119 lines
3.5 KiB
Python
119 lines
3.5 KiB
Python
from __future__ import annotations
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import time
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import xml.etree.ElementTree as ET
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import psycopg2
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import tomli
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from lib_not_dr import loggers
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with open("../../config.toml", "rb") as f:
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CONFIG = tomli.load(f)
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logger = loggers.config.get_logger("xml_parse")
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# logger.global_level = 10
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result_logger = loggers.config.get_logger("result")
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file = loggers.outstream.FileCacheOutputStream(file_name="result.log")
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result_logger.add_output(file)
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def get_db():
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connect = psycopg2.connect(
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CONFIG["db"]["url"]
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)
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return connect
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def parse_part_types(xml_file):
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tree = ET.parse(xml_file)
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root = tree.getroot()
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part_dict = {}
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# 遍历所有 PartType 元素
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for part in root.findall('PartType'):
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part_id = part.get('id')
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part_mass = float(part.get('mass')) # type: ignore
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part_dict[part_id] = part_mass * 500 # 缩放因子
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return part_dict
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def fetch_data(db_cur, offset, limit):
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xml_fetch = f"""
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WITH data AS (
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SELECT save_id as id, data
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FROM public.full_data
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WHERE "save_type" = 'ship'
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AND full_data.xml_tested
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AND save_id >= 1200000
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ORDER BY save_id ASC
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LIMIT {limit} OFFSET {offset}
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),
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parts_data AS (
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SELECT data.id, parts.part_type
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FROM data,
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XMLTABLE (
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'//Ship/Parts/Part'
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PASSING BY VALUE xmlparse(document data."data")
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COLUMNS part_type text PATH '@partType',
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part_id text PATH '@id'
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) AS parts
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)
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SELECT id,
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array_agg(part_type) AS part_types,
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array_agg(part_count) AS part_counts
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FROM (
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SELECT id, part_type, COUNT(part_type) AS part_count
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FROM parts_data
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GROUP BY id, part_type
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) AS counted_parts
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GROUP BY id;
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"""
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db_cur.execute(xml_fetch)
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return db_cur.fetchall()
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def main():
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part_mass = parse_part_types("PartList.xml")
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logger.debug(part_mass)
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db = get_db()
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db_cur = db.cursor()
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offset = 0
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limit = 100
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target_mass = 775150
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delta = 10000
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start_time = time.time()
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while True:
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datas = fetch_data(db_cur, offset, limit)
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if not datas:
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break
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for data in datas:
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logger.debug(data)
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# (id, ['pod-1', 'parachute-1', 'lander-1', 'engine-1', 'fuselage-1', 'fueltank-0'], [1, 1, 2, 1, 1, 1])
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# 解析这玩意
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# ship_mass = sum(part_mass[part] * data[2][idx] for part, idx in enumerate(data[1]))
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ship_mass = sum(part_mass[part] * count if part in part_mass else 0 for part, count in zip(data[1], data[2]))
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logger.debug(f"{data[0]}: {ship_mass}")
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# 如果在误差范围内，则输出
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if target_mass - delta <= ship_mass <= target_mass + delta:
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result_logger.info(f"Ship ID: {data[0]}")
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result_logger.info(f"Mass: {ship_mass}")
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result_logger.info(f"Part Types: {data[1]}")
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result_logger.info(f"Part Counts: {data[2]}")
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result_logger.info("=" * 20)
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logger.warn(f"Ship ID: {data[0]}")
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logger.warn(f"Mass: {ship_mass}")
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logger.warn(f"Part Types: {data[1]}")
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logger.warn(f"Part Counts: {data[2]}")
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logger.warn("=" * 20)
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offset += limit
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# 效率
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delta_t = time.time() - start_time
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speed = limit / delta_t
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logger.info(f"Offset: {offset} Speed: {speed:.2f} ships/s({delta_t:.2f}s) - {data[0]}")
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start_time = time.time()
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main()
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