Charts with MatPlotLibΒΆ
This test is done with a chart generated by matplotlib, a famous charting library for Python Language. You can get it from
Charts are another important thing in reports. Geraldo is compatible with every charting library if it has a way to render the chart as a common image format, like JPG, PNG, GIF, etc:
>>> import os
>>> cur_dir = os.path.dirname(os.path.abspath(__file__))
>>> from django.contrib.auth.models import User
>>> from reportlab.lib.pagesizes import A4
>>> from reportlab.lib.units import cm
>>> from reportlab.lib.enums import TA_CENTER, TA_JUSTIFY, TA_RIGHT
>>> from reportlab.lib.colors import navy, yellow, red
>>> from geraldo import Report, ReportBand, Label, ObjectValue, SystemField,\
... FIELD_ACTION_COUNT, FIELD_ACTION_AVG, FIELD_ACTION_MIN,\
... FIELD_ACTION_MAX, FIELD_ACTION_SUM, FIELD_ACTION_DISTINCT_COUNT, BAND_WIDTH,\
... RoundRect, Line, Image
>>> class UsersReport(Report):
... title = 'Using chart from CairoPlot'
...
... class band_summary(ReportBand):
... height = 5*cm
... elements = [
... Label(text="Users count:", top=0.1*cm, left=0.2*cm),
... ObjectValue(attribute_name='username', top=0.1*cm, left=4*cm,\
... action=FIELD_ACTION_COUNT, display_format='%s permissions found'),
...
... Label(text="Users ids average:", top=0.6*cm, left=0.2*cm),
... ObjectValue(attribute_name='id', top=0.6*cm, left=4*cm, action=FIELD_ACTION_AVG),
...
... Label(text="Users ids minimum:", top=1.1*cm, left=0.2*cm),
... ObjectValue(attribute_name='id', top=1.1*cm, left=4*cm, action=FIELD_ACTION_MIN),
...
... Label(text="Users ids maximum:", top=1.6*cm, left=0.2*cm),
... ObjectValue(attribute_name='id', top=1.6*cm, left=4*cm, action=FIELD_ACTION_MAX),
...
... Label(text="Users ids sum:", top=2.1*cm, left=0.2*cm),
... ObjectValue(attribute_name='id', top=2.1*cm, left=4*cm, action=FIELD_ACTION_SUM),
...
... Label(text="Users first name distinct:", top=2.6*cm, left=0.2*cm),
... ObjectValue(attribute_name='first_name', top=2.6*cm, left=4*cm, action=FIELD_ACTION_DISTINCT_COUNT),
...
... Image(filename=os.path.join(cur_dir, 'output/matplotlib.png'), left=11*cm, top=0.2*cm)
... ]
... borders = {'top': True}
...
... class band_page_header(ReportBand):
... height = 1.3*cm
... elements = [
... SystemField(expression='%(report_title)s', top=0.1*cm, left=0, width=BAND_WIDTH,
... style={'fontName': 'Helvetica-Bold', 'fontSize': 14, 'alignment': TA_CENTER,
... 'textColor': navy}),
... Label(text="ID", top=0.8*cm, left=0),
... Label(text="Username", top=0.8*cm, left=3*cm),
... Label(text="First name", top=0.8*cm, left=8*cm),
... Label(text="Last name", top=0.8*cm, left=13*cm),
... Label(text="Staff", top=0.8*cm, left=18*cm),
... ]
... borders = {'bottom': Line(stroke_color=navy)}
...
... class band_page_footer(ReportBand):
... height = 0.5*cm
... elements = [
... Label(text='Created with Geraldo Reports', top=0.1*cm,
... right=0),
... SystemField(expression='Printed in %(now:%Y, %b %d)s at %(now:%H:%M)s', top=0.1*cm,
... width=BAND_WIDTH, style={'alignment': TA_RIGHT}),
... ]
... borders = {'top': True}
...
... class band_detail(ReportBand):
... height = 0.7*cm
... elements = [
... ObjectValue(attribute_name='id', top=0, left=0),
... ObjectValue(attribute_name='username', top=0, left=3*cm, display_format='<font size=14 name=Helvetica>%s</font>'),
... ObjectValue(attribute_name='first_name', top=0, left=8*cm),
... ObjectValue(attribute_name='last_name', top=0, left=13*cm),
... ObjectValue(attribute_name='is_staff', top=0, left=18*cm,
... get_value=lambda instance: instance.is_staff and 'Yes' or 'No'),
... ]
Instantiating the report...
>>> queryset = User.objects.order_by('id')
>>> report = UsersReport(queryset=queryset)
Building the chart
>>> import pylab
>>> from numpy import numarray
>>>
>>> user_ids = report.queryset.filter(id__in=[1,5,7,12]).values('id','username')
>>> labels = [user['username'] for user in user_ids]
>>> data = [user['id'] for user in user_ids]
>>> left = numarray.array(range(len(data))) + 0.5
>>>
>>> tmp = pylab.bar(left, data, width=0.5)
>>> tmp = pylab.yticks(range(15))
>>> tmp = pylab.xticks(left+0.25, labels)
>>> tmp = pylab.title('Users IDs')
>>> pylab.gca().get_xaxis().tick_bottom()
>>> pylab.gca().get_yaxis().tick_left()
>>> pylab.savefig(os.path.join(cur_dir, 'output/matplotlib.png'), dpi=50)
PDF generation
>>> from geraldo.generators import PDFGenerator
>>> report.generate_by(PDFGenerator, filename=os.path.join(cur_dir, 'output/charts-matplotlib-report.pdf'))
The Result