you had previously done `%load_ext ipython`.
 
     Magics names should be without percent(s) as magics can be both cell
     and line magics.
 
     Lazy loading happen relatively late in execution process, and
     complex extensions that manipulate Python/IPython internal state or global state
     might not support lazy loading.
     """
     ).tag(
         config=True,
     )
 
     # A registry of the original objects that we've been given holding magics.
     registry = Dict()
 
     shell = Instance('IPython.core.interactiveshell.InteractiveShellABC', allow_none=True)
 
     auto_magic = Bool(True, help=
         "Automatically call line magics without requiring explicit % prefix"
     ).tag(config=True)
     @observe('auto_magic')
     def _auto_magic_changed(self, change):
         self.shell.automagic = change['new']
     
     _auto_status = [
         'Automagic is OFF, % prefix IS needed for line magics.',
         'Automagic is ON, % prefix IS NOT needed for line magics.']
 
     user_magics = Instance('IPython.core.magics.UserMagics', allow_none=True)
 
     def __init__(self, shell=None, config=None, user_magics=None, **traits):
 
         super(MagicsManager, self).__init__(shell=shell, config=config,
                                            user_magics=user_magics, **traits)
         self.magics = dict(line={}, cell={})
         # Let's add the user_magics to the registry for uniformity, so *all*
         # registered magic containers can be found there.
         self.registry[user_magics.__class__.__name__] = user_magics
 
     def auto_status(self):
         """Return descriptive string with automagic status."""
         return self._auto_status[self.auto_magic]
     
     def lsmagic(self):
         """Return a dict of currently available magic functions.
 
         The return dict has the keys 'line' and 'cell', corresponding to the
         two types of magics we support.  Each value is a list of names.
         """
         return self.magics
 
     def lsmagic_docs(self, brief=False, missing=''):
         """Return dict of documentation of magic functions.
 
         The return dict has the keys 'line' and 'cell', corresponding to the
         two types of magics we support. Each value is a dict keyed by magic
         name whose value is the function docstring. If a docstring is
         unavailable, the value of `missing` is used instead.
 
         If brief is True, only the first line of each docstring will be returned.
         """
         docs = {}
         for m_type in self.magics:
             m_docs = {}
             for m_name, m_func in self.magics[m_type].items():
                 if m_func.__doc__:
                     if brief:
                         m_docs[m_name] = m_func.__doc__.split('\n', 1)[0]
                     else:
                         m_docs[m_name] = m_func.__doc__.rstrip()
                 else:
                     m_docs[m_name] = missing
             docs[m_type] = m_docs
         return docs
 
     def register_lazy(self, name: str, fully_qualified_name: str):
         """
         Lazily register a magic via an extension.
 
 
         Parameters
         ----------
         name : str
             Name of the magic you wish to register.
         fully_qualified_name :
             Fully qualified name of the module/submodule that should be loaded
             as an extensions when the magic is first called.
             It is assumed that loading this extensions will register the given
             magic.
         """
 
         self.lazy_magics[name] = fully_qualified_name
 
     def register(self, *magic_objects):
         """Register one or more instances of Magics.
 
         Take one or more classes or instances of classes that subclass the main
         `core.Magic` class, and register them with IPython to use the magic
         functions they provide.  The registration process will then ensure that
         any methods that have decorated to provide line and/or cell magics will
         be recognized with the `%x`/`%%x` syntax as a line/cell magic
         respectively.
 
         If classes are given, they will be instantiated with the default
         constructor.  If your classes need a custom constructor, you should
         instanitate them first and pass the instance.
 
         The provided arguments can be an arbitrary mix of classes and instances.
 
         Parameters
         ----------
         *magic_objects : one or more classes or instances
         """
         # Start by validating them to ensure they have all had their magic
         # methods registered at the instance level
         for m in magic_objects:
             if not m.registered:
                 raise ValueError("Class of magics %r was constructed without "
                                  "the @register_magics class decorator")
             if isinstance(m, type):
                 # If we're given an uninstantiated class
                 m = m(shell=self.shell)
 
             # Now that we have an instance, we can register it and update the
             # table of callables
             self.registry[m.__class__.__name__] = m
             for mtype in magic_kinds:
                 self.magics[mtype].update(m.magics[mtype])
 
     def register_function(self, func, magic_kind='line', magic_name=None):
         """Expose a standalone function as magic function for IPython.
 
         This will create an IPython magic (line, cell or both) from a
         standalone function.  The functions should have the following
         signatures:
 
         * For line magics: `def f(line)`
         * For cell magics: `def f(line, cell)`
         * For a function that does both: `def f(line, cell=None)`
 
         In the latter case, the function will be called with `cell==None` when
         invoked as `%f`, and with cell as a string when invoked as `%%f`.
 
         Parameters
         ----------
         func : callable
             Function to be registered as a magic.
         magic_kind : str
             Kind of magic, one of 'line', 'cell' or 'line_cell'
         magic_name : optional str
             If given, the name the magic will have in the IPython namespace.  By
             default, the name of the function itself is used.
         """
 
         # Create the new method in the user_magics and register it in the
         # global table
         validate_type(magic_kind)
         magic_name = func.__name__ if magic_name is None else magic_name
         setattr(self.user_magics, magic_name, func)
         record_magic(self.magics, magic_kind, magic_name, func)
 
     def register_alias(self, alias_name, magic_name, magic_kind='line', magic_params=None):
         """Register an alias to a magic function.
 
         The alias is an instance of :class:`MagicAlias`, which holds the
         name and kind of the magic it should call. Binding is done at
         call time, so if the underlying magic function is changed the alias
         will call the new function.
 
         Parameters
         ----------
         alias_name : str
             The name of the magic to be registered.
         magic_name : str
             The name of an existing magic.
         magic_kind : str
             Kind of magic, one of 'line' or 'cell'
         """
 
         # `validate_type` is too permissive, as it allows 'line_cell'
         # which we do not handle.
         if magic_kind not in magic_kinds:
             raise ValueError('magic_kind must be one of %s, %s given' %
                              magic_kinds, magic_kind)
 
         alias = MagicAlias(self.shell, magic_name, magic_kind, magic_params)
         setattr(self.user_magics, alias_name, alias)
         record_magic(self.magics, magic_kind, alias_name, alias)
 
 # Key base class that provides the central functionality for magics.
 
 
 class Magics(Configurable):
     """Base class for implementing magic functions.
 
     Shell functions which can be reached as %function_name. All magic
     functions should accept a string, which they can parse for their own
     needs. This can make some functions easier to type, eg `%cd ../`
     vs. `%cd("../")`
 
     Classes providing magic functions need to subclass this class, and they
     MUST:
 
     - Use the method decorators `@line_magic` and `@cell_magic` to decorate
       individual methods as magic functions, AND
 
     - Use the class decorator `@magics_class` to ensure that the magic
       methods are properly registered at the instance level upon instance
       initialization.
 
     See :mod:`magic_functions` for examples of actual implementation classes.
     """
     # Dict holding all command-line options for each magic.
     options_table = None
     # Dict for the mapping of magic names to methods, set by class decorator
     magics = None
     # Flag to check that the class decorator was properly applied
     registered = False
     # Instance of IPython shell
     shell = None
 
     def __init__(self, shell=None, **kwargs):
         if not(self.__class__.registered):
             raise ValueError('Magics subclass without registration - '
                              'did you forget to apply @magics_class?')
         if shell is not None:
             if hasattr(shell, 'configurables'):
                 shell.configurables.append(self)
             if hasattr(shell, 'config'):
                 kwargs.setdefault('parent', shell)
 
         self.shell = shell
         self.options_table = {}
         # The method decorators are run when the instance doesn't exist yet, so
         # they can only record the names of the methods they are supposed to
         # grab.  Only now, that the instance exists, can we create the proper
         # mapping to bound methods.  So we read the info off the original names
         # table and replace each method name by the actual bound method.
         # But we mustn't clobber the *class* mapping, in case of multiple instances.
         class_magics = self.magics
         self.magics = {}
         for mtype in magic_kinds:
             tab = self.magics[mtype] = {}
             cls_tab = class_magics[mtype]
             for magic_name, meth_name in cls_tab.items():
                 if isinstance(meth_name, str):
                     # it's a method name, grab it
                     tab[magic_name] = getattr(self, meth_name)
                 else:
                     # it's the real thing
                     tab[magic_name] = meth_name
         # Configurable **needs** to be initiated at the end or the config
         # magics get screwed up.
         super(Magics, self).__init__(**kwargs)
 
     def arg_err(self,func):
         """Print docstring if incorrect arguments were passed"""
         print('Error in arguments:')
         print(oinspect.getdoc(func))
 
     def format_latex(self, strng):
         """Format a string for latex inclusion."""
 
         # Characters that need to be escaped for latex:
         escape_re = re.compile(r'(%|_|\$|#|&)',re.MULTILINE)
         # Magic command names as headers:
         cmd_name_re = re.compile(r'^(%s.*?):' % ESC_MAGIC,
                                  re.MULTILINE)
         # Magic commands
         cmd_re = re.compile(r'(?P<cmd>%s.+?\b)(?!\}\}:)' % ESC_MAGIC,
                             re.MULTILINE)
         # Paragraph continue
         par_re = re.compile(r'\\$',re.MULTILINE)
 
         # The "\n" symbol
         newline_re = re.compile(r'\\n')
 
         # Now build the string for output:
         #strng = cmd_name_re.sub(r'\n\\texttt{\\textsl{\\large \1}}:',strng)
         strng = cmd_name_re.sub(r'\n\\bigskip\n\\texttt{\\textbf{ \1}}:',
                                 strng)
         strng = cmd_re.sub(r'\\texttt{\g<cmd>}',strng)
         strng = par_re.sub(r'\\\\',strng)
         strng = escape_re.sub(r'\\\1',strng)
         strng = newline_re.sub(r'\\textbackslash{}n',strng)
         return strng
 
     def parse_options(self, arg_str, opt_str, *long_opts, **kw):
         """Parse options passed to an argument string.
 
         The interface is similar to that of :func:`getopt.getopt`, but it
         returns a :class:`~IPython.utils.struct.Struct` with the options as keys
         and the stripped argument string still as a string.
 
         arg_str is quoted as a true sys.argv vector by using shlex.split.
         This allows us to easily expand variables, glob files, quote
         arguments, etc.
 
         Parameters
         ----------
         arg_str : str
             The arguments to parse.
         opt_str : str
             The options specification.
         mode : str, default 'string'
             If given as 'list', the argument string is returned as a list (split
             on whitespace) instead of a string.
         list_all : bool, default False
             Put all option values in lists. Normally only options
             appearing more than once are put in a list.
         posix : bool, default True
             Whether to split the input line in POSIX mode or not, as per the
             conventions outlined in the :mod:`shlex` module from the standard
             library.
         """
 
         # inject default options at the beginning of the input line
         caller = sys._getframe(1).f_code.co_name
         arg_str = '%s %s' % (self.options_table.get(caller,''),arg_str)
 
         mode = kw.get('mode','string')
         if mode not in ['string','list']:
             raise ValueError('incorrect mode given: %s' % mode)
         # Get options
         list_all = kw.get('list_all',0)
         posix = kw.get('posix', os.name == 'posix')
         strict = kw.get('strict', True)
 
         preserve_non_opts = kw.get("preserve_non_opts", False)
         remainder_arg_str = arg_str
 
         # Check if we have more than one argument to warrant extra processing:
         odict = {}  # Dictionary with options
         args = arg_str.split()
         if len(args) >= 1:
             # If the list of inputs only has 0 or 1 thing in it, there's no
             # need to look for options
             argv = arg_split(arg_str, posix, strict)
             # Do regular option processing
             try:
                 opts,args = getopt(argv, opt_str, long_opts)
             except GetoptError as e:
                 raise UsageError(
                     '%s ( allowed: "%s" %s)' % (e.msg, opt_str, " ".join(long_opts))
                 ) from e
             for o, a in opts:
                 if mode == "string" and preserve_non_opts:
                     # remove option-parts from the original args-string and preserve remaining-part.
                     # This relies on the arg_split(...) and getopt(...)'s impl spec, that the parsed options are
                     # returned in the original order.
                     remainder_arg_str = remainder_arg_str.replace(o, "", 1).replace(
                         a, "", 1
                     )
                 if o.startswith("--"):
                     o = o[2:]
                 else:
                     o = o[1:]
                 try:
                     odict[o].append(a)
                 except AttributeError:
                     odict[o] = [odict[o],a]
                 except KeyError:
                     if list_all:
                         odict[o] = [a]
                     else:
                         odict[o] = a
 
         # Prepare opts,args for return
         opts = Struct(odict)
         if mode == 'string':
             if preserve_non_opts:
                 args = remainder_arg_str.lstrip()
             else:
                 args = " ".join(args)
 
         return opts,args
 
     def default_option(self, fn, optstr):
         """Make an entry in the options_table for fn, with value optstr"""
 
         if fn not in self.lsmagic():
             error("%s is not a magic function" % fn)
         self.options_table[fn] = optstr
 
 
 class MagicAlias(object):
     """An alias to another magic function.
 
     An alias is determined by its magic name and magic kind. Lookup
     is done at call time, so if the underlying magic changes the alias
     will call the new function.
 
     Use the :meth:`MagicsManager.register_alias` method or the
     `%alias_magic` magic function to create and register a new alias.
     """
     def __init__(self, shell, magic_name, magic_kind, magic_params=None):
         self.shell = shell
         self.magic_name = magic_name
         self.magic_params = magic_params
         self.magic_kind = magic_kind
 
         self.pretty_target = '%s%s' % (magic_escapes[self.magic_kind], self.magic_name)
         self.__doc__ = "Alias for `%s`." % self.pretty_target
 
         self._in_call = False
 
     def __call__(self, *args, **kwargs):
         """Call the magic alias."""
         fn = self.shell.find_magic(self.magic_name, self.magic_kind)
         if fn is None:
             raise UsageError("Magic `%s` not found." % self.pretty_target)
 
         # Protect against infinite recursion.
         if self._in_call:
             raise UsageError("Infinite recursion detected; "
                              "magic aliases cannot call themselves.")
         self._in_call = True
         try:
             if self.magic_params:
                 args_list = list(args)
                 args_list[0] = self.magic_params + " " + args[0]
                 args = tuple(args_list)
             return fn(*args, **kwargs)
         finally:
             self._in_call = False

IPython/core/magics/execution.py

@@ -1,1512 +1,1512 b''
 # -*- coding: utf-8 -*-
 """Implementation of execution-related magic functions."""
 
 # Copyright (c) IPython Development Team.
 # Distributed under the terms of the Modified BSD License.
 
 
 import ast
 import bdb
 import builtins as builtin_mod
 import cProfile as profile
 import gc
 import itertools
 import math
 import os
 import pstats
 import re
 import shlex
 import sys
 import time
 import timeit
 from ast import Module
 from io import StringIO
 from logging import error
 from pathlib import Path
 from pdb import Restart
 from warnings import warn
 
 from IPython.core import magic_arguments, oinspect, page
 from IPython.core.error import UsageError
 from IPython.core.macro import Macro
 from IPython.core.magic import (
     Magics,
     cell_magic,
     line_cell_magic,
     line_magic,
     magics_class,
     needs_local_scope,
     no_var_expand,
-    output_can_be_disabled,
+    output_can_be_silenced,
     on_off,
 )
 from IPython.testing.skipdoctest import skip_doctest
 from IPython.utils.capture import capture_output
 from IPython.utils.contexts import preserve_keys
 from IPython.utils.ipstruct import Struct
 from IPython.utils.module_paths import find_mod
 from IPython.utils.path import get_py_filename, shellglob
 from IPython.utils.timing import clock, clock2
 
 #-----------------------------------------------------------------------------
 # Magic implementation classes
 #-----------------------------------------------------------------------------
 
 
 class TimeitResult(object):
     """
     Object returned by the timeit magic with info about the run.
 
     Contains the following attributes :
 
     loops: (int) number of loops done per measurement
     repeat: (int) number of times the measurement has been repeated
     best: (float) best execution time / number
     all_runs: (list of float) execution time of each run (in s)
     compile_time: (float) time of statement compilation (s)
 
     """
     def __init__(self, loops, repeat, best, worst, all_runs, compile_time, precision):
         self.loops = loops
         self.repeat = repeat
         self.best = best
         self.worst = worst
         self.all_runs = all_runs
         self.compile_time = compile_time
         self._precision = precision
         self.timings = [ dt / self.loops for dt in all_runs]
 
     @property
     def average(self):
         return math.fsum(self.timings) / len(self.timings)
 
     @property
     def stdev(self):
         mean = self.average
         return (math.fsum([(x - mean) ** 2 for x in self.timings]) / len(self.timings)) ** 0.5
 
     def __str__(self):
         pm = '+-'
         if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
             try:
                 u'\xb1'.encode(sys.stdout.encoding)
                 pm = u'\xb1'
             except:
                 pass
         return "{mean} {pm} {std} per loop (mean {pm} std. dev. of {runs} run{run_plural}, {loops:,} loop{loop_plural} each)".format(
             pm=pm,
             runs=self.repeat,
             loops=self.loops,
             loop_plural="" if self.loops == 1 else "s",
             run_plural="" if self.repeat == 1 else "s",
             mean=_format_time(self.average, self._precision),
             std=_format_time(self.stdev, self._precision),
         )
 
     def _repr_pretty_(self, p , cycle):
         unic = self.__str__()
         p.text(u'<TimeitResult : '+unic+u'>')
 
 
 class TimeitTemplateFiller(ast.NodeTransformer):
     """Fill in the AST template for timing execution.
 
     This is quite closely tied to the template definition, which is in
     :meth:`ExecutionMagics.timeit`.
     """
     def __init__(self, ast_setup, ast_stmt):
         self.ast_setup = ast_setup
         self.ast_stmt = ast_stmt
 
     def visit_FunctionDef(self, node):
         "Fill in the setup statement"
         self.generic_visit(node)
         if node.name == "inner":
             node.body[:1] = self.ast_setup.body
 
         return node
 
     def visit_For(self, node):
         "Fill in the statement to be timed"
         if getattr(getattr(node.body[0], 'value', None), 'id', None) == 'stmt':
             node.body = self.ast_stmt.body
         return node
 
 
 class Timer(timeit.Timer):
     """Timer class that explicitly uses self.inner
     
     which is an undocumented implementation detail of CPython,
     not shared by PyPy.
     """
     # Timer.timeit copied from CPython 3.4.2
     def timeit(self, number=timeit.default_number):
         """Time 'number' executions of the main statement.
 
         To be precise, this executes the setup statement once, and
         then returns the time it takes to execute the main statement
         a number of times, as a float measured in seconds.  The
         argument is the number of times through the loop, defaulting
         to one million.  The main statement, the setup statement and
         the timer function to be used are passed to the constructor.
         """
         it = itertools.repeat(None, number)
         gcold = gc.isenabled()
         gc.disable()
         try:
             timing = self.inner(it, self.timer)
         finally:
             if gcold:
                 gc.enable()
         return timing
 
 
 @magics_class
 class ExecutionMagics(Magics):
     """Magics related to code execution, debugging, profiling, etc.
 
     """
 
     def __init__(self, shell):
         super(ExecutionMagics, self).__init__(shell)
         # Default execution function used to actually run user code.
         self.default_runner = None
 
     @skip_doctest
     @no_var_expand
     @line_cell_magic
     def prun(self, parameter_s='', cell=None):
 
         """Run a statement through the python code profiler.
 
         Usage, in line mode:
           %prun [options] statement
 
         Usage, in cell mode:
           %%prun [options] [statement]
           code...
           code...
 
         In cell mode, the additional code lines are appended to the (possibly
         empty) statement in the first line.  Cell mode allows you to easily
         profile multiline blocks without having to put them in a separate
         function.
 
         The given statement (which doesn't require quote marks) is run via the
         python profiler in a manner similar to the profile.run() function.
         Namespaces are internally managed to work correctly; profile.run
         cannot be used in IPython because it makes certain assumptions about
         namespaces which do not hold under IPython.
 
         Options:
 
         -l <limit>
           you can place restrictions on what or how much of the
           profile gets printed. The limit value can be:
 
              * A string: only information for function names containing this string
                is printed.
 
              * An integer: only these many lines are printed.
 
              * A float (between 0 and 1): this fraction of the report is printed
                (for example, use a limit of 0.4 to see the topmost 40% only).
 
           You can combine several limits with repeated use of the option. For
           example, ``-l __init__ -l 5`` will print only the topmost 5 lines of
           information about class constructors.
 
         -r
           return the pstats.Stats object generated by the profiling. This
           object has all the information about the profile in it, and you can
           later use it for further analysis or in other functions.
 
         -s <key>
           sort profile by given key. You can provide more than one key
           by using the option several times: '-s key1 -s key2 -s key3...'. The
           default sorting key is 'time'.
 
           The following is copied verbatim from the profile documentation
           referenced below:
 
           When more than one key is provided, additional keys are used as
           secondary criteria when the there is equality in all keys selected
           before them.
 
           Abbreviations can be used for any key names, as long as the
           abbreviation is unambiguous.  The following are the keys currently
           defined:
 
           ============  =====================
           Valid Arg     Meaning
           ============  =====================
           "calls"       call count
           "cumulative"  cumulative time
           "file"        file name
           "module"      file name
           "pcalls"      primitive call count
           "line"        line number
           "name"        function name
           "nfl"         name/file/line
           "stdname"     standard name
           "time"        internal time
           ============  =====================
 
           Note that all sorts on statistics are in descending order (placing
           most time consuming items first), where as name, file, and line number
           searches are in ascending order (i.e., alphabetical). The subtle
           distinction between "nfl" and "stdname" is that the standard name is a
           sort of the name as printed, which means that the embedded line
           numbers get compared in an odd way.  For example, lines 3, 20, and 40
           would (if the file names were the same) appear in the string order
           "20" "3" and "40".  In contrast, "nfl" does a numeric compare of the
           line numbers.  In fact, sort_stats("nfl") is the same as
           sort_stats("name", "file", "line").
 
         -T <filename>
           save profile results as shown on screen to a text
           file. The profile is still shown on screen.
 
         -D <filename>
           save (via dump_stats) profile statistics to given
           filename. This data is in a format understood by the pstats module, and
           is generated by a call to the dump_stats() method of profile
           objects. The profile is still shown on screen.
 
         -q
           suppress output to the pager.  Best used with -T and/or -D above.
 
         If you want to run complete programs under the profiler's control, use
         ``%run -p [prof_opts] filename.py [args to program]`` where prof_opts
         contains profiler specific options as described here.
 
         You can read the complete documentation for the profile module with::
 
           In [1]: import profile; profile.help()
 
         .. versionchanged:: 7.3
             User variables are no longer expanded,
             the magic line is always left unmodified.
 
         """
         opts, arg_str = self.parse_options(parameter_s, 'D:l:rs:T:q',
                                            list_all=True, posix=False)
         if cell is not None:
             arg_str += '\n' + cell
         arg_str = self.shell.transform_cell(arg_str)
         return self._run_with_profiler(arg_str, opts, self.shell.user_ns)
 
     def _run_with_profiler(self, code, opts, namespace):
         """
         Run `code` with profiler.  Used by ``%prun`` and ``%run -p``.
 
         Parameters
         ----------
         code : str
             Code to be executed.
         opts : Struct
             Options parsed by `self.parse_options`.
         namespace : dict
             A dictionary for Python namespace (e.g., `self.shell.user_ns`).
 
         """
 
         # Fill default values for unspecified options:
         opts.merge(Struct(D=[''], l=[], s=['time'], T=['']))
 
         prof = profile.Profile()
         try:
             prof = prof.runctx(code, namespace, namespace)
             sys_exit = ''
         except SystemExit:
             sys_exit = """*** SystemExit exception caught in code being profiled."""
 
         stats = pstats.Stats(prof).strip_dirs().sort_stats(*opts.s)
 
         lims = opts.l
         if lims:
             lims = []  # rebuild lims with ints/floats/strings
             for lim in opts.l:
                 try:
                     lims.append(int(lim))
                 except ValueError:
                     try:
                         lims.append(float(lim))
                     except ValueError:
                         lims.append(lim)
 
         # Trap output.
         stdout_trap = StringIO()
         stats_stream = stats.stream
         try:
             stats.stream = stdout_trap
             stats.print_stats(*lims)
         finally:
             stats.stream = stats_stream
 
         output = stdout_trap.getvalue()
         output = output.rstrip()
 
         if 'q' not in opts:
             page.page(output)
         print(sys_exit, end=' ')
 
         dump_file = opts.D[0]
         text_file = opts.T[0]
         if dump_file:
             prof.dump_stats(dump_file)
             print(
                 f"\n*** Profile stats marshalled to file {repr(dump_file)}.{sys_exit}"
             )
         if text_file:
             pfile = Path(text_file)
             pfile.touch(exist_ok=True)
             pfile.write_text(output, encoding="utf-8")
 
             print(
                 f"\n*** Profile printout saved to text file {repr(text_file)}.{sys_exit}"
             )
 
         if 'r' in opts:
             return stats
 
         return None
 
     @line_magic
     def pdb(self, parameter_s=''):
         """Control the automatic calling of the pdb interactive debugger.
 
         Call as '%pdb on', '%pdb 1', '%pdb off' or '%pdb 0'. If called without
         argument it works as a toggle.
 
         When an exception is triggered, IPython can optionally call the
         interactive pdb debugger after the traceback printout. %pdb toggles
         this feature on and off.
 
         The initial state of this feature is set in your configuration
         file (the option is ``InteractiveShell.pdb``).
 
         If you want to just activate the debugger AFTER an exception has fired,
         without having to type '%pdb on' and rerunning your code, you can use
         the %debug magic."""
 
         par = parameter_s.strip().lower()
 
         if par:
             try:
                 new_pdb = {'off':0,'0':0,'on':1,'1':1}[par]
             except KeyError:
                 print ('Incorrect argument. Use on/1, off/0, '
                        'or nothing for a toggle.')
                 return
         else:
             # toggle
             new_pdb = not self.shell.call_pdb
 
         # set on the shell
         self.shell.call_pdb = new_pdb
         print('Automatic pdb calling has been turned',on_off(new_pdb))
 
     @magic_arguments.magic_arguments()
     @magic_arguments.argument('--breakpoint', '-b', metavar='FILE:LINE',
         help="""
         Set break point at LINE in FILE.
         """
     )
     @magic_arguments.argument('statement', nargs='*',
         help="""
         Code to run in debugger.
         You can omit this in cell magic mode.
         """
     )
     @no_var_expand
     @line_cell_magic
     def debug(self, line='', cell=None):
         """Activate the interactive debugger.
 
         This magic command support two ways of activating debugger.
         One is to activate debugger before executing code.  This way, you
         can set a break point, to step through the code from the point.
         You can use this mode by giving statements to execute and optionally
         a breakpoint.
 
         The other one is to activate debugger in post-mortem mode.  You can
         activate this mode simply running %debug without any argument.
         If an exception has just occurred, this lets you inspect its stack
         frames interactively.  Note that this will always work only on the last
         traceback that occurred, so you must call this quickly after an
         exception that you wish to inspect has fired, because if another one
         occurs, it clobbers the previous one.
 
         If you want IPython to automatically do this on every exception, see
         the %pdb magic for more details.
 
         .. versionchanged:: 7.3
             When running code, user variables are no longer expanded,
             the magic line is always left unmodified.
 
         """
         args = magic_arguments.parse_argstring(self.debug, line)
 
         if not (args.breakpoint or args.statement or cell):
             self._debug_post_mortem()
         elif not (args.breakpoint or cell):
             # If there is no breakpoints, the line is just code to execute
             self._debug_exec(line, None)
         else:
             # Here we try to reconstruct the code from the output of
             # parse_argstring. This might not work if the code has spaces
             # For example this fails for `print("a b")`
             code = "\n".join(args.statement)
             if cell:
                 code += "\n" + cell
             self._debug_exec(code, args.breakpoint)
 
     def _debug_post_mortem(self):
         self.shell.debugger(force=True)
 
     def _debug_exec(self, code, breakpoint):
         if breakpoint:
             (filename, bp_line) = breakpoint.rsplit(':', 1)
             bp_line = int(bp_line)
         else:
             (filename, bp_line) = (None, None)
         self._run_with_debugger(code, self.shell.user_ns, filename, bp_line)
 
     @line_magic
     def tb(self, s):
         """Print the last traceback.
 
         Optionally, specify an exception reporting mode, tuning the
         verbosity of the traceback. By default the currently-active exception
         mode is used. See %xmode for changing exception reporting modes.
 
         Valid modes: Plain, Context, Verbose, and Minimal.
         """
         interactive_tb = self.shell.InteractiveTB
         if s:
             # Switch exception reporting mode for this one call.
             # Ensure it is switched back.
             def xmode_switch_err(name):
                 warn('Error changing %s exception modes.\n%s' %
                     (name,sys.exc_info()[1]))
 
             new_mode = s.strip().capitalize()
             original_mode = interactive_tb.mode
             try:
                 try:
                     interactive_tb.set_mode(mode=new_mode)
                 except Exception:
                     xmode_switch_err('user')
                 else:
                     self.shell.showtraceback()
             finally:
                 interactive_tb.set_mode(mode=original_mode)
         else:
             self.shell.showtraceback()
 
     @skip_doctest
     @line_magic
     def run(self, parameter_s='', runner=None,
                   file_finder=get_py_filename):
         """Run the named file inside IPython as a program.
 
         Usage::
 
           %run [-n -i -e -G]
                [( -t [-N<N>] | -d [-b<N>] | -p [profile options] )]
                ( -m mod | filename ) [args]
 
         The filename argument should be either a pure Python script (with
         extension ``.py``), or a file with custom IPython syntax (such as
         magics). If the latter, the file can be either a script with ``.ipy``
         extension, or a Jupyter notebook with ``.ipynb`` extension. When running
         a Jupyter notebook, the output from print statements and other
         displayed objects will appear in the terminal (even matplotlib figures
         will open, if a terminal-compliant backend is being used). Note that,
         at the system command line, the ``jupyter run`` command offers similar
         functionality for executing notebooks (albeit currently with some
         differences in supported options).
 
         Parameters after the filename are passed as command-line arguments to
         the program (put in sys.argv). Then, control returns to IPython's
         prompt.
 
         This is similar to running at a system prompt ``python file args``,
         but with the advantage of giving you IPython's tracebacks, and of
         loading all variables into your interactive namespace for further use
         (unless -p is used, see below).
 
         The file is executed in a namespace initially consisting only of
         ``__name__=='__main__'`` and sys.argv constructed as indicated. It thus
         sees its environment as if it were being run as a stand-alone program
         (except for sharing global objects such as previously imported
         modules). But after execution, the IPython interactive namespace gets
         updated with all variables defined in the program (except for __name__
         and sys.argv). This allows for very convenient loading of code for
         interactive work, while giving each program a 'clean sheet' to run in.
 
         Arguments are expanded using shell-like glob match.  Patterns
         '*', '?', '[seq]' and '[!seq]' can be used.  Additionally,
         tilde '~' will be expanded into user's home directory.  Unlike
         real shells, quotation does not suppress expansions.  Use
         *two* back slashes (e.g. ``\\\\*``) to suppress expansions.
         To completely disable these expansions, you can use -G flag.
 
         On Windows systems, the use of single quotes `'` when specifying
         a file is not supported. Use double quotes `"`.
 
         Options:
 
         -n
           __name__ is NOT set to '__main__', but to the running file's name
           without extension (as python does under import).  This allows running
           scripts and reloading the definitions in them without calling code
           protected by an ``if __name__ == "__main__"`` clause.
 
         -i
           run the file in IPython's namespace instead of an empty one. This
           is useful if you are experimenting with code written in a text editor
           which depends on variables defined interactively.
 
         -e
           ignore sys.exit() calls or SystemExit exceptions in the script
           being run.  This is particularly useful if IPython is being used to
           run unittests, which always exit with a sys.exit() call.  In such
           cases you are interested in the output of the test results, not in
           seeing a traceback of the unittest module.
 
         -t
           print timing information at the end of the run.  IPython will give
           you an estimated CPU time consumption for your script, which under
           Unix uses the resource module to avoid the wraparound problems of
           time.clock().  Under Unix, an estimate of time spent on system tasks
           is also given (for Windows platforms this is reported as 0.0).
 
         If -t is given, an additional ``-N<N>`` option can be given, where <N>
         must be an integer indicating how many times you want the script to
         run.  The final timing report will include total and per run results.
 
         For example (testing the script uniq_stable.py)::
 
             In [1]: run -t uniq_stable
 
             IPython CPU timings (estimated):
               User  :    0.19597 s.
               System:        0.0 s.
 
             In [2]: run -t -N5 uniq_stable
 
             IPython CPU timings (estimated):
             Total runs performed: 5
               Times :      Total       Per run
               User  :   0.910862 s,  0.1821724 s.
               System:        0.0 s,        0.0 s.
 
         -d
           run your program under the control of pdb, the Python debugger.
           This allows you to execute your program step by step, watch variables,
           etc.  Internally, what IPython does is similar to calling::
 
               pdb.run('execfile("YOURFILENAME")')
 
           with a breakpoint set on line 1 of your file.  You can change the line
           number for this automatic breakpoint to be <N> by using the -bN option
           (where N must be an integer). For example::
 
               %run -d -b40 myscript
 
           will set the first breakpoint at line 40 in myscript.py.  Note that
           the first breakpoint must be set on a line which actually does
           something (not a comment or docstring) for it to stop execution.
 
           Or you can specify a breakpoint in a different file::
 
               %run -d -b myotherfile.py:20 myscript
 
           When the pdb debugger starts, you will see a (Pdb) prompt.  You must
           first enter 'c' (without quotes) to start execution up to the first
           breakpoint.
 
           Entering 'help' gives information about the use of the debugger.  You
           can easily see pdb's full documentation with "import pdb;pdb.help()"
           at a prompt.
 
         -p
           run program under the control of the Python profiler module (which
           prints a detailed report of execution times, function calls, etc).
 
           You can pass other options after -p which affect the behavior of the
           profiler itself. See the docs for %prun for details.
 
           In this mode, the program's variables do NOT propagate back to the
           IPython interactive namespace (because they remain in the namespace
           where the profiler executes them).
 
           Internally this triggers a call to %prun, see its documentation for
           details on the options available specifically for profiling.
 
         There is one special usage for which the text above doesn't apply:
         if the filename ends with .ipy[nb], the file is run as ipython script,
         just as if the commands were written on IPython prompt.
 
         -m
           specify module name to load instead of script path. Similar to
           the -m option for the python interpreter. Use this option last if you
           want to combine with other %run options. Unlike the python interpreter
           only source modules are allowed no .pyc or .pyo files.
           For example::
 
               %run -m example
 
           will run the example module.
 
         -G
           disable shell-like glob expansion of arguments.
 
         """
 
         # Logic to handle issue #3664
         # Add '--' after '-m <module_name>' to ignore additional args passed to a module.
         if '-m' in parameter_s and '--' not in parameter_s:
             argv = shlex.split(parameter_s, posix=(os.name == 'posix'))
             for idx, arg in enumerate(argv):
                 if arg and arg.startswith('-') and arg != '-':
                     if arg == '-m':
                         argv.insert(idx + 2, '--')
                         break
                 else:
                     # Positional arg, break
                     break
             parameter_s = ' '.join(shlex.quote(arg) for arg in argv)
 
         # get arguments and set sys.argv for program to be run.
         opts, arg_lst = self.parse_options(parameter_s,
                                            'nidtN:b:pD:l:rs:T:em:G',
                                            mode='list', list_all=1)
         if "m" in opts:
             modulename = opts["m"][0]
             modpath = find_mod(modulename)
             if modpath is None:
                 msg = '%r is not a valid modulename on sys.path'%modulename
                 raise Exception(msg)
             arg_lst = [modpath] + arg_lst
         try:
             fpath = None # initialize to make sure fpath is in scope later
             fpath = arg_lst[0]
             filename = file_finder(fpath)
         except IndexError as e:
             msg = 'you must provide at least a filename.'
             raise Exception(msg) from e
         except IOError as e:
             try:
                 msg = str(e)
             except UnicodeError:
                 msg = e.message
             if os.name == 'nt' and re.match(r"^'.*'$",fpath):
                 warn('For Windows, use double quotes to wrap a filename: %run "mypath\\myfile.py"')
             raise Exception(msg) from e
         except TypeError:
             if fpath in sys.meta_path:
                 filename = ""
             else:
                 raise
 
         if filename.lower().endswith(('.ipy', '.ipynb')):
             with preserve_keys(self.shell.user_ns, '__file__'):
                 self.shell.user_ns['__file__'] = filename
                 self.shell.safe_execfile_ipy(filename, raise_exceptions=True)
             return
 
         # Control the response to exit() calls made by the script being run
         exit_ignore = 'e' in opts
 
         # Make sure that the running script gets a proper sys.argv as if it
         # were run from a system shell.
         save_argv = sys.argv # save it for later restoring
 
         if 'G' in opts:
             args = arg_lst[1:]
         else:
             # tilde and glob expansion
             args = shellglob(map(os.path.expanduser,  arg_lst[1:]))
 
         sys.argv = [filename] + args  # put in the proper filename
 
         if 'n' in opts:
             name = Path(filename).stem
         else:
             name = '__main__'
 
         if 'i' in opts:
             # Run in user's interactive namespace
             prog_ns = self.shell.user_ns
             __name__save = self.shell.user_ns['__name__']
             prog_ns['__name__'] = name
             main_mod = self.shell.user_module
 
             # Since '%run foo' emulates 'python foo.py' at the cmd line, we must
             # set the __file__ global in the script's namespace
             # TK: Is this necessary in interactive mode?
             prog_ns['__file__'] = filename
         else:
             # Run in a fresh, empty namespace
 
             # The shell MUST hold a reference to prog_ns so after %run
             # exits, the python deletion mechanism doesn't zero it out
             # (leaving dangling references). See interactiveshell for details
             main_mod = self.shell.new_main_mod(filename, name)
             prog_ns = main_mod.__dict__
 
         # pickle fix.  See interactiveshell for an explanation.  But we need to
         # make sure that, if we overwrite __main__, we replace it at the end
         main_mod_name = prog_ns['__name__']
 
         if main_mod_name == '__main__':
             restore_main = sys.modules['__main__']
         else:
             restore_main = False
 
         # This needs to be undone at the end to prevent holding references to
         # every single object ever created.
         sys.modules[main_mod_name] = main_mod
 
         if 'p' in opts or 'd' in opts:
             if 'm' in opts:
                 code = 'run_module(modulename, prog_ns)'
                 code_ns = {
                     'run_module': self.shell.safe_run_module,
                     'prog_ns': prog_ns,
                     'modulename': modulename,
                 }
             else:
                 if 'd' in opts:
                     # allow exceptions to raise in debug mode
                     code = 'execfile(filename, prog_ns, raise_exceptions=True)'
                 else:
                     code = 'execfile(filename, prog_ns)'
                 code_ns = {
                     'execfile': self.shell.safe_execfile,
                     'prog_ns': prog_ns,
                     'filename': get_py_filename(filename),
                 }
 
         try:
             stats = None
             if 'p' in opts:
                 stats = self._run_with_profiler(code, opts, code_ns)
             else:
                 if 'd' in opts:
                     bp_file, bp_line = parse_breakpoint(
                         opts.get('b', ['1'])[0], filename)
                     self._run_with_debugger(
                         code, code_ns, filename, bp_line, bp_file)
                 else:
                     if 'm' in opts:
                         def run():
                             self.shell.safe_run_module(modulename, prog_ns)
                     else:
                         if runner is None:
                             runner = self.default_runner
                         if runner is None:
                             runner = self.shell.safe_execfile
 
                         def run():
                             runner(filename, prog_ns, prog_ns,
                                     exit_ignore=exit_ignore)
 
                     if 't' in opts:
                         # timed execution
                         try:
                             nruns = int(opts['N'][0])
                             if nruns < 1:
                                 error('Number of runs must be >=1')
                                 return
                         except (KeyError):
                             nruns = 1
                         self._run_with_timing(run, nruns)
                     else:
                         # regular execution
                         run()
 
             if 'i' in opts:
                 self.shell.user_ns['__name__'] = __name__save
             else:
                 # update IPython interactive namespace
 
                 # Some forms of read errors on the file may mean the
                 # __name__ key was never set; using pop we don't have to
                 # worry about a possible KeyError.
                 prog_ns.pop('__name__', None)
 
                 with preserve_keys(self.shell.user_ns, '__file__'):
                     self.shell.user_ns.update(prog_ns)
         finally:
             # It's a bit of a mystery why, but __builtins__ can change from
             # being a module to becoming a dict missing some key data after
             # %run.  As best I can see, this is NOT something IPython is doing
             # at all, and similar problems have been reported before:
             # http://coding.derkeiler.com/Archive/Python/comp.lang.python/2004-10/0188.html
             # Since this seems to be done by the interpreter itself, the best
             # we can do is to at least restore __builtins__ for the user on
             # exit.
             self.shell.user_ns['__builtins__'] = builtin_mod
 
             # Ensure key global structures are restored
             sys.argv = save_argv
             if restore_main:
                 sys.modules['__main__'] = restore_main
                 if '__mp_main__' in sys.modules:
                     sys.modules['__mp_main__'] = restore_main
             else:
                 # Remove from sys.modules the reference to main_mod we'd
                 # added.  Otherwise it will trap references to objects
                 # contained therein.
                 del sys.modules[main_mod_name]
 
         return stats
 
     def _run_with_debugger(self, code, code_ns, filename=None,
                            bp_line=None, bp_file=None):
         """
         Run `code` in debugger with a break point.
 
         Parameters
         ----------
         code : str
             Code to execute.
         code_ns : dict
             A namespace in which `code` is executed.
         filename : str
             `code` is ran as if it is in `filename`.
         bp_line : int, optional
             Line number of the break point.
         bp_file : str, optional
             Path to the file in which break point is specified.
             `filename` is used if not given.
 
         Raises
         ------
         UsageError
             If the break point given by `bp_line` is not valid.
 
         """
         deb = self.shell.InteractiveTB.pdb
         if not deb:
             self.shell.InteractiveTB.pdb = self.shell.InteractiveTB.debugger_cls()
             deb = self.shell.InteractiveTB.pdb
 
         # deb.checkline() fails if deb.curframe exists but is None; it can
         # handle it not existing. https://github.com/ipython/ipython/issues/10028
         if hasattr(deb, 'curframe'):
             del deb.curframe
 
         # reset Breakpoint state, which is moronically kept
         # in a class
         bdb.Breakpoint.next = 1
         bdb.Breakpoint.bplist = {}
         bdb.Breakpoint.bpbynumber = [None]
         deb.clear_all_breaks()
         if bp_line is not None:
             # Set an initial breakpoint to stop execution
             maxtries = 10
             bp_file = bp_file or filename
             checkline = deb.checkline(bp_file, bp_line)
             if not checkline:
                 for bp in range(bp_line + 1, bp_line + maxtries + 1):
                     if deb.checkline(bp_file, bp):
                         break
                 else:
                     msg = ("\nI failed to find a valid line to set "
                            "a breakpoint\n"
                            "after trying up to line: %s.\n"
                            "Please set a valid breakpoint manually "
                            "with the -b option." % bp)
                     raise UsageError(msg)
             # if we find a good linenumber, set the breakpoint
             deb.do_break('%s:%s' % (bp_file, bp_line))
 
         if filename:
             # Mimic Pdb._runscript(...)
             deb._wait_for_mainpyfile = True
             deb.mainpyfile = deb.canonic(filename)
 
         # Start file run
         print("NOTE: Enter 'c' at the %s prompt to continue execution." % deb.prompt)
         try:
             if filename:
                 # save filename so it can be used by methods on the deb object
                 deb._exec_filename = filename
             while True:
                 try:
                     trace = sys.gettrace()
                     deb.run(code, code_ns)
                 except Restart:
                     print("Restarting")
                     if filename:
                         deb._wait_for_mainpyfile = True
                         deb.mainpyfile = deb.canonic(filename)
                     continue
                 else:
                     break
                 finally:
                     sys.settrace(trace)
             
 
         except:
             etype, value, tb = sys.exc_info()
             # Skip three frames in the traceback: the %run one,
             # one inside bdb.py, and the command-line typed by the
             # user (run by exec in pdb itself).
             self.shell.InteractiveTB(etype, value, tb, tb_offset=3)
 
     @staticmethod
     def _run_with_timing(run, nruns):
         """
         Run function `run` and print timing information.
 
         Parameters
         ----------
         run : callable
             Any callable object which takes no argument.
         nruns : int
             Number of times to execute `run`.
 
         """
         twall0 = time.perf_counter()
         if nruns == 1:
             t0 = clock2()
             run()
             t1 = clock2()
             t_usr = t1[0] - t0[0]
             t_sys = t1[1] - t0[1]
             print("\nIPython CPU timings (estimated):")
             print("  User   : %10.2f s." % t_usr)
             print("  System : %10.2f s." % t_sys)
         else:
             runs = range(nruns)
             t0 = clock2()
             for nr in runs:
                 run()
             t1 = clock2()
             t_usr = t1[0] - t0[0]
             t_sys = t1[1] - t0[1]
             print("\nIPython CPU timings (estimated):")
             print("Total runs performed:", nruns)
             print("  Times  : %10s   %10s" % ('Total', 'Per run'))
             print("  User   : %10.2f s, %10.2f s." % (t_usr, t_usr / nruns))
             print("  System : %10.2f s, %10.2f s." % (t_sys, t_sys / nruns))
         twall1 = time.perf_counter()
         print("Wall time: %10.2f s." % (twall1 - twall0))
 
     @skip_doctest
     @no_var_expand
     @line_cell_magic
     @needs_local_scope
     def timeit(self, line='', cell=None, local_ns=None):
         """Time execution of a Python statement or expression
 
         Usage, in line mode:
           %timeit [-n<N> -r<R> [-t|-c] -q -p<P> -o] statement
         or in cell mode:
           %%timeit [-n<N> -r<R> [-t|-c] -q -p<P> -o] setup_code
           code
           code...
 
         Time execution of a Python statement or expression using the timeit
         module.  This function can be used both as a line and cell magic:
 
         - In line mode you can time a single-line statement (though multiple
           ones can be chained with using semicolons).
 
         - In cell mode, the statement in the first line is used as setup code
           (executed but not timed) and the body of the cell is timed.  The cell
           body has access to any variables created in the setup code.
 
         Options:
         -n<N>: execute the given statement <N> times in a loop. If <N> is not
         provided, <N> is determined so as to get sufficient accuracy.
 
         -r<R>: number of repeats <R>, each consisting of <N> loops, and take the
         best result.
         Default: 7
 
         -t: use time.time to measure the time, which is the default on Unix.
         This function measures wall time.
 
         -c: use time.clock to measure the time, which is the default on
         Windows and measures wall time. On Unix, resource.getrusage is used
         instead and returns the CPU user time.
 
         -p<P>: use a precision of <P> digits to display the timing result.
         Default: 3
 
         -q: Quiet, do not print result.
 
         -o: return a TimeitResult that can be stored in a variable to inspect
             the result in more details.
 
         .. versionchanged:: 7.3
             User variables are no longer expanded,
             the magic line is always left unmodified.
 
         Examples
         --------
         ::
 
           In [1]: %timeit pass
           8.26 ns ± 0.12 ns per loop (mean ± std. dev. of 7 runs, 100000000 loops each)
 
           In [2]: u = None
 
           In [3]: %timeit u is None
           29.9 ns ± 0.643 ns per loop (mean ± std. dev. of 7 runs, 10000000 loops each)
 
           In [4]: %timeit -r 4 u == None
 
           In [5]: import time
 
           In [6]: %timeit -n1 time.sleep(2)
 
         The times reported by %timeit will be slightly higher than those
         reported by the timeit.py script when variables are accessed. This is
         due to the fact that %timeit executes the statement in the namespace
         of the shell, compared with timeit.py, which uses a single setup
         statement to import function or create variables. Generally, the bias
         does not matter as long as results from timeit.py are not mixed with
         those from %timeit."""
 
         opts, stmt = self.parse_options(
             line, "n:r:tcp:qo", posix=False, strict=False, preserve_non_opts=True
         )
         if stmt == "" and cell is None:
             return
         
         timefunc = timeit.default_timer
         number = int(getattr(opts, "n", 0))
         default_repeat = 7 if timeit.default_repeat < 7 else timeit.default_repeat
         repeat = int(getattr(opts, "r", default_repeat))
         precision = int(getattr(opts, "p", 3))
         quiet = 'q' in opts
         return_result = 'o' in opts
         if hasattr(opts, "t"):
             timefunc = time.time
         if hasattr(opts, "c"):
             timefunc = clock
 
         timer = Timer(timer=timefunc)
         # this code has tight coupling to the inner workings of timeit.Timer,
         # but is there a better way to achieve that the code stmt has access
         # to the shell namespace?
         transform  = self.shell.transform_cell
 
         if cell is None:
             # called as line magic
             ast_setup = self.shell.compile.ast_parse("pass")
             ast_stmt = self.shell.compile.ast_parse(transform(stmt))
         else:
             ast_setup = self.shell.compile.ast_parse(transform(stmt))
             ast_stmt = self.shell.compile.ast_parse(transform(cell))
 
         ast_setup = self.shell.transform_ast(ast_setup)
         ast_stmt = self.shell.transform_ast(ast_stmt)
 
         # Check that these compile to valid Python code *outside* the timer func
         # Invalid code may become valid when put inside the function & loop,
         # which messes up error messages.
         # https://github.com/ipython/ipython/issues/10636
         self.shell.compile(ast_setup, "<magic-timeit-setup>", "exec")
         self.shell.compile(ast_stmt, "<magic-timeit-stmt>", "exec")
 
         # This codestring is taken from timeit.template - we fill it in as an
         # AST, so that we can apply our AST transformations to the user code
         # without affecting the timing code.
         timeit_ast_template = ast.parse('def inner(_it, _timer):\n'
                                         '    setup\n'
                                         '    _t0 = _timer()\n'
                                         '    for _i in _it:\n'
                                         '        stmt\n'
                                         '    _t1 = _timer()\n'
                                         '    return _t1 - _t0\n')
 
         timeit_ast = TimeitTemplateFiller(ast_setup, ast_stmt).visit(timeit_ast_template)
         timeit_ast = ast.fix_missing_locations(timeit_ast)
 
         # Track compilation time so it can be reported if too long
         # Minimum time above which compilation time will be reported
         tc_min = 0.1
 
         t0 = clock()
         code = self.shell.compile(timeit_ast, "<magic-timeit>", "exec")
         tc = clock()-t0
 
         ns = {}
         glob = self.shell.user_ns
         # handles global vars with same name as local vars. We store them in conflict_globs.
         conflict_globs = {}
         if local_ns and cell is None:
             for var_name, var_val in glob.items():
                 if var_name in local_ns:
                     conflict_globs[var_name] = var_val
             glob.update(local_ns)
             
         exec(code, glob, ns)
         timer.inner = ns["inner"]
 
         # This is used to check if there is a huge difference between the
         # best and worst timings.
         # Issue: https://github.com/ipython/ipython/issues/6471
         if number == 0:
             # determine number so that 0.2 <= total time < 2.0
             for index in range(0, 10):
                 number = 10 ** index
                 time_number = timer.timeit(number)
                 if time_number >= 0.2:
                     break
 
         all_runs = timer.repeat(repeat, number)
         best = min(all_runs) / number
         worst = max(all_runs) / number
         timeit_result = TimeitResult(number, repeat, best, worst, all_runs, tc, precision)
 
         # Restore global vars from conflict_globs
         if conflict_globs:
            glob.update(conflict_globs)
                 
         if not quiet :
             # Check best timing is greater than zero to avoid a
             # ZeroDivisionError.
             # In cases where the slowest timing is lesser than a microsecond
             # we assume that it does not really matter if the fastest
             # timing is 4 times faster than the slowest timing or not.
             if worst > 4 * best and best > 0 and worst > 1e-6:
                 print("The slowest run took %0.2f times longer than the "
                       "fastest. This could mean that an intermediate result "
                       "is being cached." % (worst / best))
            
             print( timeit_result )
 
             if tc > tc_min:
                 print("Compiler time: %.2f s" % tc)
         if return_result:
             return timeit_result
 
     @skip_doctest
     @no_var_expand
     @needs_local_scope
     @line_cell_magic
-    @output_can_be_disabled
+    @output_can_be_silenced
     def time(self,line='', cell=None, local_ns=None):
         """Time execution of a Python statement or expression.
 
         The CPU and wall clock times are printed, and the value of the
         expression (if any) is returned.  Note that under Win32, system time
         is always reported as 0, since it can not be measured.
 
         This function can be used both as a line and cell magic:
 
         - In line mode you can time a single-line statement (though multiple
           ones can be chained with using semicolons).
 
         - In cell mode, you can time the cell body (a directly
           following statement raises an error).
 
         This function provides very basic timing functionality.  Use the timeit
         magic for more control over the measurement.
 
         .. versionchanged:: 7.3
             User variables are no longer expanded,
             the magic line is always left unmodified.
 
         Examples
         --------
         ::
 
           In [1]: %time 2**128
           CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
           Wall time: 0.00
           Out[1]: 340282366920938463463374607431768211456L
 
           In [2]: n = 1000000
 
           In [3]: %time sum(range(n))
           CPU times: user 1.20 s, sys: 0.05 s, total: 1.25 s
           Wall time: 1.37
           Out[3]: 499999500000L
 
           In [4]: %time print 'hello world'
           hello world
           CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
           Wall time: 0.00
 
         .. note::
             The time needed by Python to compile the given expression will be
             reported if it is more than 0.1s.
 
             In the example below, the actual exponentiation is done by Python
             at compilation time, so while the expression can take a noticeable
             amount of time to compute, that time is purely due to the
             compilation::
 
                 In [5]: %time 3**9999;
                 CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
                 Wall time: 0.00 s
 
                 In [6]: %time 3**999999;
                 CPU times: user 0.00 s, sys: 0.00 s, total: 0.00 s
                 Wall time: 0.00 s
                 Compiler : 0.78 s
         """
         # fail immediately if the given expression can't be compiled
         
         if line and cell:
             raise UsageError("Can't use statement directly after '%%time'!")
         
         if cell:
             expr = self.shell.transform_cell(cell)
         else:
             expr = self.shell.transform_cell(line)
 
         # Minimum time above which parse time will be reported
         tp_min = 0.1
 
         t0 = clock()
         expr_ast = self.shell.compile.ast_parse(expr)
         tp = clock()-t0
 
         # Apply AST transformations
         expr_ast = self.shell.transform_ast(expr_ast)
 
         # Minimum time above which compilation time will be reported
         tc_min = 0.1
 
         expr_val=None
         if len(expr_ast.body)==1 and isinstance(expr_ast.body[0], ast.Expr):
             mode = 'eval'
             source = '<timed eval>'
             expr_ast = ast.Expression(expr_ast.body[0].value)
         else:
             mode = 'exec'
             source = '<timed exec>'
             # multi-line %%time case
             if len(expr_ast.body) > 1 and isinstance(expr_ast.body[-1], ast.Expr):
                 expr_val= expr_ast.body[-1]
                 expr_ast = expr_ast.body[:-1]
                 expr_ast = Module(expr_ast, [])
                 expr_val = ast.Expression(expr_val.value)
 
         t0 = clock()
         code = self.shell.compile(expr_ast, source, mode)
         tc = clock()-t0
 
         # skew measurement as little as possible
         glob = self.shell.user_ns
         wtime = time.time
         # time execution
         wall_st = wtime()
         if mode=='eval':
             st = clock2()
             try:
                 out = eval(code, glob, local_ns)
             except:
                 self.shell.showtraceback()
                 return
             end = clock2()
         else:
             st = clock2()
             try:
                 exec(code, glob, local_ns)
                 out=None
                 # multi-line %%time case
                 if expr_val is not None:
                     code_2 = self.shell.compile(expr_val, source, 'eval')
                     out = eval(code_2, glob, local_ns)
             except:
                 self.shell.showtraceback()
                 return
             end = clock2()
 
         wall_end = wtime()
         # Compute actual times and report
         wall_time = wall_end - wall_st
         cpu_user = end[0] - st[0]
         cpu_sys = end[1] - st[1]
         cpu_tot = cpu_user + cpu_sys
         # On windows cpu_sys is always zero, so only total is displayed
         if sys.platform != "win32":
             print(
                 f"CPU times: user {_format_time(cpu_user)}, sys: {_format_time(cpu_sys)}, total: {_format_time(cpu_tot)}"
             )
         else:
             print(f"CPU times: total: {_format_time(cpu_tot)}")
         print(f"Wall time: {_format_time(wall_time)}")
         if tc > tc_min:
             print(f"Compiler : {_format_time(tc)}")
         if tp > tp_min:
             print(f"Parser   : {_format_time(tp)}")
         return out
 
     @skip_doctest
     @line_magic
     def macro(self, parameter_s=''):
         """Define a macro for future re-execution. It accepts ranges of history,
         filenames or string objects.
 
         Usage:\\
           %macro [options] name n1-n2 n3-n4 ... n5 .. n6 ...
 
         Options:
 
           -r: use 'raw' input.  By default, the 'processed' history is used,
           so that magics are loaded in their transformed version to valid
           Python.  If this option is given, the raw input as typed at the
           command line is used instead.
           
           -q: quiet macro definition.  By default, a tag line is printed 
           to indicate the macro has been created, and then the contents of 
           the macro are printed.  If this option is given, then no printout
           is produced once the macro is created.
 
         This will define a global variable called `name` which is a string
         made of joining the slices and lines you specify (n1,n2,... numbers
         above) from your input history into a single string. This variable
         acts like an automatic function which re-executes those lines as if
         you had typed them. You just type 'name' at the prompt and the code
         executes.
 
         The syntax for indicating input ranges is described in %history.
 
         Note: as a 'hidden' feature, you can also use traditional python slice
         notation, where N:M means numbers N through M-1.
 
         For example, if your history contains (print using %hist -n )::
 
           44: x=1
           45: y=3
           46: z=x+y
           47: print x
           48: a=5
           49: print 'x',x,'y',y
 
         you can create a macro with lines 44 through 47 (included) and line 49
         called my_macro with::
 
           In [55]: %macro my_macro 44-47 49
 
         Now, typing `my_macro` (without quotes) will re-execute all this code
         in one pass.
 
         You don't need to give the line-numbers in order, and any given line
         number can appear multiple times. You can assemble macros with any
         lines from your input history in any order.
 
         The macro is a simple object which holds its value in an attribute,
         but IPython's display system checks for macros and executes them as
         code instead of printing them when you type their name.
 
         You can view a macro's contents by explicitly printing it with::
 
           print macro_name
 
         """
         opts,args = self.parse_options(parameter_s,'rq',mode='list')
         if not args:   # List existing macros
             return sorted(k for k,v in self.shell.user_ns.items() if isinstance(v, Macro))
         if len(args) == 1:
             raise UsageError(
                 "%macro insufficient args; usage '%macro name n1-n2 n3-4...")
         name, codefrom = args[0], " ".join(args[1:])
 
         #print 'rng',ranges  # dbg
         try:
             lines = self.shell.find_user_code(codefrom, 'r' in opts)
         except (ValueError, TypeError) as e:
             print(e.args[0])
             return
         macro = Macro(lines)
         self.shell.define_macro(name, macro)
         if not ( 'q' in opts) : 
             print('Macro `%s` created. To execute, type its name (without quotes).' % name)
             print('=== Macro contents: ===')
             print(macro, end=' ')
 
     @magic_arguments.magic_arguments()
     @magic_arguments.argument('output', type=str, default='', nargs='?',
         help="""The name of the variable in which to store output.
         This is a utils.io.CapturedIO object with stdout/err attributes
         for the text of the captured output.
 
         CapturedOutput also has a show() method for displaying the output,
         and __call__ as well, so you can use that to quickly display the
         output.
 
         If unspecified, captured output is discarded.
         """
     )
     @magic_arguments.argument('--no-stderr', action="store_true",
         help="""Don't capture stderr."""
     )
     @magic_arguments.argument('--no-stdout', action="store_true",
         help="""Don't capture stdout."""
     )
     @magic_arguments.argument('--no-display', action="store_true",
         help="""Don't capture IPython's rich display."""
     )
     @cell_magic
     def capture(self, line, cell):
         """run the cell, capturing stdout, stderr, and IPython's rich display() calls."""
         args = magic_arguments.parse_argstring(self.capture, line)
         out = not args.no_stdout
         err = not args.no_stderr
         disp = not args.no_display
         with capture_output(out, err, disp) as io:
             self.shell.run_cell(cell)
         if args.output:
             self.shell.user_ns[args.output] = io
 
 def parse_breakpoint(text, current_file):
     '''Returns (file, line) for file:line and (current_file, line) for line'''
     colon = text.find(':')
     if colon == -1:
         return current_file, int(text)
     else:
         return text[:colon], int(text[colon+1:])
     
 def _format_time(timespan, precision=3):
     """Formats the timespan in a human readable form"""
 
     if timespan >= 60.0:
         # we have more than a minute, format that in a human readable form
         # Idea from http://snipplr.com/view/5713/
         parts = [("d", 60*60*24),("h", 60*60),("min", 60), ("s", 1)]
         time = []
         leftover = timespan
         for suffix, length in parts:
             value = int(leftover / length)
             if value > 0:
                 leftover = leftover % length
                 time.append(u'%s%s' % (str(value), suffix))
             if leftover < 1:
                 break
         return " ".join(time)
 
     
     # Unfortunately the unicode 'micro' symbol can cause problems in
     # certain terminals.  
     # See bug: https://bugs.launchpad.net/ipython/+bug/348466
     # Try to prevent crashes by being more secure than it needs to
     # E.g. eclipse is able to print a µ, but has no sys.stdout.encoding set.
     units = [u"s", u"ms",u'us',"ns"] # the save value   
     if hasattr(sys.stdout, 'encoding') and sys.stdout.encoding:
         try:
             u'\xb5'.encode(sys.stdout.encoding)
             units = [u"s", u"ms",u'\xb5s',"ns"]
         except:
             pass
     scaling = [1, 1e3, 1e6, 1e9]
         
     if timespan > 0.0:
         order = min(-int(math.floor(math.log10(timespan)) // 3), 3)
     else:
         order = 3
     return u"%.*g %s" % (precision, timespan * scaling[order], units[order])