Hola-
I also recently was tasked by my wife to help her personalize letters
to all the Relief Society. Enter python and OOo. The attached python
script will extract all Relief Society members from the csv dump
(based on gender and date script is run). I assume everyone else
does/will do this in their favorite language, but in case any python
people are interested here it is.
enjoy,
matt
ps - mail merging and label generated is a pain. (I haven't done it
since the days of DOS, but I wanted to throw something through my 24
inch monitor a couple times. My wife thought it was funny.....)
"""
Convert MLS Membership.csv dump to Relief Society only. I also add 3 extra
name columns ("First", "Last", "First and Last") useful for doing mail merges.
Here's the usage:
usage: Utility to extract current RS members based on todays date
options:
-h, --help show this help message and exit
-i FIN, --in-file=FIN
specify MLS export to read from
-o FOUT, --out-file=FOUT
name of Relief Society file
Licensed under PSF license.
Copyright 2007 - matt harrison
"""
import datetime
import time
import csv
import optparse
HEADERS=["Indiv ID","Full Name","Preferred Name","MRN","HofH ID","HH Position","HH Order","Phone 1","Phone 2","E-mail Address","Street 1","Street 2","D/P","City","Postal","State/Prov","Country","2-Street 1","2-Street 2","2-D/P","2-City","2-Zip","2-State/Prov","2-Country","Ward GEO Code","Stake GEO Code","Sex","Birth","Baptized","Confirmed","Endowed","Rec Exp","Priesthood","Mission","Married","Spouse Member","Sealed to Spouse","Sealed to Prior"]
def get_data(filename):
"""return an iteration of dicts"""
fin = open(filename)
reader = csv.DictReader(fin)
for line in reader:
#extra comma in header puts empty field remove it
del line[""]
yield line
def rs_iter(data_iter):
for data in data_iter:
if is_rs(data):
yield data
def add_names_iter(data_iter):
"""Take Preferred Name column and make 3 new columns
First, Last and First and Last
"""
#update HEADERS
for name in ["First", "Last", "First and Last"]:
if name not in HEADERS:
global HEADERS
HEADERS.append(name)
for data in data_iter:
preferred = data["Preferred Name"]
split_index = preferred.index(", ")
last = preferred[:split_index]
first = preferred[split_index+2:]
first_last = " ".join([first, last])
data["First"] = first
data["Last"] = last
data["First and Last"] = first_last
yield data
def to_file(data_iter, filename):
fout = open(filename, 'w')
#get data first since it updates HEADERS possibly
datas = [x for x in data_iter]
fout.write(",".join(HEADERS)+"\n")
writer = csv.DictWriter(fout, fieldnames=HEADERS)
for data in datas:
writer.writerow(data)
fout.close()
def is_rs(record):
return is_18(record) and is_female(record)
def is_female(record):
return record["Sex"] == "Female"
def is_18(record):
"""
>>> is_18(dict(Birth="09/17/75"))
True
>>> is_18(dict(Birth="08/14/89"))
True
>>> is_18(dict(Birth="08/16/90"))
False
"""
today = datetime.date.today()
#if empty assume they are too old to ask hence, hence True
if not record["Birth"]:
return True
birth = datetime.date(*time.strptime(record["Birth"], "%d %b %Y")[:3])
return today.year - birth.year > 18 or \
(today.year - birth.year == 18 and \
today.month >= birth.month and \
today.day >= birth.day)
def test():
import doctest
doctest.testmod()
def main():
p = optparse.OptionParser(usage="Utility to extract current RS members based on todays date")
p.add_option("-i", "--in-file", action="store", dest="fin",
default="Membership.csv",
help="specify MLS export to read from")
p.add_option("-o", "--out-file", action="store", dest="fout",
default="RS.csv",
help="name of Relief Society file")
p.add_option("-t", action="store_true", dest="test",
help="run file tests")
opt, args = p.parse_args()
if opt.test:
test()
else:
to_file(add_names_iter(rs_iter(get_data(opt.fin))), opt.fout)
if __name__ == "__main__":
main()
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