Update app.py

app.py

@@ -1,219 +1,43 @@
-import io, os, re
-from typing import List, Dict
-import streamlit as st
-import pandas as pd
-
-# --- PDF text
-import pdfplumber
-from pypdf import PdfReader
-
-# --- OCR
-from pdf2image import convert_from_bytes
-import pytesseract
-from PIL import Image
-
-# ======================================================================
-# SCHEMA TABELLA
-# ======================================================================
-SCHEMA = [
-    "Piece","SKU","Title","Capacity","% Recycled","Weight","Color","Material / Resin","Class","Source File",
-    "Component","Function","General description of the packaging","Material Ref GCAS","Material Family"
-]
-
 # ======================================================================
-# LETTURA PDF E OCR
-# ======================================================================
-def extract_text_pages(pdf_bytes: bytes) -> List[str]:
-    try:
-        with pdfplumber.open(io.BytesIO(pdf_bytes)) as pdf:
-            return [p.extract_text() or "" for p in pdf.pages]
-    except Exception:
-        pass
-    try:
-        reader = PdfReader(io.BytesIO(pdf_bytes))
-        return [(p.extract_text() or "") for p in reader.pages]
-    except Exception:
-        return []
-
-def run_ocr(pdf_bytes: bytes, lang: str, dpi: int, tesseract_cmd: str | None) -> List[str]:
-    if tesseract_cmd:
-        pytesseract.pytesseract.tesseract_cmd = tesseract_cmd
-    imgs = convert_from_bytes(pdf_bytes, dpi=dpi)
-    config = "--psm 6 -c preserve_interword_spaces=1"
-    return [pytesseract.image_to_string(im, lang=lang, config=config) or "" for im in imgs]
-
-# ======================================================================
-# REGEX E PARSER
-# ======================================================================
-SKU_RE = re.compile(r"\b(?:Name|SKU|Part(?:\s*No\.?)?)\s*[:#]?\s*([A-Z0-9\-_/\.]{5,})", re.I)
-TITLE_RE = re.compile(r"\bTitle\s*[:\-]\s*(.+)", re.I)
-CLASS_RE = re.compile(r"\bClass\s*([A-Za-z ]+)", re.I)
-
-def _first(text, pat): 
-    m = pat.search(text or ""); return m.group(1).strip() if m else ""
-
-def capacity_from(t): 
-    m=re.search(r"([0-9]+(?:[.,][0-9]+)?)\s*(L|Liter|ml|mL)\b",t or "",re.I)
-    if not m: return ""
-    return f"{m.group(1).replace(',','.')} {m.group(2).upper().replace('LITER','L').replace('ML','ml')}"
-
-def color_from(t):
-    m=re.search(r"(?:Part\s*Color|Color)\s*[:\-]?\s*([A-Z ]{3,})",t,re.I)
-    if m: return m.group(1).strip()
-    m=re.search(r"\b([A-Z ]{4,}(?:GREEN|WHITE|BLACK|BLUE|RED|CLEAR)[A-Z ]*)\b",t)
-    return m.group(1).strip() if m else ""
-
-def material_from(t):
-    for l in (t or "").splitlines():
-        if re.search(r"\bRESIN\b",l,re.I): return l.strip()
-    m=re.search(r"(SERIOPLAST.*?RESIN)",t,re.I)
-    return m.group(1).strip() if m else ""
-
-# ======================================================================
-# WEIGHT PARSER → restituisce solo "94±3g"
-# ======================================================================
-WEIGHT_VALUE_RE = re.compile(r"\bweight\b[^\n\r]{0,80}?([0-9]+(?:[.,][0-9]+)?\s*(?:±|\+/?-|\+-)?\s*[0-9]*\s*(?:mg|g|kg))\b", re.I)
+# WEIGHT PARSER → restituisce SOLO il valore, es. "94±3g" (no "Weight")
+# ======================================================================
+WEIGHT_VALUE_RE = re.compile(
+    r"""(?ix)                       # i=ignorecase, x=verbose
+    \bweight\b
+    [^\n\r]{0,80}?                  # pochi caratteri sulla stessa riga
+    (                               # ======= GRUPPO CATTURATO =======
+        (?:\d+(?:[.,]\d+)?\s*       # valore principale es. 94 o 94,5
+           (?:±|\+/?-|\+-)\s*       # simbolo tolleranza: ±  o +/- o +-
+           \d+(?:[.,]\d+)?\s*       # tolleranza es. 3 o 3,0
+           (?:mg|g|kg)              # unità
+        )
+        |
+        (?:\d+(?:[.,]\d+)?\s*(?:mg|g|kg))  # fallback: solo "94 g"
+    )                               # =================================
+    """,
+)
+
+def _normalize_weight(s: str) -> str:
+    # compatta spazi, normalizza simbolo e virgole → "94±3g"
+    s = (s or "").strip()
+    s = s.replace(" ", "")
+    s = s.replace("+/-", "±").replace("+-", "±")
+    s = s.replace(",", ".")
+    return s
 
 def weight_from(t: str) -> str:
-    if not t: return ""
+    if not t:
+        return ""
     m = WEIGHT_VALUE_RE.search(t)
-    if m: return re.sub(r"\s+", "", m.group(1)).replace(",", ".")
-    for line in t.splitlines():
+    if m:
+        return _normalize_weight(m.group(1))
+    # Fallback riga-per-riga (OCR con spezzature strane)
+    for line in (t or "").splitlines():
         if "weight" in line.lower():
-            m2 = re.search(r"([0-9]+(?:[.,][0-9]+)?\s*(?:±|\+/?-|\+-)?\s*[0-9]*\s*(?:mg|g|kg))", line, re.I)
-            if m2: return re.sub(r"\s+", "", m2.group(1)).replace(",", ".")
-    return ""
-
-# ======================================================================
-# ALTRE FUNZIONI (uguali a prima)
-# ======================================================================
-_ALLOWED_PIECES={"ribbon":"ribbon","bottle":"bottle","film bundle":"film bundle","container":"container",
-"label - adhesive":"LABEL - ADHESIVE","label adhesive":"LABEL - ADHESIVE","label-adhesive":"LABEL - ADHESIVE",
-"label - back":"LABEL - BACK","back label":"LABEL - BACK","label back":"LABEL - BACK","closure":"CLOSURE"}
-_PACK_COMP_TYPE_RE=re.compile(r"Packaging\s+Component\s+Type\s*[:\-]?\s*([^\n\r]+)",re.I)
-
-def _normalize_piece(s):
-    s2=re.sub(r"\s+"," ",(s or "").strip().lower())
-    for k,v in _ALLOWED_PIECES.items():
-        if k in s2: return v
+            m2 = re.search(
+                r"(?ix)\bweight\b[^\n\r]*?((?:\d+(?:[.,]\d+)?\s*(?:±|\+/?-|\+-)\s*\d+(?:[.,]\d+)?\s*(?:mg|g|kg))|(?:\d+(?:[.,]\d+)?\s*(?:mg|g|kg)))",
+                line,
+            )
+            if m2:
+                return _normalize_weight(m2.group(1))
     return ""
-
-def piece_from(t,cls):
-    m=_PACK_COMP_TYPE_RE.search(t or "")
-    if m: val=_normalize_piece(m.group(1)); 
-    if m and val: return val
-    if cls:
-        if "bottle" in cls.lower(): return "bottle"
-        if "cap" in cls.lower(): return "CLOSURE"
-        if "corrugated" in cls.lower(): return "container"
-        if "label" in cls.lower(): return "LABEL - BACK"
-    return ""
-
-FUNCTION_RE=re.compile(r"\b(Primary|Secondary(?:\s*or\s*Tertiary)?|Tertiary)\b",re.I)
-
-def component_from(t,piece,cls):
-    txt=t.lower()
-    if "label" in txt: return "Labels"
-    if piece: return piece
-    if cls and "bottle" in cls.lower(): return "Bottle"
-    return ""
-
-def function_from(t):
-    m=FUNCTION_RE.search(t or ""); return m.group(1).title() if m else ""
-
-def material_ref_gcas_from(t):
-    m=re.findall(r"\b(\d{7,9})\b",t or ""); return ", ".join(sorted(set(m))) if m else ""
-
-def material_family_from(t):
-    fams=["Monolayer HDPE","Polypropylene (PP)","Paper","Rigid Paper – Corrugated Case"]
-    for f in fams:
-        if f.lower() in (t or "").lower(): return f
-    if re.search(r"\bHDPE\b",t): return "Monolayer HDPE"
-    if re.search(r"\bPP\b",t,re.I): return "Polypropylene (PP)"
-    return ""
-
-# ======================================================================
-# PARSER PRINCIPALE
-# ======================================================================
-def parse_record(pages: List[str], source_name: str) -> Dict[str,str]:
-    full="\n".join(pages or [""])
-    sku=_first(full,SKU_RE)
-    title=_first(full,TITLE_RE)
-    cls=_first(full,CLASS_RE)
-    cap=capacity_from(title) or capacity_from(full)
-    color=color_from(full)
-    material=material_from(full)
-    piece=piece_from(full,cls)
-    comp=component_from(full,piece,cls)
-    func=function_from(full)
-    gcas=material_ref_gcas_from(full)
-    mfam=material_family_from(full)
-    wght=weight_from(full)
-    return {
-        "Piece":piece or "","SKU":sku or "","Title":title or "","Capacity":cap or "",
-        "% Recycled":"–","Weight":wght or "–","Color":color or "","Material / Resin":material or "",
-        "Class":cls or "","Source File":source_name,"Component":comp or "","Function":func or "",
-        "General description of the packaging":"","Material Ref GCAS":gcas or "","Material Family":mfam or ""
-    }
-
-# ======================================================================
-# STREAMLIT UI
-# ======================================================================
-st.set_page_config(page_title="PDF → Table (OCR-ready)", layout="wide")
-st.title("📄→📊 PDF → Table (OCR-ready)")
-st.caption("Estrae automaticamente i campi, incluso il peso dalle immagini OCR.")
-
-with st.sidebar:
-    files=st.file_uploader("Seleziona PDF",type=["pdf"],accept_multiple_files=True)
-    st.markdown("---")
-    st.subheader("OCR")
-    ocr_fallback=st.checkbox("Usa OCR se non c'è testo",value=True)
-    ocr_lang=st.text_input("Lingue OCR (comma)",value="eng,ita")
-    ocr_dpi=st.number_input("DPI OCR",200,600,300,50)
-    tess_path=st.text_input("Percorso Tesseract (se non nel PATH)",value="")
-    run_btn=st.button("▶️ Estrai")
-
-if not run_btn:
-    st.info("Carica i PDF e premi **Estrai**.")
-    st.stop()
-if not files:
-    st.warning("Nessun PDF caricato.")
-    st.stop()
-
-lang="+".join([p.strip() for p in ocr_lang.split(",") if p.strip()]) or "eng"
-tess_cmd=tess_path.strip() or None
-rows,errors=[],[]
-
-for up in files:
-    try:
-        raw=up.read()
-        pages=extract_text_pages(raw)
-        if ocr_fallback and not any((p or "").strip() for p in pages):
-            pages=run_ocr(raw,lang=lang,dpi=int(ocr_dpi),tesseract_cmd=tess_cmd)
-        rec=parse_record(pages,up.name)
-        # se Weight vuoto, prova OCR
-        if (not rec.get("Weight") or rec["Weight"]=="–") and ocr_fallback:
-            ocr_pages=run_ocr(raw,lang=lang,dpi=int(ocr_dpi),tesseract_cmd=tess_cmd)
-            w_ocr=weight_from("\n".join(ocr_pages))
-            if w_ocr: rec["Weight"]=w_ocr
-        rows.append(rec)
-    except Exception as e:
-        errors.append((up.name,str(e)))
-
-if errors:
-    with st.expander("Errori"):
-        for n,e in errors: st.error(f"{n}: {e}")
-
-df=pd.DataFrame(rows,columns=SCHEMA)
-st.success(f"Creat{ 'e' if len(df)!=1 else 'a' } {len(df)} riga/e.")
-st.dataframe(df,use_container_width=True)
-
-c1,c2=st.columns(2)
-with c1:
-    st.download_button("⬇️ CSV",df.to_csv(index=False).encode("utf-8"),"table.csv","text/csv")
-with c2:
-    bio=io.BytesIO()
-    with pd.ExcelWriter(bio,engine="openpyxl") as xw:
-        df.to_excel(xw,index=False,sheet_name="data")
-    st.download_button("⬇️ Excel",bio.getvalue(),"table.xlsx","application/vnd.openxmlformats-officedocument.spreadsheetml.sheet")
-