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Implement a couple of suggestions from @jhamrick
Thomas Kluyver -
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1 How IPython Works
1 How IPython works
2 2 =================
3 3
4 4 Terminal IPython
5 5 ----------------
6 6
7 7 When you type ``ipython``, you get the original IPython interface, running in
8 8 the terminal. It does something like this::
9 9
10 10 while True:
11 11 code = input(">>> ")
12 12 exec(code)
13 13
14 14 Of course, it's much more complicated, because it has to deal with multi-line
15 15 code, tab completion using :mod:`readline`, magic commands, and so on. But the
16 16 model is like that: prompt the user for some code, and when they've entered it,
17 17 exec it in the same process.
18 18
19 19 The IPython Kernel
20 20 ------------------
21 21
22 22 All the other interfaces—the Notebook, the Qt console, ``ipython console`` in
23 23 the terminal, and third party interfaces—use the IPython Kernel. This is a
24 24 separate process which is responsible for running user code, and things like
25 25 computing possible completions. Frontends communicate with it using JSON
26 messages sent over ZeroMQ sockets; the protocol they use is described in
26 messages sent over `ZeroMQ <http://zeromq.org/>`_ sockets; the protocol they use is described in
27 27 :doc:`messaging`.
28 28
29 29 The core execution machinery for the kernel is shared with terminal IPython:
30 30
31 31 .. image:: figs/ipy_kernel_and_terminal.png
32 32
33 33 A kernel process can be connected to more than one frontend simultaneously. In
34 34 this case, the different frontends will have access to the same variables.
35 35
36 36 .. TODO: Diagram illustrating this?
37 37
38 38 This design was intended to allow easy development of different frontends based
39 39 on the same kernel, but it also made it possible to support new languages in the
40 40 same frontends, by developing kernels in those languages, and we are refining
41 41 IPython to make that more practical.
42 42
43 43 Today, there are two ways to develop a kernel for another language. Wrapper
44 44 kernels reuse the communications machinery from IPython, and implement only the
45 45 core execution part. Native kernels implement execution and communications in
46 46 the target language:
47 47
48 48 .. image:: figs/other_kernels.png
49 49
50 Wrapper kernels are easier to write quickly for languages that have good Python
51 wrappers, like `Oct2Py <http://blink1073.github.io/oct2py/>`_ for Octave, or
52 languages where it's impractical to implement the communications machinery, like
53 `bash_kernel <https://pypi.python.org/pypi/bash_kernel>`_. Native kernels are
54 likely to be better maintained by the community using them, like
55 `IJulia <https://github.com/JuliaLang/IJulia.jl>`_ or `IHaskell <https://github.com/gibiansky/IHaskell>`_.
56
50 57 .. seealso::
51 58
52 59 :doc:`kernels`
53 60
54 61 :doc:`wrapperkernels`
55 62
56 63 Notebooks
57 64 ---------
58 65
59 66 The Notebook frontend does something extra. In addition to running your code, it
60 67 stores code and output, together with markdown notes, in an editable document
61 68 called a notebook. When you save it, this is sent from your browser to the
62 69 notebook server, which saves it on disk as a JSON file with a ``.ipynb``
63 70 extension.
64 71
65 72 .. image:: figs/notebook_components.png
66 73
67 74 The notebook server, not the kernel, is responsible for saving and loading
68 75 notebooks, so you can edit notebooks even if you don't have the kernel for that
69 76 language—you just won't be able to run code. The kernel doesn't know anything
70 77 about the notebook document: it just gets sent cells of code to execute when the
71 78 user runs them.
72 79
73 80 Exporting to other formats
74 81 ``````````````````````````
75 82
76 83 The Nbconvert tool in IPython converts notebook files to other formats, such as
77 84 HTML, LaTeX, or reStructuredText. This conversion goes through a series of steps:
78 85
79 86 .. image:: figs/nbconvert.png
80 87
81 88 1. Preprocessors modify the notebook in memory. E.g. ExecutePreprocessor runs
82 89 the code in the notebook and updates the output.
83 90 2. An exporter converts the notebook to another file format. Most of the
84 91 exporters use templates for this.
85 92 3. Postprocessors work on the file produced by exporting.
86 93
87 94 The `nbviewer <http://nbviewer.ipython.org/>`_ website uses nbconvert with the
88 95 HTML exporter. When you give it a URL, it fetches the notebook from that URL,
89 96 converts it to HTML, and serves that HTML to you.
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