Nome

DAQ/Bot_DAQ.spec

@@ -0,0 +1,38 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+
+a = Analysis(
+    ['d:\\Trabalhos\\Bot DAQ\\DAQ\\Untitled-1.py'],
+    pathex=[],
+    binaries=[],
+    datas=[],
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name='Bot_DAQ',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=False,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)

DAQ/Construção de Databases.py

@@ -0,0 +1,229 @@
+import os
+import re
+import tkinter as tk
+from tkinter import ttk, filedialog, messagebox
+from datetime import datetime
+
+import pandas as pd
+import pdfplumber
+
+
+START_MARKER = "Planeamento e execução da formação – Respostas:"
+END_MARKER   = "Ação dos formadores"
+
+
+def clean_cell(x) -> str:
+    if x is None:
+        return ""
+    x = str(x).replace("\n", " ").replace("\r", " ").strip()
+    x = re.sub(r"\s+", " ", x)
+    return x
+
+
+def normalize_df(df: pd.DataFrame) -> pd.DataFrame:
+    df = df.copy()
+    df = df.applymap(clean_cell)
+    df = df.loc[~(df.apply(lambda r: all(v == "" for v in r), axis=1))].reset_index(drop=True)
+    return df
+
+
+def df_text(df: pd.DataFrame) -> str:
+    vals = df.astype(str).fillna("").values.flatten().tolist()
+    return " ".join(vals)
+
+
+def safe_filename(s: str) -> str:
+    s = re.sub(r"[\\/:*?\"<>|]+", "_", s)
+    s = re.sub(r"\s+", "_", s.strip())
+    return s[:180] if len(s) > 180 else s
+
+
+def save_outputs(df: pd.DataFrame, pdf_path: str, year: str, course: str, out_dir: str):
+    os.makedirs(out_dir, exist_ok=True)
+    stamp = datetime.now().strftime("%Y%m%d_%H%M%S")
+
+    base = f"{safe_filename(os.path.splitext(os.path.basename(pdf_path))[0])}__{safe_filename(course)}__{safe_filename(year)}__{stamp}"
+    csv_path = os.path.join(out_dir, base + ".csv")
+    xlsx_path = os.path.join(out_dir, base + ".xlsx")
+
+    df.to_csv(csv_path, index=False, encoding="utf-8-sig")
+    df.to_excel(xlsx_path, index=False)
+    return csv_path, xlsx_path
+
+
+def normalize_marker(s: str) -> str:
+    s = s.replace("–", "-")
+    s = re.sub(r"\s+", " ", s).strip().lower()
+    return s
+
+
+def find_target_table(pdf_path: str):
+    start_n = normalize_marker(START_MARKER)
+    end_n   = normalize_marker(END_MARKER)
+
+    with pdfplumber.open(pdf_path) as pdf:
+        start_page_idx = None
+        for i, page in enumerate(pdf.pages):
+            text = page.extract_text() or ""
+            tnorm = normalize_marker(text)
+            if start_n in tnorm:
+                start_page_idx = i
+                break
+        if start_page_idx is None:
+            raise ValueError(f"Não encontrei o início do bloco: '{START_MARKER}'")
+        end_page_idx = None
+        for j in range(start_page_idx, len(pdf.pages)):
+            text = pdf.pages[j].extract_text() or ""
+            tnorm = normalize_marker(text)
+            if end_n in tnorm:
+                end_page_idx = j
+                break
+
+        if end_page_idx is None:
+            raise ValueError(f"Encontrei o início, mas não encontrei o fim do bloco: '{END_MARKER}'")
+        candidate_tables = []
+        for pno in range(start_page_idx, end_page_idx + 1):
+            page = pdf.pages[pno]
+            tables = page.extract_tables() or []
+            page_text = normalize_marker(page.extract_text() or "")
+
+            for ti, tbl in enumerate(tables, start=1):
+                if not tbl or len(tbl) < 2:
+                    continue
+                df = pd.DataFrame(tbl[1:], columns=tbl[0])
+                df = normalize_df(df)
+                raw = df_text(df)
+                raw_n = normalize_marker(raw)
+
+                score = 0
+                r, c = df.shape
+                if c >= 3: score += 10
+                if r >= 4: score += 10
+                if pno == start_page_idx:
+                    score += 15
+                for kw in ["respostas", "planeamento", "execução", "formação", "formadores"]:
+                    if kw in raw_n:
+                        score += 2
+                empties = (df == "").sum().sum()
+                total = r * c
+                if total and empties / total > 0.6:
+                    score -= 10
+
+                candidate_tables.append((score, pno, ti, df))
+
+        if not candidate_tables:
+            raise ValueError("Encontrei o bloco, mas não encontrei tabelas nesse intervalo.")
+        candidate_tables.sort(key=lambda x: x[0], reverse=True)
+        best_score, best_pno, best_ti, best_df = candidate_tables[0]
+
+        return {
+            "start_page": start_page_idx + 1,
+            "end_page": end_page_idx + 1,
+            "best_page": best_pno + 1,
+            "best_table_id": f"p{best_pno+1}_t{best_ti}",
+            "score": best_score,
+            "df": best_df
+        }
+
+
+class App(tk.Tk):
+    def __init__(self):
+        super().__init__()
+        self.title("Extrair Tabela do PDF (bloco entre títulos)")
+        self.geometry("820x300")
+        self.resizable(False, False)
+
+        self.pdf_path = tk.StringVar(value="")
+        self.year_var = tk.StringVar(value="")
+        self.course_var = tk.StringVar(value="")
+        self.outdir_var = tk.StringVar(value="output_tables")
+
+        self._build_ui()
+
+    def _build_ui(self):
+        frm = ttk.Frame(self, padding=14)
+        frm.pack(fill="both", expand=True)
+
+        # PDF
+        ttk.Label(frm, text="PDF:").grid(row=0, column=0, sticky="w")
+        ttk.Entry(frm, textvariable=self.pdf_path, width=74).grid(row=0, column=1, sticky="w", padx=(8, 8))
+        ttk.Button(frm, text="Escolher...", command=self.on_browse_pdf).grid(row=0, column=2, sticky="w")
+
+        # Ano
+        ttk.Label(frm, text="Ano:").grid(row=1, column=0, sticky="w", pady=(12, 0))
+        ttk.Entry(frm, textvariable=self.year_var, width=20).grid(row=1, column=1, sticky="w", padx=(8, 0), pady=(12, 0))
+
+        # Curso
+        ttk.Label(frm, text="Curso:").grid(row=2, column=0, sticky="w", pady=(12, 0))
+        ttk.Entry(frm, textvariable=self.course_var, width=50).grid(row=2, column=1, sticky="w", padx=(8, 0), pady=(12, 0))
+
+        # Output dir
+        ttk.Label(frm, text="Pasta de saída:").grid(row=3, column=0, sticky="w", pady=(12, 0))
+        ttk.Entry(frm, textvariable=self.outdir_var, width=40).grid(row=3, column=1, sticky="w", padx=(8, 0), pady=(12, 0))
+
+        # info sobre markers
+        info = (
+            f"Vai extrair a tabela do bloco:\n"
+            f"INÍCIO: {START_MARKER}\n"
+            f"FIM: {END_MARKER}"
+        )
+        ttk.Label(frm, text=info).grid(row=4, column=0, columnspan=3, sticky="w", pady=(14, 0))
+
+        # Botões
+        btns = ttk.Frame(frm)
+        btns.grid(row=5, column=0, columnspan=3, sticky="e", pady=(18, 0))
+        ttk.Button(btns, text="Extrair", command=self.on_extract).pack(side="right", padx=(8, 0))
+        ttk.Button(btns, text="Sair", command=self.destroy).pack(side="right")
+
+    def on_browse_pdf(self):
+        path = filedialog.askopenfilename(
+            title="Seleciona um PDF",
+            filetypes=[("PDF files", "*.pdf"), ("All files", "*.*")]
+        )
+        if path:
+            self.pdf_path.set(path)
+
+    def on_extract(self):
+        pdf_path = self.pdf_path.get().strip()
+        year = self.year_var.get().strip()
+        course = self.course_var.get().strip()
+        outdir = self.outdir_var.get().strip() or "output_tables"
+
+        if not pdf_path or not os.path.exists(pdf_path):
+            messagebox.showerror("Erro", "Seleciona um PDF válido.")
+            return
+        if not year:
+            messagebox.showerror("Erro", "Preenche o Ano.")
+            return
+        if not course:
+            messagebox.showerror("Erro", "Preenche o Curso.")
+            return
+
+        try:
+            self.configure(cursor="watch")
+            self.update_idletasks()
+
+            result = find_target_table(pdf_path)
+            df = result["df"]
+
+            csv_path, xlsx_path = save_outputs(df, pdf_path, year, course, outdir)
+
+            messagebox.showinfo(
+                "OK",
+                "Tabela extraída com sucesso!\n\n"
+                f"Bloco encontrado nas páginas: {result['start_page']} → {result['end_page']}\n"
+                f"Tabela escolhida: {result['best_table_id']} (score={result['score']})\n"
+                f"Dimensões: {df.shape[0]} x {df.shape[1]}\n\n"
+                f"CSV: {csv_path}\n"
+                f"XLSX: {xlsx_path}"
+            )
+
+        except Exception as e:
+            messagebox.showerror("Erro", f"Falhou.\n\nDetalhes: {e}")
+        finally:
+            self.configure(cursor="")
+            self.update_idletasks()
+
+
+if __name__ == "__main__":
+    App().mainloop()

DAQ/Untitled-1.ipynb

@@ -0,0 +1,865 @@
+{
+ "cells": [
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "1f540c43",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "import os\n",
+    "import tkinter as tk\n",
+    "from tkinter import filedialog, simpledialog, messagebox\n",
+    "import re\n",
+    "from datetime import datetime\n",
+    "import pandas as pd\n",
+    "import pdfplumber\n",
+    "from tkinter import messagebox\n",
+    "import sys\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 43,
+   "id": "74f35480",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "START_MARKER = \"Planeamento e execução da formação – Respostas:\"\n",
+    "END_MARKER   = \"Ação dos formadores\"\n",
+    "OUT_DIR = \"output_tables\"\n",
+    "os.makedirs(OUT_DIR, exist_ok=True)\n",
+    "\n",
+    "root = tk.Tk()\n",
+    "root.withdraw() \n",
+    "root.update()\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 44,
+   "id": "8b51acae",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'D:\\\\DAQ\\\\Relatorios\\\\2CFPQP-ART\\\\2CFPQP_RAI_Art.pdf'"
+      ]
+     },
+     "execution_count": 44,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "pdf_path = filedialog.askopenfilename(\n",
+    "    title=\"Seleciona o PDF\",\n",
+    "    filetypes=[(\"PDF files\", \"*.pdf\"), (\"All files\", \"*.*\")]\n",
+    ")\n",
+    "\n",
+    "if not pdf_path:\n",
+    "    messagebox.showerror(\"Erro\", \"Nenhum PDF selecionado.\")\n",
+    "    raise SystemExit\n",
+    "\n",
+    "pdf_path = os.path.abspath(pdf_path)\n",
+    "pdf_path\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 45,
+   "id": "e62c1fbb",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2CFPQP-Art'"
+      ]
+     },
+     "execution_count": 45,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "course_name = simpledialog.askstring(\n",
+    "    title=\"Nome do Curso\",\n",
+    "    prompt=\"Introduz o nome do curso:\"\n",
+    ")\n",
+    "\n",
+    "if not course_name:\n",
+    "    messagebox.showerror(\"Erro\", \"Nome do curso não foi preenchido.\")\n",
+    "    raise SystemExit\n",
+    "\n",
+    "course_name\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 46,
+   "id": "212eb52c",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "'2024'"
+      ]
+     },
+     "execution_count": 46,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "year = simpledialog.askstring(\n",
+    "    title=\"Ano\",\n",
+    "    prompt=\"Introduz o ano (ex: 2024):\"\n",
+    ")\n",
+    "\n",
+    "if not year or not year.isdigit():\n",
+    "    messagebox.showerror(\"Erro\", \"Ano inválido.\")\n",
+    "    raise SystemExit\n",
+    "\n",
+    "year\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 47,
+   "id": "5a225637",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def norm_text(s: str) -> str:\n",
+    "    if not s:\n",
+    "        return \"\"\n",
+    "    s = s.replace(\"–\", \"-\")\n",
+    "    s = re.sub(r\"\\s+\", \" \", s).strip().lower()\n",
+    "    return s\n",
+    "\n",
+    "def clean_cell(x) -> str:\n",
+    "    if x is None:\n",
+    "        return \"\"\n",
+    "    x = str(x).replace(\"\\n\", \" \").replace(\"\\r\", \" \").strip()\n",
+    "    x = re.sub(r\"\\s+\", \" \", x)\n",
+    "    return x\n",
+    "\n",
+    "def normalize_df(df: pd.DataFrame) -> pd.DataFrame:\n",
+    "    df = df.copy().applymap(clean_cell)\n",
+    "    df = df.loc[~(df.apply(lambda r: all(v == \"\" for v in r), axis=1))].reset_index(drop=True)\n",
+    "    return df\n",
+    "\n",
+    "def df_flattext(df: pd.DataFrame) -> str:\n",
+    "    vals = df.astype(str).fillna(\"\").values.flatten().tolist()\n",
+    "    return \" \".join(vals)\n",
+    "\n",
+    "def safe_filename(s: str) -> str:\n",
+    "    s = re.sub(r\"[\\\\/:*?\\\"<>|]+\", \"_\", s)\n",
+    "    s = re.sub(r\"\\s+\", \"_\", s.strip())\n",
+    "    return s[:180]\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 48,
+   "id": "990ce85a",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/plain": [
+       "(7, 8)"
+      ]
+     },
+     "execution_count": 48,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "start_n = norm_text(START_MARKER)\n",
+    "end_n   = norm_text(END_MARKER)\n",
+    "with pdfplumber.open(pdf_path) as pdf:\n",
+    "    start_page = None\n",
+    "    end_page = None\n",
+    "    for i, page in enumerate(pdf.pages):\n",
+    "        txt = norm_text(page.extract_text() or \"\")\n",
+    "        if start_n in txt:\n",
+    "            start_page = i\n",
+    "            break\n",
+    "    if start_page is None:\n",
+    "        raise ValueError(f\"Não encontrei o início: {START_MARKER}\")\n",
+    "    for j in range(start_page, len(pdf.pages)):\n",
+    "        txt = norm_text(pdf.pages[j].extract_text() or \"\")\n",
+    "        if end_n in txt:\n",
+    "            end_page = j\n",
+    "            break\n",
+    "    if end_page is None:\n",
+    "        raise ValueError(f\"Encontrei o início, mas não encontrei o fim: {END_MARKER}\")\n",
+    "(start_page + 1, end_page + 1)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 49,
+   "id": "43916fc0",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\garci\\AppData\\Local\\Temp\\ipykernel_17004\\2567387785.py:16: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
+      "  df = df.copy().applymap(clean_cell)\n",
+      "C:\\Users\\garci\\AppData\\Local\\Temp\\ipykernel_17004\\2567387785.py:16: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
+      "  df = df.copy().applymap(clean_cell)\n",
+      "C:\\Users\\garci\\AppData\\Local\\Temp\\ipykernel_17004\\2567387785.py:16: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
+      "  df = df.copy().applymap(clean_cell)\n",
+      "C:\\Users\\garci\\AppData\\Local\\Temp\\ipykernel_17004\\2567387785.py:16: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
+      "  df = df.copy().applymap(clean_cell)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/plain": [
+       "4"
+      ]
+     },
+     "execution_count": 49,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "candidates = []\n",
+    "\n",
+    "with pdfplumber.open(pdf_path) as pdf:\n",
+    "    for pno in range(start_page, end_page + 1):\n",
+    "        page = pdf.pages[pno]\n",
+    "        tables = page.extract_tables() or []\n",
+    "\n",
+    "        for ti, tbl in enumerate(tables, start=1):\n",
+    "            if not tbl or len(tbl) < 2:\n",
+    "                continue\n",
+    "            header = tbl[0]\n",
+    "            body = tbl[1:]\n",
+    "            df = pd.DataFrame(body, columns=header)\n",
+    "            df = normalize_df(df)\n",
+    "\n",
+    "            r, c = df.shape\n",
+    "            if r < 2 or c < 2:\n",
+    "                continue\n",
+    "            text_n = norm_text(df_flattext(df))\n",
+    "            score = 0\n",
+    "            if c >= 3: score += 10\n",
+    "            if r >= 4: score += 10\n",
+    "            if pno == start_page: score += 15\n",
+    "            for kw in [\"planeamento\", \"execucao\", \"formacao\", \"respostas\", \"formadores\"]:\n",
+    "                if kw in text_n:\n",
+    "                    score += 2\n",
+    "\n",
+    "            empties = (df == \"\").sum().sum()\n",
+    "            total = r * c\n",
+    "            if total and empties / total > 0.6:\n",
+    "                score -= 10\n",
+    "\n",
+    "            candidates.append((score, pno, ti, df))\n",
+    "\n",
+    "len(candidates)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 50,
+   "id": "cd4bd06b",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stdout",
+     "output_type": "stream",
+     "text": [
+      "Bloco: páginas 7 → 8\n",
+      "Tabela escolhida: p7_t1 (score=35)\n",
+      "Dimensões: (18, 4)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>Indicadores</th>\n",
+       "      <th>Avaliação</th>\n",
+       "      <th>None</th>\n",
+       "      <th>Ganhos / Perdas</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1. Intervenção da Unidade Formadora</td>\n",
+       "      <td>Inicial</td>\n",
+       "      <td>Final</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.1 Apoio Técnico administrativo</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>3.91</td>\n",
+       "      <td>N/A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.2 Alojamento</td>\n",
+       "      <td>4.55</td>\n",
+       "      <td>4.45</td>\n",
+       "      <td>-0.1</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>1.3 Alimentação</td>\n",
+       "      <td>4.27</td>\n",
+       "      <td>4.0</td>\n",
+       "      <td>-0.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>2. Intervenção da Direção de Curso</td>\n",
+       "      <td>Inicial</td>\n",
+       "      <td>Final</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>2.1 Apoio prestado pela Direção de Curso</td>\n",
+       "      <td>N/A</td>\n",
+       "      <td>4.09</td>\n",
+       "      <td>N/A</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3. Programa de Curso</td>\n",
+       "      <td>Inicial</td>\n",
+       "      <td>Final</td>\n",
+       "      <td></td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>3.1 Grau de dificuldade do curso</td>\n",
+       "      <td>3.55</td>\n",
+       "      <td>3.27</td>\n",
+       "      <td>-0.28</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>3.2 Utilidade do Curso para futuras funções</td>\n",
+       "      <td>4.09</td>\n",
+       "      <td>3.82</td>\n",
+       "      <td>-0.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>3.3 Motivação e participação</td>\n",
+       "      <td>4.45</td>\n",
+       "      <td>4.09</td>\n",
+       "      <td>-0.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>3.4 Grau de conhecimento adquirido com o curso</td>\n",
+       "      <td>3.73</td>\n",
+       "      <td>4.09</td>\n",
+       "      <td>0.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>4. Funcionamento do Curso</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>Média</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>4.1 Objetivo do curso</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>3.64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>4.2 Conteúdo do curso</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>14</th>\n",
+       "      <td>4.3 Adequação dos trabalhos/exercícios</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>3.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>15</th>\n",
+       "      <td>4.4 Instalações afetas à formação</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>3.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>16</th>\n",
+       "      <td>4.5 Meios audiovisuais e didáticos</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>17</th>\n",
+       "      <td>4.6 Documentos e bibliografias disponibilizadas</td>\n",
+       "      <td></td>\n",
+       "      <td></td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                        Indicadores Avaliação   None  \\\n",
+       "0               1. Intervenção da Unidade Formadora   Inicial  Final   \n",
+       "1                  1.1 Apoio Técnico administrativo       N/A   3.91   \n",
+       "2                                    1.2 Alojamento      4.55   4.45   \n",
+       "3                                   1.3 Alimentação      4.27    4.0   \n",
+       "4                2. Intervenção da Direção de Curso   Inicial  Final   \n",
+       "5          2.1 Apoio prestado pela Direção de Curso       N/A   4.09   \n",
+       "6                              3. Programa de Curso   Inicial  Final   \n",
+       "7                  3.1 Grau de dificuldade do curso      3.55   3.27   \n",
+       "8       3.2 Utilidade do Curso para futuras funções      4.09   3.82   \n",
+       "9                      3.3 Motivação e participação      4.45   4.09   \n",
+       "10   3.4 Grau de conhecimento adquirido com o curso      3.73   4.09   \n",
+       "11                        4. Funcionamento do Curso                    \n",
+       "12                            4.1 Objetivo do curso                    \n",
+       "13                            4.2 Conteúdo do curso                    \n",
+       "14           4.3 Adequação dos trabalhos/exercícios                    \n",
+       "15                4.4 Instalações afetas à formação                    \n",
+       "16               4.5 Meios audiovisuais e didáticos                    \n",
+       "17  4.6 Documentos e bibliografias disponibilizadas                    \n",
+       "\n",
+       "   Ganhos / Perdas  \n",
+       "0                   \n",
+       "1              N/A  \n",
+       "2             -0.1  \n",
+       "3            -0.27  \n",
+       "4                   \n",
+       "5              N/A  \n",
+       "6                   \n",
+       "7            -0.28  \n",
+       "8            -0.27  \n",
+       "9            -0.36  \n",
+       "10            0.36  \n",
+       "11           Média  \n",
+       "12            3.64  \n",
+       "13            3.55  \n",
+       "14            3.36  \n",
+       "15            3.82  \n",
+       "16            4.09  \n",
+       "17            4.09  "
+      ]
+     },
+     "execution_count": 50,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "if not candidates:\n",
+    "    raise ValueError(\"Encontrei o bloco, mas não encontrei tabelas nas páginas desse intervalo.\")\n",
+    "\n",
+    "candidates.sort(key=lambda x: x[0], reverse=True)\n",
+    "best_score, best_pno, best_ti, best_df = candidates[0]\n",
+    "\n",
+    "print(f\"Bloco: páginas {start_page+1} → {end_page+1}\")\n",
+    "print(f\"Tabela escolhida: p{best_pno+1}_t{best_ti} (score={best_score})\")\n",
+    "print(\"Dimensões:\", best_df.shape)\n",
+    "\n",
+    "best_df.head(30)\n"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 51,
+   "id": "884d3881",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def dot_to_comma(df: pd.DataFrame) -> pd.DataFrame:\n",
+    "    df = df.copy()\n",
+    "\n",
+    "    def convert(x):\n",
+    "        if isinstance(x, (int, float)):\n",
+    "            return str(x).replace(\".\", \",\")\n",
+    "        if isinstance(x, str):\n",
+    "            # só troca se parecer número (ex: \"3.5\")\n",
+    "            if re.fullmatch(r\"-?\\d+\\.\\d+\", x):\n",
+    "                return x.replace(\".\", \",\")\n",
+    "        return x\n",
+    "\n",
+    "    return df.applymap(convert)"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 52,
+   "id": "f1d5c545",
+   "metadata": {},
+   "outputs": [
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>0</th>\n",
+       "      <th>1</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>0</th>\n",
+       "      <td>1.1 Apoio Técnico administrativo</td>\n",
+       "      <td>3.91</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>1</th>\n",
+       "      <td>1.2 Alojamento</td>\n",
+       "      <td>4.45</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>2</th>\n",
+       "      <td>1.3 Alimentação</td>\n",
+       "      <td>4.0</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>3</th>\n",
+       "      <td>2.1 Apoio prestado pela Direção de Curso</td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>4</th>\n",
+       "      <td>3.1 Grau de dificuldade do curso</td>\n",
+       "      <td>3.27</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>5</th>\n",
+       "      <td>3.2 Utilidade do Curso para futuras funções</td>\n",
+       "      <td>3.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>6</th>\n",
+       "      <td>3.3 Motivação e participação</td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>7</th>\n",
+       "      <td>3.4 Grau de conhecimento adquirido com o curso</td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>8</th>\n",
+       "      <td>4.1 Objetivo do curso</td>\n",
+       "      <td>3.64</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>9</th>\n",
+       "      <td>4.2 Conteúdo do curso</td>\n",
+       "      <td>3.55</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>10</th>\n",
+       "      <td>4.3 Adequação dos trabalhos/exercícios</td>\n",
+       "      <td>3.36</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>11</th>\n",
+       "      <td>4.4 Instalações afetas à formação</td>\n",
+       "      <td>3.82</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>12</th>\n",
+       "      <td>4.5 Meios audiovisuais e didáticos</td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "    <tr>\n",
+       "      <th>13</th>\n",
+       "      <td>4.6 Documentos e bibliografias disponibilizadas</td>\n",
+       "      <td>4.09</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                                                  0     1\n",
+       "0                  1.1 Apoio Técnico administrativo  3.91\n",
+       "1                                    1.2 Alojamento  4.45\n",
+       "2                                   1.3 Alimentação   4.0\n",
+       "3          2.1 Apoio prestado pela Direção de Curso  4.09\n",
+       "4                  3.1 Grau de dificuldade do curso  3.27\n",
+       "5       3.2 Utilidade do Curso para futuras funções  3.82\n",
+       "6                      3.3 Motivação e participação  4.09\n",
+       "7    3.4 Grau de conhecimento adquirido com o curso  4.09\n",
+       "8                             4.1 Objetivo do curso  3.64\n",
+       "9                             4.2 Conteúdo do curso  3.55\n",
+       "10           4.3 Adequação dos trabalhos/exercícios  3.36\n",
+       "11                4.4 Instalações afetas à formação  3.82\n",
+       "12               4.5 Meios audiovisuais e didáticos  4.09\n",
+       "13  4.6 Documentos e bibliografias disponibilizadas  4.09"
+      ]
+     },
+     "execution_count": 52,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "rows_config = {\n",
+    "    1: [0, 2],\n",
+    "    2: [0, 2],\n",
+    "    3: [0, 2],\n",
+    "    5: [0, 2],\n",
+    "    7: [0, 2],\n",
+    "    8: [0, 2],\n",
+    "    9: [0, 2],\n",
+    "    10: [0, 2],\n",
+    "    12: [0, 3],\n",
+    "    13: [0, 3],\n",
+    "    14: [0, 3],\n",
+    "    15: [0, 3],\n",
+    "    16: [0, 3],\n",
+    "    17: [0, 3]\n",
+    "}\n",
+    "\n",
+    "new_rows = []\n",
+    "\n",
+    "for row_idx, col_idxs in rows_config.items():\n",
+    "    values = best_df.iloc[row_idx, col_idxs].tolist()\n",
+    "    new_rows.append(values)\n",
+    "\n",
+    "new_df = pd.DataFrame(new_rows)\n",
+    "new_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": 53,
+   "id": "5dfa7c90",
+   "metadata": {},
+   "outputs": [
+    {
+     "name": "stderr",
+     "output_type": "stream",
+     "text": [
+      "C:\\Users\\garci\\AppData\\Local\\Temp\\ipykernel_17004\\2220260037.py:13: FutureWarning: DataFrame.applymap has been deprecated. Use DataFrame.map instead.\n",
+      "  return df.applymap(convert)\n"
+     ]
+    },
+    {
+     "data": {
+      "text/html": [
+       "<div>\n",
+       "<style scoped>\n",
+       "    .dataframe tbody tr th:only-of-type {\n",
+       "        vertical-align: middle;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe tbody tr th {\n",
+       "        vertical-align: top;\n",
+       "    }\n",
+       "\n",
+       "    .dataframe thead th {\n",
+       "        text-align: right;\n",
+       "    }\n",
+       "</style>\n",
+       "<table border=\"1\" class=\"dataframe\">\n",
+       "  <thead>\n",
+       "    <tr style=\"text-align: right;\">\n",
+       "      <th></th>\n",
+       "      <th>1.1 Apoio Técnico administrativo</th>\n",
+       "      <th>1.2 Alojamento</th>\n",
+       "      <th>1.3 Alimentação</th>\n",
+       "      <th>2.1 Apoio prestado pela Direção de Curso</th>\n",
+       "      <th>3.1 Grau de dificuldade do curso</th>\n",
+       "      <th>3.2 Utilidade do Curso para futuras funções</th>\n",
+       "      <th>3.3 Motivação e participação</th>\n",
+       "      <th>3.4 Grau de conhecimento adquirido com o curso</th>\n",
+       "      <th>4.1 Objetivo do curso</th>\n",
+       "      <th>4.2 Conteúdo do curso</th>\n",
+       "      <th>4.3 Adequação dos trabalhos/exercícios</th>\n",
+       "      <th>4.4 Instalações afetas à formação</th>\n",
+       "      <th>4.5 Meios audiovisuais e didáticos</th>\n",
+       "      <th>4.6 Documentos e bibliografias disponibilizadas</th>\n",
+       "    </tr>\n",
+       "  </thead>\n",
+       "  <tbody>\n",
+       "    <tr>\n",
+       "      <th>2024 - 2CFPQP-Art</th>\n",
+       "      <td>3,91</td>\n",
+       "      <td>4,45</td>\n",
+       "      <td>4,0</td>\n",
+       "      <td>4,09</td>\n",
+       "      <td>3,27</td>\n",
+       "      <td>3,82</td>\n",
+       "      <td>4,09</td>\n",
+       "      <td>4,09</td>\n",
+       "      <td>3,64</td>\n",
+       "      <td>3,55</td>\n",
+       "      <td>3,36</td>\n",
+       "      <td>3,82</td>\n",
+       "      <td>4,09</td>\n",
+       "      <td>4,09</td>\n",
+       "    </tr>\n",
+       "  </tbody>\n",
+       "</table>\n",
+       "</div>"
+      ],
+      "text/plain": [
+       "                  1.1 Apoio Técnico administrativo 1.2 Alojamento  \\\n",
+       "2024 - 2CFPQP-Art                             3,91           4,45   \n",
+       "\n",
+       "                  1.3 Alimentação 2.1 Apoio prestado pela Direção de Curso  \\\n",
+       "2024 - 2CFPQP-Art             4,0                                     4,09   \n",
+       "\n",
+       "                  3.1 Grau de dificuldade do curso  \\\n",
+       "2024 - 2CFPQP-Art                             3,27   \n",
+       "\n",
+       "                  3.2 Utilidade do Curso para futuras funções  \\\n",
+       "2024 - 2CFPQP-Art                                        3,82   \n",
+       "\n",
+       "                  3.3 Motivação e participação  \\\n",
+       "2024 - 2CFPQP-Art                         4,09   \n",
+       "\n",
+       "                  3.4 Grau de conhecimento adquirido com o curso  \\\n",
+       "2024 - 2CFPQP-Art                                           4,09   \n",
+       "\n",
+       "                  4.1 Objetivo do curso 4.2 Conteúdo do curso  \\\n",
+       "2024 - 2CFPQP-Art                  3,64                  3,55   \n",
+       "\n",
+       "                  4.3 Adequação dos trabalhos/exercícios  \\\n",
+       "2024 - 2CFPQP-Art                                   3,36   \n",
+       "\n",
+       "                  4.4 Instalações afetas à formação  \\\n",
+       "2024 - 2CFPQP-Art                              3,82   \n",
+       "\n",
+       "                  4.5 Meios audiovisuais e didáticos  \\\n",
+       "2024 - 2CFPQP-Art                               4,09   \n",
+       "\n",
+       "                  4.6 Documentos e bibliografias disponibilizadas  \n",
+       "2024 - 2CFPQP-Art                                            4,09  "
+      ]
+     },
+     "execution_count": 53,
+     "metadata": {},
+     "output_type": "execute_result"
+    }
+   ],
+   "source": [
+    "data_dict = dict(zip(new_df[0], new_df[1]))\n",
+    "final_df = pd.DataFrame([data_dict])\n",
+    "final_df.index = [f\"{year} - {course_name}\"]\n",
+    "final_df = dot_to_comma(final_df)\n",
+    "final_df"
+   ]
+  },
+  {
+   "cell_type": "code",
+   "execution_count": null,
+   "id": "10337d57",
+   "metadata": {},
+   "outputs": [],
+   "source": [
+    "def save_row_if_new(final_df: pd.DataFrame, xlsx_path: str, row_name: str, sheet_name: str = \"Resultados\"):\n",
+    "    root = tk.Tk()\n",
+    "    root.withdraw()\n",
+    "    if not os.path.exists(xlsx_path):\n",
+    "        final_df.to_excel(xlsx_path, sheet_name=sheet_name, index=True)\n",
+    "        messagebox.showinfo(\"OK\", f\"Ficheiro criado e linha guardada:\\n{row_name}\\n\\n{xlsx_path}\")\n",
+    "        return False \n",
+    "    try:\n",
+    "        existing = pd.read_excel(xlsx_path, sheet_name=sheet_name, index_col=0)\n",
+    "    except ValueError:\n",
+    "        final_df.to_excel(xlsx_path, sheet_name=sheet_name, index=True)\n",
+    "        messagebox.showinfo(\"OK\", f\"Sheet '{sheet_name}' criada e linha guardada:\\n{row_name}\")\n",
+    "        return False\n",
+    "    if row_name in existing.index.astype(str):\n",
+    "        messagebox.showwarning(\"Já existe\", f\"Já existe uma linha com este nome:\\n{row_name}\\n\\nNada foi gravado.\")\n",
+    "        return True\n",
+    "    updated = pd.concat([existing, final_df], axis=0)\n",
+    "    with pd.ExcelWriter(xlsx_path, engine=\"openpyxl\", mode=\"w\") as writer:\n",
+    "        updated.to_excel(writer, sheet_name=sheet_name, index=True)\n",
+    "    messagebox.showinfo(\"OK\", f\"Linha adicionada com sucesso:\\n{row_name}\\n\\n{xlsx_path}\")\n",
+    "    return False\n",
+    "row_name = f\"{year} - {course_name}\"\n",
+    "xlsx_path = \"BDpowerbi.xlsx\"\n",
+    "_duplicado = save_row_if_new(final_df, xlsx_path, row_name, sheet_name=\"Resultados\")\n",
+    "\n",
+    "sys.exit(0)"
+   ]
+  }
+ ],
+ "metadata": {
+  "kernelspec": {
+   "display_name": "Python 3",
+   "language": "python",
+   "name": "python3"
+  },
+  "language_info": {
+   "codemirror_mode": {
+    "name": "ipython",
+    "version": 3
+   },
+   "file_extension": ".py",
+   "mimetype": "text/x-python",
+   "name": "python",
+   "nbconvert_exporter": "python",
+   "pygments_lexer": "ipython3",
+   "version": "3.14.2"
+  }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 5
+}

DAQ/Untitled-1.py

@@ -0,0 +1,242 @@
+import os
+import re
+import sys
+from datetime import datetime
+import tkinter as tk
+from tkinter import filedialog, simpledialog, messagebox
+
+import pandas as pd
+import pdfplumber
+
+
+START_MARKER = "Planeamento e execução da formação – "
+END_MARKER = "Ação dos formadores"
+
+
+def norm_text(s: str) -> str:
+    if not s:
+        return ""
+    s = s.replace("–", "-")
+    s = re.sub(r"\s+", " ", s).strip().lower()
+    return s
+
+
+def clean_cell(x) -> str:
+    if x is None:
+        return ""
+    x = str(x).replace("\n", " ").replace("\r", " ").strip()
+    x = re.sub(r"\s+", " ", x)
+    return x
+
+def convert(x):
+    if isinstance(x, (int, float)):
+        return str(x).replace(".", ",")
+    if isinstance(x, str):
+        import re
+        if re.fullmatch(r"-?\d+\.\d+", x):
+            return x.replace(".", ",")
+    return x
+
+def normalize_df(df: pd.DataFrame) -> pd.DataFrame:
+    df = df.copy()
+    df = df.apply(lambda col: col.map(clean_cell))
+    df = df.apply(lambda col: col.map(convert))
+    df = df.loc[
+        ~(df.apply(lambda r: all(v == "" for v in r), axis=1))
+    ].reset_index(drop=True)
+
+    return df
+
+
+
+def df_flattext(df: pd.DataFrame) -> str:
+    vals = df.astype(str).fillna("").values.flatten().tolist()
+    return " ".join(vals)
+
+
+def safe_filename(s: str) -> str:
+    s = re.sub(r"[\\/:*?\"<>|]+", "_", s)
+    s = re.sub(r"\s+", "_", s.strip())
+    return s[:180]
+
+
+def dot_to_comma(df: pd.DataFrame) -> pd.DataFrame:
+    df = df.copy()
+
+    def convert(x):
+        if isinstance(x, (int, float)):
+            return str(x).replace(".", ",")
+        if isinstance(x, str):
+            if re.fullmatch(r"-?\d+\.\d+", x):
+                return x.replace(".", ",")
+        return x
+
+    return df.apply(lambda col: col.map(convert))
+
+
+def save_row_if_new(
+    final_df: pd.DataFrame,
+    xlsx_path: str,
+    row_name: str,
+    sheet_name: str = "Resultados",
+):
+    root = tk.Tk()
+    root.withdraw()
+    if not os.path.exists(xlsx_path):
+        final_df.to_excel(xlsx_path, sheet_name=sheet_name, index=True)
+        messagebox.showinfo("OK", f"Ficheiro criado e linha guardada:\n{row_name}\n\n{xlsx_path}")
+        return False
+    try:
+        existing = pd.read_excel(xlsx_path, sheet_name=sheet_name, index_col=0)
+    except ValueError:
+        final_df.to_excel(xlsx_path, sheet_name=sheet_name, index=True)
+        messagebox.showinfo("OK", f"Sheet '{sheet_name}' criada e linha guardada:\n{row_name}")
+        return False
+    if row_name in existing.index.astype(str):
+        messagebox.showwarning(
+            "Já existe",
+            f"Já existe uma linha com este nome:\n{row_name}\n\nNada foi gravado.",
+        )
+        return True
+    updated = pd.concat([existing, final_df], axis=0)
+    with pd.ExcelWriter(xlsx_path, engine="openpyxl", mode="w") as writer:
+        updated.to_excel(writer, sheet_name=sheet_name, index=True)
+    messagebox.showinfo("OK", f"Linha adicionada com sucesso:\n{row_name}\n\n{xlsx_path}")
+    return False
+
+
+def main() -> int:
+
+    root = tk.Tk()
+    root.withdraw()
+    root.update()
+
+    pdf_path = filedialog.askopenfilename(
+        title="Seleciona o PDF",
+        filetypes=[("PDF files", "*.pdf"), ("All files", "*.*")],
+    )
+    if not pdf_path:
+        messagebox.showerror("Erro", "Nenhum PDF selecionado.")
+        return 1
+
+    pdf_path = os.path.abspath(pdf_path)
+
+    course_name = simpledialog.askstring(
+        title="Nome do Curso",
+        prompt="Introduz o nome do curso:",
+    )
+    if not course_name:
+        messagebox.showerror("Erro", "Nome do curso nÃo foi preenchido.")
+        return 1
+
+    year = simpledialog.askstring(
+        title="Ano",
+        prompt="Introduz o ano (ex: 2024):",
+    )
+    if not year or not year.isdigit():
+        messagebox.showerror("Erro", "Ano inválido.")
+        return 1
+
+    start_n = norm_text(START_MARKER)
+    end_n = norm_text(END_MARKER)
+    with pdfplumber.open(pdf_path) as pdf:
+        start_page = None
+        end_page = None
+        for i, page in enumerate(pdf.pages):
+            txt = norm_text(page.extract_text() or "")
+            if start_n in txt:
+                start_page = i
+                break
+        if start_page is None:
+            raise ValueError(f"Não encontrei o ini­cio: {START_MARKER}")
+        for j in range(start_page, len(pdf.pages)):
+            txt = norm_text(pdf.pages[j].extract_text() or "")
+            if end_n in txt:
+                end_page = j
+                break
+        if end_page is None:
+            raise ValueError(f"Encontrei o inicio, mas não encontrei o fim: {END_MARKER}")
+
+    candidates = []
+    with pdfplumber.open(pdf_path) as pdf:
+        for pno in range(start_page, end_page + 1):
+            page = pdf.pages[pno]
+            tables = page.extract_tables() or []
+
+            for ti, tbl in enumerate(tables, start=1):
+                if not tbl or len(tbl) < 2:
+                    continue
+                header = tbl[0]
+                body = tbl[1:]
+                df = pd.DataFrame(body, columns=header)
+                df = normalize_df(df)
+
+                r, c = df.shape
+                if r < 2 or c < 2:
+                    continue
+                text_n = norm_text(df_flattext(df))
+                score = 0
+                if c >= 3:
+                    score += 10
+                if r >= 4:
+                    score += 10
+                if pno == start_page:
+                    score += 15
+                for kw in ["planeamento", "execucao", "formacao", "respostas", "formadores"]:
+                    if kw in text_n:
+                        score += 2
+
+                empties = (df == "").sum().sum()
+                total = r * c
+                if total and empties / total > 0.6:
+                    score -= 10
+
+                candidates.append((score, pno, ti, df))
+
+    if not candidates:
+        raise ValueError("Encontrei o bloco, mas não encontrei tabelas nas páginas desse intervalo.")
+
+    candidates.sort(key=lambda x: x[0], reverse=True)
+    best_score, best_pno, best_ti, best_df = candidates[0]
+
+    print(f"Bloco: páginas {start_page+1} até {end_page+1}")
+    print(f"Tabela escolhida: p{best_pno+1}_t{best_ti} (score={best_score})")
+    print("Dimensões:", best_df.shape)
+
+    rows_config = {
+        1: [0, 2],
+        2: [0, 2],
+        3: [0, 2],
+        5: [0, 2],
+        7: [0, 2],
+        8: [0, 2],
+        9: [0, 2],
+        10: [0, 2],
+        12: [0, 3],
+        13: [0, 3],
+        14: [0, 3],
+        15: [0, 3],
+        16: [0, 3],
+        17: [0, 3],
+    }
+
+    new_rows = []
+    for row_idx, col_idxs in rows_config.items():
+        values = best_df.iloc[row_idx, col_idxs].tolist()
+        new_rows.append(values)
+
+    new_df = pd.DataFrame(new_rows)
+
+    data_dict = dict(zip(new_df[0], new_df[1]))
+    final_df = pd.DataFrame([data_dict])
+    final_df.index = [f"{year} - {course_name}"]
+    final_df = dot_to_comma(final_df)
+
+    row_name = f"{year} - {course_name}"
+    xlsx_path = "BDpowerbi.xlsx"
+    save_row_if_new(final_df, xlsx_path, row_name, sheet_name="Resultados")
+    return 0
+
+
+if __name__ == "__main__":
+    sys.exit(main())

Relatórios Internos/ReportCreator.spec

@@ -0,0 +1,38 @@
+# -*- mode: python ; coding: utf-8 -*-
+
+
+a = Analysis(
+    ['reportcreator.py'],
+    pathex=[],
+    binaries=[],
+    datas=[('Anexo RAI..docx', '.'), ('OllamaInstall.txt', '.')],
+    hiddenimports=[],
+    hookspath=[],
+    hooksconfig={},
+    runtime_hooks=[],
+    excludes=[],
+    noarchive=False,
+    optimize=0,
+)
+pyz = PYZ(a.pure)
+
+exe = EXE(
+    pyz,
+    a.scripts,
+    a.binaries,
+    a.datas,
+    [],
+    name='ReportCreator',
+    debug=False,
+    bootloader_ignore_signals=False,
+    strip=False,
+    upx=True,
+    upx_exclude=[],
+    runtime_tmpdir=None,
+    console=False,
+    disable_windowed_traceback=False,
+    argv_emulation=False,
+    target_arch=None,
+    codesign_identity=None,
+    entitlements_file=None,
+)

Relatórios Internos/build/ReportCreator/warn-ReportCreator.txt

@@ -0,0 +1,435 @@
+
+This file lists modules PyInstaller was not able to find. This does not
+necessarily mean these modules are required for running your program. Both
+Python's standard library and 3rd-party Python packages often conditionally
+import optional modules, some of which may be available only on certain
+platforms.
+
+Types of import:
+* top-level: imported at the top-level - look at these first
+* conditional: imported within an if-statement
+* delayed: imported within a function
+* optional: imported within a try-except-statement
+
+IMPORTANT: Do NOT post this list to the issue-tracker. Use it as a basis for
+            tracking down the missing module yourself. Thanks!
+
+missing module named pyimod02_importers - imported by C:\Users\17525206\AppData\Local\Programs\Python\Python312\Lib\site-packages\PyInstaller\hooks\rthooks\pyi_rth_pkgutil.py (delayed), C:\Users\17525206\AppData\Local\Programs\Python\Python312\Lib\site-packages\PyInstaller\hooks\rthooks\pyi_rth_pkgres.py (delayed)
+missing module named pwd - imported by posixpath (delayed, conditional, optional), shutil (delayed, optional), tarfile (optional), pathlib (delayed, optional), subprocess (delayed, conditional, optional), http.server (delayed, optional), psutil (optional), netrc (delayed, conditional), getpass (delayed), setuptools._distutils.util (delayed, conditional, optional), setuptools._vendor.backports.tarfile (optional), setuptools._distutils.archive_util (optional)
+missing module named grp - imported by shutil (delayed, optional), tarfile (optional), pathlib (delayed, optional), subprocess (delayed, conditional, optional), setuptools._vendor.backports.tarfile (optional), setuptools._distutils.archive_util (optional)
+missing module named _posixsubprocess - imported by subprocess (conditional), multiprocessing.util (delayed)
+missing module named fcntl - imported by subprocess (optional)
+missing module named urllib.urlopen - imported by urllib (delayed, optional), lxml.html (delayed, optional)
+missing module named urllib.urlencode - imported by urllib (delayed, optional), lxml.html (delayed, optional)
+missing module named posix - imported by os (conditional, optional), shutil (conditional), importlib._bootstrap_external (conditional), posixpath (optional)
+missing module named resource - imported by posix (top-level), IPython.utils.timing (optional)
+missing module named _manylinux - imported by packaging._manylinux (delayed, optional), setuptools._vendor.packaging._manylinux (delayed, optional)
+missing module named _posixshmem - imported by multiprocessing.resource_tracker (conditional), multiprocessing.shared_memory (conditional)
+missing module named multiprocessing.set_start_method - imported by multiprocessing (top-level), multiprocessing.spawn (top-level)
+missing module named multiprocessing.get_start_method - imported by multiprocessing (top-level), multiprocessing.spawn (top-level)
+missing module named _frozen_importlib_external - imported by importlib._bootstrap (delayed), importlib (optional), importlib.abc (optional), zipimport (top-level)
+missing module named multiprocessing.get_context - imported by multiprocessing (top-level), multiprocessing.pool (top-level), multiprocessing.managers (top-level), multiprocessing.sharedctypes (top-level)
+missing module named multiprocessing.TimeoutError - imported by multiprocessing (top-level), multiprocessing.pool (top-level)
+missing module named _scproxy - imported by urllib.request (conditional)
+missing module named termios - imported by tty (top-level), getpass (optional), IPython.core.page (delayed, optional), prompt_toolkit.input.vt100 (top-level)
+missing module named multiprocessing.BufferTooShort - imported by multiprocessing (top-level), multiprocessing.connection (top-level)
+missing module named multiprocessing.AuthenticationError - imported by multiprocessing (top-level), multiprocessing.connection (top-level)
+missing module named multiprocessing.Process - imported by multiprocessing (top-level), jupyter_client.ssh.tunnel (top-level)
+missing module named asyncio.DefaultEventLoopPolicy - imported by asyncio (delayed, conditional), asyncio.events (delayed, conditional)
+missing module named annotationlib - imported by typing_extensions (conditional), IPython.lib.pretty (conditional)
+missing module named '_typeshed.importlib' - imported by pkg_resources (conditional)
+missing module named _typeshed - imported by numpy.random.bit_generator (top-level), prompt_toolkit.eventloop.inputhook (conditional), setuptools._distutils.dist (conditional), setuptools.command.bdist_egg (conditional), setuptools.glob (conditional), setuptools._vendor.wheel.wheelfile (conditional), setuptools.compat.py311 (conditional), pkg_resources (conditional)
+missing module named jnius - imported by platformdirs.android (delayed, conditional, optional)
+missing module named android - imported by platformdirs.android (delayed, conditional, optional)
+missing module named usercustomize - imported by site (delayed, optional)
+missing module named sitecustomize - imported by site (delayed, optional)
+missing module named readline - imported by cmd (delayed, conditional, optional), code (delayed, conditional, optional), pdb (delayed, optional), pstats (conditional, optional), site (delayed, optional), rlcompleter (optional)
+missing module named trove_classifiers - imported by setuptools.config._validate_pyproject.formats (optional)
+missing module named setuptools._vendor.backports.zstd - imported by setuptools._vendor.backports (top-level), urllib3.util.request (conditional, optional), urllib3.response (conditional, optional)
+missing module named importlib_resources - imported by setuptools._vendor.jaraco.text (optional)
+excluded module named _frozen_importlib - imported by importlib (optional), importlib.abc (optional), zipimport (top-level)
+missing module named vms_lib - imported by platform (delayed, optional)
+missing module named 'java.lang' - imported by platform (delayed, optional)
+missing module named java - imported by platform (delayed)
+missing module named _winreg - imported by platform (delayed, optional), pygments.formatters.img (optional)
+missing module named collections.Mapping - imported by collections (optional), pytz.lazy (optional), parso.python.tree (optional)
+missing module named simplejson - imported by requests.compat (conditional, optional)
+missing module named dummy_threading - imported by requests.cookies (optional)
+missing module named compression - imported by urllib3.util.request (conditional, optional), urllib3.response (conditional, optional)
+missing module named 'h2.events' - imported by urllib3.http2.connection (top-level)
+missing module named 'h2.connection' - imported by urllib3.http2.connection (top-level)
+missing module named h2 - imported by urllib3.http2.connection (top-level)
+missing module named brotli - imported by urllib3.util.request (optional), urllib3.response (optional)
+missing module named brotlicffi - imported by urllib3.util.request (optional), urllib3.response (optional)
+missing module named socks - imported by urllib3.contrib.socks (optional)
+missing module named cryptography - imported by urllib3.contrib.pyopenssl (top-level), requests (conditional, optional)
+missing module named 'OpenSSL.crypto' - imported by urllib3.contrib.pyopenssl (delayed, conditional)
+missing module named 'cryptography.x509' - imported by urllib3.contrib.pyopenssl (delayed, optional)
+missing module named OpenSSL - imported by urllib3.contrib.pyopenssl (top-level)
+missing module named chardet - imported by pygments.lexer (delayed, conditional, optional), requests (optional)
+missing module named 'pyodide.ffi' - imported by urllib3.contrib.emscripten.fetch (delayed, optional)
+missing module named pyodide - imported by urllib3.contrib.emscripten.fetch (top-level)
+missing module named js - imported by urllib3.contrib.emscripten.fetch (top-level)
+missing module named htmlentitydefs - imported by lxml.html.soupparser (optional)
+missing module named BeautifulSoup - imported by lxml.html.soupparser (optional)
+missing module named bs4 - imported by pandas.io.html (delayed), lxml.html.soupparser (optional)
+missing module named urlparse - imported by lxml.ElementInclude (optional), lxml.html.html5parser (optional)
+missing module named urllib2 - imported by lxml.ElementInclude (optional), lxml.html.html5parser (optional)
+missing module named 'html5lib.treebuilders' - imported by lxml.html.html5parser (top-level)
+missing module named html5lib - imported by lxml.html._html5builder (top-level), lxml.html.html5parser (top-level)
+missing module named 'cython.cimports' - imported by lxml.html.diff (optional), zmq.backend.cython._zmq (top-level)
+missing module named cython - imported by lxml.html.diff (optional), lxml.html._difflib (optional), zmq.backend.cython._zmq (top-level)
+missing module named lxml_html_clean - imported by lxml.html.clean (optional)
+missing module named cssselect - imported by lxml.cssselect (optional)
+missing module named six.moves.range - imported by six.moves (top-level), dateutil.rrule (top-level)
+runtime module named six.moves - imported by dateutil.tz.tz (top-level), dateutil.tz._factories (top-level), dateutil.tz.win (top-level), dateutil.rrule (top-level)
+missing module named dateutil.tz.tzfile - imported by dateutil.tz (top-level), dateutil.zoneinfo (top-level)
+missing module named StringIO - imported by six (conditional)
+missing module named numexpr - imported by pandas.core.computation.expressions (conditional), pandas.core.computation.engines (delayed)
+missing module named numba - imported by pandas.core._numba.executor (delayed, conditional), pandas.core.util.numba_ (delayed, conditional), pandas.core.window.numba_ (delayed, conditional), pandas.core.window.online (delayed, conditional), pandas.core._numba.kernels.mean_ (top-level), pandas.core._numba.kernels.shared (top-level), pandas.core._numba.kernels.sum_ (top-level), pandas.core._numba.kernels.min_max_ (top-level), pandas.core._numba.kernels.var_ (top-level), pandas.core.groupby.numba_ (delayed, conditional), pandas.core._numba.extensions (top-level)
+missing module named 'numba.extending' - imported by pandas.core._numba.kernels.sum_ (top-level)
+missing module named 'pyarrow.compute' - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.reshape.merge (delayed, conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.arrays.arrow.accessors (conditional)
+missing module named 'numba.typed' - imported by pandas.core._numba.extensions (delayed)
+missing module named 'numba.core' - imported by pandas.core._numba.extensions (top-level)
+missing module named pyarrow - imported by pandas.core.arrays._arrow_string_mixins (conditional), pandas.core.arrays.masked (delayed), pandas.core.arrays.boolean (delayed, conditional), pandas.core.arrays.numeric (delayed, conditional), pandas.core.arrays.arrow._arrow_utils (top-level), pandas.core.interchange.utils (delayed, conditional), pandas.core.strings.accessor (delayed, conditional), pandas.io._util (conditional), pandas.io.parsers.base_parser (delayed, conditional), pandas.core.arrays.interval (delayed), pandas.core.arrays.arrow.extension_types (top-level), pandas.core.arrays.period (delayed), pandas.core.methods.describe (delayed, conditional), pandas.io.sql (delayed, conditional), pandas.core.arrays.string_arrow (conditional), pandas.core.reshape.merge (delayed, conditional), pandas.core.arrays.arrow.array (conditional), pandas.core.interchange.buffer (conditional), pandas.io.feather_format (delayed), pandas.core.indexes.base (delayed, conditional), pandas.core.dtypes.cast (delayed, conditional), pandas.core.arrays.string_ (delayed, conditional), pandas.core.arrays.arrow.accessors (conditional), pandas.core.dtypes.dtypes (delayed, conditional), pandas.compat.pyarrow (optional), pandas.core.reshape.encoding (delayed, conditional), pandas._testing (conditional)
+missing module named numpy._core.result_type - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.number - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.object_ - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.max - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.isnan - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.inf - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.errstate - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.array2string - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.all - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.signbit - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy (conditional)
+missing module named numpy._core.isscalar - imported by numpy._core (delayed), numpy.testing._private.utils (delayed), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named win32pdh - imported by numpy.testing._private.utils (delayed, conditional)
+missing module named numpy._core.ndarray - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy.lib._utils_impl (top-level), numpy (conditional)
+missing module named numpy._core.isnat - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional)
+missing module named numpy._core.intp - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.float32 - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.empty - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.array_repr - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional)
+missing module named numpy._core.array - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.testing._private.utils (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.arange - imported by numpy._core (top-level), numpy.testing._private.utils (top-level), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.void - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.vecmat - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ushort - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.unsignedinteger - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ulonglong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ulong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uintp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uintc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.uint64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint32 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint16 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.uint - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ubyte - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.trunc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.true_divide - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.timedelta64 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.tanh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.tan - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.subtract - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.str_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.square - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.spacing - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.sinh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.signedinteger - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.short - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.rint - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.right_shift - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.remainder - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.radians - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.rad2deg - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.power - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.positive - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.pi - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.not_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.nextafter - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.negative - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.modf - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.mod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.minimum - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.maximum - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.matvec - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.longlong - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.longdouble - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.long - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_xor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_or - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_not - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logical_and - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logaddexp2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.logaddexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log10 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log1p - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.log - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.less_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.less - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.left_shift - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ldexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.lcm - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.integer - imported by numpy._core (conditional), numpy (conditional), numpy.fft._helper (top-level)
+missing module named numpy._core.int64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int32 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int16 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.int8 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.hypot - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.heaviside - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.half - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.greater_equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.greater - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.gcd - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.frompyfunc - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.frexp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmin - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fmax - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floor_divide - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.floating - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.float_power - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.float16 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.fabs - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.expm1 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.exp2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.exp - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.euler_gamma - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.equal - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.e - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.divmod - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.degrees - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.deg2rad - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.datetime64 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.cosh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.cos - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.copysign - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.conjugate - imported by numpy._core (conditional), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.conj - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.complex64 - imported by numpy._core (conditional), numpy (conditional), numpy._array_api_info (top-level)
+missing module named numpy._core.clongdouble - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.character - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.ceil - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.cbrt - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bytes_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.byte - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bool_ - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_xor - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_or - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_count - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.bitwise_and - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arctanh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arctan2 - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arctan - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arcsinh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arcsin - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arccosh - imported by numpy._core (conditional), numpy (conditional)
+missing module named numpy._core.arccos - imported by numpy._core (conditional), numpy (conditional)
+missing module named _dummy_thread - imported by numpy._core.arrayprint (optional)
+missing module named threadpoolctl - imported by numpy.lib._utils_impl (delayed, optional)
+missing module named numpy._core.vstack - imported by numpy._core (top-level), numpy.lib._shape_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.atleast_3d - imported by numpy._core (top-level), numpy.lib._shape_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.ones - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.hstack - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.atleast_1d - imported by numpy._core (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.linspace - imported by numpy._core (top-level), numpy.lib._index_tricks_impl (top-level), numpy (conditional)
+missing module named numpy._core.iinfo - imported by numpy._core (top-level), numpy.lib._twodim_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.zeros - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.vecdot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.transpose - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._function_base_impl (top-level), numpy (conditional)
+missing module named numpy._core.trace - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.tensordot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.swapaxes - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.sum - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.sqrt - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.sort - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.single - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.sign - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.reciprocal - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.prod - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.outer - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.newaxis - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.multiply - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.moveaxis - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.matrix_transpose - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.matmul - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.isfinite - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.intc - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.inexact - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.finfo - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.empty_like - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.double - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.dot - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._polynomial_impl (top-level), numpy (conditional)
+missing module named numpy._core.divide - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.diagonal - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.csingle - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.cross - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.count_nonzero - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.complexfloating - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.cdouble - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.atleast_2d - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.asarray - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy.lib._array_utils_impl (top-level), numpy (conditional), numpy.fft._helper (top-level), numpy.fft._pocketfft (top-level)
+missing module named numpy._core.asanyarray - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.argsort - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.amin - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.amax - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named numpy._core.add - imported by numpy._core (top-level), numpy.linalg._linalg (top-level), numpy (conditional)
+missing module named 'scipy.stats' - imported by pandas.core.nanops (delayed, conditional)
+missing module named scipy - imported by pandas.core.dtypes.common (delayed, conditional, optional), pandas.core.missing (delayed)
+missing module named 'yapf.yapflib' - imported by IPython.terminal.interactiveshell (delayed)
+missing module named yapf - imported by IPython.terminal.interactiveshell (delayed)
+missing module named black - imported by IPython.terminal.interactiveshell (delayed)
+missing module named jupyter_ai - imported by IPython.terminal.shortcuts.auto_suggest (delayed, optional)
+missing module named jupyter_ai_magics - imported by IPython.terminal.shortcuts.auto_suggest (delayed, optional)
+missing module named prompt_toolkit.filters.vi_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.document (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.key_binding.bindings.page_navigation (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named prompt_toolkit.filters.control_is_searchable - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.search (top-level)
+missing module named prompt_toolkit.filters.vi_insert_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.layout.containers (top-level), prompt_toolkit.key_binding.bindings.basic (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named prompt_toolkit.filters.emacs_insert_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.layout.containers (top-level), prompt_toolkit.key_binding.bindings.basic (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named prompt_toolkit.filters.is_done - imported by prompt_toolkit.filters (top-level), prompt_toolkit.shortcuts.choice_input (top-level), prompt_toolkit.widgets.base (top-level), prompt_toolkit.shortcuts.progress_bar.base (top-level), prompt_toolkit.shortcuts.prompt (top-level), prompt_toolkit.layout.menus (top-level)
+missing module named prompt_toolkit.filters.has_completions - imported by prompt_toolkit.filters (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.widgets.dialogs (top-level), prompt_toolkit.layout.menus (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named prompt_toolkit.filters.is_searching - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.vi (top-level), prompt_toolkit.search (top-level), prompt_toolkit.key_binding.bindings.search (top-level)
+missing module named prompt_toolkit.filters.is_read_only - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.vi (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level)
+missing module named prompt_toolkit.filters.has_arg - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.vi (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level), prompt_toolkit.shortcuts.prompt (top-level)
+missing module named prompt_toolkit.filters.vi_search_direction_reversed - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level)
+missing module named prompt_toolkit.filters.shift_selection_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level)
+missing module named prompt_toolkit.filters.is_multiline - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.basic (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level)
+missing module named prompt_toolkit.filters.in_paste_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.basic (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level)
+missing module named prompt_toolkit.filters.has_selection - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.bindings.basic (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level), prompt_toolkit.key_binding.bindings.open_in_editor (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named prompt_toolkit.filters.emacs_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.key_binding.bindings.emacs (top-level), prompt_toolkit.key_binding.bindings.auto_suggest (top-level), prompt_toolkit.key_binding.bindings.open_in_editor (top-level), prompt_toolkit.key_binding.bindings.page_navigation (top-level)
+missing module named prompt_toolkit.filters.buffer_has_focus - imported by prompt_toolkit.filters (top-level), prompt_toolkit.key_binding.defaults (top-level), prompt_toolkit.key_binding.bindings.page_navigation (top-level)
+missing module named prompt_toolkit.filters.vi_navigation_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.key_binding.bindings.open_in_editor (top-level)
+missing module named prompt_toolkit.filters.has_validation_error - imported by prompt_toolkit.filters (top-level), prompt_toolkit.widgets.toolbars (top-level)
+missing module named pygments.lexers.PrologLexer - imported by pygments.lexers (top-level), pygments.lexers.cplint (top-level)
+missing module named PIL - imported by matplotlib_inline.config (delayed, optional), openpyxl.drawing.image (optional), pygments.formatters.img (optional)
+missing module named ctags - imported by pygments.formatters.html (optional)
+missing module named pygments.formatters.LatexFormatter - imported by pygments.formatters (delayed), IPython.lib.display (delayed)
+missing module named pygments.formatters.HtmlFormatter - imported by pygments.formatters (delayed), IPython.lib.display (delayed), IPython.core.oinspect (top-level), stack_data.core (delayed)
+missing module named pygments.lexers.PythonLexer - imported by pygments.lexers (top-level), IPython.core.oinspect (top-level)
+missing module named prompt_toolkit.filters.renderer_height_is_known - imported by prompt_toolkit.filters (top-level), prompt_toolkit.shortcuts.choice_input (top-level), prompt_toolkit.shortcuts.progress_bar.base (top-level), prompt_toolkit.shortcuts.prompt (top-level)
+missing module named prompt_toolkit.filters.has_focus - imported by prompt_toolkit.filters (top-level), prompt_toolkit.widgets.base (top-level), prompt_toolkit.widgets.toolbars (top-level), prompt_toolkit.widgets.dialogs (top-level), prompt_toolkit.shortcuts.prompt (top-level), IPython.terminal.shortcuts.filters (top-level)
+missing module named win32clipboard - imported by IPython.lib.clipboard (delayed, optional)
+missing module named numpydoc - imported by jedi.inference.docstrings (delayed)
+missing module named sqlite3.OperationalError - imported by sqlite3 (optional), IPython.core.history (optional)
+missing module named sqlite3.DatabaseError - imported by sqlite3 (optional), IPython.core.history (optional)
+missing module named 'IPython.config' - imported by IPython.core.history (conditional)
+missing module named sip - imported by IPython.external.qt_loaders (delayed, optional)
+missing module named 'nbformat.sign' - imported by IPython.core.magics.basic (delayed)
+missing module named nbformat - imported by IPython.core.magics.basic (delayed), IPython.core.interactiveshell (delayed, conditional)
+missing module named traitlets.config.Application - imported by traitlets.config (delayed, conditional), traitlets.log (delayed, conditional), ipykernel.kernelspec (top-level)
+missing module named argcomplete - imported by traitlets.config.loader (delayed, optional), traitlets.config.argcomplete_config (optional), IPython.core.tips (optional)
+missing module named win32evtlog - imported by logging.handlers (delayed, optional)
+missing module named win32evtlogutil - imported by logging.handlers (delayed, optional)
+missing module named prompt_toolkit.filters.vi_insert_multiple_mode - imported by prompt_toolkit.filters (top-level), prompt_toolkit.layout.processors (top-level)
+missing module named pexpect - imported by IPython.utils._process_posix (delayed, conditional), jupyter_client.ssh.tunnel (optional)
+missing module named System - imported by IPython.utils._process_cli (top-level)
+missing module named clr - imported by IPython.utils._process_cli (top-level)
+missing module named trio - imported by IPython.core.async_helpers (delayed), ipykernel.trio_runner (top-level)
+missing module named curio - imported by IPython.core.async_helpers (delayed)
+missing module named pytest - imported by executing._pytest_utils (delayed, optional), pandas._testing._io (delayed), pandas._testing (delayed)
+missing module named 'astroid.node_classes' - imported by asttokens.astroid_compat (optional)
+missing module named 'astroid.nodes' - imported by asttokens.astroid_compat (optional), asttokens.util (optional)
+missing module named astroid - imported by asttokens.astroid_compat (optional)
+missing module named _curses - imported by curses (top-level), curses.has_key (top-level)
+missing module named 'matplotlib.figure' - imported by matplotlib_inline.backend_inline (top-level), pandas.plotting._misc (conditional)
+missing module named 'matplotlib.backends' - imported by matplotlib_inline.backend_inline (top-level)
+missing module named 'matplotlib._pylab_helpers' - imported by matplotlib_inline.backend_inline (top-level)
+missing module named matplotlib - imported by matplotlib_inline.backend_inline (top-level), pandas.io.formats.style (optional)
+missing module named docrepr - imported by IPython.core.interactiveshell (optional)
+missing module named cPickle - imported by IPython.external.pickleshare (optional)
+missing module named netifaces - imported by jupyter_client.localinterfaces (delayed)
+missing module named msgpack - imported by jupyter_client.session (optional)
+missing module named orjson - imported by jupyter_client.session (optional)
+missing module named gevent - imported by zmq.green.core (top-level), zmq.green.poll (top-level)
+missing module named 'gevent.core' - imported by zmq.green.core (delayed, optional)
+missing module named 'gevent.hub' - imported by zmq.green.core (top-level)
+missing module named 'gevent.event' - imported by zmq.green.core (top-level)
+missing module named zmq.backend.zmq_version_info - imported by zmq.backend (top-level), zmq.sugar.version (top-level)
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+missing module named zmq.backend.Socket - imported by zmq.backend (top-level), zmq.sugar.socket (top-level)
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+missing module named pyczmq - imported by zmq.sugar.context (delayed)
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+missing module named zmq.ZMQError - imported by zmq (delayed, optional), zmq.sugar.attrsettr (delayed, optional)
+missing module named zmq.backend.zmq_errno - imported by zmq.backend (delayed), zmq.error (delayed, conditional)
+missing module named zmq.backend.strerror - imported by zmq.backend (delayed), zmq.error (delayed)
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+missing module named add_code_to_python_process - imported by debugpy.server.cli (delayed, optional)
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+missing module named sets - imported by pytz.tzinfo (optional)
+missing module named UserDict - imported by pytz.lazy (optional)
+missing module named 'scipy.sparse' - imported by pandas.core.arrays.sparse.array (conditional), pandas.core.arrays.sparse.scipy_sparse (delayed, conditional), pandas.core.arrays.sparse.accessor (delayed)
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+missing module named tables - imported by pandas.io.pytables (delayed, conditional)
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+missing module named yaml - imported by numpy.__config__ (delayed)
+missing module named numpy._distributor_init_local - imported by numpy (optional), numpy._distributor_init (optional)
+missing module named 'matplotlib.axes' - imported by pandas.plotting._core (conditional), pandas.plotting._misc (conditional), pandas._testing.asserters (delayed)
+missing module named 'matplotlib.artist' - imported by pandas._testing.asserters (delayed)
+missing module named 'matplotlib.table' - imported by pandas.plotting._misc (conditional)