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build_db.py
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build_db.py
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#!/usr/bin/env python3
import os
import json
import sqlite3
import argparse
from classifier import Classifier
from multi_classifier import MultiClassifier
from prepare_training_data import CLIENTS
DB_CLIENTS = [client for client in CLIENTS if client != "Other"]
def list_all_files(classify_dir):
for root, _, files in os.walk(classify_dir):
for filename in files:
yield os.path.join(root, filename)
def create_block_db(db_path):
if os.path.exists(db_path):
print("deleting existing database")
os.remove(db_path)
conn = sqlite3.connect(db_path)
conn.execute(
"""CREATE TABLE blocks (
slot INT,
parent_slot INTEGER,
proposer_index INT,
best_guess_single TEXT,
best_guess_multi TEXT,
pr_grandine FLOAT DEFAULT 0.0,
pr_lighthouse FLOAT,
pr_lodestar FLOAT,
pr_nimbus FLOAT,
pr_prysm FLOAT,
pr_teku FLOAT,
graffiti_guess TEXT,
UNIQUE(slot, proposer_index)
)
"""
)
conn.execute("CREATE INDEX block_proposers ON blocks (proposer_index)")
conn.execute("CREATE INDEX block_slots ON blocks (slot)")
return conn
def open_block_db(db_path):
if not os.path.exists(db_path):
raise Exception(f"no database found at {db_path}")
return sqlite3.connect(db_path)
def open_or_create_db(db_path, force_create=False):
if os.path.exists(db_path) and not force_create:
return open_block_db(db_path)
else:
return create_block_db(db_path)
def slot_range_from_filename(filename) -> (int, int):
parts = os.path.splitext(os.path.basename(filename))[0].split("_")
start_slot = int(parts[1])
end_slot = int(parts[3])
return (start_slot, end_slot)
def build_block_db(db_path, classifier, classify_dir, force_rebuild=False):
conn = open_or_create_db(db_path, force_create=force_rebuild)
for input_file in list_all_files(classify_dir):
start_slot, end_slot = slot_range_from_filename(input_file)
if slot_range_known_to_db(conn, start_slot, end_slot):
print(f"skipping {input_file} (assumed known)")
continue
print(f"classifying rewards from file {input_file}")
with open(input_file, "r") as f:
block_rewards = json.load(f)
update_block_db(conn, classifier, block_rewards)
return conn
def update_block_db(conn, classifier, block_rewards):
for block_reward in block_rewards:
label, multilabel, prob_by_client, graffiti_guess = classifier.classify(
block_reward
)
proposer_index = block_reward["meta"]["proposer_index"]
slot = int(block_reward["meta"]["slot"])
parent_slot = int(block_reward["meta"]["parent_slot"])
insert_block(
conn,
slot,
parent_slot,
proposer_index,
label,
multilabel,
prob_by_client,
graffiti_guess,
)
conn.commit()
def insert_block(
conn,
slot,
parent_slot,
proposer_index,
label,
multilabel,
prob_by_client,
graffiti_guess,
):
pr_clients = [prob_by_client.get(client) or 0.0 for client in DB_CLIENTS]
conn.execute(
"""INSERT INTO blocks (slot, parent_slot, proposer_index, best_guess_single,
best_guess_multi, pr_grandine, pr_lighthouse, pr_lodestar,
pr_nimbus, pr_prysm, pr_teku, graffiti_guess)
VALUES (?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?, ?)""",
(
slot,
parent_slot,
proposer_index,
label,
multilabel,
*pr_clients,
graffiti_guess,
),
)
def get_greatest_block_slot(block_db):
res = list(block_db.execute("SELECT MAX(slot) FROM blocks"))
assert len(res) == 1
slot = res[0][0]
if slot is None:
return 0
else:
return int(slot)
def get_missing_parent_blocks(block_db):
res = block_db.execute(
"""SELECT slot, parent_slot FROM blocks b1
WHERE
(SELECT slot FROM blocks WHERE slot = b1.parent_slot) IS NULL
AND slot <> 1"""
)
return [(int(x[0]), int(x[1])) for x in res]
def get_greatest_prior_block_slot(block_db, slot):
res = list(block_db.execute("SELECT MAX(slot) FROM blocks WHERE slot < ?", (slot,)))
assert len(res) == 1
slot = res[0][0]
if slot is None:
return None
else:
return int(slot)
def get_sync_gaps(block_db):
missing_parent_slots = get_missing_parent_blocks(block_db)
gaps = []
for block_slot, parent_slot in missing_parent_slots:
prior_slot = get_greatest_prior_block_slot(block_db, parent_slot)
if prior_slot is None:
start_slot = 0
else:
start_slot = prior_slot + 1
end_slot = block_slot - 1
assert end_slot >= start_slot
gaps.append({"start": start_slot, "end": end_slot})
return gaps
def slot_range_known_to_db(block_db, start_slot, end_slot):
res = list(
block_db.execute(
"SELECT COUNT(*) FROM blocks WHERE slot >= ? AND slot <= ?",
(start_slot, end_slot),
)
)
assert len(res) == 1
count = int(res[0][0])
return count > 0
def get_sync_status(block_db):
greatest_block_slot = get_greatest_block_slot(block_db)
synced = len(get_missing_parent_blocks(block_db)) == 0
return {"greatest_block_slot": greatest_block_slot, "synced": synced}
def get_blocks_per_client(block_db, start_slot, end_slot):
blocks_per_client = {client: 0 for client in ["Uncertain", *CLIENTS]}
client_counts = block_db.execute(
"""SELECT best_guess_single, COUNT(proposer_index)
FROM blocks
WHERE slot >= ? AND slot < ?
GROUP BY best_guess_single""",
(start_slot, end_slot),
)
for client, count in client_counts:
blocks_per_client[client] = int(count)
return blocks_per_client
def get_validator_blocks(block_db, validator_index, since_slot=None):
since_slot = since_slot or 0
rows = block_db.execute(
"""SELECT slot, best_guess_single, best_guess_multi, pr_grandine, pr_lighthouse,
pr_lodestar, pr_nimbus, pr_prysm, pr_teku
FROM blocks WHERE proposer_index = ? AND slot >= ?""",
(validator_index, since_slot),
)
def row_to_json(row):
slot = row[0]
best_guess_single = row[1]
best_guess_multi = row[2]
probability_map = {client: row[3 + i] for i, client in enumerate(DB_CLIENTS)}
return {
"slot": slot,
"best_guess_single": best_guess_single,
"best_guess_multi": best_guess_multi,
"probability_map": probability_map,
}
return [row_to_json(row) for row in rows]
def get_all_validators_latest_blocks(block_db):
rows = block_db.execute(
"""SELECT b1.proposer_index, b1.slot, b1.best_guess_single
FROM blocks b1
JOIN (SELECT MAX(slot) AS slot, proposer_index FROM blocks GROUP BY proposer_index)
AS b2 ON b1.slot = b2.slot AND b1.proposer_index = b2.proposer_index;"""
)
def row_to_json(row):
proposer_index = int(row[0])
slot = row[1]
best_guess_single = row[2]
return {
"proposer_index": proposer_index,
"slot": slot,
"best_guess_single": best_guess_single,
}
return [row_to_json(row) for row in rows]
def get_blocks(block_db, start_slot, end_slot=None):
end_slot = end_slot or (1 << 62)
rows = block_db.execute(
"""SELECT slot, proposer_index, best_guess_single, best_guess_multi, pr_grandine,
pr_lighthouse, pr_lodestar, pr_nimbus, pr_prysm, pr_teku
FROM blocks WHERE slot >= ? AND slot < ?""",
(start_slot, end_slot),
)
def row_to_json(row):
slot = row[0]
proposer_index = int(row[1])
best_guess_single = row[2]
best_guess_multi = row[3]
probability_map = {client: row[4 + i] for i, client in enumerate(DB_CLIENTS)}
return {
"slot": slot,
"proposer_index": proposer_index,
"best_guess_single": best_guess_single,
"best_guess_multi": best_guess_multi,
"probability_map": probability_map,
}
return [row_to_json(row) for row in rows]
def count_true_positives(block_db, client, slot_lower, slot_upper):
rows = block_db.execute(
"""SELECT COUNT(*) FROM blocks
WHERE best_guess_single = ? AND graffiti_guess = ? AND
slot >= ? AND slot < ?""",
(client, client, slot_lower, slot_upper),
)
return int(list(rows)[0][0])
def count_true_negatives(block_db, client, slot_lower, slot_upper):
rows = block_db.execute(
"""SELECT COUNT(*) FROM blocks
WHERE best_guess_single <> ? AND graffiti_guess <> ? AND graffiti_guess IS NOT NULL AND
slot >= ? AND slot < ?""",
(client, client, slot_lower, slot_upper),
)
return int(list(rows)[0][0])
def count_false_positives(block_db, client, slot_lower, slot_upper):
rows = block_db.execute(
"""SELECT COUNT(*) FROM blocks
WHERE best_guess_single = ? AND graffiti_guess <> ? AND graffiti_guess IS NOT NULL AND
slot >= ? AND slot < ?""",
(client, client, slot_lower, slot_upper),
)
return int(list(rows)[0][0])
def count_false_negatives(block_db, client, slot_lower, slot_upper):
rows = block_db.execute(
"""SELECT COUNT(*) FROM blocks
WHERE best_guess_single <> ? AND graffiti_guess = ? AND
slot >= ? AND slot < ?""",
(client, client, slot_lower, slot_upper),
)
return int(list(rows)[0][0])
def parse_args():
parser = argparse.ArgumentParser()
parser.add_argument("--db-path", required=True, help="path to sqlite database file")
parser.add_argument(
"--data-dir", required=True, help="training data for classifier(s)"
)
parser.add_argument("--classify-dir", required=True, help="data to classify")
parser.add_argument(
"--multi-classifier",
default=False,
action="store_true",
help="build MultiClassifier from datadir",
)
parser.add_argument(
"--force-rebuild", action="store_true", help="delete any existing database"
)
return parser.parse_args()
def main():
args = parse_args()
db_path = args.db_path
data_dir = args.data_dir
data_to_classify = args.classify_dir
if args.multi_classifier:
classifier = MultiClassifier(data_dir)
else:
print("loading single classifier")
classifier = Classifier(data_dir)
print("loaded")
conn = build_block_db(
db_path, classifier, data_to_classify, force_rebuild=args.force_rebuild
)
conn.close()
if __name__ == "__main__":
main()