init: AI培训与智能巡检系统
This commit is contained in:
selfrelease
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"""清洗规则：单元格清理、数值+单位拆分、年代解析、状态/国别规范化。
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对应任务 T-1.2（清洗）。所有函数均为纯函数，便于单元测试（T-1.2 UT）。
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"""
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import re
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# 占位/空值标记
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_EMPTY_MARKERS = {"", "-", "——", "—", "/", "N/A", "n/a", "无", "未知"}
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def clean_cell(value) -> str:
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"""清理单元格：去换行、压缩空白、trim。返回字符串。"""
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if value is None:
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return ""
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s = str(value).replace("\n", "").replace("\r", "")
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s = s.replace("\u3000", " ")
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s = re.sub(r"\s+", " ", s).strip()
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return s
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def is_empty(value) -> bool:
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"""判断是否为空/占位值。"""
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return clean_cell(value) in _EMPTY_MARKERS
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# 匹配前导数字（含小数、千分位、负号），后跟可选单位
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_NUM_RE = re.compile(r"-?\d+(?:\.\d+)?")
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def parse_value_unit(raw, default_unit: str = ""):
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"""从形如 '400km/h（试验）'、'17t'、'2×92(100)'、'126.0'、'——'
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中拆出 (数值: float|None, 单位: str, 原文: str)。
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规则：取第一个出现的数值作为主数值；单位优先取 default_unit，
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否则尝试从数值后紧跟的字母/单位片段提取；无数值则返回 (None, '', 原文)。
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"""
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text = clean_cell(raw)
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if text in _EMPTY_MARKERS:
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return None, "", text
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m = _NUM_RE.search(text)
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if not m:
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return None, "", text
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value = float(m.group())
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unit = default_unit
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if not unit:
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# 取数值之后紧邻的单位片段（字母 / 常见单位字符）
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rest = text[m.end():]
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um = re.match(r"\s*([A-Za-z%/·³²]+(?:/[A-Za-z]+)?)", rest)
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if um:
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unit = um.group(1)
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return value, unit, text
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def parse_year(raw):
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"""解析年份：'1971 年'、'2006'、'2007-12-22 00:00:00' -> int|None。"""
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text = clean_cell(raw)
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if text in _EMPTY_MARKERS:
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return None
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m = re.search(r"(1[89]\d{2}|20\d{2})", text)
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return int(m.group(1)) if m else None
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def normalize_status(raw) -> str:
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"""把自由文本状态规范到枚举之一。"""
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text = clean_cell(raw)
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if not text:
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return "未知"
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mapping = [
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("半封存", "半封存"),
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("封存", "封存"),
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("现役", "现役"),
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("在役", "现役"),
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("退役", "退役"),
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("淘汰", "退役"),
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("报废", "报废"),
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("保存", "保存"),
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("试验", "试验"),
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("样车", "试验"),
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]
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for kw, val in mapping:
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if kw in text:
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return val
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return "未知"
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# 国别属性的简单启发式推断（默认国产；后续众包修订可覆盖）
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_IMPORT_HINTS = ["进口", "苏联", "罗马尼亚", "法国", "日本", "德国", "美国", "捷克"]
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def infer_country_type(*texts) -> str:
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blob = " ".join(clean_cell(t) for t in texts)
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if "合资" in blob:
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return "中外合资"
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if "仿制" in blob or "引进" in blob:
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return "引进仿制"
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for h in _IMPORT_HINTS:
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if h in blob:
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return "进口"
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return "国产"
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def forward_fill(values):
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"""对一列做向前填充（处理合并单元格被拆空的 系列 列）。"""
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out, last = [], ""
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for v in values:
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c = clean_cell(v)
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if c:
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last = c
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out.append(last)
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return out
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"""统一字段字典与枚举。
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将各 sheet 中形态各异的表头映射到规范字段名（canonical），
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并声明哪些字段是"数值 + 单位"型（需要拆分）。
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对应任务 T-1.1（字段字典）/ T-1.2（字段映射）。
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"""
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# 规范字段 -> 该字段的同义表头集合（去空格后匹配）
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# 注意：表头里常含空格/换行，匹配前统一做 normalize_header() 处理。
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FIELD_SYNONYMS = {
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"series": ["系列"],
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"model_code": ["型号", "型号(代号)", "车型", "车型代码", "小表编号车型"],
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"full_name": ["车型全称", "车型名称"],
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"first_year": ["首产时间", "制造时间", "生产时间"],
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"last_year": ["停产时间"],
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"manufacturer": ["生产商", "主要生产厂商", "生产厂商", "制造商"],
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"length": ["车体长度/mm", "机车长度/mm", "车辆全长/mm", "车体全长/mm"],
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"width": ["车体宽度/mm", "机车宽度/mm"],
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"height": ["车体高度/mm"],
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"wheelbase": ["轴距/mm", "车辆定距/mm"],
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"weight": ["整备重量/t", "自重/t", "整备重量/轴重/t", "整备重量/节数"],
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"axle_load": ["轴重/t"],
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"axle_arrangement": ["轴列式", "轴式", "轴列式(标准编组)"],
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"tractive_start": ["牵引力(起动)/kN"],
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"tractive_cont": ["牵引力(持续)/kN"],
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"power_kw": ["牵引力/kW"],
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"efficiency": ["传动效率", "机械效率"],
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"drive": ["传动方式/动力来源", "供电方式(传动方式)", "供电方式", "制动方式"],
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"max_speed": ["最高运行时速", "最高运营时速", "构造速度/km/h", "运行时速",
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"最高速度", "构造速度"],
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"usage": ["用途", "主要用途", "核心运行区段/主题"],
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"production_count": ["产量", "累计产量", "生产台数", "生产数量",
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"累计产量/配属"],
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"capacity": ["容积/m³", "定员/人"],
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"load": ["载重/t"],
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"bogie": ["转向架型号"],
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"coupler": ["车钩类型"],
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# 个体（Unit）粒度字段
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"car_number": ["车号", "编号"],
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"function": ["功能"],
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"depot": ["配属", "所属路局"],
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"livery": ["颜色", "涂装"],
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"status": ["状态"],
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"side_mark": ["侧标"],
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"note": ["备注"],
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"location": ["存放位置"],
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"formation": ["动力车、拖车", "动力车拖车"],
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"predecessor": ["前身(部分含)", "前身"],
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"lifespan": ["最大使用寿命(结合实际)"],
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"tour_name": ["旅游列车名称"],
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"tractor_models": ["牵引机车常用型号"],
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}
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# "数值 + 单位"型字段：导入时拆出 <field>_value(float) 与 <field>_unit(text)
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NUMERIC_UNIT_FIELDS = {
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"length": "mm", "width": "mm", "height": "mm", "wheelbase": "mm",
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"weight": "t", "axle_load": "t", "load": "t",
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"tractive_start": "kN", "tractive_cont": "kN", "power_kw": "kW",
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"max_speed": "km/h", "capacity": "",
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}
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# 状态枚举（规范化目标）
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STATUS_ENUM = ["现役", "封存", "半封存", "报废", "退役", "保存", "试验", "未知"]
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# 国别属性枚举
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COUNTRY_TYPE_ENUM = ["国产", "进口", "引进仿制", "中外合资", "未知"]
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# sheet 文件名 -> 分类配置
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# grain: "model" 车型粒度 / "unit" 个体粒度
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CATEGORY_CONFIG = {
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"中国蒸汽汽车统计表（建国前）": {"category": "蒸汽机车", "subcat": "建国前", "grain": "model"},
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"中国蒸汽机车型号表（建国后）": {"category": "蒸汽机车", "subcat": "建国后", "grain": "model"},
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"北京表（蒸汽机车）": {"category": "蒸汽机车", "subcat": "北京现存", "grain": "unit"},
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"全国普速客车型号统计表": {"category": "客车", "subcat": "普速客车", "grain": "model"},
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"全国电力机车型号表": {"category": "电力机车", "subcat": "", "grain": "model",
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"col_override": {0: "series", 1: "model_code"}},
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"全国内燃机车型号表": {"category": "内燃机车", "subcat": "", "grain": "model"},
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"CJ型动车组、早期动车组及和谐号统计表": {"category": "动车组", "subcat": "CJ/早期/和谐号", "grain": "model"},
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"全国复兴号统计表": {"category": "动车组", "subcat": "复兴号", "grain": "model"},
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"中国铁路货车统计表": {"category": "货车", "subcat": "", "grain": "model"},
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"中国铁路普速检测车统计表": {"category": "检测车", "subcat": "普速检测", "grain": "unit"},
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"中国高速综合检测列车统计表": {"category": "检测车", "subcat": "高速综合检测", "grain": "unit"},
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"中国旅游列车统计表": {"category": "旅游列车", "subcat": "", "grain": "model"},
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}
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# 用于识别"表头行"的关键 token（normalize 后）
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HEADER_TOKENS = {"型号", "车号", "车型代码", "车型", "旅游列车名称", "小表编号",
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"型号(代号)", "系列", "车型全称"}
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# 反向索引：normalized header -> canonical field
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_REVERSE = {}
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for _canon, _syns in FIELD_SYNONYMS.items():
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for _s in _syns:
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_REVERSE[_s] = _canon
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def normalize_header(h: str) -> str:
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"""规范化表头：去除空白、换行、全角空格，并将全角括号转半角。"""
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if h is None:
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return ""
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s = (h.replace("\n", "").replace("\r", "")
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.replace(" ", "").replace("\u3000", "").strip())
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s = s.replace("（", "(").replace("）", ")")
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return s
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def map_header(h: str):
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"""把原始表头映射到 canonical 字段名，未知返回 None。"""
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return _REVERSE.get(normalize_header(h))
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"""ETL 导入管线：12 张 CSV -> 清洗 -> SQLite + JSON + 导入报告。
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对应任务 T-1.2。运行：
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python3 -m app.etl.importer # 从 Train/ 目录运行
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或：
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python3 app/etl/importer.py
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"""
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import csv
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import json
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import os
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import sqlite3
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import sys
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from . import field_dict as fd
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from . import clean as cl
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HERE = os.path.dirname(os.path.abspath(__file__))
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APP_DIR = os.path.dirname(HERE)
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ROOT = os.path.dirname(APP_DIR) # Train/
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CSV_DIR = os.path.join(ROOT, "csv")
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OUT_DIR = os.path.join(APP_DIR, "data")
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DB_PATH = os.path.join(OUT_DIR, "machines.db")
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JSON_PATH = os.path.join(OUT_DIR, "machines.json")
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REPORT_PATH = os.path.join(OUT_DIR, "import_report.md")
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SCHEMA_PATH = os.path.join(HERE, "schema.sql")
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def find_header_row(rows):
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"""返回表头行索引：含 >=3 个非空单元且命中关键 token 的首行。"""
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for i, row in enumerate(rows):
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cells = [fd.normalize_header(c) for c in row]
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nonempty = [c for c in cells if c]
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if len(nonempty) >= 3 and (set(cells) & fd.HEADER_TOKENS):
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return i
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return None
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def build_column_map(header_row):
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"""列索引 -> canonical 字段名（未知列保留为 raw::原表头）。"""
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col_map = {}
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for idx, h in enumerate(header_row):
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canon = fd.map_header(h)
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norm = fd.normalize_header(h)
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if canon:
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col_map[idx] = canon
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elif norm:
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col_map[idx] = "raw::" + norm
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return col_map
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def clean_record(row, col_map):
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"""把一行映射为 canonical 字段 dict（含 raw:: 保真列）。"""
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rec, raw = {}, {}
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for idx, field in col_map.items():
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value = row[idx] if idx < len(row) else ""
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if field.startswith("raw::"):
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c = cl.clean_cell(value)
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if c:
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raw[field[5:]] = c
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continue
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rec[field] = value
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rec["_raw_extra"] = raw
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return rec
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def to_model_row(rec, category_id, sheet, series_value):
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"""构造 model 表插入字典。"""
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raw_all = dict(rec.get("_raw_extra", {}))
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m = {
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"category_id": category_id,
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"series": cl.clean_cell(rec.get("series") or series_value),
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"model_code": cl.clean_cell(rec.get("model_code")),
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"full_name": cl.clean_cell(rec.get("full_name")),
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"manufacturer": cl.clean_cell(rec.get("manufacturer")),
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"first_year": cl.parse_year(rec.get("first_year")),
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"last_year": cl.parse_year(rec.get("last_year")),
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"status": cl.normalize_status(rec.get("status")),
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"usage": cl.clean_cell(rec.get("usage")),
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"production_count": cl.clean_cell(rec.get("production_count")),
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"axle_arrangement": cl.clean_cell(rec.get("axle_arrangement")),
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"drive": cl.clean_cell(rec.get("drive")),
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"efficiency": cl.clean_cell(rec.get("efficiency")),
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"country": "中国",
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"country_type": cl.infer_country_type(
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rec.get("manufacturer"), rec.get("model_code"),
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rec.get("usage"), rec.get("production_count")),
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"source_sheet": sheet,
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}
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# 数值+单位字段拆分
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for field, default_unit in fd.NUMERIC_UNIT_FIELDS.items():
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if field not in fd.FIELD_SYNONYMS:
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continue
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val, unit, _ = cl.parse_value_unit(rec.get(field), default_unit)
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m[field + "_value"] = val
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m[field + "_unit"] = unit or default_unit
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if rec.get(field) is not None:
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raw_all[field] = cl.clean_cell(rec.get(field))
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# 把所有 canonical 原文也并入 raw_json 保真
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for k, v in rec.items():
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if k == "_raw_extra":
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continue
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c = cl.clean_cell(v)
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if c:
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raw_all[k] = c
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m["raw_json"] = json.dumps(raw_all, ensure_ascii=False)
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return m
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def to_unit_row(rec, category_id, sheet):
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raw_all = dict(rec.get("_raw_extra", {}))
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for k, v in rec.items():
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if k == "_raw_extra":
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continue
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c = cl.clean_cell(v)
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if c:
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raw_all[k] = c
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return {
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"category_id": category_id,
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"car_number": cl.clean_cell(rec.get("car_number")),
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"model_name": cl.clean_cell(rec.get("full_name") or rec.get("model_code")),
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"function": cl.clean_cell(rec.get("function")),
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"depot": cl.clean_cell(rec.get("depot")),
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"livery": cl.clean_cell(rec.get("livery")),
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"status": cl.normalize_status(rec.get("status")),
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"location": cl.clean_cell(rec.get("location")),
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"note": cl.clean_cell(rec.get("note")),
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"raw_json": json.dumps(raw_all, ensure_ascii=False),
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"source_sheet": sheet,
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}
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def _insert(conn, table, row):
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cols = list(row.keys())
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ph = ",".join(["?"] * len(cols))
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conn.execute(
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f"INSERT INTO {table} ({','.join(cols)}) VALUES ({ph})",
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[row[c] for c in cols],
|
||||
)
|
||||
|
||||
|
||||
def import_all(csv_dir=CSV_DIR, db_path=DB_PATH):
|
||||
os.makedirs(OUT_DIR, exist_ok=True)
|
||||
if os.path.exists(db_path):
|
||||
os.remove(db_path)
|
||||
conn = sqlite3.connect(db_path)
|
||||
with open(SCHEMA_PATH, encoding="utf-8") as f:
|
||||
conn.executescript(f.read())
|
||||
|
||||
report = {"sheets": [], "models": 0, "units": 0, "skipped": 0, "review": []}
|
||||
export = {"categories": [], "models": [], "units": []}
|
||||
cat_ids = {}
|
||||
|
||||
for sheet, cfg in fd.CATEGORY_CONFIG.items():
|
||||
path = os.path.join(csv_dir, sheet + ".csv")
|
||||
entry = {"sheet": sheet, "category": cfg["category"], "grain": cfg["grain"],
|
||||
"rows": 0, "imported": 0, "skipped": 0, "note": ""}
|
||||
if not os.path.exists(path):
|
||||
entry["note"] = "文件缺失"
|
||||
report["sheets"].append(entry)
|
||||
continue
|
||||
with open(path, encoding="utf-8-sig") as fh:
|
||||
rows = list(csv.reader(fh))
|
||||
if not rows:
|
||||
entry["note"] = "空表（无数据）"
|
||||
report["sheets"].append(entry)
|
||||
continue
|
||||
|
||||
key = (cfg["category"], cfg["subcat"])
|
||||
if key not in cat_ids:
|
||||
cur = conn.execute(
|
||||
"INSERT INTO category(name, subcat, slug) VALUES (?,?,?)",
|
||||
(cfg["category"], cfg["subcat"], None))
|
||||
cat_ids[key] = cur.lastrowid
|
||||
export["categories"].append(
|
||||
{"id": cur.lastrowid, "name": cfg["category"], "subcat": cfg["subcat"]})
|
||||
category_id = cat_ids[key]
|
||||
|
||||
hidx = find_header_row(rows)
|
||||
if hidx is None:
|
||||
entry["note"] = "未识别表头行"
|
||||
report["sheets"].append(entry)
|
||||
continue
|
||||
col_map = build_column_map(rows[hidx])
|
||||
# 应用 per-sheet 列覆盖（处理表头标注与实际不符的脏表）
|
||||
for idx, field in cfg.get("col_override", {}).items():
|
||||
col_map[idx] = field
|
||||
data_rows = rows[hidx + 1:]
|
||||
entry["rows"] = len(data_rows)
|
||||
|
||||
# 系列列向前填充（合并单元格）
|
||||
series_col = next((i for i, f in col_map.items() if f == "series"), None)
|
||||
if series_col is not None:
|
||||
filled = cl.forward_fill([r[series_col] if series_col < len(r) else ""
|
||||
for r in data_rows])
|
||||
else:
|
||||
filled = [""] * len(data_rows)
|
||||
|
||||
for r, series_value in zip(data_rows, filled):
|
||||
rec = clean_record(r, col_map)
|
||||
if cfg["grain"] == "unit":
|
||||
car = cl.clean_cell(rec.get("car_number"))
|
||||
if not car:
|
||||
entry["skipped"] += 1
|
||||
report["skipped"] += 1
|
||||
continue
|
||||
row = to_unit_row(rec, category_id, sheet)
|
||||
_insert(conn, "unit", row)
|
||||
export["units"].append(row)
|
||||
report["units"] += 1
|
||||
entry["imported"] += 1
|
||||
else:
|
||||
code = cl.clean_cell(rec.get("model_code")) or \
|
||||
cl.clean_cell(rec.get("tour_name")) or \
|
||||
cl.clean_cell(rec.get("full_name"))
|
||||
if not code:
|
||||
entry["skipped"] += 1
|
||||
report["skipped"] += 1
|
||||
continue
|
||||
row = to_model_row(rec, category_id, sheet, series_value)
|
||||
if not row["model_code"]:
|
||||
row["model_code"] = code
|
||||
_insert(conn, "model", row)
|
||||
export["models"].append(row)
|
||||
report["models"] += 1
|
||||
entry["imported"] += 1
|
||||
# 年代逻辑校验 -> 待复核
|
||||
if (row["first_year"] and row["last_year"]
|
||||
and row["first_year"] > row["last_year"]):
|
||||
report["review"].append(
|
||||
f"{sheet} / {code}: 首产年 {row['first_year']} > 停产年 {row['last_year']}")
|
||||
report["sheets"].append(entry)
|
||||
|
||||
conn.commit()
|
||||
conn.close()
|
||||
|
||||
with open(JSON_PATH, "w", encoding="utf-8") as f:
|
||||
json.dump(export, f, ensure_ascii=False, indent=2)
|
||||
_write_report(report)
|
||||
return report
|
||||
|
||||
|
||||
def _write_report(report):
|
||||
lines = ["# ETL 导入报告\n",
|
||||
f"- 车型(Model)：**{report['models']}**",
|
||||
f"- 个体(Unit)：**{report['units']}**",
|
||||
f"- 跳过(无主键)：**{report['skipped']}**",
|
||||
f"- 待人工复核：**{len(report['review'])}**\n",
|
||||
"## 分表明细\n",
|
||||
"| 分类表 | 分类 | 粒度 | 数据行 | 入库 | 跳过 | 备注 |",
|
||||
"|---|---|---|---|---|---|---|"]
|
||||
for s in report["sheets"]:
|
||||
lines.append(f"| {s['sheet']} | {s['category']} | {s['grain']} | "
|
||||
f"{s['rows']} | {s['imported']} | {s['skipped']} | {s['note']} |")
|
||||
if report["review"]:
|
||||
lines.append("\n## 待人工复核\n")
|
||||
for r in report["review"]:
|
||||
lines.append(f"- {r}")
|
||||
with open(REPORT_PATH, "w", encoding="utf-8") as f:
|
||||
f.write("\n".join(lines) + "\n")
|
||||
|
||||
|
||||
if __name__ == "__main__":
|
||||
rep = import_all()
|
||||
print(f"导入完成：Model={rep['models']} Unit={rep['units']} "
|
||||
f"跳过={rep['skipped']} 待复核={len(rep['review'])}")
|
||||
print(f"输出：\n {DB_PATH}\n {JSON_PATH}\n {REPORT_PATH}")
|
||||
sys.exit(0)
|
||||
@@ -0,0 +1,77 @@
|
||||
-- 中国机车图鉴 · 数据底座 schema（SQLite，设计为可移植到 PostgreSQL）
|
||||
-- 对应任务 T-1.1。三层模型：Category -> Model -> Unit，加 Model 关系表。
|
||||
|
||||
PRAGMA foreign_keys = ON;
|
||||
|
||||
CREATE TABLE IF NOT EXISTS category (
|
||||
id INTEGER PRIMARY KEY,
|
||||
name TEXT NOT NULL,
|
||||
subcat TEXT DEFAULT '',
|
||||
slug TEXT,
|
||||
UNIQUE(name, subcat)
|
||||
);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS model (
|
||||
id INTEGER PRIMARY KEY,
|
||||
category_id INTEGER NOT NULL REFERENCES category(id),
|
||||
series TEXT DEFAULT '',
|
||||
model_code TEXT NOT NULL,
|
||||
full_name TEXT DEFAULT '',
|
||||
aliases TEXT DEFAULT '',
|
||||
manufacturer TEXT DEFAULT '',
|
||||
country TEXT DEFAULT '中国',
|
||||
country_type TEXT DEFAULT '国产', -- 国产/进口/引进仿制/中外合资/未知
|
||||
first_year INTEGER,
|
||||
last_year INTEGER,
|
||||
status TEXT DEFAULT '未知',
|
||||
usage TEXT DEFAULT '',
|
||||
production_count TEXT DEFAULT '',
|
||||
axle_arrangement TEXT DEFAULT '',
|
||||
drive TEXT DEFAULT '',
|
||||
efficiency TEXT DEFAULT '',
|
||||
-- 数值 + 单位（拆分存储）
|
||||
length_value REAL, length_unit TEXT,
|
||||
width_value REAL, width_unit TEXT,
|
||||
height_value REAL, height_unit TEXT,
|
||||
wheelbase_value REAL, wheelbase_unit TEXT,
|
||||
weight_value REAL, weight_unit TEXT,
|
||||
axle_load_value REAL, axle_load_unit TEXT,
|
||||
load_value REAL, load_unit TEXT,
|
||||
tractive_start_value REAL, tractive_start_unit TEXT,
|
||||
tractive_cont_value REAL, tractive_cont_unit TEXT,
|
||||
power_kw_value REAL, power_kw_unit TEXT,
|
||||
max_speed_value REAL, max_speed_unit TEXT,
|
||||
capacity_value REAL, capacity_unit TEXT,
|
||||
raw_json TEXT, -- 原始清洗后所有列，保真不丢字段
|
||||
source_sheet TEXT
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_model_category ON model(category_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_model_code ON model(model_code);
|
||||
CREATE INDEX IF NOT EXISTS idx_model_first_year ON model(first_year);
|
||||
|
||||
CREATE TABLE IF NOT EXISTS unit (
|
||||
id INTEGER PRIMARY KEY,
|
||||
category_id INTEGER NOT NULL REFERENCES category(id),
|
||||
model_id INTEGER REFERENCES model(id),
|
||||
car_number TEXT,
|
||||
model_name TEXT DEFAULT '',
|
||||
function TEXT DEFAULT '',
|
||||
depot TEXT DEFAULT '',
|
||||
livery TEXT DEFAULT '',
|
||||
status TEXT DEFAULT '未知',
|
||||
location TEXT DEFAULT '',
|
||||
note TEXT DEFAULT '',
|
||||
raw_json TEXT,
|
||||
source_sheet TEXT
|
||||
);
|
||||
CREATE INDEX IF NOT EXISTS idx_unit_category ON unit(category_id);
|
||||
CREATE INDEX IF NOT EXISTS idx_unit_car_number ON unit(car_number);
|
||||
|
||||
-- 车型族谱关系（父型号/衍生/国外原型），本期预留，后续填充
|
||||
CREATE TABLE IF NOT EXISTS model_relation (
|
||||
id INTEGER PRIMARY KEY,
|
||||
from_model_id INTEGER NOT NULL REFERENCES model(id),
|
||||
to_model_id INTEGER NOT NULL REFERENCES model(id),
|
||||
rel_type TEXT NOT NULL, -- parent / derivative / prototype
|
||||
UNIQUE(from_model_id, to_model_id, rel_type)
|
||||
);
|
||||
Reference in New Issue
Block a user