MEP25: Serialization

.. contents::

:local:

Status

**Discussion**

Branches and Pull requests

* development branches:

* related pull requests:

Abstract

This MEP aims at adding a serializable ``Controller`` objects to act

as an ``Artist`` managers. Users would then communicate changes to an

``Artist`` via a ``Controller``. In this way, functionality of the

``Controller`` objects may be added incrementally since each

``Artist`` is still responsible for drawing everything. The goal is to

create an API that is usable both by graphing libraries requiring

high-level descriptions of figures and libraries requiring low-level

interpretations.

Detailed description

Matplotlib is a core plotting engine with an API that many users

already understand. It's difficult/impossible for other graphing

libraries to (1) get a complete figure description, (2) output raw

data from the figure object as the user has provided it, (3)

understand the semantics of the figure objects without heuristics,

and (4) give matplotlib a complete figure description to visualize. In

addition, because an ``Artist`` has no conception of its own semantics

within the figure, it's difficult to interact with them in a natural

way.

In this sense, matplotlib will adopt a standard

Model-View-Controller (MVC) framework. The *Model* will be the user

defined data, style, and semantics. The *Views* are the ensemble of

each individual ``Artist``, which are responsible for producing the

final image based on the *model*. The *Controller* will be the

``Controller`` object managing its set of ``Artist`` objects.

The ``Controller`` must be able to export the information that it's

carrying about the figure on command, perhaps via a ``to_json`` method

or similar. Because it would be extremely extraneous to duplicate all

of the information in the model with the controller, only

user-specified information (data + style) are explicitly kept. If a

user wants more information (defaults) from the view/model, it should

be able to query for it.

- This might be annoying to do, non-specified kwargs are pulled from

the rcParams object which is in turn created from reading a user

specified file and can be dynamically changed at run time. I

suppose we could keep a dict of default defaults and compare against

that. Not clear how this will interact with the style sheet

[[MEP26]] - @tacaswell

Additional Notes:

* The `raw data` does not necessarily need to be a ``list``,

``ndarray``, etc. Rather, it can more abstractly just have a method

to yield data when needed.

* Because the ``Controller`` will contain extra information that users

may not want to keep around, it should *not* be created by

default. You should be able to both (a) instantiate a ``Controller``

with a figure and (b) build a figure with a ``Controller``.

Use Cases:

* Export all necessary informat

* Serializing a matplotlib figure, saving it, and being able to rerun later.

* Any other source sending an appropriately formatted representation to matplotlib to open

Examples

Here are some examples of what the controllers should be able to do.

1. Instantiate a matplotlib figure from a serialized representation (e.g., JSON): ::

2. Manage artists from the controller (e.g., Line2D): ::

3. Export serializable figure representation: ::

Implementation

1. Create base ``Controller`` objects that are able to manage

``Artist`` objects (e.g., ``Hist``)

Comments:

* initialization should happen via unpacking ``**``, so we need a

copy of call signature parameter for the ``Artist`` we're

ultimately trying to control. Unfortunate hard-coded

repetition...

* should the additional ``**kwargs`` accepted by each ``Artist``

be tracked at the ``Controller``

* how does a ``Controller`` know which artist belongs where? E.g.,

do we need to pass ``axes`` references?

Progress:

* A simple NB demonstrating some functionality for

``Line2DController`` objects:

http://nbviewer.ipython.org/gist/theengineear/f0aa8d79f64325e767c0

2. Write in protocols for the ``Controller`` to *update* the model.

Comments:

* how should containers be dealt with? E.g., what happens to old

patches when we re-bin a histogram?

* in the link from (1), the old line is completely destroyed and

redrawn, what if something is referencing it?

3. Create method by which a json object can be assembled from the

``Controllers``

4. Deal with serializing the unserializable aspects of a figure (e.g.,

non-affine transforms?)

5. Be able to instantiate from a serialized representation

6. Reimplement the existing pyplot and Axes method,

e.g. ``pyplot.hist`` and ``Axes.hist`` in terms of the new

controller class.

> @theengineer: in #2 above, what do you mean by *get updates* from

each ``Artist``?

^ Yup. The ``Controller`` *shouldn't* need to get updated. This just

happens in #3. Delete comments when you see this.

Backward compatibility

* pickling will change

* non-affine transformations will require a defined pickling method

Alternatives

PR #3150 suggested adding semantics by parasitically attaching extra

containers to axes objects. This is a more complete solution with what

should be a more developed/flexible/powerful framework.

.. _MEP-index:

Matplotlib Enhancement Proposals

.. htmlonly::

:Release: |version|

:Date: |today|

.. toctree::

:maxdepth: 1

template

MEP25

MEP Template

This MEP template is a guideline of the sections that a MEP should contain. Extra sections may be added if appropriate, and unnecessary sections may be noted as such.

Status

MEPs go through a number of phases in their lifetime:

- **Discussion**: The MEP is being actively discussed on the mailing list and it is being improved by its author. The mailing list discussion of the MEP should include the MEP number (MEPxxx) in the subject line so they can be easily related to the MEP.

- **Progress**: Consensus was reached on the mailing list and implementation work has begun.

- **Completed**: The implementation has been merged into master.

- **Superseded**: This MEP has been abandoned in favor of another approach.

Branches and Pull requests

All development branches containing work on this MEP should be linked to from here.

All pull requests submitted relating to this MEP should be linked to from here. (A MEP does not need to be implemented in a single pull request if it makes sense to implement it in discrete phases).

Abstract

The abstract should be a short description of what the MEP will achieve.

Detailed description

This section describes the need for the MEP. It should describe the existing problem that it is trying to solve and why this MEP makes the situation better. It should include examples of how the new functionality would be used and perhaps some use cases.

Implementation

This section lists the major steps required to implement the MEP. Where possible, it should be noted where one step is dependent on another, and which steps may be optionally omitted. Where it makes sense, each step should include a link related pull requests as the implementation progresses.

Backward compatibility

This section describes the ways in which the MEP breaks backward incompatibility.

Alternatives

If there were any alternative solutions to solving the same problem, they should be discussed here, along with a justification for the chosen approach.

MEP/index