 | webplotlibA package for creating server-side charts/graphs using matplotlib |
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A package for creating server-side charts/graphs using matplotlib As a developer, the need to display data charts and graphs on your web site/service presents two major generation options: server-side, or client/browser-side.- The primary benefits of server-side chart generation are: completely consistent display across browsers (even IE can handle showing images), and re-use of the chart image outside the browser, e.g. in generating PDF documents.- The primary benefit of client/browser-side chart generation are: interactivity (if needed) and generally more dynamic behavior, e.g. immediately updated charts with a user's new input.webplotlib is a Python library that could be for you if you want Python server-side chart generation, providing a convenient and modular package/API. It is GPL licensed.InstallationNOTE: Even though I wrote this package for a Django context, it can easily be used without/outside Django. See below for more details.webplotlib has these direct dependencies:- Matplotlib - you can get this via your OS packaging system, or install from source. I prefer to install version 1.0.1 from source. You can install this globally (e.g. sudo pip install numpy) or locally to one virtualenv (pip install numpy). Matplotlib has numerous system dependencies, e.g. on Ubuntu, install packages: python, python-dev, libpng12-dev, libfreetype6-dev.- Numpy, which you'll need for Matplotlib too. You can also install this globally or for the virtualenv (pip install numpy). For its full functionality you may want to install system dependencies, e.g. on Ubuntu, the packages libatlas-base-dev, gfortran, gcc, g++ packages. py.test, if you want to run the unit tests.With dependencies installed, install webplotlib from PyPI with:pip install webplotlibOr you can install from source (presumably you're already in a virtualenv) via github.Usage:While I wrote webplotlib to work with a Django project, currently there are no direct dependencies on Django, so you can treat webplotlib like any other Python package and call it directly with,from webplotlib.chart_builders import create_chart_as_png_str# When you have at least one sequence (list, tuple, iterable)# of data, you can plot it:chart_png_str = create_chart_as_png_str( 'timeseries', {'data': ], 'names': 'MyDataLine'}, labels_dct={'title': 'TheBigBoard', 'x': 'Data', 'y': 'Value'})# Save chart_png_str, etc.More examples of usage can be found in the test_chart_builders.py module.Django integration: I found confusing and inconsistent examples of integrating Matplotlib with Django on the web, so experimented a bit on my own. You can see some examples in webplotlib's views.py file which shows how to serve/return server-side generated PNG charts directly as a string - which can be handy for rapid feedback when you want to style a chart.So to use webplotlib in Django, update your Django project's settings.py INSTALLED_APPS to include 'webplotlib' and also update your project's urls.py file (there's nothing in models.py yet) to have something like,urlpatterns = patterns('', ... (r'^wpl/', include('webplotlib.urls')), ... )Also, consider using webplotlib with my app django-metaimage, which readily handles creating new images and saving them to a useful Django ORM model instance/representation.TestingBasic unit tests can be run using Tox or py.test.History + Designwebplotlib relies on Matplotlib - the most powerful and popular Python charting package available - for the actual chart generation. But what I found (as of Spring 2011) was a lack of well-abstracted examples of Matplotlib usage in web environments, as well as a lack of examples using its non-interactive, object-oriented, programmer's interface (by contrast, there are tons of examples for interactive user-driven chart creation, emulating MATLAB). Thus the need to write a new app that could quickly be used to generate server-side charts.I wanted a way to generate a Matplotlib chart (time-series and bar charts initially) with a single function call that would create and return the raw chart data/image as a string - from there it's easy to save it, or process it further (e.g. add watermark), or return it via HTTP, etc. After studying lots of online examples and documentation, experimenting, and refactoring, enter webplotlib. Initially it supports time-series and bar charts, taking sequences and returning non-ugly charts as PNG-image strings you can readily use. There will be more abstractions (e.g. defining chart templates separately) and improvements to come, but this version is usable now.Alternatives: Why not use a Flash library? Not OSS, same limitations as Javascript library. And why not use a Javascript library? After looking at a bunch of client-side libraries (Grafico, Highcharts, flot, Google Chart Tools, dygraphs, Raphaël), I thought Protovis was it - the one tool to rule them all. But after making sense of their docs and examples, I found displays were inconsistent: simple charts would look fine in Firefox 3/4 but show up in Chrome without tick marks and labels, which was unacceptable. And I didn't even bother looking at IE rendering, where more pain was likely. Furthermore, my requirements changed; I needed to use the charts in reporting, so it was essential to have the charts as images, consistent across several mediums. So server-side generation was the way to go, and with Python, one finds out very quickly there's no serious competition to Matplotlib. Requirements: · Python
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