Upload logbook_availability_query.py

logbook_availability_query.py

@@ -0,0 +1,401 @@
+import pandas as pd
+import os
+from datetime import datetime
+
+
+# ============================
+# 自动定位项目路径
+# ============================
+
+BASE_DIR = os.path.dirname(
+    os.path.dirname(
+        os.path.abspath(__file__)
+    )
+)
+
+
+DATA_PATH = os.path.join(
+    BASE_DIR,
+    "data",
+    "logbook_availability.csv"
+)
+
+
+OUTPUT_DIR = os.path.join(
+    BASE_DIR,
+    "output"
+)
+
+
+
+# ============================
+# markdown生成函数
+# 替代 pandas.to_markdown()
+# ============================
+
+def dataframe_to_markdown(df, max_rows=10):
+
+    if df.empty:
+        return "暂无数据"
+
+
+    df=df.head(max_rows)
+
+
+    columns=df.columns.tolist()
+
+
+    md="| " + " | ".join(columns)+" |\n"
+
+    md+="| "+" | ".join(
+        ["---"]*len(columns)
+    )+" |\n"
+
+
+    for _,row in df.iterrows():
+
+        md+="| "+" | ".join(
+            str(x)
+            for x in row.tolist()
+        )+" |\n"
+
+
+    return md
+
+
+
+# ============================
+# 参数检查
+# ============================
+
+def check_year(value,name):
+
+    if value is None:
+        return None
+
+
+    try:
+        return int(value)
+
+    except:
+
+        raise ValueError(
+            f"{name}必须是年份数字，例如2020"
+        )
+
+
+
+
+# ============================
+# 主查询函数
+# ============================
+
+def query_logbook_availability(
+        region=None,
+        year_start=None,
+        year_end=None,
+        species=None,
+        data_type=None,
+        output_format="markdown"
+):
+
+    """
+    查询logbook数据可用性
+
+    返回:
+    summary
+    records
+    preview_markdown
+    csv_path
+    excel_path
+    source_files
+
+    """
+
+
+    try:
+
+        # ------------------
+        # 参数校验
+        # ------------------
+
+        year_start = check_year(
+            year_start,
+            "year_start"
+        )
+
+        year_end = check_year(
+            year_end,
+            "year_end"
+        )
+
+
+
+        if year_start and year_end:
+
+            if year_start > year_end:
+
+                return {
+
+                    "summary":
+                    "错误：开始年份不能大于结束年份",
+
+                    "records":[]
+
+                }
+
+
+
+        # ------------------
+        # 文件检查
+        # ------------------
+
+        if not os.path.exists(DATA_PATH):
+
+            return {
+
+                "summary":
+                f"找不到数据文件:{DATA_PATH}",
+
+                "records":[]
+
+            }
+
+
+
+        # ------------------
+        # 读取数据
+        # ------------------
+
+        df=pd.read_csv(
+            DATA_PATH
+        )
+
+
+        # year强制转换
+
+        if "year" in df.columns:
+
+            df["year"]=pd.to_numeric(
+                df["year"],
+                errors="coerce"
+            )
+
+
+        result=df.copy()
+
+
+
+        # ------------------
+        # 条件过滤
+        # ------------------
+
+        if region:
+
+            result=result[
+                result["region"]
+                .astype(str)
+                .str.contains(
+                    region,
+                    na=False
+                )
+            ]
+
+
+
+        if species:
+
+            result=result[
+                result["species"]
+                .astype(str)
+                .str.contains(
+                    species,
+                    na=False
+                )
+            ]
+
+
+
+        if data_type:
+
+            result=result[
+                result["data_type"]
+                .astype(str)
+                .str.contains(
+                    data_type,
+                    na=False
+                )
+            ]
+
+
+
+        if year_start:
+
+            result=result[
+                result.year>=year_start
+            ]
+
+
+
+        if year_end:
+
+            result=result[
+                result.year<=year_end
+            ]
+
+
+
+        # ------------------
+        # 无结果
+        # ------------------
+
+        if result.empty:
+
+            return {
+
+                "summary":
+                "没有找到符合条件的logbook数据",
+
+                "records":[],
+
+                "preview_markdown":
+                "暂无数据",
+
+                "source_files":
+                [
+                    DATA_PATH
+                ]
+
+            }
+
+
+
+        # ------------------
+        # 统计信息
+        # ------------------
+
+        summary={
+
+            "records_count":
+            len(result),
+
+            "year_range":
+            [
+                int(result.year.min()),
+                int(result.year.max())
+            ],
+
+            "regions":
+            result.region.unique().tolist(),
+
+            "species":
+            result.species.unique().tolist()
+
+        }
+
+
+
+        # ------------------
+        # 输出文件
+        # ------------------
+
+        os.makedirs(
+            OUTPUT_DIR,
+            exist_ok=True
+        )
+
+
+        timestamp=datetime.now()\
+            .strftime("%Y%m%d_%H%M%S")
+
+
+        csv_path=None
+        excel_path=None
+
+
+
+        if output_format in [
+            "csv",
+            "excel"
+        ]:
+
+            csv_path=os.path.join(
+                OUTPUT_DIR,
+                f"logbook_{timestamp}.csv"
+            )
+
+
+            result.to_csv(
+                csv_path,
+                index=False,
+                encoding="utf-8-sig"
+            )
+
+
+
+        if output_format=="excel":
+
+            excel_path=os.path.join(
+                OUTPUT_DIR,
+                f"logbook_{timestamp}.xlsx"
+            )
+
+
+            result.to_excel(
+                excel_path,
+                index=False
+            )
+
+
+
+        # ------------------
+        # Agent标准返回
+        # ------------------
+
+        return {
+
+
+            "summary":
+            summary,
+
+
+            "records":
+            result.to_dict(
+                orient="records"
+            ),
+
+
+            "preview_markdown":
+            dataframe_to_markdown(
+                result
+            ),
+
+
+            "csv_path":
+            csv_path,
+
+
+            "excel_path":
+            excel_path,
+
+
+            "source_files":
+            [
+                DATA_PATH
+            ]
+
+        }
+
+
+
+    except Exception as e:
+
+
+        return {
+
+            "summary":
+            f"查询失败:{str(e)}",
+
+            "records":[]
+
+        }