Document is_complete messages

Also, bump message spec version

IPython/core/release.py

@@ -1,150 +1,150 b''
 # -*- coding: utf-8 -*-
 """Release data for the IPython project."""
 
 #-----------------------------------------------------------------------------
 #  Copyright (c) 2008, IPython Development Team.
 #  Copyright (c) 2001, Fernando Perez <[e-mail]>
 #  Copyright (c) 2001, Janko Hauser <[e-mail]>
 #  Copyright (c) 2001, Nathaniel Gray <[e-mail]>
 #
 #  Distributed under the terms of the Modified BSD License.
 #
 #  The full license is in the file COPYING.txt, distributed with this software.
 #-----------------------------------------------------------------------------
 
 # Name of the package for release purposes.  This is the name which labels
 # the tarballs and RPMs made by distutils, so it's best to lowercase it.
 name = 'ipython'
 
 # IPython version information.  An empty _version_extra corresponds to a full
 # release.  'dev' as a _version_extra string means this is a development
 # version
 _version_major = 3
 _version_minor = 0
 _version_patch = 0
 _version_extra = 'dev'
 # _version_extra = 'rc1'
 # _version_extra = ''  # Uncomment this for full releases
 
 # release.codename is deprecated in 2.0, will be removed in 3.0
 codename = ''
 
 # Construct full version string from these.
 _ver = [_version_major, _version_minor, _version_patch]
 
 __version__ = '.'.join(map(str, _ver))
 if _version_extra:
     __version__ = __version__ + '-' + _version_extra
 
 version = __version__  # backwards compatibility name
 version_info = (_version_major, _version_minor, _version_patch, _version_extra)
 
 # Change this when incrementing the kernel protocol version
-kernel_protocol_version_info = (5, 0)
+kernel_protocol_version_info = (5, 1)
 kernel_protocol_version = "%i.%i" % kernel_protocol_version_info
 
 description = "IPython: Productive Interactive Computing"
 
 long_description = \
 """
 IPython provides a rich toolkit to help you make the most out of using Python
 interactively.  Its main components are:
 
 * Powerful interactive Python shells (terminal- and Qt-based).
 * A web-based interactive notebook environment with all shell features plus
   support for embedded figures, animations and rich media.
 * Support for interactive data visualization and use of GUI toolkits.
 * Flexible, embeddable interpreters to load into your own projects.
 * A high-performance library for high level and interactive parallel computing
   that works in multicore systems, clusters, supercomputing and cloud scenarios.
 
 The enhanced interactive Python shells have the following main features:
 
 * Comprehensive object introspection.
 
 * Input history, persistent across sessions.
 
 * Caching of output results during a session with automatically generated
   references.
 
 * Extensible tab completion, with support by default for completion of python
   variables and keywords, filenames and function keywords.
 
 * Extensible system of 'magic' commands for controlling the environment and
   performing many tasks related either to IPython or the operating system.
 
 * A rich configuration system with easy switching between different setups
   (simpler than changing $PYTHONSTARTUP environment variables every time).
 
 * Session logging and reloading.
 
 * Extensible syntax processing for special purpose situations.
 
 * Access to the system shell with user-extensible alias system.
 
 * Easily embeddable in other Python programs and GUIs.
 
 * Integrated access to the pdb debugger and the Python profiler.
 
 The parallel computing architecture has the following main features:
 
 * Quickly parallelize Python code from an interactive Python/IPython session.
 
 * A flexible and dynamic process model that be deployed on anything from
   multicore workstations to supercomputers.
 
 * An architecture that supports many different styles of parallelism, from
   message passing to task farming.
 
 * Both blocking and fully asynchronous interfaces.
 
 * High level APIs that enable many things to be parallelized in a few lines
   of code.
 
 * Share live parallel jobs with other users securely.
 
 * Dynamically load balanced task farming system.
 
 * Robust error handling in parallel code.
 
 The latest development version is always available from IPython's `GitHub
 site <http://github.com/ipython>`_.
 """
 
 license = 'BSD'
 
 authors = {'Fernando' : ('Fernando Perez','[e-mail]'),
            'Janko'    : ('Janko Hauser','[e-mail]'),
            'Nathan'   : ('Nathaniel Gray','[e-mail]'),
            'Ville'    : ('Ville Vainio','[e-mail]'),
            'Brian'    : ('Brian E Granger', '[e-mail]'),
            'Min'      : ('Min Ragan-Kelley', '[e-mail]'),
            'Thomas'   : ('Thomas A. Kluyver', '[e-mail]'),
            'Jorgen'   : ('Jorgen Stenarson', '[e-mail]'),
            'Matthias' : ('Matthias Bussonnier', '[e-mail]'),
            }
 
 author = 'The IPython Development Team'
 
 author_email = '[e-mail]'
 
 url = 'http://ipython.org'
 
 download_url = 'https://github.com/ipython/ipython/downloads'
 
 platforms = ['Linux','Mac OSX','Windows XP/Vista/7/8']
 
 keywords = ['Interactive','Interpreter','Shell','Parallel','Distributed',
             'Web-based computing', 'Qt console', 'Embedding']
 
 classifiers = [
     'Intended Audience :: Developers',
     'Intended Audience :: Science/Research',
     'License :: OSI Approved :: BSD License',
     'Programming Language :: Python',
     'Programming Language :: Python :: 2',
     'Programming Language :: Python :: 2.7',
     'Programming Language :: Python :: 3',
     'Topic :: System :: Distributed Computing',
     'Topic :: System :: Shells'
     ]

docs/source/development/messaging.rst

@@ -1,1066 +1,1095 b''
 .. _messaging:
 
 ======================
  Messaging in IPython
 ======================
 
 
 Versioning
 ==========
 
 The IPython message specification is versioned independently of IPython.
-The current version of the specification is 5.0.
+The current version of the specification is 5.1.
 
 
 Introduction
 ============
 
 This document explains the basic communications design and messaging
 specification for how the various IPython objects interact over a network
 transport.  The current implementation uses the ZeroMQ_ library for messaging
 within and between hosts.
 
 .. Note::
 
    This document should be considered the authoritative description of the
    IPython messaging protocol, and all developers are strongly encouraged to
    keep it updated as the implementation evolves, so that we have a single
    common reference for all protocol details.
 
 The basic design is explained in the following diagram:
 
 .. image:: figs/frontend-kernel.png
    :width: 450px
    :alt: IPython kernel/frontend messaging architecture.
    :align: center
    :target: ../_images/frontend-kernel.png
 
 A single kernel can be simultaneously connected to one or more frontends.  The
 kernel has three sockets that serve the following functions:
 
 1. Shell: this single ROUTER socket allows multiple incoming connections from
    frontends, and this is the socket where requests for code execution, object
    information, prompts, etc. are made to the kernel by any frontend.  The
    communication on this socket is a sequence of request/reply actions from
    each frontend and the kernel.
 
 2. IOPub: this socket is the 'broadcast channel' where the kernel publishes all
    side effects (stdout, stderr, etc.) as well as the requests coming from any
    client over the shell socket and its own requests on the stdin socket.  There
    are a number of actions in Python which generate side effects: :func:`print`
    writes to ``sys.stdout``, errors generate tracebacks, etc.  Additionally, in
    a multi-client scenario, we want all frontends to be able to know what each
    other has sent to the kernel (this can be useful in collaborative scenarios,
    for example).  This socket allows both side effects and the information
    about communications taking place with one client over the shell channel
    to be made available to all clients in a uniform manner.
 
 3. stdin: this ROUTER socket is connected to all frontends, and it allows
    the kernel to request input from the active frontend when :func:`raw_input` is called.
    The frontend that executed the code has a DEALER socket that acts as a 'virtual keyboard'
    for the kernel while this communication is happening (illustrated in the
    figure by the black outline around the central keyboard).  In practice,
    frontends may display such kernel requests using a special input widget or
    otherwise indicating that the user is to type input for the kernel instead
    of normal commands in the frontend.
 
    All messages are tagged with enough information (details below) for clients
    to know which messages come from their own interaction with the kernel and
    which ones are from other clients, so they can display each type
    appropriately.
 
 4. Control: This channel is identical to Shell, but operates on a separate socket,
    to allow important messages to avoid queueing behind execution requests (e.g. shutdown or abort).
 
 The actual format of the messages allowed on each of these channels is
 specified below.  Messages are dicts of dicts with string keys and values that
 are reasonably representable in JSON.  Our current implementation uses JSON
 explicitly as its message format, but this shouldn't be considered a permanent
 feature.  As we've discovered that JSON has non-trivial performance issues due
 to excessive copying, we may in the future move to a pure pickle-based raw
 message format.  However, it should be possible to easily convert from the raw
 objects to JSON, since we may have non-python clients (e.g. a web frontend).
 As long as it's easy to make a JSON version of the objects that is a faithful
 representation of all the data, we can communicate with such clients.
 
 .. Note::
 
    Not all of these have yet been fully fleshed out, but the key ones are, see
    kernel and frontend files for actual implementation details.
 
 General Message Format
 ======================
 
 A message is defined by the following four-dictionary structure::
 
     {
       # The message header contains a pair of unique identifiers for the
       # originating session and the actual message id, in addition to the
       # username for the process that generated the message.  This is useful in
       # collaborative settings where multiple users may be interacting with the
       # same kernel simultaneously, so that frontends can label the various
       # messages in a meaningful way.
       'header' : {
                     'msg_id' : uuid,
                     'username' : str,
                     'session' : uuid,
                     # All recognized message type strings are listed below.
                     'msg_type' : str,
                     # the message protocol version
                     'version' : '5.0',
          },
 
       # In a chain of messages, the header from the parent is copied so that
       # clients can track where messages come from.
       'parent_header' : dict,
       
       # Any metadata associated with the message.
       'metadata' : dict,
       
       # The actual content of the message must be a dict, whose structure
       # depends on the message type.
       'content' : dict,
     }
 
 .. versionchanged:: 5.0
 
     ``version`` key added to the header.
 
 .. _wire_protocol:
 
 The Wire Protocol
 =================
 
 
 This message format exists at a high level,
 but does not describe the actual *implementation* at the wire level in zeromq.
 The canonical implementation of the message spec is our :class:`~IPython.kernel.zmq.session.Session` class.
 
 .. note::
 
     This section should only be relevant to non-Python consumers of the protocol.
     Python consumers should simply import and use IPython's own implementation of the wire protocol
     in the :class:`IPython.kernel.zmq.session.Session` object.
 
 Every message is serialized to a sequence of at least six blobs of bytes:
 
 .. sourcecode:: python
 
     [
       b'u-u-i-d',         # zmq identity(ies)
       b'<IDS|MSG>',       # delimiter
       b'baddad42',        # HMAC signature
       b'{header}',        # serialized header dict
       b'{parent_header}', # serialized parent header dict
       b'{metadata}',      # serialized metadata dict
       b'{content},        # serialized content dict
       b'blob',            # extra raw data buffer(s)
       ...
     ]
 
 The front of the message is the ZeroMQ routing prefix,
 which can be zero or more socket identities.
 This is every piece of the message prior to the delimiter key ``<IDS|MSG>``.
 In the case of IOPub, there should be just one prefix component,
 which is the topic for IOPub subscribers, e.g. ``execute_result``, ``display_data``.
 
 .. note::
 
     In most cases, the IOPub topics are irrelevant and completely ignored,
     because frontends just subscribe to all topics.
     The convention used in the IPython kernel is to use the msg_type as the topic,
     and possibly extra information about the message, e.g. ``execute_result`` or ``stream.stdout``
 
 After the delimiter is the `HMAC`_ signature of the message, used for authentication.
 If authentication is disabled, this should be an empty string.
 By default, the hashing function used for computing these signatures is sha256.
 
 .. _HMAC: http://en.wikipedia.org/wiki/HMAC
 
 .. note::
 
     To disable authentication and signature checking,
     set the `key` field of a connection file to an empty string.
 
 The signature is the HMAC hex digest of the concatenation of:
 
 - A shared key (typically the ``key`` field of a connection file)
 - The serialized header dict
 - The serialized parent header dict
 - The serialized metadata dict
 - The serialized content dict
 
 In Python, this is implemented via:
 
 .. sourcecode:: python
 
     # once:
     digester = HMAC(key, digestmod=hashlib.sha256)
     
     # for each message
     d = digester.copy()
     for serialized_dict in (header, parent, metadata, content):
         d.update(serialized_dict)
     signature = d.hexdigest()
 
 After the signature is the actual message, always in four frames of bytes.
 The four dictionaries that compose a message are serialized separately,
 in the order of header, parent header, metadata, and content.
 These can be serialized by any function that turns a dict into bytes.
 The default and most common serialization is JSON, but msgpack and pickle
 are common alternatives.
 
 After the serialized dicts are zero to many raw data buffers,
 which can be used by message types that support binary data (mainly apply and data_pub).
 
 
 Python functional API
 =====================
 
 As messages are dicts, they map naturally to a ``func(**kw)`` call form.  We
 should develop, at a few key points, functional forms of all the requests that
 take arguments in this manner and automatically construct the necessary dict
 for sending.
 
 In addition, the Python implementation of the message specification extends
 messages upon deserialization to the following form for convenience::
 
     {
       'header' : dict,
       # The msg's unique identifier and type are always stored in the header,
       # but the Python implementation copies them to the top level.
       'msg_id' : uuid,
       'msg_type' : str,
       'parent_header' : dict,
       'content' : dict,
       'metadata' : dict,
     }
 
 All messages sent to or received by any IPython process should have this
 extended structure.
 
 
 Messages on the shell ROUTER/DEALER sockets
 ===========================================
 
 .. _execute:
 
 Execute
 -------
 
 This message type is used by frontends to ask the kernel to execute code on
 behalf of the user, in a namespace reserved to the user's variables (and thus
 separate from the kernel's own internal code and variables).
 
 Message type: ``execute_request``::
 
     content = {
         # Source code to be executed by the kernel, one or more lines.
     'code' : str,
 
     # A boolean flag which, if True, signals the kernel to execute
     # this code as quietly as possible.
     # silent=True forces store_history to be False,
     # and will *not*:
     #   - broadcast output on the IOPUB channel
     #   - have an execute_result
     # The default is False.
     'silent' : bool,
 
     # A boolean flag which, if True, signals the kernel to populate history
     # The default is True if silent is False.  If silent is True, store_history
     # is forced to be False.
     'store_history' : bool,
 
     # A dict mapping names to expressions to be evaluated in the
     # user's dict. The rich display-data representation of each will be evaluated after execution.
     # See the display_data content for the structure of the representation data.
     'user_expressions' : dict,
 
     # Some frontends do not support stdin requests.
     # If raw_input is called from code executed from such a frontend,
     # a StdinNotImplementedError will be raised.
     'allow_stdin' : True,
     }
 
 .. versionchanged:: 5.0
 
     ``user_variables`` removed, because it is redundant with user_expressions.
 
 The ``code`` field contains a single string (possibly multiline) to be executed.
 
 The ``user_expressions`` field deserves a detailed explanation.  In the past, IPython had
 the notion of a prompt string that allowed arbitrary code to be evaluated, and
 this was put to good use by many in creating prompts that displayed system
 status, path information, and even more esoteric uses like remote instrument
 status acquired over the network.  But now that IPython has a clean separation
 between the kernel and the clients, the kernel has no prompt knowledge; prompts
 are a frontend feature, and it should be even possible for different
 frontends to display different prompts while interacting with the same kernel.
 ``user_expressions`` can be used to retrieve this information.
 
 Any error in evaluating any expression in ``user_expressions`` will result in
 only that key containing a standard error message, of the form::
 
     {
         'status' : 'error',
         'ename' : 'NameError',
         'evalue' : 'foo',
         'traceback' : ...
     }
 
 .. Note::
 
    In order to obtain the current execution counter for the purposes of
    displaying input prompts, frontends may make an execution request with an
    empty code string and ``silent=True``.
 
 Upon completion of the execution request, the kernel *always* sends a reply,
 with a status code indicating what happened and additional data depending on
 the outcome.  See :ref:`below <execution_results>` for the possible return
 codes and associated data.
 
 .. seealso::
 
     :ref:`execution_semantics`
 
 .. _execution_counter:
 
 Execution counter (prompt number)
 ~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~~
 
 The kernel should have a single, monotonically increasing counter of all execution
 requests that are made with ``store_history=True``. This counter is used to populate
 the ``In[n]`` and ``Out[n]`` prompts.  The value of this counter will be returned as the
 ``execution_count`` field of all ``execute_reply`` and ``execute_input`` messages.
 
 .. _execution_results:
 
 Execution results
 ~~~~~~~~~~~~~~~~~
     
 Message type: ``execute_reply``::
 
     content = {
       # One of: 'ok' OR 'error' OR 'abort'
       'status' : str,
 
       # The global kernel counter that increases by one with each request that 
       # stores history.  This will typically be used by clients to display
       # prompt numbers to the user.  If the request did not store history, this will
       # be the current value of the counter in the kernel.
       'execution_count' : int,
     }
 
 When status is 'ok', the following extra fields are present::
 
     {
       # 'payload' will be a list of payload dicts.
       # Each execution payload is a dict with string keys that may have been
       # produced by the code being executed.  It is retrieved by the kernel at
       # the end of the execution and sent back to the front end, which can take
       # action on it as needed.
       # The only requirement of each payload dict is that it have a 'source' key,
       # which is a string classifying the payload (e.g. 'pager').
       'payload' : list(dict),
 
       # Results for the user_expressions.
       'user_expressions' : dict,
     }
 
 .. versionchanged:: 5.0
 
     ``user_variables`` is removed, use user_expressions instead.
 
 .. admonition:: Execution payloads
     
    The notion of an 'execution payload' is different from a return value of a
    given set of code, which normally is just displayed on the execute_result stream
    through the PUB socket.  The idea of a payload is to allow special types of
    code, typically magics, to populate a data container in the IPython kernel
    that will be shipped back to the caller via this channel.  The kernel
    has an API for this in the PayloadManager::
 
        ip.payload_manager.write_payload(payload_dict)
 
    which appends a dictionary to the list of payloads.
    
    The payload API is not yet stabilized,
    and should probably not be supported by non-Python kernels at this time.
    In such cases, the payload list should always be empty.
 
    
 When status is 'error', the following extra fields are present::
 
     {
       'ename' : str,   # Exception name, as a string
       'evalue' : str,  # Exception value, as a string
 
       # The traceback will contain a list of frames, represented each as a
       # string.  For now we'll stick to the existing design of ultraTB, which
       # controls exception level of detail statefully.  But eventually we'll
       # want to grow into a model where more information is collected and
       # packed into the traceback object, with clients deciding how little or
       # how much of it to unpack.  But for now, let's start with a simple list
       # of strings, since that requires only minimal changes to ultratb as
       # written.
       'traceback' : list,
     }
 
 
 When status is 'abort', there are for now no additional data fields.  This
 happens when the kernel was interrupted by a signal.
 
 .. _msging_inspection:
 
 Introspection
 -------------
 
 Code can be inspected to show useful information to the user.
 It is up to the Kernel to decide what information should be displayed, and its formatting.
 
 Message type: ``inspect_request``::
 
     content = {
         # The code context in which introspection is requested
         # this may be up to an entire multiline cell.
         'code' : str,
         
         # The cursor position within 'code' (in unicode characters) where inspection is requested
         'cursor_pos' : int,
 
         # The level of detail desired.  In IPython, the default (0) is equivalent to typing
         # 'x?' at the prompt, 1 is equivalent to 'x??'.
         # The difference is up to kernels, but in IPython level 1 includes the source code
         # if available.
         'detail_level' : 0 or 1,
     }
 
 .. versionchanged:: 5.0
 
     ``object_info_request`` renamed to ``inspect_request``.
 
 .. versionchanged:: 5.0
 
     ``name`` key replaced with ``code`` and ``cursor_pos``,
     moving the lexing responsibility to the kernel.
 
 The reply is a mime-bundle, like a `display_data`_ message,
 which should be a formatted representation of information about the context.
 In the notebook, this is used to show tooltips over function calls, etc.
 
 Message type: ``inspect_reply``::
 
     content = {
         # 'ok' if the request succeeded or 'error', with error information as in all other replies.
         'status' : 'ok',
         
         # data can be empty if nothing is found
         'data' : dict,
         'metadata' : dict,
     }
 
 .. versionchanged:: 5.0
 
     ``object_info_reply`` renamed to ``inspect_reply``.
 
 .. versionchanged:: 5.0
 
     Reply is changed from structured data to a mime bundle,  allowing formatting decisions to be made by the kernel.
 
 .. _msging_completion:
 
 Completion
 ----------
 
 Message type: ``complete_request``::
 
     content = {
         # The code context in which completion is requested
         # this may be up to an entire multiline cell, such as
         # 'foo = a.isal'
         'code' : str,
         
         # The cursor position within 'code' (in unicode characters) where completion is requested
         'cursor_pos' : int,
     }
 
 .. versionchanged:: 5.0
 
     ``line``, ``block``, and ``text`` keys are removed in favor of a single ``code`` for context.
     Lexing is up to the kernel.
 
 
 Message type: ``complete_reply``::
 
     content = {
     # The list of all matches to the completion request, such as
     # ['a.isalnum', 'a.isalpha'] for the above example.
     'matches' : list,
     
     # The range of text that should be replaced by the above matches when a completion is accepted.
     # typically cursor_end is the same as cursor_pos in the request.
     'cursor_start' : int,
     'cursor_end' : int,
     
     # Information that frontend plugins might use for extra display information about completions.
     'metadata' : dict,
     
     # status should be 'ok' unless an exception was raised during the request,
     # in which case it should be 'error', along with the usual error message content
     # in other messages.
     'status' : 'ok'
     }
 
 .. versionchanged:: 5.0
 
     - ``matched_text`` is removed in favor of ``cursor_start`` and ``cursor_end``.
     - ``metadata`` is added for extended information.
 
 .. _msging_history:
 
 History
 -------
 
 For clients to explicitly request history from a kernel.  The kernel has all
 the actual execution history stored in a single location, so clients can
 request it from the kernel when needed.
 
 Message type: ``history_request``::
 
     content = {
     
       # If True, also return output history in the resulting dict.
       'output' : bool,
 
       # If True, return the raw input history, else the transformed input.
       'raw' : bool,
 
       # So far, this can be 'range', 'tail' or 'search'.
       'hist_access_type' : str,
       
       # If hist_access_type is 'range', get a range of input cells. session can
       # be a positive session number, or a negative number to count back from
       # the current session.
       'session' : int,
       # start and stop are line numbers within that session.
       'start' : int,
       'stop' : int,
       
       # If hist_access_type is 'tail' or 'search', get the last n cells.
       'n' : int,
       
       # If hist_access_type is 'search', get cells matching the specified glob
       # pattern (with * and ? as wildcards).
       'pattern' : str,
 
       # If hist_access_type is 'search' and unique is true, do not
       # include duplicated history.  Default is false.
       'unique' : bool,
       
     }
 
 .. versionadded:: 4.0
    The key ``unique`` for ``history_request``.
 
 Message type: ``history_reply``::
 
     content = {
       # A list of 3 tuples, either:
       # (session, line_number, input) or
       # (session, line_number, (input, output)),
       # depending on whether output was False or True, respectively.
       'history' : list,
     }
 
+.. _msging_is_complete:
+
+Code completeness
+-----------------
+
+.. versionadded:: 5.1
+
+When the user enters a line in a console style interface, the console must
+decide whether to immediately execute the current code, or whether to show a
+continuation prompt for further input. For instance, in Python ``a = 5`` would
+be executed immediately, while ``for i in range(5):`` would expect further input.
+
+Frontends may have ways to override this, forcing the code to be sent for
+execution or forcing a continuation prompt. If the kernel does not reply promptly,
+the frontend will probably default to sending the code to be executed.
+
+Message type: ``is_complete_request``::
+
+    content = {
+        # The code entered so far as a multiline string
+        'code' : str,
+    }
+
+Message type: ``complete_reply``::
+
+    content = {
+        # True if the code is ready to execute, False if not
+        'complete' : bool,
+    }
 
 Connect
 -------
 
 When a client connects to the request/reply socket of the kernel, it can issue
 a connect request to get basic information about the kernel, such as the ports
 the other ZeroMQ sockets are listening on. This allows clients to only have
 to know about a single port (the shell channel) to connect to a kernel.
 
 Message type: ``connect_request``::
 
     content = {
     }
 
 Message type: ``connect_reply``::
 
     content = {
         'shell_port' : int,   # The port the shell ROUTER socket is listening on.
         'iopub_port' : int,   # The port the PUB socket is listening on.
         'stdin_port' : int,   # The port the stdin ROUTER socket is listening on.
         'hb_port' : int,      # The port the heartbeat socket is listening on.
     }
 
 .. _msging_kernel_info:
 
 Kernel info
 -----------
 
 If a client needs to know information about the kernel, it can
 make a request of the kernel's information.
 This message can be used to fetch core information of the
 kernel, including language (e.g., Python), language version number and
 IPython version number, and the IPython message spec version number.
 
 Message type: ``kernel_info_request``::
 
     content = {
     }
 
 Message type: ``kernel_info_reply``::
 
     content = {
         # Version of messaging protocol.
         # The first integer indicates major version.  It is incremented when
         # there is any backward incompatible change.
         # The second integer indicates minor version.  It is incremented when
         # there is any backward compatible change.
         'protocol_version': 'X.Y.Z',
 
         # The kernel implementation name
         # (e.g. 'ipython' for the IPython kernel)
         'implementation': str,
 
         # Implementation version number.
         # The version number of the kernel's implementation
         # (e.g. IPython.__version__ for the IPython kernel)
         'implementation_version': 'X.Y.Z', 
 
         # Programming language in which kernel is implemented.
         # Kernel included in IPython returns 'python'.
         'language': str,
         
         # Language version number.
         # It is Python version number (e.g., '2.7.3') for the kernel
         # included in IPython.
         'language_version': 'X.Y.Z',
 
         # A banner of information about the kernel,
         # which may be desplayed in console environments.
         'banner' : str,
     }
 
 .. versionchanged:: 5.0
 
     Versions changed from lists of integers to strings.
     
 .. versionchanged:: 5.0
 
     ``ipython_version`` is removed.
 
 .. versionchanged:: 5.0
 
     ``implementation``, ``implementation_version``, and ``banner`` keys are added.
 
 .. _msging_shutdown:
 
 Kernel shutdown
 ---------------
 
 The clients can request the kernel to shut itself down; this is used in
 multiple cases:
 
 - when the user chooses to close the client application via a menu or window
   control.
 - when the user types 'exit' or 'quit' (or their uppercase magic equivalents).
 - when the user chooses a GUI method (like the 'Ctrl-C' shortcut in the
   IPythonQt client) to force a kernel restart to get a clean kernel without
   losing client-side state like history or inlined figures.
 
 The client sends a shutdown request to the kernel, and once it receives the
 reply message (which is otherwise empty), it can assume that the kernel has
 completed shutdown safely.
 
 Upon their own shutdown, client applications will typically execute a last
 minute sanity check and forcefully terminate any kernel that is still alive, to
 avoid leaving stray processes in the user's machine.
 
 Message type: ``shutdown_request``::
 
     content = {
         'restart' : bool # whether the shutdown is final, or precedes a restart
     }
 
 Message type: ``shutdown_reply``::
 
     content = {
         'restart' : bool # whether the shutdown is final, or precedes a restart
     }
 
 .. Note::
 
    When the clients detect a dead kernel thanks to inactivity on the heartbeat
    socket, they simply send a forceful process termination signal, since a dead
    process is unlikely to respond in any useful way to messages.
     
 
 Messages on the PUB/SUB socket
 ==============================
 
 Streams (stdout,  stderr, etc)
 ------------------------------
 
 Message type: ``stream``::
 
     content = {
         # The name of the stream is one of 'stdout', 'stderr'
         'name' : str,
     
         # The data is an arbitrary string to be written to that stream
         'data' : str,
     }
 
 Display Data
 ------------
 
 This type of message is used to bring back data that should be displayed (text,
 html, svg, etc.) in the frontends. This data is published to all frontends.
 Each message can have multiple representations of the data; it is up to the
 frontend to decide which to use and how. A single message should contain all
 possible representations of the same information. Each representation should
 be a JSON'able data structure, and should be a valid MIME type.
 
 Some questions remain about this design:
 
 * Do we use this message type for execute_result/displayhook? Probably not, because
   the displayhook also has to handle the Out prompt display. On the other hand
   we could put that information into the metadata section.
 
 .. _display_data:
 
 Message type: ``display_data``::
 
     content = {
 
         # Who create the data
         'source' : str,
 
         # The data dict contains key/value pairs, where the keys are MIME
         # types and the values are the raw data of the representation in that
         # format.
         'data' : dict,
 
         # Any metadata that describes the data
         'metadata' : dict
     }
 
 
 The ``metadata`` contains any metadata that describes the output.
 Global keys are assumed to apply to the output as a whole.
 The ``metadata`` dict can also contain mime-type keys, which will be sub-dictionaries,
 which are interpreted as applying only to output of that type.
 Third parties should put any data they write into a single dict
 with a reasonably unique name to avoid conflicts.
 
 The only metadata keys currently defined in IPython are the width and height
 of images::
 
     metadata = {
       'image/png' : {
         'width': 640,
         'height': 480
       }
     }
 
 
 .. versionchanged:: 5.0
 
     `application/json` data should be unpacked JSON data,
     not double-serialized as a JSON string.
 
 
 Raw Data Publication
 --------------------
 
 ``display_data`` lets you publish *representations* of data, such as images and html.
 This ``data_pub`` message lets you publish *actual raw data*, sent via message buffers.
 
 data_pub messages are constructed via the :func:`IPython.lib.datapub.publish_data` function:
 
 .. sourcecode:: python
 
     from IPython.kernel.zmq.datapub import publish_data
     ns = dict(x=my_array)
     publish_data(ns)
 
 
 Message type: ``data_pub``::
 
     content = {
         # the keys of the data dict, after it has been unserialized
         'keys' : ['a', 'b']
     }
     # the namespace dict will be serialized in the message buffers,
     # which will have a length of at least one
     buffers = [b'pdict', ...]
 
 
 The interpretation of a sequence of data_pub messages for a given parent request should be
 to update a single namespace with subsequent results.
 
 .. note::
 
     No frontends directly handle data_pub messages at this time.
     It is currently only used by the client/engines in :mod:`IPython.parallel`,
     where engines may publish *data* to the Client,
     of which the Client can then publish *representations* via ``display_data``
     to various frontends.
 
 Code inputs
 -----------
 
 To let all frontends know what code is being executed at any given time, these
 messages contain a re-broadcast of the ``code`` portion of an
 :ref:`execute_request <execute>`, along with the :ref:`execution_count
 <execution_counter>`.
 
 Message type: ``execute_input``::
 
     content = {
         'code' : str,  # Source code to be executed, one or more lines
 
         # The counter for this execution is also provided so that clients can
         # display it, since IPython automatically creates variables called _iN
         # (for input prompt In[N]).
         'execution_count' : int
     }
 
 .. versionchanged:: 5.0
 
     ``pyin`` is renamed to ``execute_input``.
 
 
 Execution results
 -----------------
 
 Results of an execution are published as an ``execute_result``.
 These are identical to `display_data`_ messages, with the addition of an ``execution_count`` key.
 
 Results can have multiple simultaneous formats depending on its
 configuration. A plain text representation should always be provided
 in the ``text/plain`` mime-type. Frontends are free to display any or all of these
 according to its capabilities.
 Frontends should ignore mime-types they do not understand. The data itself is
 any JSON object and depends on the format. It is often, but not always a string.
 
 Message type: ``execute_result``::
 
     content = {
 
         # The counter for this execution is also provided so that clients can
         # display it, since IPython automatically creates variables called _N
         # (for prompt N).
         'execution_count' : int,
 
         # data and metadata are identical to a display_data message.
         # the object being displayed is that passed to the display hook,
         # i.e. the *result* of the execution.
         'data' : dict,
         'metadata' : dict,
     }
 
 Execution errors
 ----------------
 
 When an error occurs during code execution
 
 Message type: ``error``::
 
     content = {
        # Similar content to the execute_reply messages for the 'error' case,
        # except the 'status' field is omitted.
     }
 
 .. versionchanged:: 5.0
 
     ``pyerr`` renamed to ``error``
 
 Kernel status
 -------------
 
 This message type is used by frontends to monitor the status of the kernel.
 
 Message type: ``status``::
 
     content = {
         # When the kernel starts to handle a message, it will enter the 'busy'
         # state and when it finishes, it will enter the 'idle' state.
         # The kernel will publish state 'starting' exactly once at process startup.
         execution_state : ('busy', 'idle', 'starting')
     }
 
 .. versionchanged:: 5.0
 
     Busy and idle messages should be sent before/after handling every message,
     not just execution.
 
 Clear output
 ------------
 
 This message type is used to clear the output that is visible on the frontend.
 
 Message type: ``clear_output``::
 
     content = {
 
         # Wait to clear the output until new output is available.  Clears the
         # existing output immediately before the new output is displayed.  
         # Useful for creating simple animations with minimal flickering.
         'wait' : bool,
     }
 
 .. versionchanged:: 4.1
 
     ``stdout``, ``stderr``, and ``display`` boolean keys for selective clearing are removed,
     and ``wait`` is added.
     The selective clearing keys are ignored in v4 and the default behavior remains the same,
     so v4 clear_output messages will be safely handled by a v4.1 frontend.
 
 
 Messages on the stdin ROUTER/DEALER sockets
 ===========================================
 
 This is a socket where the request/reply pattern goes in the opposite direction:
 from the kernel to a *single* frontend, and its purpose is to allow
 ``raw_input`` and similar operations that read from ``sys.stdin`` on the kernel
 to be fulfilled by the client. The request should be made to the frontend that
 made the execution request that prompted ``raw_input`` to be called. For now we
 will keep these messages as simple as possible, since they only mean to convey
 the ``raw_input(prompt)`` call.
 
 Message type: ``input_request``::
 
     content = {
         # the text to show at the prompt
         'prompt' : str,
         # Is the request for a password?
         # If so, the frontend shouldn't echo input.
         'password' : bool
     }
 
 Message type: ``input_reply``::
 
     content = { 'value' : str }
 
 
 When ``password`` is True, the frontend should not echo the input as it is entered.
 
 .. versionchanged:: 5.0
 
     ``password`` key added.
 
 .. note::
 
     The stdin socket of the client is required to have the same zmq IDENTITY
     as the client's shell socket.
     Because of this, the ``input_request`` must be sent with the same IDENTITY
     routing prefix as the ``execute_reply`` in order for the frontend to receive
     the message.
 
 .. note::
 
    We do not explicitly try to forward the raw ``sys.stdin`` object, because in
    practice the kernel should behave like an interactive program.  When a
    program is opened on the console, the keyboard effectively takes over the
    ``stdin`` file descriptor, and it can't be used for raw reading anymore.
    Since the IPython kernel effectively behaves like a console program (albeit
    one whose "keyboard" is actually living in a separate process and
    transported over the zmq connection), raw ``stdin`` isn't expected to be
    available.
 
 .. _kernel_heartbeat:
 
 Heartbeat for kernels
 =====================
 
 Clients send ping messages on a REQ socket, which are echoed right back
 from the Kernel's REP socket. These are simple bytestrings, not full JSON messages described above.
 
 
 Custom Messages
 ===============
 
 .. versionadded:: 4.1
 
 IPython 2.0 (msgspec v4.1) adds a messaging system for developers to add their own objects with Frontend
 and Kernel-side components, and allow them to communicate with each other.
 To do this, IPython adds a notion of a ``Comm``, which exists on both sides,
 and can communicate in either direction.
 
 These messages are fully symmetrical - both the Kernel and the Frontend can send each message,
 and no messages expect a reply.
 The Kernel listens for these messages on the Shell channel,
 and the Frontend listens for them on the IOPub channel.
 
 Opening a Comm
 --------------
 
 Opening a Comm produces a ``comm_open`` message, to be sent to the other side::
 
     {
       'comm_id' : 'u-u-i-d',
       'target_name' : 'my_comm',
       'data' : {}
     }
 
 Every Comm has an ID and a target name.
 The code handling the message on the receiving side is responsible for maintaining a mapping
 of target_name keys to constructors.
 After a ``comm_open`` message has been sent,
 there should be a corresponding Comm instance on both sides.
 The ``data`` key is always a dict and can be any extra JSON information used in initialization of the comm.
 
 If the ``target_name`` key is not found on the receiving side,
 then it should immediately reply with a ``comm_close`` message to avoid an inconsistent state.
 
 Comm Messages
 -------------
 
 Comm messages are one-way communications to update comm state,
 used for synchronizing widget state, or simply requesting actions of a comm's counterpart.
 
 Essentially, each comm pair defines their own message specification implemented inside the ``data`` dict.
 
 There are no expected replies (of course, one side can send another ``comm_msg`` in reply).
 
 Message type: ``comm_msg``::
 
     {
       'comm_id' : 'u-u-i-d',
       'data' : {}
     }
 
 Tearing Down Comms
 ------------------
 
 Since comms live on both sides, when a comm is destroyed the other side must be notified.
 This is done with a ``comm_close`` message.
 
 Message type: ``comm_close``::
 
     {
       'comm_id' : 'u-u-i-d',
       'data' : {}
     }
 
 Output Side Effects
 -------------------
 
 Since comm messages can execute arbitrary user code,
 handlers should set the parent header and publish status busy / idle,
 just like an execute request.
 
 
 To Do
 =====
 
 Missing things include:
 
 * Important: finish thinking through the payload concept and API.
 
 .. include:: ../links.txt

docs/source/development/wrapperkernels.rst

@@ -1,153 +1,164 b''
 Making simple Python wrapper kernels
 ====================================
 
 .. versionadded:: 3.0
 
 You can now re-use the kernel machinery in IPython to easily make new kernels.
 This is useful for languages that have Python bindings, such as `Octave
 <http://www.gnu.org/software/octave/>`_ (via
 `Oct2Py <http://blink1073.github.io/oct2py/docs/index.html>`_), or languages
 where the REPL can be controlled in a tty using `pexpect <http://pexpect.readthedocs.org/en/latest/>`_,
 such as bash.
 
 .. seealso::
 
    `bash_kernel <https://github.com/takluyver/bash_kernel>`_
      A simple kernel for bash, written using this machinery
 
 Required steps
 --------------
 
 Subclass :class:`IPython.kernel.zmq.kernelbase.Kernel`, and implement the
 following methods and attributes:
 
 .. class:: MyKernel
 
    .. attribute:: implementation
                   implementation_version
                   language
                   language_version
                   banner
     
      Information for :ref:`msging_kernel_info` replies. 'Implementation' refers
      to the kernel (e.g. IPython), and 'language' refers to the language it
      interprets (e.g. Python). The 'banner' is displayed to the user in console
      UIs before the first prompt. All of these values are strings.
 
    .. method:: do_execute(code, silent, store_history=True, user_expressions=None, allow_stdin=False)
    
      Execute user code.
      
      :param str code: The code to be executed.
      :param bool silent: Whether to display output.
      :param bool store_history: Whether to record this code in history and
          increase the execution count. If silent is True, this is implicitly
          False.
      :param dict user_expressions: Mapping of names to expressions to evaluate
          after the code has run. You can ignore this if you need to.
      :param bool allow_stdin: Whether the frontend can provide input on request
          (e.g. for Python's :func:`raw_input`).
      
      Your method should return a dict containing the fields described in
      :ref:`execution_results`. To display output, it can send messages
      using :meth:`~IPython.kernel.zmq.kernelbase.Kernel.send_response`.
      See :doc:`messaging` for details of the different message types.
 
 To launch your kernel, add this at the end of your module::
 
     if __name__ == '__main__':
         from IPython.kernel.zmq.kernelapp import IPKernelApp
         IPKernelApp.launch_instance(kernel_class=MyKernel)
 
 Example
 -------
 
 ``echokernel.py`` will simply echo any input it's given to stdout::
 
     from IPython.kernel.zmq.kernelbase import Kernel
 
     class EchoKernel(Kernel):
         implementation = 'Echo'
         implementation_version = '1.0'
         language = 'no-op'
         language_version = '0.1'
         banner = "Echo kernel - as useful as a parrot"
 
         def do_execute(self, code, silent, store_history=True, user_expressions=None,
                        allow_stdin=False):
             if not silent:
                 stream_content = {'name': 'stdout', 'data':code}
                 self.send_response(self.iopub_socket, 'stream', stream_content)
 
             return {'status': 'ok',
                     # The base class increments the execution count
                     'execution_count': self.execution_count,
                     'payload': [],
                     'user_expressions': {},
                    }
 
     if __name__ == '__main__':
         from IPython.kernel.zmq.kernelapp import IPKernelApp
         IPKernelApp.launch_instance(kernel_class=EchoKernel)
 
 Here's the Kernel spec ``kernel.json`` file for this::
 
     {"argv":["python","-m","echokernel", "-f", "{connection_file}"],
      "display_name":"Echo",
      "language":"no-op"
     }
 
 
 Optional steps
 --------------
 
 You can override a number of other methods to improve the functionality of your
 kernel. All of these methods should return a dictionary as described in the
 relevant section of the :doc:`messaging spec <messaging>`.
 
 .. class:: MyKernel
 
    .. method:: do_complete(code, cusor_pos)
 
      Code completion
      
      :param str code: The code already present
      :param int cursor_pos: The position in the code where completion is requested
      
      .. seealso::
      
         :ref:`msging_completion` messages
 
    .. method:: do_inspect(code, cusor_pos, detail_level=0)
 
      Object introspection
      
      :param str code: The code
      :param int cursor_pos: The position in the code where introspection is requested
      :param int detail_level: 0 or 1 for more or less detail. In IPython, 1 gets
          the source code.
      
      .. seealso::
      
         :ref:`msging_inspection` messages
 
    .. method:: do_history(hist_access_type, output, raw, session=None, start=None, stop=None, n=None, pattern=None, unique=False)
 
      History access. Only the relevant parameters for the type of history
      request concerned will be passed, so your method definition must have defaults
      for all the arguments shown with defaults here.
 
      .. seealso::
      
         :ref:`msging_history` messages
 
+   .. method:: do_is_complete(code)
+   
+     Is code entered in a console-like interface complete and ready to execute,
+     or should a continuation prompt be shown?
+     
+     :param str code: The code entered so far - possibly multiple lines
+     
+     .. seealso::
+     
+        :ref:`msging_is_complete` messages
+
    .. method:: do_shutdown(restart)
 
      Shutdown the kernel. You only need to handle your own clean up - the kernel
      machinery will take care of cleaning up its own things before stopping.
      
      :param bool restart: Whether the kernel will be started again afterwards
      
      .. seealso::
      
         :ref:`msging_shutdown` messages