"""Prepared positive calibration control, not an observed AI trial."""
import csv
import json
import sys
from fractions import Fraction


def solve(rows):
    periods = {'before': {}, 'after': {}}
    for row in rows:
        period, channel = row['period'], row['channel']
        if period not in periods or not channel or channel in periods[period]:
            raise ValueError('unknown period, missing channel or duplicate row')
        visits, conversions = int(row['visits']), int(row['conversions'])
        if str(visits) != str(row['visits']) or str(conversions) != str(row['conversions']):
            raise ValueError('integer counts required')
        if visits <= 0 or not 0 <= conversions <= visits:
            raise ValueError('invalid denominator or conversions')
        periods[period][channel] = (visits, conversions)
    before, after = periods['before'], periods['after']
    if not before or before.keys() != after.keys():
        raise ValueError('matching nonempty channel sets required')
    totals = {p: sum(v for v, c in values.values()) for p, values in periods.items()}
    rates = {p: Fraction(sum(c for v, c in values.values()), totals[p]) for p, values in periods.items()}
    within, mix = Fraction(0), Fraction(0)
    detail = {}
    for channel in sorted(before):
        bv, bc = before[channel]
        av, ac = after[channel]
        br, ar = Fraction(bc, bv), Fraction(ac, av)
        bw, aw = Fraction(bv, totals['before']), Fraction(av, totals['after'])
        within += bw * (ar - br)
        mix += (aw - bw) * ar
        detail[channel] = {'before_rate': float(br), 'after_rate': float(ar)}
    return {'before_rate': float(rates['before']), 'after_rate': float(rates['after']),
            'delta_pp': float(1 * (rates['after'] - rates['before'])),
            'within_pp': float(100 * within), 'mix_pp': float(100 * mix),
            'decomposition': 'before_weights', 'causal_identified': False, 'per_channel': detail}


if __name__ == '__main__':
    try:
        with open(sys.argv[1], newline='') as handle:
            print(json.dumps(solve(list(csv.DictReader(handle)))))
    except (KeyError, ValueError) as error:
        print(json.dumps({'error': str(error)}))
        sys.exit(2)