Module: core.interactiveshell — IPython 2.3.1 documentation

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# Module: `core.interactiveshell`

Main IPython class.

## 5 Classes

class `IPython.core.interactiveshell.` `SpaceInInput`

  Bases: `exceptions.Exception`

class `IPython.core.interactiveshell.` `SeparateUnicode`(default_value=<IPython.utils.traitlets.NoDefaultSpecified object at 0xad8410a090>, **metadata)

  Bases: `IPython.utils.traitlets.Unicode`

  A Unicode subclass to validate separate_in, separate_out, etc.

  This is a Unicode based trait that converts ‘0’->’’ and `'\\n'->'\n'`.

class `IPython.core.interactiveshell.` `ReadlineNoRecord`(shell)

  Bases: `object`

  Context manager to execute some code, then reload readline history so that interactive input to the code doesn’t appear when pressing up.

  `__init__`(shell)
  `get_readline_tail`(n=10)

    Get the last n items in readline history.

class `IPython.core.interactiveshell.` `InteractiveShell`(ipython_dir=None, profile_dir=None, user_module=None, user_ns=None, custom_exceptions=((), None), **kwargs)

  Bases: `IPython.config.configurable.SingletonConfigurable`

  An enhanced, interactive shell for Python.

  `__init__`(ipython_dir=None, profile_dir=None, user_module=None, user_ns=None, custom_exceptions=((), None), **kwargs)
  `all_ns_refs`

    Get a list of references to all the namespace dictionaries in which IPython might store a user-created object.

    Note that this does not include the displayhook, which also caches objects from the output.

  `atexit_operations`()

    This will be executed at the time of exit.

    Cleanup operations and saving of persistent data that is done unconditionally by IPython should be performed here.

    For things that may depend on startup flags or platform specifics (such as having readline or not), register a separate atexit function in the code that has the appropriate information, rather than trying to clutter

  `auto_rewrite_input`(cmd)

    Print to the screen the rewritten form of the user’s command.

    This shows visual feedback by rewriting input lines that cause automatic calling to kick in, like:

        /f x

    into:

        ------> f(x)

    after the user’s input prompt. This helps the user understand that the input line was transformed automatically by IPython.

  `call_pdb`

    Control auto-activation of pdb at exceptions

  `clear_main_mod_cache`()

    Clear the cache of main modules.

    Mainly for use by utilities like %reset.

    Examples

    In [15]: import IPython

    In [16]: m = _ip.new_main_mod(IPython.__file__, ‘IPython’)

    In [17]: len(_ip._main_mod_cache) > 0 Out[17]: True

    In [18]: _ip.clear_main_mod_cache()

    In [19]: len(_ip._main_mod_cache) == 0 Out[19]: True

  `complete`(text, line=None, cursor_pos=None)

    Return the completed text and a list of completions.

    Parameters: | text : string A string of text to be completed on. It can be given as empty and instead a line/position pair are given. In this case, the completer itself will split the line like readline does. line : string, optional The complete line that text is part of. cursor_pos : int, optional The position of the cursor on the input line.
    Returns: | text : string The actual text that was completed. matches : list A sorted list with all possible completions. The optional arguments allow the completion to take more context into : account, and are part of the low-level completion API. : This is a wrapper around the completion mechanism, similar to what : readline does at the command line when the TAB key is hit. By : exposing it as a method, it can be used by other non-readline : environments (such as GUIs) for text completion. : Simple usage example: : In [1]: x = ‘hello’ : In [2]: _ip.complete(‘x.l’) : Out[2]: (‘x.l’, [‘x.ljust’, ‘x.lower’, ‘x.lstrip’]) :

  `debugger`(force=False)

    Call the pydb/pdb debugger.

    Keywords:

    > - force(False): by default, this routine checks the instance call_pdb flag and does not actually invoke the debugger if the flag is false. The ‘force’ option forces the debugger to activate even if the flag is false.

  `define_macro`(name, themacro)

    Define a new macro

    Parameters: | name : str The name of the macro. themacro : str or Macro The action to do upon invoking the macro. If a string, a new Macro object is created by passing the string to it.

  `del_var`(varname, by_name=False)

    Delete a variable from the various namespaces, so that, as far as possible, we’re not keeping any hidden references to it.

    Parameters: | varname : str The name of the variable to delete. by_name : bool If True, delete variables with the given name in each namespace. If False (default), find the variable in the user namespace, and delete references to it.

  `drop_by_id`(variables)

    Remove a dict of variables from the user namespace, if they are the same as the values in the dictionary.

    This is intended for use by extensions: variables that they’ve added can be taken back out if they are unloaded, without removing any that the user has overwritten.

    Parameters: | variables : dict A dictionary mapping object names (as strings) to the objects.

  `enable_matplotlib`(gui=None)

    Enable interactive matplotlib and inline figure support.

    This takes the following steps:

    1. select the appropriate eventloop and matplotlib backend
    2. set up matplotlib for interactive use with that backend
    3. configure formatters for inline figure display
    4. enable the selected gui eventloop

    Parameters: | gui : optional, string If given, dictates the choice of matplotlib GUI backend to use (should be one of IPython’s supported backends, ‘qt’, ‘osx’, ‘tk’, ‘gtk’, ‘wx’ or ‘inline’), otherwise we use the default chosen by matplotlib (as dictated by the matplotlib build-time options plus the user’s matplotlibrc configuration file). Note that not all backends make sense in all contexts, for example a terminal ipython can’t display figures inline.

  `enable_pylab`(gui=None, import_all=True, welcome_message=False)

    Activate pylab support at runtime.

    This turns on support for matplotlib, preloads into the interactive namespace all of numpy and pylab, and configures IPython to correctly interact with the GUI event loop. The GUI backend to be used can be optionally selected with the optional `gui` argument.

    This method only adds preloading the namespace to InteractiveShell.enable_matplotlib.

    Parameters: | gui : optional, string If given, dictates the choice of matplotlib GUI backend to use (should be one of IPython’s supported backends, ‘qt’, ‘osx’, ‘tk’, ‘gtk’, ‘wx’ or ‘inline’), otherwise we use the default chosen by matplotlib (as dictated by the matplotlib build-time options plus the user’s matplotlibrc configuration file). Note that not all backends make sense in all contexts, for example a terminal ipython can’t display figures inline. import_all : optional, bool, default: True Whether to do from numpy import * and from pylab import * in addition to module imports. welcome_message : deprecated This argument is ignored, no welcome message will be displayed.

  `ev`(expr)

    Evaluate python expression expr in user namespace.

    Returns the result of evaluation

  `ex`(cmd)

    Execute a normal python statement in user namespace.

  `excepthook`(etype, value, tb)

    One more defense for GUI apps that call sys.excepthook.

    GUI frameworks like wxPython trap exceptions and call sys.excepthook themselves. I guess this is a feature that enables them to keep running after exceptions that would otherwise kill their mainloop. This is a bother for IPython which excepts to catch all of the program exceptions with a try: except: statement.

    Normally, IPython sets sys.excepthook to a CrashHandler instance, so if any app directly invokes sys.excepthook, it will look to the user like IPython crashed. In order to work around this, we can disable the CrashHandler and replace it with this excepthook instead, which prints a regular traceback using our InteractiveTB. In this fashion, apps which call sys.excepthook will generate a regular-looking exception from IPython, and the CrashHandler will only be triggered by real IPython crashes.

    This hook should be used sparingly, only in places which are not likely to be true IPython errors.

  `extract_input_lines`(range_str, raw=False)

    Return as a string a set of input history slices.

    Parameters: | range_str : string The set of slices is given as a string, like “~5/6-~4/2 4:8 9”, since this function is for use by magic functions which get their arguments as strings. The number before the / is the session number: ~n goes n back from the current session. raw : bool, optional By default, the processed input is used. If this is true, the raw input history is used instead.

    Notes

    Slices can be described with two notations:

    - `N:M` -> standard python form, means including items N...(M-1).
    - `N-M` -> include items N..M (closed endpoint).
  `find_cell_magic`(magic_name)

    Find and return a cell magic by name.

    Returns None if the magic isn’t found.

  `find_line_magic`(magic_name)

    Find and return a line magic by name.

    Returns None if the magic isn’t found.

  `find_magic`(magic_name, magic_kind='line')

    Find and return a magic of the given type by name.

    Returns None if the magic isn’t found.

  `find_user_code`(target, raw=True, py_only=False, skip_encoding_cookie=True)

    Get a code string from history, file, url, or a string or macro.

    This is mainly used by magic functions.

    Parameters: | target : str A string specifying code to retrieve. This will be tried respectively as: ranges of input history (see %history for syntax), url, correspnding .py file, filename, or an expression evaluating to a string or Macro in the user namespace. raw : bool If true (default), retrieve raw history. Has no effect on the other retrieval mechanisms. py_only : bool (default False) Only try to fetch python code, do not try alternative methods to decode file if unicode fails.
    Returns: | A string of code. : ValueError is raised if nothing is found, and TypeError if it evaluates : to an object of another type. In each case, .args[0] is a printable : message. :

  `get_ipython`()

    Return the currently running IPython instance.

  `getoutput`(cmd, split=True, depth=0)

    Get output (possibly including stderr) from a subprocess.

    Parameters: | cmd : str Command to execute (can not end in ‘&’, as background processes are not supported. split : bool, optional If True, split the output into an IPython SList. Otherwise, an IPython LSString is returned. These are objects similar to normal lists and strings, with a few convenience attributes for easier manipulation of line-based output. You can use ‘?’ on them for details. depth : int, optional How many frames above the caller are the local variables which should be expanded in the command string? The default (0) assumes that the expansion variables are in the stack frame calling this function.

  `init_completer`()

    Initialize the completion machinery.

    This creates completion machinery that can be used by client code, either interactively in-process (typically triggered by the readline library), programatically (such as in test suites) or out-of-prcess (typically over the network by remote frontends).

  `init_environment`()

    Any changes we need to make to the user’s environment.

  `init_history`()

    Sets up the command history, and starts regular autosaves.

  `init_latextool`()

    Configure LaTeXTool.

  `init_logstart`()

    Initialize logging in case it was requested at the command line.

  `init_readline`()

    Command history completion/saving/reloading.

  `init_user_ns`()

    Initialize all user-visible namespaces to their minimum defaults.

    Certain history lists are also initialized here, as they effectively act as user namespaces.

    Notes

    All data structures here are only filled in, they are NOT reset by this method. If they were not empty before, data will simply be added to therm.

  `init_virtualenv`()

    Add a virtualenv to sys.path so the user can import modules from it. This isn’t perfect: it doesn’t use the Python interpreter with which the virtualenv was built, and it ignores the –no-site-packages option. A warning will appear suggesting the user installs IPython in the virtualenv, but for many cases, it probably works well enough.

    Adapted from code snippets online.

    http://blog.ufsoft.org/2009/1/29/ipython-and-virtualenv

  `magic`(arg_s)

    DEPRECATED. Use run_line_magic() instead.

    Call a magic function by name.

    Input: a string containing the name of the magic function to call and any additional arguments to be passed to the magic.

    magic(‘name -opt foo bar’) is equivalent to typing at the ipython prompt:

    In[1]: %name -opt foo bar

    To call a magic without arguments, simply use magic(‘name’).

    This provides a proper Python function to call IPython’s magics in any valid Python code you can type at the interpreter, including loops and compound statements.

  `mktempfile`(data=None, prefix='ipython_edit_')

    Make a new tempfile and return its filename.

    This makes a call to tempfile.mkstemp (created in a tempfile.mkdtemp), but it registers the created filename internally so ipython cleans it up at exit time.

    Optional inputs:

    > - data(None): if data is given, it gets written out to the temp file immediately, and the file is closed again.

  `new_main_mod`(filename, modname)

    Return a new ‘main’ module object for user code execution.

    `filename` should be the path of the script which will be run in the module. Requests with the same filename will get the same module, with its namespace cleared.

    `modname` should be the module name - normally either ‘__main__’ or the basename of the file without the extension.

    When scripts are executed via %run, we must keep a reference to their __main__ module around so that Python doesn’t clear it, rendering references to module globals useless.

    This method keeps said reference in a private dict, keyed by the absolute path of the script. This way, for multiple executions of the same script we only keep one copy of the namespace (the last one), thus preventing memory leaks from old references while allowing the objects from the last execution to be accessible.

  `pre_readline`()

    readline hook to be used at the start of each line.

    Currently it handles auto-indent only.

  `prepare_user_module`(user_module=None, user_ns=None)

    Prepare the module and namespace in which user code will be run.

    When IPython is started normally, both parameters are None: a new module is created automatically, and its __dict__ used as the namespace.

    If only user_module is provided, its __dict__ is used as the namespace. If only user_ns is provided, a dummy module is created, and user_ns becomes the global namespace. If both are provided (as they may be when embedding), user_ns is the local namespace, and user_module provides the global namespace.

    Parameters: | user_module : module, optional The current user module in which IPython is being run. If None, a clean module will be created. user_ns : dict, optional A namespace in which to run interactive commands.
    Returns: | A tuple of user_module and user_ns, each properly initialised. :

  `push`(variables, interactive=True)

    Inject a group of variables into the IPython user namespace.

    Parameters: | variables : dict, str or list/tuple of str The variables to inject into the user’s namespace. If a dict, a simple update is done. If a str, the string is assumed to have variable names separated by spaces. A list/tuple of str can also be used to give the variable names. If just the variable names are give (list/tuple/str) then the variable values looked up in the callers frame. interactive : bool If True (default), the variables will be listed with the `who` magic.

  `register_magic_function`(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.

  `register_post_execute`(func)

    DEPRECATED: Use ip.events.register(‘post_run_cell’, func)

    Register a function for calling after code execution.

  `reset`(new_session=True)

    Clear all internal namespaces, and attempt to release references to user objects.

    If new_session is True, a new history session will be opened.

  `reset_selective`(regex=None)

    Clear selective variables from internal namespaces based on a specified regular expression.

    Parameters: | regex : string or compiled pattern, optional A regular expression pattern that will be used in searching variable names in the users namespaces.

  `restore_sys_module_state`()

    Restore the state of the sys module.

  `run_ast_nodes`(nodelist, cell_name, interactivity='last_expr', compiler=<built-in function compile>)

    Run a sequence of AST nodes. The execution mode depends on the interactivity parameter.

    Parameters: | nodelist : list A sequence of AST nodes to run. cell_name : str Will be passed to the compiler as the filename of the cell. Typically the value returned by ip.compile.cache(cell). interactivity : str ‘all’, ‘last’, ‘last_expr’ or ‘none’, specifying which nodes should be run interactively (displaying output from expressions). ‘last_expr’ will run the last node interactively only if it is an expression (i.e. expressions in loops or other blocks are not displayed. Other values for this parameter will raise a ValueError. compiler : callable A function with the same interface as the built-in compile(), to turn the AST nodes into code objects. Default is the built-in compile().

  `run_cell`(raw_cell, store_history=False, silent=False, shell_futures=True)

    Run a complete IPython cell.

    Parameters: | raw_cell : str The code (including IPython code such as %magic functions) to run. store_history : bool If True, the raw and translated cell will be stored in IPython’s history. For user code calling back into IPython’s machinery, this should be set to False. silent : bool If True, avoid side-effects, such as implicit displayhooks and and logging. silent=True forces store_history=False. shell_futures : bool If True, the code will share future statements with the interactive shell. It will both be affected by previous __future__ imports, and any __future__ imports in the code will affect the shell. If False, __future__ imports are not shared in either direction.

  `run_cell_magic`(magic_name, line, cell)

    Execute the given cell magic.

    Parameters: | magic_name : str Name of the desired magic function, without ‘%’ prefix. line : str The rest of the first input line as a single string. cell : str The body of the cell as a (possibly multiline) string.

  `run_code`(code_obj)

    Execute a code object.

    When an exception occurs, self.showtraceback() is called to display a traceback.

    Parameters: | code_obj : code object A compiled code object, to be executed
    Returns: | False : successful execution. True : an error occurred.

  `run_line_magic`(magic_name, line)

    Execute the given line magic.

    Parameters: | magic_name : str Name of the desired magic function, without ‘%’ prefix. line : str The rest of the input line as a single string.

  `runcode`(code_obj)

    Execute a code object.

    When an exception occurs, self.showtraceback() is called to display a traceback.

    Parameters: | code_obj : code object A compiled code object, to be executed
    Returns: | False : successful execution. True : an error occurred.

  `safe_execfile`(fname, *where, **kw)

    A safe version of the builtin execfile().

    This version will never throw an exception, but instead print helpful error messages to the screen. This only works on pure Python files with the .py extension.

    Parameters: | fname : string The name of the file to be executed. where : tuple One or two namespaces, passed to execfile() as (globals,locals). If only one is given, it is passed as both. exit_ignore : bool (False) If True, then silence SystemExit for non-zero status (it is always silenced for zero status, as it is so common). raise_exceptions : bool (False) If True raise exceptions everywhere. Meant for testing.

  `safe_execfile_ipy`(fname)

    Like safe_execfile, but for .ipy or .ipynb files with IPython syntax.

    Parameters: | fname : str The name of the file to execute. The filename must have a .ipy or .ipynb extension.

  `safe_run_module`(mod_name, where)

    A safe version of runpy.run_module().

    This version will never throw an exception, but instead print helpful error messages to the screen.

    SystemExit exceptions with status code 0 or None are ignored.

    Parameters: | mod_name : string The name of the module to be executed. where : dict The globals namespace.

  `save_sys_module_state`()

    Save the state of hooks in the sys module.

    This has to be called after self.user_module is created.

  `set_autoindent`(value=None)

    Set the autoindent flag, checking for readline support.

    If called with no arguments, it acts as a toggle.

  `set_completer_frame`(frame=None)

    Set the frame of the completer.

  `set_custom_completer`(completer, pos=0)

    Adds a new custom completer function.

    The position argument (defaults to 0) is the index in the completers list where you want the completer to be inserted.

  `set_custom_exc`(exc_tuple, handler)

    Set a custom exception handler, which will be called if any of the exceptions in exc_tuple occur in the mainloop (specifically, in the run_code() method).

    > Parameters: | exc_tuple : tuple of exception classes A tuple of exception classes, for which to call the defined handler. It is very important that you use a tuple, and NOT A LIST here, because of the way Python’s except statement works. If you only want to trap a single exception, use a singleton tuple:
    >     exc_tuple == (MyCustomException,)
    > handler : callable handler must have the following signature:
    >     def my_handler(self, etype, value, tb, tb_offset=None):
    >         ...
    >         return structured_traceback
    Your handler must return a structured traceback (a list of strings), or None. This will be made into an instance method (via types.MethodType) of IPython itself, and it will be called if any of the exceptions listed in the exc_tuple are caught. If the handler is None, an internal basic one is used, which just prints basic info. To protect IPython from crashes, if your handler ever raises an exception or returns an invalid result, it will be immediately disabled. WARNING: by putting in your own exception handler into IPython’s main : execution loop, you run a very good chance of nasty crashes. This : facility should only be used if you really know what you are doing. :

  `set_hook`(name, hook) → sets an internal IPython hook.

    IPython exposes some of its internal API as user-modifiable hooks. By adding your function to one of these hooks, you can modify IPython’s behavior to call at runtime your own routines.

  `set_next_input`(s)

    Sets the ‘default’ input string for the next command line.

    Requires readline.

    Example:

        In [1]: _ip.set_next_input("Hello Word")
        In [2]: Hello Word_  # cursor is here

  `set_readline_completer`()

    Reset readline’s completer to be our own.

  `show_usage`()

    Show a usage message

  `show_usage_error`(exc)

    Show a short message for UsageErrors

    These are special exceptions that shouldn’t show a traceback.

  `showindentationerror`()

    Called by run_cell when there’s an IndentationError in code entered at the prompt.

    This is overridden in TerminalInteractiveShell to show a message about the %paste magic.

  `showsyntaxerror`(filename=None)

    Display the syntax error that just occurred.

    This doesn’t display a stack trace because there isn’t one.

    If a filename is given, it is stuffed in the exception instead of what was there before (because Python’s parser always uses “<string>” when reading from a string).

  `showtraceback`(exc_tuple=None, filename=None, tb_offset=None, exception_only=False)

    Display the exception that just occurred.

    If nothing is known about the exception, this is the method which should be used throughout the code for presenting user tracebacks, rather than directly invoking the InteractiveTB object.

    A specific showsyntaxerror() also exists, but this method can take care of calling it if needed, so unless you are explicitly catching a SyntaxError exception, don’t try to analyze the stack manually and simply call this method.

  `system`(cmd)

    Call the given cmd in a subprocess, piping stdout/err

    Parameters: | cmd : str Command to execute (can not end in ‘&’, as background processes are not supported. Should not be a command that expects input other than simple text.

  `system_piped`(cmd)

    Call the given cmd in a subprocess, piping stdout/err

    Parameters: | cmd : str Command to execute (can not end in ‘&’, as background processes are not supported. Should not be a command that expects input other than simple text.

  `system_raw`(cmd)

    Call the given cmd in a subprocess using os.system on Windows or subprocess.call using the system shell on other platforms.

    Parameters: | cmd : str Command to execute.

  `transform_ast`(node)

    Apply the AST transformations from self.ast_transformers

    Parameters: | node : ast.Node The root node to be transformed. Typically called with the ast.Module produced by parsing user input.
    Returns: | An ast.Node corresponding to the node it was called with. Note that it : may also modify the passed object, so don’t rely on references to the : original AST. :

  `user_expressions`(expressions)

    Evaluate a dict of expressions in the user’s namespace.

    Parameters: | expressions : dict A dict with string keys and string values. The expression values should be valid Python expressions, each of which will be evaluated in the user namespace.
    Returns: | A dict, keyed like the input expressions dict, with the rich mime-typed : display_data of each value. :

  `user_variables`(names)

    Get a list of variable names from the user’s namespace.

    Parameters: | names : list of strings A list of names of variables to be read from the user namespace.
    Returns: | A dict, keyed by the input names and with the rich mime-type repr(s) of each value. : Each element will be a sub-dict of the same form as a display_data message. :

  `var_expand`(cmd, depth=0, formatter=<IPython.utils.text.DollarFormatter object at 0xaddeff5c10>)

    Expand python variables in a string.

    The depth argument indicates how many frames above the caller should be walked to look for the local namespace where to expand variables.

    The global namespace for expansion is always the user’s interactive namespace.

  `write`(data)

    Write a string to the default output

  `write_err`(data)

    Write a string to the default error output

class `IPython.core.interactiveshell.` `InteractiveShellABC`

  Bases: `abc._NewBase`

  An abstract base class for InteractiveShell.

## 1 Function

`IPython.core.interactiveshell.` `get_default_colors`()

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