An example of using python-saucebrush with legislators.csv from the Sunlight Foundation Congress API bulk download.

mmmsaucebrush.py

from saucebrush import emitters, filters, sources, stats
import saucebrush
import us

CHAMBERS = {"House": "Rep", "Senate": "Sen"}
STATES = [s.abbr for s in us.STATES]
TERRITORIES = [t.abbr for t in us.TERRITORIES]


class StateFilter(filters.ConditionalFilter):
    def __init__(self, states):
        self.states = [states] if isinstance(states, basestring) else states
    
    def test_record(self, record):
        return record["state"] in self.states
    
    
class InOfficeFilter(filters.ConditionalFilter):
    def test_record(self, record):
        return record["in_office"] == "1"


class ChamberFilter(filters.ConditionalFilter):
    def __init__(self, chamber):
        if chamber not in CHAMBERS:
            raise ValueError("chamber must be one of: %s" % ", ".join(CHAMBERS.keys()))
        self.title = CHAMBERS[chamber]
    
    def test_record(self, record):
        return record["title"] == self.title


if __name__ == "__main__":
    
    histogram = stats.Histogram('state')

    with open("legislators.csv") as infile:
    
        saucebrush.run_recipe(
            sources.CSVSource(infile),
            InOfficeFilter(),
            ChamberFilter("House"),
            # ChamberFilter("Senate"),
            StateFilter(STATES),
            # StateFilter(TERRITORIES),
            histogram,
            emitters.CountEmitter(),
        )

    print histogram
    

output.txt

434

AK     *
AL     *******
AR     ****
AZ     *********
CA     *****************************************************
CO     *******
CT     *****
DC     *
DE     *
FL     ***************************
GA     **************
HI     **
IA     ****
ID     **
IL     *****************
IN     *********
KS     ****
KY     ******
LA     ******
MA     *********
MD     ********
ME     **
MI     **************
MN     ********
MO     ********
MS     ****
MT     *
NC     *************
ND     *
NE     ***
NH     **
NJ     ************
NM     ***
NV     ****
NY     ***************************
OH     ****************
OK     *****
OR     *****
PA     ******************
RI     **
SC     ******
SD     *
TN     *********
TX     ************************************
UT     ****
VA     ***********
VT     *
WA     **********
WI     ********
WV     ***
WY     *