[DRAFT] Parsing the Congressmember Data for our birthday Flask app

Note: Explanation in process

Parsing the data

It's worth browsing the legislator data file in a spreadsheet to get a feel for what it contains. I've embedded it in a Gist below:

Basic filter.py script with a parsing function

This script uses the read_data() method from fetch.py to download the data – if it doesn't already exist – then provide it as raw text. The csv.DictReader class is used to turn the lines of text into a list of dictionaries:

from fetch import read_data
from csv import DictReader
def parse_data():
    """
    Returns a list of dictionaries from the raw text
    based on what fetch.read_data() returns
    """
    txt = read_data()
    lines = txt.splitlines()
    return list(DictReader(lines))

Final version of filter.py

from fetch import read_data
from csv import DictReader
def parse_data():
    """
    Returns a list of dictionaries from the raw text
    based on what fetch.read_data() returns
    """
    txt = read_data()
    lines = txt.splitlines()
    return list(DictReader(lines))
def get_birthday_rows_by_month_day(mth_day):
    """
    Calls parse_data to get a list of dicts
    Expects mth_day to be a string in this format:
        MM-DD, e.g. "05-12", (May 12)
    Returns a list of dicts that includes:
    - dicts with 'in_office' == '1' (legislators still in office)
    - dicts with the month and day components of 'birthdate'
        equal to the mth_day string
    """
    newrows = []
    original_rows = parse_data()
    for row in original_rows:
        if row['in_office'] == '1':
            rbdate = row['birthdate'][5:]
            if rbdate == mth_day:
                newrows.append(row)
    # all done
    return newrows