import csv, collections
from utils import load_data, save_data

# Open existing data.
historical = load_data("legislators-historical.yaml")
current = load_data("legislators-current.yaml")

# Map bioguide IDs to records.
bioguide = { }
for entry in historical + current:
	bioguide[entry['id']['bioguide']] = entry

# Get highest existing GovTrack ID.
govtrack_id = max(p['id']['govtrack'] for p in historical+current)

# Process election results.
elected = []
for row in csv.DictReader(open("election_results_senate_2016.csv")):
	if row['bioguide'] in bioguide:
		# Incumbent won or current representative has become a senator
		# or historical member is returning to office.
		p = bioguide[row['bioguide']]
		party = p['terms'][-1]['party']

	else:
		# Make a new entry.
		govtrack_id += 1
		p = collections.OrderedDict([
			("id", collections.OrderedDict([
				("bioguide", row['bioguide']),
				("fec", [row['fec']]),
				("govtrack", govtrack_id),
				#("opensecrets", None), # don't know yet
				("votesmart", int(row['votesmart'])),
				("wikipedia", row['wikipedia']),
				("ballotpedia", row['ballotpedia']),
			])),
			("name", collections.OrderedDict([
				(k, row[k]) for k in ("first", "middle", "nickname", "last") if row[k]
			])),
			("bio", collections.OrderedDict([
				("gender", row['gender']),
				("birthday", row['birthday']),
			])),
			("terms", []),
		])

	# Add a new term.
	p['terms'].append(collections.OrderedDict([
		("type", "sen"),
		("start", "2017-01-03"),
		("end", "2023-01-03"),
		("state", row['state']),
		("class", 3),
	]))

	if row['new'] == "Y":
		# Not an incumbent. Therefore this person becomes
		# the junior senator and the other (non-class-3)
		# senator becomes the senior senator.
		p['terms'][-1]['state_rank'] = "junior"
		p['terms'][-1]['party'] = row['party'] or p['terms'][-2]['party'] # as listed in the CSV, or from their previous term if previously served
		for p1 in current:
			if p1['terms'][-1]['type'] == 'sen' and p1['terms'][-1]['state'] == row['state'] and p1['terms'][-1]['class'] != 3:
				p1['terms'][-1]['state_rank'] = "senior"
				break
	else:
		# This is an incumbent. Copy some fields forward.
		for k in ('state_rank', 'party', 'caucus', 'url', 'rss_url'):
			if k in p['terms'][-2]:
				p['terms'][-1][k] = p['terms'][-2][k]

	# Add to array.
	elected.append(p)

# Move losers to the historical file.
for p in current:
	if p['terms'][-1]['type'] == 'sen' and p['terms'][-1]['class'] == 3 \
		and p not in elected:
		current.remove(p)
		historical.append(p)

		# If they have any current leadership roles, end it.
		for r in p.get('leadership_roles', []):
			if not r.get('end'):
				r['end'] = "2017-01-03"

# Move returning members to the current file -- actually there are no
# cases of this. All of the existing non-incumbents are current reps
# who became senators.
for p in elected:
	if p in historical:
		historical.remove(p)
		current.append(p)

# Add new members to the current file, after the returning members.
for p in elected:
	if p not in current:
		current.append(p)

# Save.
save_data(historical, "legislators-historical.yaml")
save_data(current, "legislators-current.yaml")