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#format wiki
#language en
== Using MatPlotLib to dynamically generate charts in a Django web service ==
You need to have a working Django installation, plus matplotlib.

=== Example 1 - PIL Buffer ===
{{{
# file charts.py
def simple(request):
    import random
    import django
    import datetime
    
    from matplotlib.backends.backend_agg import FigureCanvasAgg as FigureCanvas
    from matplotlib.figure import Figure
    from matplotlib.dates import DateFormatter

    fig=Figure()
    ax=fig.add_subplot(111)
    x=[]
    y=[]
    now=datetime.datetime.now()
    delta=datetime.timedelta(days=1)
    for i in range(10):
        x.append(now)
        now+=delta
        y.append(random.randint(0, 1000))
    ax.plot_date(x, y, '-')
    ax.xaxis.set_major_formatter(DateFormatter('%Y-%m-%d'))
    fig.autofmt_xdate()
    canvas=FigureCanvas(fig)
    response=django.http.HttpResponse(content_type='image/png')
    canvas.print_png(response)
    return response
}}}

Since some versions of Internet Explorer ignore the content_type. The URL should end with
".png". You can create an entry in your urls.py like this:
{{{
    ...
    (r'^charts/simple.png$', 'myapp.views.charts.simple'),
    ...
}}}
----
 CategoryCookbookMatplotlib