diff --git a/API DADOS DA PATENTE.py b/API DADOS DA PATENTE.py
new file mode 100644
index 0000000..5849f8c
--- /dev/null
+++ b/API DADOS DA PATENTE.py	
@@ -0,0 +1,584 @@
+import requests
+import xmltodict
+import csv
+import re
+import time
+import datetime
+from requests.auth import HTTPBasicAuth
+from typing import Optional, Dict, Any, List
+
+# ==============================================================================
+# ⚠️ CONFIGURAÇÃO OBRIGATÓRIA
+# ------------------------------------------------------------------------------
+# SUBSTITUA PELAS SUAS CHAVES DE CONSUMO OBTIDAS NO PORTAL DO DESENVOLVEDOR DO EPO
+CONSUMER_KEY = "3APxH4wxYoY7aZibQ4jDP9YGjezGbWzfcGji9xA6j3qY0ea1"
+CONSUMER_SECRET = "OCeAZAVzxdlLZ80IJ4sootDyI8iKpleu3pD3qEGh1R1BYALewAfyRuhASN1XnJBk"
+
+# Caminhos dos arquivos
+INPUT_FILE = r"C:\Users\Licitações\PycharmProjects\WEBSCRAPPING\PATENTES ADAPTADAS.txt"
+OUTPUT_FILE = "patentes_dados_simples_inventor.csv"
+
+# Variáveis globais
+ACCESS_TOKEN = None
+MAX_RETRIES = 5  # Número máximo de tentativas em caso de falha de conexão ou 429
+
+# CONSTANTES PARA CÁLCULO DE MÉTRICAS DO INVENTOR
+PORTFOLIO_SAMPLE_SIZE = 25  # Limite de patentes do portfólio para amostrar e calcular médias
+RECENCY_YEARS_PERIOD = 5  # Duração de cada período (A e B) para o cálculo da Taxa de Crescimento (5 anos)
+
+
+# ==============================================================================
+
+
+# --- 1. FUNÇÃO DE AUTENTICAÇÃO ---
+def get_access_token():
+    """Obtém o Access Token via OAuth 2.0 usando as chaves de consumidor."""
+    global ACCESS_TOKEN
+    token_url = "https://ops.epo.org/3.2/auth/accesstoken"
+    try:
+        response = requests.post(
+            token_url,
+            data={'grant_type': 'client_credentials'},
+            auth=HTTPBasicAuth(CONSUMER_KEY, CONSUMER_SECRET),
+            headers={'Content-Type': 'application/x-www-form-urlencoded'}
+        )
+        response.raise_for_status()
+        token_data = response.json()
+        ACCESS_TOKEN = token_data.get('access_token')
+        print("✅ Access Token obtido com sucesso.")
+        return ACCESS_TOKEN
+
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Erro ao obter o token: {e}")
+        return None
+
+
+# --- FUNÇÃO AUXILIAR PARA TRATAMENTO DE RETRY E 429 ---
+def make_ops_request(url: str, headers: Dict[str, str], identifier: str, max_retries: int = MAX_RETRIES) -> Optional[
+    requests.Response]:
+    """
+    Realiza a requisição, tratando o limite de taxa (429) e erros de conexão.
+    """
+    for attempt in range(max_retries):
+        try:
+            response = requests.get(url, headers=headers)
+
+            if response.status_code == 429:
+                retry_after = response.headers.get('Retry-After')
+                try:
+                    wait_time = int(retry_after)
+                except (TypeError, ValueError):
+                    wait_time = 60
+
+                print(
+                    f"   [ALERTA 429 - {identifier}]: Limite de requisições atingido. Tentativa {attempt + 1}/{max_retries}. Esperando por {wait_time} segundos...")
+                time.sleep(wait_time)
+
+                if attempt == max_retries - 1:
+                    print(f"   [FALHA 429]: Tentativas esgotadas para {identifier}.")
+                    return None
+                continue
+
+            response.raise_for_status()
+            return response
+
+        except requests.exceptions.HTTPError as e:
+            if response.status_code == 404:
+                return response
+            return None
+
+        except requests.exceptions.RequestException:
+            if attempt < max_retries - 1:
+                print(
+                    f"   [ERRO CONEXÃO]: Falha de conexão para {identifier}. Tentando novamente... ({attempt + 1}/{max_retries})")
+                time.sleep(5)
+                continue
+            return None
+
+    return None
+
+
+# --- FUNÇÃO AUXILIAR DE EXTRAÇÃO DO NÚMERO ---
+def extract_pub_number(link):
+    """Extrai o número de publicação no formato EPODOC."""
+    wipo_docid_match = re.search(r'docId=([A-Z]{2}\d+[A-Z]?\d*)', link)
+    if wipo_docid_match:
+        return wipo_docid_match.group(1)
+
+    epo_pattern = re.search(r'([A-Z]{2}\d+[A-Z]?\d*)', link)
+    if epo_pattern:
+        return epo_pattern.group(1).replace('patent/', '')
+    google_match = re.search(r'patent/([A-Z]{2}\d+)', link)
+    if google_match:
+        return google_match.group(1)
+    return None
+
+
+# --- 2. EXTRAÇÃO DE CITAÇÕES E DATA PARA UM ID ESPECÍFICO ---
+def get_citation_and_date(pub_number: str, headers: Dict[str, str]) -> Dict[str, Any]:
+    """Obtém contagens de citações (forward/backward) e data de publicação."""
+    base_url = "https://ops.epo.org/rest-services"
+    citations_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/citations"
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/biblio"
+
+    forward_cites, backward_cites, pub_date = 0, 0, None
+
+    # 1. Citações
+    cites_response = make_ops_request(citations_url, headers, f"Citação {pub_number}")
+    if cites_response and cites_response.status_code == 200:
+        try:
+            cites_data = xmltodict.parse(cites_response.text)
+
+            # Citações Forward (Referenced by)
+            forward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:forward-citations', {}).get('citation', [])
+            if isinstance(forward_list, dict): forward_list = [forward_list]
+            forward_cites = len(forward_list)
+
+            # Citações Backward (References)
+            backward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:backward-citations', {}).get('citation', [])
+            if isinstance(backward_list, dict): backward_list = [backward_list]
+            backward_cites = len(backward_list)
+        except Exception:
+            pass
+
+            # 2. Data de Publicação (necessária para Recência)
+    biblio_response = make_ops_request(biblio_url, headers, f"Biblio Date {pub_number}")
+    if biblio_response and biblio_response.status_code == 200:
+        try:
+            biblio_data = xmltodict.parse(biblio_response.text)
+            date_raw = \
+            biblio_data.get('ops:world-patent-data', {}).get('exchange-documents', {}).get('exchange-document', {}).get(
+                'bibliographic-data', {}).get('publication-reference', {}).get('document-id', [{}])[0].get('date')
+            if date_raw:
+                pub_date = date_raw
+        except Exception:
+            pass
+
+    return {
+        'forward_cites': forward_cites,
+        'backward_cites': backward_cites,
+        'pub_date': pub_date
+    }
+
+
+# --- 3. FUNÇÃO PARA EXTRAIR MÉTRICAS DO PORTFÓLIO DO INVENTOR ---
+def get_inventor_portfolio_metrics(inventor_name: str) -> Dict[str, Any]:
+    """
+    Calcula Recência (Taxa de Crescimento Refinada), Qualidade e Cobertura do Inventor.
+    """
+    if not inventor_name or not ACCESS_TOKEN:
+        return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Consulta de busca (in= para Inventor) - usa o nome já limpo (SOBRENOME, NOME)
+    search_url = f"{base_url}/rest-services/published-data/search/biblio?query=in%3D%22{requests.utils.quote(inventor_name)}%22&range=1-{PORTFOLIO_SAMPLE_SIZE}"
+
+    print(
+        f"   [BUSCA PORTFÓLIO]: Buscando amostra de {PORTFOLIO_SAMPLE_SIZE} patentes para o Inventor '{inventor_name}'...")
+
+    search_response = make_ops_request(search_url, headers, f"Busca {inventor_name}")
+
+    total_patents_found = 0
+    patent_ids = []
+
+    if search_response and search_response.status_code == 200:
+        try:
+            search_data = xmltodict.parse(search_response.text)
+
+            total_patents_found = int(
+                search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get('@total-result-count', 0))
+
+            biblio_search = search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {})
+            hits = biblio_search.get('ops:search-result', {}).get('ops:publication-reference', [])
+
+            if isinstance(hits, dict):
+                hits = [hits]
+
+            for hit in hits:
+                doc_id_list = hit.get('document-id', [])
+                if isinstance(doc_id_list, dict): doc_id_list = [doc_id_list]
+
+                for doc_id in doc_id_list:
+                    if doc_id.get('doc-number'):
+                        patent_ids.append(doc_id.get('doc-number'))
+                        break
+
+        except Exception as e:
+            print(f"   [ERRO PARSING BUSCA]: Falha ao processar a busca para {inventor_name}: {e}")
+            return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+    if not patent_ids:
+        print(f"   [ALERTA PORTFÓLIO]: Nenhuma patente encontrada na amostra para o Inventor '{inventor_name}'.")
+        return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': total_patents_found}
+
+    # ----------------------------------------------------------------------
+    # ITERAÇÃO SOBRE A AMOSTRA E AGREGAÇÃO DE DADOS
+    # ----------------------------------------------------------------------
+
+    total_forward_cites = 0
+    total_backward_cites = 0
+    total_family_size = 0
+    publication_years = {}  # {year: count}
+
+    current_year = datetime.datetime.now().year
+
+    print(f"   [CALC. MÉTRICAS]: Processando amostra de {len(patent_ids)} patentes do Inventor...")
+
+    for pub_id in patent_ids:
+
+        # Coleta de Citações e Data
+        metrics = get_citation_and_date(pub_id, headers)
+
+        total_forward_cites += metrics['forward_cites']
+        total_backward_cites += metrics['backward_cites']
+
+        if metrics['pub_date']:
+            try:
+                year = int(metrics['pub_date'][:4])
+                publication_years[year] = publication_years.get(year, 0) + 1
+            except (ValueError, TypeError):
+                pass
+
+        # Coleta de Tamanho da Família
+        family_url = f"{base_url}/family/publication/epodoc/{pub_id}"
+        family_response = make_ops_request(family_url, headers, f"Família {pub_id}")
+
+        family_count = 0
+        if family_response and family_response.status_code == 200:
+            try:
+                family_data = xmltodict.parse(family_response.text)
+                family_members_raw = family_data.get('ops:world-patent-data', {}).get('ops:patent-family', {}).get(
+                    'ops:family-member', [])
+
+                if isinstance(family_members_raw, dict): family_members_raw = [family_members_raw]
+
+                family_count = len(family_members_raw)
+                total_family_size += family_count
+            except Exception:
+                pass
+
+        time.sleep(1)  # Pausa curta
+
+    # ----------------------------------------------------------------------
+    # CÁLCULO DAS MÉTRICAS FINAIS
+    # ----------------------------------------------------------------------
+
+    sample_count = len(patent_ids)
+
+    # 1. Qualidade do Inventor (Média de Citações)
+    total_cites = total_forward_cites + total_backward_cites
+    quality = round(total_cites / sample_count, 2) if sample_count > 0 else 0
+
+    # 2. Cobertura do Inventor (Média de Membros da Família)
+    coverage = round(total_family_size / sample_count, 2) if sample_count > 0 else 0
+
+    # 3. Recência do Inventor (Taxa de Crescimento em 5 anos) - Lógica Refinada
+
+    # Define os anos dos períodos
+    year_end_A = current_year
+    year_start_A = year_end_A - RECENCY_YEARS_PERIOD + 1
+    year_start_B = year_start_A - RECENCY_YEARS_PERIOD
+
+    # Soma as patentes em cada período
+    patents_A = sum(
+        count for year, count in publication_years.items()
+        if year >= year_start_A and year <= year_end_A
+    )
+    patents_B = sum(
+        count for year, count in publication_years.items()
+        if year >= year_start_B and year < year_start_A
+    )
+
+    recency_growth_rate = 0.0
+    if patents_B > 0:
+        # Crescimento percentual normal
+        recency_growth_rate = round((patents_A - patents_B) / patents_B, 4)
+    elif patents_A > 0:
+        # TRATAMENTO REFINADO para INÍCIO DE ATIVIDADE (P_B = 0, P_A > 0)
+
+        # Encontra o ano mais antigo de publicação no Período A
+        recent_years_with_patents = [year for year in publication_years.keys()
+                                     if year >= year_start_A and year <= year_end_A]
+
+        min_recent_year = min(recent_years_with_patents) if recent_years_with_patents else year_end_A
+
+        # Calcula o número de anos ativos (inclui o ano atual)
+        years_active = current_year - min_recent_year + 1
+
+        # Métrica: Volume Médio Anual no período A (resolve a "explosão")
+        recency_growth_rate = round(patents_A / years_active, 4)
+
+    # Se P_A=0 e P_B=0, a taxa é 0.
+
+    print(
+        f"   [MÉTRICAS INVENTOR]: Qualidade Média: {quality}, Cobertura Média: {coverage}, Recência (Taxa Cresc.): {recency_growth_rate}")
+
+    return {
+        'recency_growth_rate': recency_growth_rate,
+        'quality': quality,
+        'coverage': coverage,
+        'portfolio_size': total_patents_found
+    }
+
+
+# --- 4. FUNÇÃO DE EXTRAÇÃO DE DADOS BÁSICOS E INVENTOR ---
+def get_patent_data(publication_number: str) -> Optional[Dict[str, Any]]:
+    """Consulta OPS para obter Classes, Família, e o nome do PRIMEIRO Inventor."""
+    global ACCESS_TOKEN
+    if not ACCESS_TOKEN: return None
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Inicializa variáveis
+    ipc_list, cpc_list = [], []
+    family_count = 'N/A'
+    biblio_success = False
+    family_members_list = []
+    ipc_diversity = 0
+    cpc_diversity = 0
+    inventor_name = None
+
+    # ----------------------------------------------------------------------
+    # A) REQUISIÇÃO PARA DADOS BIBLIOGRÁFICOS (IPC/CPC/Inventor)
+    # ----------------------------------------------------------------------
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{publication_number}/biblio"
+    biblio_response = make_ops_request(biblio_url, headers, publication_number)
+
+    if biblio_response and biblio_response.status_code == 200:
+        try:
+            biblio_data = xmltodict.parse(biblio_response.text)
+            biblio_success = True
+
+            # Funções auxiliares
+            def safe_extract_text(data):
+                if isinstance(data, list):
+                    result = []
+                    for item in data:
+                        if isinstance(item, dict) and 'text' in item:
+                            result.append(item['text'].strip())
+                    return result
+                elif isinstance(data, dict) and 'text' in data:
+                    return [data['text'].strip()]
+                return []
+
+            def build_cpc_code(cpc_item):
+                if not isinstance(cpc_item, dict) or cpc_item.get('classification-scheme', {}).get('@scheme') not in [
+                    'CPCI', 'CPC']: return None
+                section = cpc_item.get('section', '')
+                class_ = cpc_item.get('class', '')
+                subclass = cpc_item.get('subclass', '')
+                main_group = cpc_item.get('main-group', '')
+                subgroup = cpc_item.get('subgroup', '')
+                if section and class_ and subclass and main_group and subgroup:
+                    return f"{section}{class_}{subclass} {main_group}/{subgroup}"
+                return None
+
+            exchange_docs_container = biblio_data.get('ops:world-patent-data', {}).get('exchange-documents')
+            if exchange_docs_container:
+                exchange_docs = exchange_docs_container.get('exchange-document')
+
+                if isinstance(exchange_docs, list):
+                    exchange_doc = exchange_docs[0]
+                else:
+                    exchange_doc = exchange_docs
+
+                if exchange_doc:
+                    bib_data = exchange_doc.get('bibliographic-data', {})
+
+                    # Extração e Limpeza do PRIMEIRO Inventor
+                    inventors = bib_data.get('parties', {}).get('inventors', {}).get('inventor', [])
+                    if isinstance(inventors, dict): inventors = [inventors]
+
+                    if inventors:
+                        first_inventor = inventors[0]
+                        addressbook = first_inventor.get('addressbook', {})
+                        last_name = addressbook.get('last-name')
+                        first_name = addressbook.get('first-name')
+
+
+                        if last_name and first_name:
+                            # Formato preferido para busca EPO: "SOBRENOME, NOME"
+                            inventor_name = f"{first_name}, {last_name}"
+                        else:
+                            # Fallback para o nome não estruturado e limpeza do código do país
+                            name_container = first_inventor.get('inventor-name', {}).get('name')
+                            if name_container:
+                                # Remove código de país tipo [US] e espaços extras
+                                inventor_name = re.sub(r'\s*\[[A-Z]{2,3}\]\s*', '', name_container).strip()
+                                partes = inventor_name.split()
+                                partes.append(partes.pop(0))
+                                inventor_name = ' '.join(partes)
+                                print(inventor_name)
+                                print("até aqui funciona")
+
+
+                    # Extração de IPC e CPC (mantido)
+                    ipc_parent = bib_data.get('classifications-ipcr', {})
+                    ipc_data = ipc_parent.get('classification-ipcr', [])
+                    ipc_list = safe_extract_text(ipc_data)
+
+                    patent_classes = bib_data.get('patent-classifications', {})
+                    cpc_items = patent_classes.get('patent-classification', [])
+                    if isinstance(cpc_items, dict): cpc_items = [cpc_items]
+                    for item in cpc_items:
+                        cpc_code = build_cpc_code(item)
+                        if cpc_code: cpc_list.append(cpc_code)
+
+                    ipc_list = list(set(ipc_list))
+                    cpc_list = list(set(cpc_list))
+
+                    ipc_diversity = len(set(ipc[:4] for ipc in ipc_list if len(ipc) >= 4))
+                    cpc_diversity = len(set(re.match(r'([A-Z]\d{2}[A-Z])', cpc).group(1) for cpc in cpc_list if
+                                            re.match(r'([A-Z]\d{2}[A-Z])', cpc)))
+
+
+        except Exception as e:
+            print(f"   [ERRO PROCESSAMENTO XML BIBLIO]: Falha ao processar XML de {publication_number}: {e}")
+            biblio_success = False
+
+    # ----------------------------------------------------------------------
+    # B) REQUISIÇÃO PARA DADOS DA FAMÍLIA (Lógica anterior)
+    # ----------------------------------------------------------------------
+    family_url = f"{base_url}/family/publication/epodoc/{publication_number}"
+    family_response = make_ops_request(family_url, headers, publication_number)
+
+    if family_response and family_response.status_code == 200:
+        try:
+            family_data = xmltodict.parse(family_response.text)
+            family_container = family_data.get('ops:world-patent-data', {}).get('ops:patent-family')
+
+            # Lógica de extração de Family Count e Members (mantida)
+            if family_container:
+                family_members_raw = family_container.get('ops:family-member')
+                if isinstance(family_members_raw, dict):
+                    members_to_process = [family_members_raw]
+                elif isinstance(family_members_raw, list):
+                    members_to_process = family_members_raw
+                else:
+                    members_to_process = []
+                family_count = len(members_to_process)
+                for member in members_to_process:
+                    try:
+                        pub_ref = member.get('ops:publication-reference', {})
+                        doc_ids = pub_ref.get('document-id')
+                        if isinstance(doc_ids, dict): doc_ids = [doc_ids]
+                        for doc_id in doc_ids:
+                            doc_num = doc_id.get('doc-number')
+                            if doc_num:
+                                family_members_list.append(doc_num)
+                                break
+                    except Exception:
+                        continue
+            else:
+                family_count = 0
+        except Exception:
+            family_count = 'ERRO'
+    else:
+        family_count = 'FALHA REQ'
+
+    if not biblio_success and family_count in ('ERRO', 'FALHA REQ', 0, 'N/A'):
+        return None
+
+    return {
+        'inventor_name': inventor_name,
+        'family_count': family_count,
+        'family_members': family_members_list,
+        'num_ipc': len(ipc_list),
+        'num_cpc': len(cpc_list),
+        'ipc_diversity': ipc_diversity,
+        'cpc_diversity': cpc_diversity,
+        'IPC': ipc_list,
+        'CPC': cpc_list
+    }
+
+
+# --- FLUXO PRINCIPAL DO SCRIPT ---
+if __name__ == "__main__":
+
+    if not get_access_token():
+        print("\nO script não pode continuar sem um Access Token válido.")
+    else:
+        try:
+            with open(INPUT_FILE, 'r', encoding='utf-8') as f:
+                links = [line.strip() for line in f.readlines() if line.strip()]
+
+        except FileNotFoundError:
+            print(f"\n❌ ERRO: Arquivo de entrada não encontrado: {INPUT_FILE}")
+            exit()
+
+        with open(OUTPUT_FILE, 'w', newline='', encoding='utf-8') as csvfile:
+
+            # --- COLUNAS ATUALIZADAS PARA INVENTOR E NOVA MÉTRICA DE RECÊNCIA ---
+            fieldnames = ['link', 'publication_number', 'inventor_name', 'inventor_portfolio_size',
+                          'inventor_recency_growth_rate', 'inventor_quality_avg_cites', 'inventor_coverage_avg_family',
+                          'family_count', 'family_members', 'num_ipc', 'num_cpc', 'ipc_diversity', 'cpc_diversity',
+                          'IPC', 'CPC']
+            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+            writer.writeheader()
+
+            for i, link in enumerate(links, 1):
+                pub_number = extract_pub_number(link)
+                total_links = len(links)
+
+                if not pub_number:
+                    print(f"[{i}/{total_links}] ⚠️ Não extraído do link/número: {link}")
+                    fail_data = {f: 'N/A' for f in fieldnames}
+                    fail_data.update({'link': link, 'publication_number': 'N/A'})
+                    writer.writerow(fail_data)
+                    continue
+
+                print(f"[{i}/{total_links}] Processando {pub_number}...")
+
+                # 1. Extrai dados básicos e o NOME do PRIMEIRO Inventor (agora limpo)
+                basic_data = get_patent_data(pub_number)
+
+                if not basic_data:
+                    print(f"   [FALHA TOTAL]: Não foi possível obter dados básicos de {pub_number}.")
+                    fail_data = {f: 'FALHA' for f in fieldnames}
+                    fail_data.update({'link': link, 'publication_number': pub_number,
+                                      'num_ipc': 0, 'num_cpc': 0, 'ipc_diversity': 0, 'cpc_diversity': 0})
+                    writer.writerow(fail_data)
+                    time.sleep(3)
+                    continue
+
+                # 2. Extrai Características do Inventor (usando o nome limpo)
+                inventor_name = basic_data.get('inventor_name')
+                inventor_metrics = {}
+
+                if inventor_name:
+                    print(f"   [INVENTOR]: Extraindo características do Inventor principal: '{inventor_name}'.")
+                    inventor_metrics = get_inventor_portfolio_metrics(inventor_name)
+                else:
+                    print("   [ALERTA INVENTOR]: Inventor não encontrado na patente. Métricas setadas para 0/N/A.")
+                    inventor_metrics = {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+                # 3. CONSOLIDAÇÃO E ESCRITA
+
+                row_data = {
+                    'link': link,
+                    'publication_number': pub_number,
+                    'inventor_name': inventor_name if inventor_name else 'N/A',
+                    'inventor_portfolio_size': inventor_metrics['portfolio_size'],
+                    'inventor_recency_growth_rate': inventor_metrics['recency_growth_rate'],
+                    'inventor_quality_avg_cites': inventor_metrics['quality'],
+                    'inventor_coverage_avg_family': inventor_metrics['coverage'],
+                    'family_count': basic_data['family_count'],
+                    'family_members': ', '.join(basic_data['family_members']),
+                    'num_ipc': basic_data['num_ipc'],
+                    'num_cpc': basic_data['num_cpc'],
+                    'ipc_diversity': basic_data['ipc_diversity'],
+                    'cpc_diversity': basic_data['cpc_diversity'],
+                    'IPC': ', '.join(basic_data['IPC']),
+                    'CPC': ', '.join(basic_data['CPC'])
+                }
+
+                writer.writerow(row_data)
+
+                time.sleep(3)
+
+        print(f"\n✨ Processamento concluído. Resultados salvos em: {OUTPUT_FILE}")
diff --git a/API INVENTORES.py b/API INVENTORES.py
new file mode 100644
index 0000000..8a3b881
--- /dev/null
+++ b/API INVENTORES.py	
@@ -0,0 +1,462 @@
+import requests
+import xmltodict
+import csv
+import re
+import time
+import datetime
+from requests.auth import HTTPBasicAuth
+from typing import Optional, Dict, Any
+
+# ==============================================================================
+# ⚠️ CONFIGURAÇÃO OBRIGATÓRIA
+# ------------------------------------------------------------------------------
+CONSUMER_KEY = "3APxH4wxYoY7aZibQ4jDP9YGjezGbWzfcGji9xA6j3qY0ea1"
+CONSUMER_SECRET = "OCeAZAVzxdlLZ80IJ4sootDyI8iKpleu3pD3qEGh1R1BYALewAfyRuhASN1XnJBk"
+
+# Arquivo de entrada: lista de nomes de inventores (um por linha)
+INPUT_FILE = r"C:\Users\ATAF IP\COMPRAS\INVENTORES.txt"
+OUTPUT_FILE = "inventores_metricas.csv"
+
+ACCESS_TOKEN = None
+MAX_RETRIES = 5
+PORTFOLIO_SAMPLE_SIZE = 25  # Limite de patentes do portfólio para amostrar
+RECENCY_YEARS_PERIOD = 5  # Duração de cada período para cálculo da Taxa de Crescimento
+
+
+# ==============================================================================
+
+
+def get_access_token():
+    """Obtém o Access Token via OAuth 2.0."""
+    global ACCESS_TOKEN
+    token_url = "https://ops.epo.org/3.2/auth/accesstoken"
+    try:
+        response = requests.post(
+            token_url,
+            data={'grant_type': 'client_credentials'},
+            auth=HTTPBasicAuth(CONSUMER_KEY, CONSUMER_SECRET),
+            headers={'Content-Type': 'application/x-www-form-urlencoded'}
+        )
+        response.raise_for_status()
+        token_data = response.json()
+        ACCESS_TOKEN = token_data.get('access_token')
+        print("✅ Access Token obtido com sucesso.")
+        return ACCESS_TOKEN
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Erro ao obter o token: {e}")
+        return None
+
+
+def make_ops_request(url: str, headers: Dict[str, str], identifier: str, max_retries: int = MAX_RETRIES) -> Optional[
+    requests.Response]:
+    """Realiza a requisição com tratamento de retry e 429."""
+    for attempt in range(max_retries):
+        try:
+            response = requests.get(url, headers=headers)
+
+            if response.status_code == 429:
+                retry_after = response.headers.get('Retry-After')
+                try:
+                    wait_time = int(retry_after)
+                except (TypeError, ValueError):
+                    wait_time = 60
+
+                print(
+                    f"   [ALERTA 429 - {identifier}]: Limite atingido. Tentativa {attempt + 1}/{max_retries}. Esperando {wait_time}s...")
+                time.sleep(wait_time)
+
+                if attempt == max_retries - 1:
+                    print(f"   [FALHA 429]: Tentativas esgotadas para {identifier}.")
+                    return None
+                continue
+
+            response.raise_for_status()
+            return response
+
+        except requests.exceptions.HTTPError as e:
+            if response.status_code == 404:
+                return response
+            return None
+
+        except requests.exceptions.RequestException:
+            if attempt < max_retries - 1:
+                print(
+                    f"   [ERRO CONEXÃO]: Falha para {identifier}. Tentando novamente... ({attempt + 1}/{max_retries})")
+                time.sleep(5)
+                continue
+            return None
+
+    return None
+
+
+def clean_inventor_name(name: str) -> str:
+    """Limpa e formata o nome do inventor."""
+    if not name:
+        return None
+
+    # Remove códigos de país [US], [BR], etc
+    name = re.sub(r'\s*\[[A-Z]{2,3}\]\s*', '', name).strip()
+
+    # Remove pontuações extras
+    name = re.sub(r'[.,;]+$', '', name).strip()
+
+    # Remove espaços múltiplos
+    name = re.sub(r'\s+', ' ', name)
+
+    return name if name else None
+
+
+def get_citation_and_date(pub_number: str, headers: Dict[str, str]) -> Dict[str, Any]:
+    """Obtém contagens de citações e data de publicação."""
+    base_url = "https://ops.epo.org/rest-services"
+    citations_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/citations"
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/biblio"
+
+    forward_cites, backward_cites, pub_date = 0, 0, None
+
+    # Citações
+    cites_response = make_ops_request(citations_url, headers, f"Citação {pub_number}")
+    if cites_response and cites_response.status_code == 200:
+        try:
+            cites_data = xmltodict.parse(cites_response.text)
+
+            forward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:forward-citations', {}).get('citation', [])
+            if isinstance(forward_list, dict): forward_list = [forward_list]
+            forward_cites = len(forward_list)
+
+            backward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:backward-citations', {}).get('citation', [])
+            if isinstance(backward_list, dict): backward_list = [backward_list]
+            backward_cites = len(backward_list)
+        except Exception:
+            pass
+
+    # Data de Publicação
+    biblio_response = make_ops_request(biblio_url, headers, f"Biblio Date {pub_number}")
+    if biblio_response and biblio_response.status_code == 200:
+        try:
+            biblio_data = xmltodict.parse(biblio_response.text)
+            date_raw = \
+            biblio_data.get('ops:world-patent-data', {}).get('exchange-documents', {}).get('exchange-document', {}).get(
+                'bibliographic-data', {}).get('publication-reference', {}).get('document-id', [{}])[0].get('date')
+            if date_raw:
+                pub_date = date_raw
+        except Exception:
+            pass
+
+    return {
+        'forward_cites': forward_cites,
+        'backward_cites': backward_cites,
+        'pub_date': pub_date
+    }
+
+
+def get_inventor_portfolio_metrics(inventor_name: str) -> Dict[str, Any]:
+    """Calcula métricas completas do portfólio do inventor."""
+    if not inventor_name or not ACCESS_TOKEN:
+        return {
+            'portfolio_size': 0,
+            'recency_growth_rate': 0,
+            'quality_avg_cites': 0,
+            'coverage_avg_family': 0,
+            'total_forward_cites': 0,
+            'total_backward_cites': 0,
+            'avg_forward_cites': 0,
+            'avg_backward_cites': 0,
+            'years_active': 0,
+            'first_patent_year': 'N/A',
+            'last_patent_year': 'N/A',
+            'patents_last_5_years': 0
+        }
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Limpa o nome do inventor
+    inventor_name = clean_inventor_name(inventor_name)
+
+    # Encoding correto para a busca
+    encoded_name = requests.utils.quote(inventor_name)
+    search_url = f"{base_url}/published-data/search/biblio?q=in%3D{encoded_name}&Range=1-{PORTFOLIO_SAMPLE_SIZE}"
+
+    print(f"   [BUSCA PORTFÓLIO]: Buscando patentes do inventor '{inventor_name}'...")
+    print(f"   [URL]: {search_url}")
+
+    search_response = make_ops_request(search_url, headers, f"Busca {inventor_name}")
+
+    total_patents_found = 0
+    patent_ids = []
+
+    if search_response and search_response.status_code == 200:
+        try:
+            search_data = xmltodict.parse(search_response.text)
+
+            # Debug: salvar resposta para análise
+            with open('debug_search_response.xml', 'w', encoding='utf-8') as debug_file:
+                debug_file.write(search_response.text)
+
+            total_patents_found = int(
+                search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get('@total-result-count', 0))
+
+            print(f"   [RESULTADO]: {total_patents_found} patentes encontradas no portfólio total.")
+
+            biblio_search = search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {})
+
+            # Tentar diferentes estruturas de resposta
+            search_result = biblio_search.get('ops:search-result', {})
+
+            # Estrutura 1: ops:publication-reference
+            hits = search_result.get('ops:publication-reference', [])
+
+            # Estrutura 2: exchange-documents
+            if not hits:
+                exchange_docs = search_result.get('exchange-documents', {})
+                if exchange_docs:
+                    # Se já for lista, usa direto
+                    if isinstance(exchange_docs, list):
+                        hits = exchange_docs
+                    else:
+                        hits = exchange_docs.get('exchange-document', [])
+
+            # Estrutura 3: Direto no biblio-search
+            if not hits:
+                hits = biblio_search.get('ops:publication-reference', [])
+
+            # Estrutura 4: Verificar se search-result tem exchange-document direto
+            if not hits:
+                hits = search_result.get('exchange-document', [])
+
+            if isinstance(hits, dict):
+                hits = [hits]
+
+            print(f"   [DEBUG HITS]: Encontrados {len(hits)} resultados para processar")
+
+            for idx, hit in enumerate(hits):
+                # Tentar extrair document-id de diferentes locais
+                doc_id_list = hit.get('document-id', [])
+
+                # Se não encontrou, tentar em bibliographic-data
+                if not doc_id_list:
+                    bib_data = hit.get('bibliographic-data', {})
+                    pub_ref = bib_data.get('publication-reference', {})
+                    doc_id_list = pub_ref.get('document-id', [])
+
+                if isinstance(doc_id_list, dict):
+                    doc_id_list = [doc_id_list]
+
+                for doc_id in doc_id_list:
+                    doc_num = doc_id.get('doc-number')
+                    if doc_num:
+                        patent_ids.append(doc_num)
+                        print(f"      [{idx + 1}] Adicionado: {doc_num}")
+                        break
+
+        except Exception as e:
+            print(f"   [ERRO PARSING BUSCA]: {e}")
+            import traceback
+            traceback.print_exc()
+            return {
+                'portfolio_size': 0,
+                'recency_growth_rate': 0,
+                'quality_avg_cites': 0,
+                'coverage_avg_family': 0,
+                'total_forward_cites': 0,
+                'total_backward_cites': 0,
+                'avg_forward_cites': 0,
+                'avg_backward_cites': 0,
+                'years_active': 0,
+                'first_patent_year': 'N/A',
+                'last_patent_year': 'N/A',
+                'patents_last_5_years': 0
+            }
+    else:
+        print(
+            f"   [ALERTA]: Nenhum resultado na busca. Status: {search_response.status_code if search_response else 'None'}")
+
+    if not patent_ids:
+        print(f"   [ALERTA PORTFÓLIO]: Nenhuma patente encontrada na amostra.")
+        return {
+            'portfolio_size': total_patents_found,
+            'recency_growth_rate': 0,
+            'quality_avg_cites': 0,
+            'coverage_avg_family': 0,
+            'total_forward_cites': 0,
+            'total_backward_cites': 0,
+            'avg_forward_cites': 0,
+            'avg_backward_cites': 0,
+            'years_active': 0,
+            'first_patent_year': 'N/A',
+            'last_patent_year': 'N/A',
+            'patents_last_5_years': 0
+        }
+
+    # Processamento da amostra
+    total_forward_cites = 0
+    total_backward_cites = 0
+    total_family_size = 0
+    publication_years = {}
+    current_year = datetime.datetime.now().year
+
+    print(f"   [CALC. MÉTRICAS]: Processando {len(patent_ids)} patentes da amostra...")
+
+    for idx, pub_id in enumerate(patent_ids, 1):
+        print(f"      [{idx}/{len(patent_ids)}] Processando {pub_id}...")
+
+        metrics = get_citation_and_date(pub_id, headers)
+
+        total_forward_cites += metrics['forward_cites']
+        total_backward_cites += metrics['backward_cites']
+
+        if metrics['pub_date']:
+            try:
+                year = int(metrics['pub_date'][:4])
+                publication_years[year] = publication_years.get(year, 0) + 1
+            except (ValueError, TypeError):
+                pass
+
+        # Família
+        family_url = f"{base_url}/family/publication/epodoc/{pub_id}"
+        family_response = make_ops_request(family_url, headers, f"Família {pub_id}")
+
+        if family_response and family_response.status_code == 200:
+            try:
+                family_data = xmltodict.parse(family_response.text)
+                family_members_raw = family_data.get('ops:world-patent-data', {}).get('ops:patent-family', {}).get(
+                    'ops:family-member', [])
+
+                if isinstance(family_members_raw, dict):
+                    family_members_raw = [family_members_raw]
+
+                family_count = len(family_members_raw)
+                total_family_size += family_count
+            except Exception:
+                pass
+
+        time.sleep(1)
+
+    sample_count = len(patent_ids)
+
+    # Cálculo das métricas
+    total_cites = total_forward_cites + total_backward_cites
+    quality = round(total_cites / sample_count, 2) if sample_count > 0 else 0
+    avg_forward = round(total_forward_cites / sample_count, 2) if sample_count > 0 else 0
+    avg_backward = round(total_backward_cites / sample_count, 2) if sample_count > 0 else 0
+    coverage = round(total_family_size / sample_count, 2) if sample_count > 0 else 0
+
+    # Anos de atividade
+    years_list = list(publication_years.keys())
+    first_year = min(years_list) if years_list else 'N/A'
+    last_year = max(years_list) if years_list else 'N/A'
+    years_active = (last_year - first_year + 1) if isinstance(first_year, int) and isinstance(last_year, int) else 0
+
+    # Patentes nos últimos 5 anos
+    patents_last_5 = sum(count for year, count in publication_years.items() if year >= current_year - 5)
+
+    # Recência (Taxa de Crescimento)
+    year_end_A = current_year
+    year_start_A = year_end_A - RECENCY_YEARS_PERIOD + 1
+    year_start_B = year_start_A - RECENCY_YEARS_PERIOD
+
+    patents_A = sum(count for year, count in publication_years.items() if year >= year_start_A and year <= year_end_A)
+    patents_B = sum(count for year, count in publication_years.items() if year >= year_start_B and year < year_start_A)
+
+    recency_growth_rate = 0.0
+    if patents_B > 0:
+        recency_growth_rate = round((patents_A - patents_B) / patents_B, 4)
+    elif patents_A > 0:
+        recent_years_with_patents = [year for year in publication_years.keys() if
+                                     year >= year_start_A and year <= year_end_A]
+        min_recent_year = min(recent_years_with_patents) if recent_years_with_patents else year_end_A
+        years_active_recent = current_year - min_recent_year + 1
+        recency_growth_rate = round(patents_A / years_active_recent, 4)
+
+    print(f"   [MÉTRICAS]: Qualidade: {quality}, Cobertura: {coverage}, Recência: {recency_growth_rate}")
+
+    return {
+        'portfolio_size': total_patents_found,
+        'recency_growth_rate': recency_growth_rate,
+        'quality_avg_cites': quality,
+        'coverage_avg_family': coverage,
+        'total_forward_cites': total_forward_cites,
+        'total_backward_cites': total_backward_cites,
+        'avg_forward_cites': avg_forward,
+        'avg_backward_cites': avg_backward,
+        'years_active': years_active,
+        'first_patent_year': first_year,
+        'last_patent_year': last_year,
+        'patents_last_5_years': patents_last_5
+    }
+
+
+# === FLUXO PRINCIPAL ===
+if __name__ == "__main__":
+
+    if not get_access_token():
+        print("\n❌ O script não pode continuar sem um Access Token válido.")
+        exit()
+
+    # Lê lista de inventores
+    try:
+        with open(INPUT_FILE, 'r', encoding='utf-8') as f:
+            inventors = [line.strip() for line in f.readlines() if line.strip()]
+
+    except FileNotFoundError:
+        print(f"\n❌ ERRO: Arquivo de entrada não encontrado: {INPUT_FILE}")
+        exit()
+
+    print(f"\n📋 Total de inventores a processar: {len(inventors)}\n")
+
+    # Cria arquivo CSV de saída
+    with open(OUTPUT_FILE, 'w', newline='', encoding='utf-8') as csvfile:
+
+        fieldnames = [
+            'inventor_name',
+            'portfolio_size',
+            'recency_growth_rate',
+            'quality_avg_cites',
+            'coverage_avg_family',
+            'total_forward_cites',
+            'total_backward_cites',
+            'avg_forward_cites',
+            'avg_backward_cites',
+            'years_active',
+            'first_patent_year',
+            'last_patent_year',
+            'patents_last_5_years'
+        ]
+
+        writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+        writer.writeheader()
+
+        for i, inventor_name in enumerate(inventors, 1):
+            print(f"\n[{i}/{len(inventors)}] ========== Processando Inventor: {inventor_name} ==========")
+
+            # Extrai métricas do inventor
+            metrics = get_inventor_portfolio_metrics(inventor_name)
+
+            # Prepara dados para escrita
+            row_data = {
+                'inventor_name': inventor_name,
+                'portfolio_size': metrics['portfolio_size'],
+                'recency_growth_rate': metrics['recency_growth_rate'],
+                'quality_avg_cites': metrics['quality_avg_cites'],
+                'coverage_avg_family': metrics['coverage_avg_family'],
+                'total_forward_cites': metrics['total_forward_cites'],
+                'total_backward_cites': metrics['total_backward_cites'],
+                'avg_forward_cites': metrics['avg_forward_cites'],
+                'avg_backward_cites': metrics['avg_backward_cites'],
+                'years_active': metrics['years_active'],
+                'first_patent_year': metrics['first_patent_year'],
+                'last_patent_year': metrics['last_patent_year'],
+                'patents_last_5_years': metrics['patents_last_5_years']
+            }
+
+            writer.writerow(row_data)
+
+            print(f"   ✅ Dados salvos para {inventor_name}")
+
+            # Pausa entre inventores para não sobrecarregar a API
+            time.sleep(3)
+
+    print(f"\n✨ Processamento concluído! Resultados salvos em: {OUTPUT_FILE}")
\ No newline at end of file
diff --git a/Data/wipoResults.xls b/Data/wipoResults.xls
deleted file mode 100644
index c3a6b19..0000000
Binary files a/Data/wipoResults.xls and /dev/null differ
diff --git a/Data/wipo_with_methanol.xls b/Data/wipo_with_methanol.xls
new file mode 100644
index 0000000..3a85a89
Binary files /dev/null and b/Data/wipo_with_methanol.xls differ
diff --git a/Data/wipo_without_methanol.xls b/Data/wipo_without_methanol.xls
new file mode 100644
index 0000000..3d92588
Binary files /dev/null and b/Data/wipo_without_methanol.xls differ
diff --git a/GOOGLE WEBSCRAPPING TRIAL.py b/GOOGLE WEBSCRAPPING TRIAL.py
new file mode 100644
index 0000000..41cb816
--- /dev/null
+++ b/GOOGLE WEBSCRAPPING TRIAL.py	
@@ -0,0 +1,243 @@
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.chrome.options import Options
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+from selenium.common.exceptions import TimeoutException
+from bs4 import BeautifulSoup
+from openpyxl import load_workbook
+import spacy
+from collections import Counter
+import re
+from datetime import datetime
+
+# Caminho do Excel
+excel_path = r"C:\Users\Licitações\Downloads\WEBSCRAPPING.xlsx"
+
+# Abre o Excel
+wb = load_workbook(excel_path)
+ws = wb["Planilha1"]
+
+# Configurações do Chrome
+chrome_options = Options()
+# chrome_options.add_argument("--headless")  # descomente se quiser rodar sem abrir janela
+driver = webdriver.Chrome(options=chrome_options)
+wait = WebDriverWait(driver, 10)
+
+# Carrega modelo spaCy
+nlp = spacy.load("en_core_web_sm")
+
+# Contadores de progresso
+total_links = 0
+links_modificados = 0
+links_sem_dados = 0
+
+
+def extract_from_soup(soup, driver):
+    """Extrai todas as informações da patente e retorna em um dicionário."""
+    result = {}
+
+    # Inventores
+    inventors = []
+    important_people = soup.select("dl.important-people.style-scope.patent-result")
+    if important_people:
+        dl = important_people[0]
+        dt_inventor = dl.find("dt", string=lambda x: x and "Inventor" in x)
+        if dt_inventor:
+            for dd in dt_inventor.find_all_next("dd"):
+                state = dd.find("state-modifier")
+                if state and state.has_attr("data-inventor"):
+                    inventors.append(state["data-inventor"])
+                else:
+                    break
+    result["inventors_count"] = len(inventors)
+
+    # Imagens
+    image_tags = soup.select("section#thumbnails img")
+    result["images_count"] = len(image_tags)
+
+    # Backward citations
+    backward = []
+    citations_section = soup.find("h3", id="patentCitations")
+    if citations_section:
+        table = citations_section.find_next("div", class_="responsive-table")
+        if table:
+            for m in table.find_all("state-modifier"):
+                data = m.get("data-result", "")
+                if "patent/" in data:
+                    backward.append(data.split("patent/")[-1].split("/")[0])
+    result["backward_count"] = len(backward)
+
+    # Forward citations
+    cited_by = []
+    cited_by_section = soup.find("h3", id="citedBy")
+    if cited_by_section:
+        table = cited_by_section.find_next("div", class_="responsive-table")
+        if table:
+            for m in table.find_all("state-modifier"):
+                data = m.get("data-result", "")
+                if "patent/" in data:
+                    cited_by.append(data.split("patent/")[-1].split("/")[0])
+    result["forward_count"] = len(cited_by)
+
+    # Título e substantivos
+    title_tag = soup.find("h1", class_="scroll-target style-scope patent-result")
+    title_text = title_tag.get_text(strip=True) if title_tag else ""
+    result["title_text"] = title_text
+    doc = nlp(title_text)
+    result["num_nouns"] = sum(1 for token in doc if token.pos_ == "NOUN")
+
+    # Priority apps
+    priority_apps = []
+    priority_section = soup.find("h3", id="appsClaimingPriority")
+    if priority_section:
+        table = priority_section.find_next("div", class_="responsive-table style-scope patent-result")
+        if table:
+            for row_div in table.find_all("div", class_="tr style-scope patent-result"):
+                if row_div.find("span", class_="th style-scope patent-result"):
+                    continue
+                state = row_div.find("state-modifier")
+                if state and state.has_attr("data-result"):
+                    priority_apps.append(state["data-result"])
+    result["priority_count"] = len(priority_apps)
+
+    # Similaridade título/descrição
+    try:
+        desc_element = wait.until(
+            EC.presence_of_element_located((By.XPATH, "//patent-text/div/section"))
+        )
+        description_text = desc_element.text.strip()
+    except TimeoutException:
+        description_text = ""
+
+    doc_desc = nlp(description_text)
+    desc_words = [t.lemma_.lower() for t in doc_desc if t.is_alpha and not t.is_stop]
+    word_freq = Counter(desc_words)
+    top_10 = [w for w, _ in word_freq.most_common(10)]
+
+    doc_title = nlp(title_text)
+    title_words = [t.lemma_.lower() for t in doc_title if t.is_alpha and not t.is_stop]
+    result["similarity_score"] = sum(title_words.count(w) for w in top_10)
+
+    # NPL citations
+    num_npl = 0
+    npl_section = soup.find("h3", id="nplCitations")
+    if npl_section:
+        match = re.search(r"\((\d+)\)", npl_section.get_text(strip=True))
+        if match:
+            num_npl = int(match.group(1))
+        else:
+            table = npl_section.find_next("div", class_="responsive-table")
+            if table:
+                num_npl = len(table.find_all("div", class_="tr style-scope patent-result"))
+    result["npl_count"] = num_npl
+
+    # Número de claims
+    num_claims = 0
+    for c in soup.find_all("div", class_="flex style-scope patent-result"):
+        text = c.get_text(strip=True)
+        if "Claims" in text or "Reivindicações" in text:
+            span = c.find("span", class_="style-scope patent-result")
+            if span:
+                m = re.search(r"\((\d+)\)", span.get_text(strip=True))
+                if m:
+                    num_claims = int(m.group(1))
+                    break
+    result["num_claims"] = num_claims
+
+    # Data de aplicação
+    app_date_tag = soup.find("div", class_="filed style-scope application-timeline")
+    if app_date_tag:
+        app_date = app_date_tag.get_text(strip=True)
+        try:
+            app_date = datetime.strptime(app_date, "%Y-%m-%d").strftime("%d-%m-%Y")
+        except ValueError:
+            pass
+    else:
+        app_date = ""
+    result["app_date"] = app_date
+
+    return result
+
+
+# Loop principal
+for row in range(2, 102):
+    url_original = ws[f"A{row}"].value
+    if not url_original:
+        continue
+
+    total_links += 1
+    print(f"\n[Linha {row}] Acessando: {url_original}")
+    urls_to_try = [url_original]
+
+    # cria variação /BRPI se aplicável
+    if "/patent/BR" in url_original and "BRPI" not in url_original:
+        urls_to_try.append(url_original.replace("/patent/BR", "/patent/BRPI", 1))
+
+    final_results = None
+    link_used = "Link original"
+
+    for idx, url in enumerate(urls_to_try, start=1):
+        try:
+            driver.get(url)
+            wait.until(EC.presence_of_element_located((By.CSS_SELECTOR, "body")))
+            soup = BeautifulSoup(driver.page_source, "html.parser")
+            results = extract_from_soup(soup, driver)
+
+            found_any = any([
+                results["inventors_count"],
+                results["images_count"],
+                results["backward_count"],
+                results["forward_count"],
+                results["num_nouns"],
+                results["priority_count"],
+                results["similarity_score"],
+                results["npl_count"],
+                results["num_claims"],
+                bool(results["app_date"]),
+                bool(results["title_text"]),
+            ])
+
+            if found_any:
+                final_results = results
+                if url != url_original:
+                    ws[f"A{row}"] = url
+                    link_used = "Link modificado"
+                    links_modificados += 1
+                print(f"  ✅ Dados encontrados (tentativa {idx})")
+                break
+            else:
+                print(f"  ⚠️ Nenhum dado na tentativa {idx}")
+        except TimeoutException:
+            print(f"  ⏳ Timeout ao acessar {url}")
+        except Exception as e:
+            print(f"  ❌ Erro inesperado: {e}")
+
+    # Grava resultados
+    if final_results:
+        ws[f"B{row}"] = final_results["inventors_count"]
+        ws[f"C{row}"] = final_results["images_count"]
+        ws[f"D{row}"] = final_results["backward_count"]
+        ws[f"E{row}"] = final_results["forward_count"]
+        ws[f"F{row}"] = final_results["num_nouns"]
+        ws[f"G{row}"] = final_results["priority_count"]
+        ws[f"H{row}"] = final_results["similarity_score"]
+        ws[f"I{row}"] = final_results["npl_count"]
+        ws[f"J{row}"] = final_results["num_claims"]
+        ws[f"K{row}"] = final_results["app_date"]
+        ws[f"L{row}"] = link_used
+    else:
+        ws[f"L{row}"] = "Sem dados"
+        links_sem_dados += 1
+
+# Finaliza
+driver.quit()
+wb.save(excel_path)
+
+# 📊 Resumo final
+print("\n====================== RESUMO ======================")
+print(f"🔍 Total de patentes analisadas: {total_links}")
+print(f"🧩 Links modificados:            {links_modificados}")
+print(f"⚠️  Patentes sem dados:           {links_sem_dados}")
+print("✅ Processo concluído. Dados salvos no Excel.")
+print("====================================================")
diff --git a/INVENTORES.txt b/INVENTORES.txt
new file mode 100644
index 0000000..a504b66
--- /dev/null
+++ b/INVENTORES.txt
@@ -0,0 +1,3 @@
+PINTO JOSE RICARDO MEDEIROS
+GALVAO CELIA MARIA ARAUJO
+AUDI RICARDO
\ No newline at end of file
diff --git a/PATENTES ADAPTADAS.txt b/PATENTES ADAPTADAS.txt
new file mode 100644
index 0000000..554c40d
--- /dev/null
+++ b/PATENTES ADAPTADAS.txt	
@@ -0,0 +1,6242 @@
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diff --git a/PATENTES WIPO TO GOOGLE.py b/PATENTES WIPO TO GOOGLE.py
new file mode 100644
index 0000000..0fb2e69
--- /dev/null
+++ b/PATENTES WIPO TO GOOGLE.py	
@@ -0,0 +1,121 @@
+import time
+import re
+import pandas as pd
+from tqdm import tqdm
+from selenium import webdriver
+from selenium.webdriver.chrome.options import Options
+from selenium.webdriver.chrome.service import Service
+from webdriver_manager.chrome import ChromeDriverManager
+from selenium.webdriver.common.by import By
+from selenium.webdriver.support.ui import WebDriverWait
+from selenium.webdriver.support import expected_conditions as EC
+
+# ---------- CONFIG ----------
+file_path = r"C:\Users\ATAF IP\COMPRAS\wipo_with_methanol (1).xlsx"
+sheet_name = "ResultSet"
+# small delay between requests (increase if you get blocks)
+DELAY_BETWEEN = 1.0
+# timeout for element load
+WAIT_TIMEOUT = 20
+# ----------------------------
+
+# Ler planilha
+df = pd.read_excel(file_path, sheet_name=sheet_name)
+
+# Garante que existe uma coluna B para armazenar o ID da patente e que ela aceita strings
+if df.shape[1] < 2:
+    df.insert(1, 'Patent_ID', pd.NA)
+else:
+    # renomeia a segunda coluna para um nome consistente (opcional)
+    second_col = df.columns[1]
+    if second_col != "Patent_ID":
+        df.rename(columns={second_col: "Patent_ID"}, inplace=True)
+
+df['Patent_ID'] = df['Patent_ID'].astype(object)  # evita FutureWarning ao atribuir strings
+
+# Configurações do Chrome (headless)
+options = Options()
+# se sua versão do Chrome for antiga, substitua por "--headless"
+# options.add_argument("--headless=new")
+options.add_argument("--no-sandbox")
+options.add_argument("--disable-dev-shm-usage")
+options.add_argument("--disable-gpu")
+options.add_argument("--window-size=1920,1080")
+
+service = Service(ChromeDriverManager().install())
+driver = webdriver.Chrome(service=service, options=options)
+wait = WebDriverWait(driver, WAIT_TIMEOUT)
+
+# Itera por todos os índices (inclui o índice 0 — ou seja, a "primeira" linha de dados)
+for idx in tqdm(df.index[1850:1900             ].tolist(), desc="Extraindo patentes"):
+    link = df.at[idx, df.columns[0]]
+
+    # pula célula vazia ou valores óbvios não-URL
+    if pd.isna(link):
+        continue
+    if not isinstance(link, str):
+        link = str(link)
+    if not link.lower().startswith("http"):
+        tqdm.write(f"Pulando valor não-URL na Excel linha {idx+2}: {link!r}")
+        continue
+
+    time.sleep(5)
+    try:
+        driver.get(link)
+
+        # tenta localizar o elemento principal
+        text = None
+        try:
+            el = wait.until(
+                EC.presence_of_element_located((By.CSS_SELECTOR, "div.ps-page-header--subtitle--text"))
+            )
+            text = el.text.strip()
+        except Exception:
+            # fallback via JS
+            text = driver.execute_script(
+                "const e=document.querySelector('div.ps-page-header--subtitle--text'); return e?e.innerText:null;"
+            )
+            if not text:
+                # outro fallback por XPath (caso a estrutura varie)
+                elems = driver.find_elements(By.XPATH, "/html/body/div[2]/div[2]/form/div/h1/div/div[1]")
+                if elems:
+                    text = elems[0].text.strip()
+
+        if not text:
+            tqdm.write(f"⚠️ Elemento não encontrado na Excel linha {idx+2} ({link})")
+            df.at[idx, "Patent_ID"] = pd.NA
+            continue
+
+        # extrai o identificador com regex (procura padrão tipo 'WO2015135046' ou 'BRPI...'):
+        m = re.search(r'\b([A-Z]{1,5}\d{2,}[A-Z0-9\-]*)\b', text)
+        if m:
+            patent_id = m.group(1)
+        else:
+            # fallback: pega primeiro token que contenha letra+digito
+            patent_id = None
+            for t in text.split():
+                if re.search(r'[A-Za-z]\d', t):
+                    patent_id = t
+                    break
+            patent_id = patent_id or text.split()[0]
+
+        df.at[idx, "Patent_ID"] = str(patent_id)
+        tqdm.write(f"✅ {patent_id} extraído da Excel linha {idx+2}")
+
+    except Exception as e:
+        tqdm.write(f"⚠️ Erro na Excel linha {idx+2}: {e}")
+        df.at[idx, "Patent_ID"] = pd.NA
+
+    time.sleep(DELAY_BETWEEN)
+
+driver.quit()
+
+# Faz backup do arquivo original e grava a aba substituída
+backup_path = file_path.replace(".xlsx", ".backup.xlsx")
+df.to_excel(backup_path, sheet_name=sheet_name, index=False)
+
+with pd.ExcelWriter(file_path, engine="openpyxl", mode="a", if_sheet_exists="replace") as writer:
+    df.to_excel(writer, sheet_name=sheet_name, index=False)
+
+print("✅ Processo concluído. Backup salvo em:", backup_path)
+print("Verifique a célula B2 (Excel) para confirmar que o primeiro registro foi salvo.")
diff --git a/PATENTS WIPO TO GOOGLE FINALIZADO.xlsx b/PATENTS WIPO TO GOOGLE FINALIZADO.xlsx
new file mode 100644
index 0000000..3958f14
Binary files /dev/null and b/PATENTS WIPO TO GOOGLE FINALIZADO.xlsx differ
diff --git a/SCRAPPER.py b/SCRAPPER.py
new file mode 100644
index 0000000..2ef2fe4
--- /dev/null
+++ b/SCRAPPER.py
@@ -0,0 +1,191 @@
+from selenium import webdriver
+from selenium.webdriver.common.by import By
+from selenium.webdriver.chrome.options import Options
+from selenium.common.exceptions import TimeoutException
+from bs4 import BeautifulSoup
+from openpyxl import load_workbook
+import time
+import spacy
+from collections import Counter
+
+# Caminho do Excel
+excel_path = r"C:\Users\ATAF IP\COMPRAS\WEBSCRAPPING.xlsx"
+
+# Abre o Excel
+wb = load_workbook(excel_path)
+ws = wb.active
+
+# Configurações do Chrome (headless para ficar mais rápido)
+chrome_options = Options()
+chrome_options.add_argument("--headless")
+driver = webdriver.Chrome(options=chrome_options)
+
+# Carrega modelo spaCy em português (faça isso fora do loop se possível)
+nlp = spacy.load("pt_core_news_sm")
+
+# Loop nas linhas da planilha (a partir da linha 2)
+for row in range(2, ws.max_row + 1):
+    url = ws[f"A{row}"].value
+    if not url:
+        continue
+
+    print(f"[Linha {row}] Acessando: {url}")
+    try:
+        driver.get(url)
+        time.sleep(3)  # esperar renderização JS
+        soup = BeautifulSoup(driver.page_source, "html.parser")
+
+        # ---------------- Inventores - Resolvido - COLUNA B ----------------
+        inventors = []
+
+        try:
+            # Seleciona o bloco que contém "important-people"
+            important_people = soup.select('dl.important-people.style-scope.patent-result')
+
+            if important_people:
+                dl = important_people[0]
+                # encontra o <dt> com texto "Inventor" ou "Inventors"
+                dt_inventor = dl.find('dt', string=lambda x: x and 'Inventor' in x)
+                if dt_inventor:
+                    # percorre todos os <dd> depois do <dt> de inventores
+                    for dd in dt_inventor.find_all_next('dd'):
+                        state = dd.find('state-modifier')  # pega o elemento filho que contém data-inventor
+                        if state and state.has_attr('data-inventor'):
+                            inventors.append(state['data-inventor'])
+                        else:
+                            break  # para ao encontrar outro tipo de <dd>
+
+        except Exception as e:
+            print(f"  Erro ao buscar inventores: {e}")
+
+        # Salva número de inventores no Excel (coluna B)
+        num_inventors = len(inventors)
+        ws[f"B{row}"] = num_inventors
+
+        # ---------------- Imagens - Resolvido - COLUNA C ----------------
+        image_tags = soup.select('section#thumbnails img')
+        ws[f"C{row}"] = len(image_tags)
+
+        # ---------------- Patentes citadas (backward citations)  - Resolvido - COLUNA D ----------------
+        backward = []
+        citations_section = soup.find('h3', id="patentCitations")
+        if citations_section:
+            table = citations_section.find_next('div', class_='responsive-table')
+            if table:
+                modifiers = table.find_all('state-modifier')
+                for m in modifiers:
+                    data = m.get('data-result', '')
+                    if 'patent/' in data:
+                        backward.append(data.split('patent/')[-1].split('/')[0])
+        ws[f"D{row}"] = len(backward)
+
+        # ---------------- Cited by (forward citations) - Resolvido - COLUNA E ----------------
+        cited_by = []
+        cited_by_section = soup.find('h3', id="citedBy")
+        if cited_by_section:
+            table = cited_by_section.find_next('div', class_='responsive-table')
+            if table:
+                modifiers = table.find_all('state-modifier')
+                for m in modifiers:
+                    data = m.get('data-result', '')
+                    if 'patent/' in data:
+                        cited_by.append(data.split('patent/')[-1].split('/')[0])
+        ws[f"E{row}"] = len(cited_by)
+
+        # ---------------- Métrica 6: Número de substantivos no título - RESOLVIDO - COLUNA F ---------------
+
+        # Extrai o título da patente
+        title_tag = soup.find('h1', class_='scroll-target style-scope patent-result')
+        title_text = title_tag.get_text(strip=True) if title_tag else ""
+
+        # Processa o texto com spaCy
+        doc = nlp(title_text)
+
+        # Conta o número de substantivos
+        num_nouns = sum(1 for token in doc if token.pos_ == "NOUN")
+
+        # Salva no Excel (coluna J, por exemplo)
+        ws[f"F{row}"] = num_nouns
+
+        # ---------------- Métrica: Número de aplicações reivindicando prioridade ----------------
+        priority_apps = []
+
+        # Localiza a seção pelo ID appsClaimingPriority
+        priority_section = soup.find('h3', id='appsClaimingPriority')
+        if priority_section:
+            # Pega a tabela imediatamente após o <h3>
+            table = priority_section.find_next('div', class_='responsive-table style-scope patent-result')
+            if table:
+                rows = table.find_all('div', class_='tr style-scope patent-result')
+                for row_div in rows:
+                    # Ignora cabeçalhos (<th>)
+                    if row_div.find('span', class_='th style-scope patent-result'):
+                        continue
+
+                    # Tenta pegar data-result do state-modifier
+                    state = row_div.find('state-modifier')
+                    if state and state.has_attr('data-result'):
+                        priority_apps.append(state['data-result'])
+                    else:
+                        # Senão, pega o texto do primeiro <span> da linha
+                        span = row_div.find('span', class_='td nowrap style-scope patent-result')
+                        if span and span.get_text(strip=True):
+                            priority_apps.append(span.get_text(strip=True))
+
+        num_priority_apps = len(priority_apps)
+        ws[f"G{row}"] = num_priority_apps
+
+        # ---------------- Métrica: Frequência das 10 palavras mais comuns na descrição que aparecem no título (preciso com spaCy) ----------------
+
+        # Localiza o elemento da descrição
+        desc_element = driver.find_elements(By.XPATH,
+                                            '/html/body/search-app/search-result/search-ui/div/div/div/div/div/'
+                                            'result-container/patent-result/div/div/div/div[2]/div[1]/section/'
+                                            'patent-text/div/section')
+
+        if desc_element:
+            description_text = desc_element[0].text.strip()
+        else:
+            description_text = ""
+
+        # Processa a descrição com spaCy
+        doc_desc = nlp(description_text)
+
+
+        # Mantém apenas palavras alfabéticas, não stopwords
+        desc_words = [token.lemma_.lower() for token in doc_desc if token.is_alpha and not token.is_stop]
+
+
+        # Conta frequência das palavras
+        word_freq = Counter(desc_words)
+
+
+        # Pega as 10 mais comuns
+        top_10_words = [w for w, _ in word_freq.most_common(10)]
+        print(top_10_words)
+
+        # Processa o título com spaCy
+        doc_title = nlp(title_text)
+        title_words = [token.lemma_.lower() for token in doc_title if token.is_alpha and not token.is_stop]
+
+        # Soma quantas vezes as 10 palavras mais frequentes da descrição aparecem no título
+        freq_in_title = sum(title_words.count(w) for w in top_10_words)
+
+        # Salva no Excel (por exemplo, na coluna H)
+        ws[f"H{row}"] = freq_in_title
+
+        print(f"  Inventores: {num_inventors}, Imagens: {len(image_tags)}, Backward: {len(backward)}, "
+              f"Forward: {len(cited_by)}, Substantivos: {num_nouns}, "
+              f"Prioridade: {num_priority_apps}, Similaridade Título-Descrição: {ws[f'H{row}'].value}")
+
+    except TimeoutException:
+        print("  Tempo esgotado ao acessar a página")
+        ws[f"H{row}"] = "ERRO"
+    except Exception as e:
+        print(f"  Erro inesperado: {e}")
+        ws[f"H{row}"] = "ERRO"
+
+# Fecha navegador e salva Excel
+driver.quit()
+wb.save(excel_path)
+print("Processo concluído. Dados salvos no Excel.")
\ No newline at end of file
diff --git a/WEBSCRAPPING EPO 2.py b/WEBSCRAPPING EPO 2.py
new file mode 100644
index 0000000..11d7fca
--- /dev/null
+++ b/WEBSCRAPPING EPO 2.py	
@@ -0,0 +1,247 @@
+import requests
+import xmltodict
+import csv
+import re
+import time
+from requests.auth import HTTPBasicAuth
+
+# ==============================================================================
+# ⚠️ CONFIGURAÇÃO OBRIGATÓRIA
+# ------------------------------------------------------------------------------
+# SUBSTITUA PELAS SUAS CHAVES DE CONSUMO OBTIDAS NO PORTAL DO DESENVOLVEDOR DO EPO
+CONSUMER_KEY = "3APxH4wxYoY7aZibQ4jDP9YGjezGbWzfcGji9xA6j3qY0ea1"
+CONSUMER_SECRET = "OCeAZAVzxdlLZ80IJ4sootDyI8iKpleu3pD3qEGh1R1BYALewAfyRuhASN1XnJBk"
+
+# Caminhos dos arquivos
+INPUT_FILE = r"C:\Users\ATAF IP\COMPRAS\patentes.txt"
+OUTPUT_FILE = "patentes_dados_simples.csv"  # Nome de arquivo alterado para não sobrescrever
+
+# Variável global para armazenar o token
+ACCESS_TOKEN = None
+
+
+# ==============================================================================
+
+
+# --- 1. FUNÇÃO DE AUTENTICAÇÃO ---
+def get_access_token():
+    """Obtém o Access Token via OAuth 2.0 usando as chaves de consumidor."""
+    global ACCESS_TOKEN
+
+    token_url = "https://ops.epo.org/3.2/auth/accesstoken"
+    try:
+        response = requests.post(
+            token_url,
+            data={'grant_type': 'client_credentials'},
+            auth=HTTPBasicAuth(CONSUMER_KEY, CONSUMER_SECRET),
+            headers={'Content-Type': 'application/x-www-form-urlencoded'}
+        )
+        response.raise_for_status()
+
+        token_data = response.json()
+        ACCESS_TOKEN = token_data.get('access_token')
+        print("✅ Access Token obtido com sucesso.")
+        return ACCESS_TOKEN
+
+    except requests.exceptions.HTTPError as e:
+        print(f"❌ Erro HTTP ao obter o token: {e}")
+        return None
+    except Exception as e:
+        print(f"❌ Erro desconhecido ao obter o token: {e}")
+        return None
+
+
+# --- 2. FUNÇÃO AUXILIAR DE EXTRAÇÃO DO NÚMERO ---
+def extract_pub_number(link):
+    """Extrai o número de publicação no formato EPODOC (e.g., WO2013142934)."""
+    # Lógica de extração inalterada (mantém a compatibilidade com o formato BR9905240)
+    epo_pattern = re.search(r'([A-Z]{2}\d+[A-Z]?\d*)', link)
+    if epo_pattern:
+        return epo_pattern.group(1).replace('patent/', '')
+    google_match = re.search(r'patent/([A-Z]{2}\d+)', link)
+    if google_match:
+        return google_match.group(1)
+    return None
+
+
+# --- 3. FUNÇÃO DE EXTRAÇÃO DE DADOS (CORRIGIDA) ---
+def get_patent_data(publication_number):
+    """Consulta OPS para obter Contagem de Família, Número de IPCs e Número de CPCs."""
+    global ACCESS_TOKEN, PRINTED_XML
+    if not ACCESS_TOKEN:
+        return None
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Inicializa variáveis
+    ipc_list, cpc_list = [], []
+    family_count = 'N/A'
+
+    # ----------------------------------------------------------------------
+    # A) REQUISIÇÃO PARA DADOS BIBLIOGRÁFICOS (IPC/CPC)
+    # ----------------------------------------------------------------------
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{publication_number}/biblio"
+
+    try:
+        biblio_response = requests.get(biblio_url, headers=headers)
+        biblio_response.raise_for_status()
+
+        biblio_data = xmltodict.parse(biblio_response.text)
+
+        # Usamos uma função aninhada para extrair o texto de classificações de forma segura
+        def safe_extract_text(data):
+            # Se for uma lista de classificações (o caso mais comum)
+            if isinstance(data, list):
+                return [c.get('text', '').strip() for c in data if isinstance(c, dict) and 'text' in c]
+            # Se for um único dicionário
+            elif isinstance(data, dict) and 'text' in data:
+                return [data['text'].strip()]
+            return []
+
+        # Função para construir o código CPC completo
+        def build_cpc_code(cpc_item):
+            # Ignora classificações sem esquema (deve ser 'CPCI' ou 'CPC')
+            if not isinstance(cpc_item, dict) or cpc_item.get('classification-scheme', {}).get('@scheme') not in [
+                'CPCI', 'CPC']:
+                return None
+
+            # Constrói o código no formato SECTIONCLASS/MAINGROUP
+            section = cpc_item.get('section', '')
+            class_ = cpc_item.get('class', '')
+            subclass = cpc_item.get('subclass', '')
+            main_group = cpc_item.get('main-group', '')
+            subgroup = cpc_item.get('subgroup', '')
+
+            # Combina: C08B 1/00
+            if section and class_ and subclass and main_group and subgroup:
+                return f"{section}{class_}{subclass} {main_group}/{subgroup}"
+            return None
+
+        try:
+            exchange_docs = biblio_data['ops:world-patent-data']['exchange-documents']['exchange-document']
+            exchange_doc = exchange_docs[0] if isinstance(exchange_docs, list) else exchange_docs
+
+            # 1. Extração de IPC (Corrigido para a tag 'classifications-ipcr')
+            ipc_parent = exchange_doc.get('bibliographic-data', {}).get('classifications-ipcr', {})
+            ipc_data = ipc_parent.get('classification-ipcr', [])
+            ipc_list = safe_extract_text(ipc_data)
+
+            # 2. Extração de CPC (Implementação de nova lógica)
+            patent_classes = exchange_doc.get('bibliographic-data', {}).get('patent-classifications', {})
+            cpc_items = patent_classes.get('patent-classification', [])
+
+            # Garante que cpc_items seja sempre uma lista para iteração
+            if isinstance(cpc_items, dict):
+                cpc_items = [cpc_items]
+            elif not isinstance(cpc_items, list):
+                cpc_items = []
+
+            # Constrói a lista de CPCs
+            for item in cpc_items:
+                cpc_code = build_cpc_code(item)
+                if cpc_code:
+                    cpc_list.append(cpc_code)
+
+            # Remove duplicatas
+            ipc_list = list(set(ipc_list))
+            cpc_list = list(set(cpc_list))
+
+        except (KeyError, TypeError, IndexError) as e:
+            print(
+                f"   [ERRO EXTRAÇÃO CLASSES]: Falha ao analisar estrutura de classes: {e}. O XML pode ter uma estrutura inesperada.")
+
+    except requests.exceptions.HTTPError as e:
+        print(f"   [ERRO BIBLIO]: {e.response.status_code} para {publication_number}. Classificações não obtidas.")
+    except Exception as e:
+        print(f"   [ERRO BIBLIO]: Falha ao processar XML de {publication_number}: {e}")
+
+    # ----------------------------------------------------------------------
+    # B) REQUISIÇÃO PARA DADOS DA FAMÍLIA DE PATENTES (Contagem) - MANTIDO
+    # ----------------------------------------------------------------------
+    # ... (o código para Family Count permanece o mesmo, pois já está funcionando) ...
+    family_url = f"{base_url}/family/publication/epodoc/{publication_number}"
+
+    try:
+        family_response = requests.get(family_url, headers=headers)
+        family_response.raise_for_status()
+        family_data = xmltodict.parse(family_response.text)
+
+        family_members = family_data['ops:world-patent-data']['ops:patent-family']['ops:family-member']
+        if isinstance(family_members, list):
+            family_count = len(family_members)
+        elif isinstance(family_members, dict):
+            family_count = 1
+        else:
+            family_count = 0
+
+    except requests.exceptions.HTTPError:
+        family_count = 'ERRO'
+    except Exception:
+        family_count = 'ERRO'
+
+    # Retorna as 3 métricas solicitadas
+    return {
+        'family_count': family_count,
+        'num_ipc': len(ipc_list),
+        'num_cpc': len(cpc_list),
+        'IPC': ipc_list,
+        'CPC': cpc_list
+    }
+
+
+# --- 4. FLUXO PRINCIPAL DO SCRIPT ---
+if __name__ == "__main__":
+
+    if not get_access_token():
+        print("\nO script não pode continuar sem um Access Token válido.")
+    else:
+        try:
+            with open(INPUT_FILE, 'r', encoding='utf-8') as f:
+                links = [line.strip() for line in f.readlines() if line.strip()]
+        except FileNotFoundError:
+            print(f"\n❌ ERRO: Arquivo de entrada não encontrado: {INPUT_FILE}")
+            exit()
+
+        with open(OUTPUT_FILE, 'w', newline='', encoding='utf-8') as csvfile:
+            # FIELDNAMES AJUSTADOS PARA AS 3 MÉTRICAS SOLICITADAS
+            fieldnames = ['link', 'publication_number', 'family_count', 'num_ipc', 'num_cpc', 'IPC', 'CPC']
+            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+            writer.writeheader()
+
+            for i, link in enumerate(links, 1):
+                pub_number = extract_pub_number(link)
+                total_links = len(links)
+
+                if not pub_number:
+                    print(f"[{i}/{total_links}] ⚠️ Não extraído do link: {link}")
+                    writer.writerow(
+                        {'link': link, 'publication_number': 'N/A', 'family_count': 'N/A', 'num_ipc': 'N/A',
+                         'num_cpc': 'N/A', 'IPC': 'N/A', 'CPC': 'N/A'})
+                    continue
+
+                print(f"[{i}/{total_links}] Processando {pub_number}...")
+                data = get_patent_data(pub_number)
+
+                if data:
+                    writer.writerow({
+                        'link': link,
+                        'publication_number': pub_number,
+                        'family_count': data['family_count'],
+                        'num_ipc': data['num_ipc'],
+                        'num_cpc': data['num_cpc'],
+                        'IPC': ', '.join(data['IPC']),
+                        'CPC': ', '.join(data['CPC'])
+                    })
+                    print(
+                        f"   [SUCESSO] Dados de {pub_number} salvos (Família: {data['family_count']}, IPCs: {data['num_ipc']}, CPCs: {data['num_cpc']}).")
+                else:
+                    print(f"   [FALHA] Não foi possível obter dados completos de {pub_number}")
+                    writer.writerow(
+                        {'link': link, 'publication_number': pub_number, 'family_count': 'FALHA', 'num_ipc': 'FALHA',
+                         'num_cpc': 'FALHA', 'IPC': 'FALHA', 'CPC': 'FALHA'})
+
+                # Pausa obrigatória
+                time.sleep(3)
+
+        print(f"\n✨ Processamento concluído. Resultados salvos em: {OUTPUT_FILE}")
\ No newline at end of file
diff --git a/WEBSCRAPPING TRIAL.xlsx b/WEBSCRAPPING TRIAL.xlsx
new file mode 100644
index 0000000..18f3687
Binary files /dev/null and b/WEBSCRAPPING TRIAL.xlsx differ
diff --git a/WEBSCRAPPING.xlsx b/WEBSCRAPPING.xlsx
new file mode 100644
index 0000000..bcc878f
Binary files /dev/null and b/WEBSCRAPPING.xlsx differ
diff --git a/webscrapping_deprec/WEBSCRAPPING ADVANCED.py b/webscrapping_deprec/WEBSCRAPPING ADVANCED.py
new file mode 100644
index 0000000..aa0764d
--- /dev/null
+++ b/webscrapping_deprec/WEBSCRAPPING ADVANCED.py	
@@ -0,0 +1,584 @@
+import requests
+import xmltodict
+import csv
+import re
+import time
+import datetime
+from requests.auth import HTTPBasicAuth
+from typing import Optional, Dict, Any, List
+
+# ==============================================================================
+# ⚠️ CONFIGURAÇÃO OBRIGATÓRIA
+# ------------------------------------------------------------------------------
+# SUBSTITUA PELAS SUAS CHAVES DE CONSUMO OBTIDAS NO PORTAL DO DESENVOLVEDOR DO EPO
+CONSUMER_KEY = "3APxH4wxYoY7aZibQ4jDP9YGjezGbWzfcGji9xA6j3qY0ea1"
+CONSUMER_SECRET = "OCeAZAVzxdlLZ80IJ4sootDyI8iKpleu3pD3qEGh1R1BYALewAfyRuhASN1XnJBk"
+
+# Caminhos dos arquivos
+INPUT_FILE = r"C:\Users\Licitações\Downloads\PATENTES ADAPTADAS.txt"
+OUTPUT_FILE = "patentes_dados_simples_inventor.csv"
+
+# Variáveis globais
+ACCESS_TOKEN = None
+MAX_RETRIES = 5  # Número máximo de tentativas em caso de falha de conexão ou 429
+
+# CONSTANTES PARA CÁLCULO DE MÉTRICAS DO INVENTOR
+PORTFOLIO_SAMPLE_SIZE = 25  # Limite de patentes do portfólio para amostrar e calcular médias
+RECENCY_YEARS_PERIOD = 5  # Duração de cada período (A e B) para o cálculo da Taxa de Crescimento (5 anos)
+
+
+# ==============================================================================
+
+
+# --- 1. FUNÇÃO DE AUTENTICAÇÃO ---
+def get_access_token():
+    """Obtém o Access Token via OAuth 2.0 usando as chaves de consumidor."""
+    global ACCESS_TOKEN
+    token_url = "https://ops.epo.org/3.2/auth/accesstoken"
+    try:
+        response = requests.post(
+            token_url,
+            data={'grant_type': 'client_credentials'},
+            auth=HTTPBasicAuth(CONSUMER_KEY, CONSUMER_SECRET),
+            headers={'Content-Type': 'application/x-www-form-urlencoded'}
+        )
+        response.raise_for_status()
+        token_data = response.json()
+        ACCESS_TOKEN = token_data.get('access_token')
+        print("✅ Access Token obtido com sucesso.")
+        return ACCESS_TOKEN
+
+    except requests.exceptions.RequestException as e:
+        print(f"❌ Erro ao obter o token: {e}")
+        return None
+
+
+# --- FUNÇÃO AUXILIAR PARA TRATAMENTO DE RETRY E 429 ---
+def make_ops_request(url: str, headers: Dict[str, str], identifier: str, max_retries: int = MAX_RETRIES) -> Optional[
+    requests.Response]:
+    """
+    Realiza a requisição, tratando o limite de taxa (429) e erros de conexão.
+    """
+    for attempt in range(max_retries):
+        try:
+            response = requests.get(url, headers=headers)
+
+            if response.status_code == 429:
+                retry_after = response.headers.get('Retry-After')
+                try:
+                    wait_time = int(retry_after)
+                except (TypeError, ValueError):
+                    wait_time = 60
+
+                print(
+                    f"   [ALERTA 429 - {identifier}]: Limite de requisições atingido. Tentativa {attempt + 1}/{max_retries}. Esperando por {wait_time} segundos...")
+                time.sleep(wait_time)
+
+                if attempt == max_retries - 1:
+                    print(f"   [FALHA 429]: Tentativas esgotadas para {identifier}.")
+                    return None
+                continue
+
+            response.raise_for_status()
+            return response
+
+        except requests.exceptions.HTTPError as e:
+            if response.status_code == 404:
+                return response
+            return None
+
+        except requests.exceptions.RequestException:
+            if attempt < max_retries - 1:
+                print(
+                    f"   [ERRO CONEXÃO]: Falha de conexão para {identifier}. Tentando novamente... ({attempt + 1}/{max_retries})")
+                time.sleep(5)
+                continue
+            return None
+
+    return None
+
+
+# --- FUNÇÃO AUXILIAR DE EXTRAÇÃO DO NÚMERO ---
+def extract_pub_number(link):
+    """Extrai o número de publicação no formato EPODOC."""
+    wipo_docid_match = re.search(r'docId=([A-Z]{2}\d+[A-Z]?\d*)', link)
+    if wipo_docid_match:
+        return wipo_docid_match.group(1)
+
+    epo_pattern = re.search(r'([A-Z]{2}\d+[A-Z]?\d*)', link)
+    if epo_pattern:
+        return epo_pattern.group(1).replace('patent/', '')
+    google_match = re.search(r'patent/([A-Z]{2}\d+)', link)
+    if google_match:
+        return google_match.group(1)
+    return None
+
+
+# --- 2. EXTRAÇÃO DE CITAÇÕES E DATA PARA UM ID ESPECÍFICO ---
+def get_citation_and_date(pub_number: str, headers: Dict[str, str]) -> Dict[str, Any]:
+    """Obtém contagens de citações (forward/backward) e data de publicação."""
+    base_url = "https://ops.epo.org/rest-services"
+    citations_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/citations"
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{pub_number}/biblio"
+
+    forward_cites, backward_cites, pub_date = 0, 0, None
+
+    # 1. Citações
+    cites_response = make_ops_request(citations_url, headers, f"Citação {pub_number}")
+    if cites_response and cites_response.status_code == 200:
+        try:
+            cites_data = xmltodict.parse(cites_response.text)
+
+            # Citações Forward (Referenced by)
+            forward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:forward-citations', {}).get('citation', [])
+            if isinstance(forward_list, dict): forward_list = [forward_list]
+            forward_cites = len(forward_list)
+
+            # Citações Backward (References)
+            backward_list = cites_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get(
+                'ops:backward-citations', {}).get('citation', [])
+            if isinstance(backward_list, dict): backward_list = [backward_list]
+            backward_cites = len(backward_list)
+        except Exception:
+            pass
+
+            # 2. Data de Publicação (necessária para Recência)
+    biblio_response = make_ops_request(biblio_url, headers, f"Biblio Date {pub_number}")
+    if biblio_response and biblio_response.status_code == 200:
+        try:
+            biblio_data = xmltodict.parse(biblio_response.text)
+            date_raw = \
+            biblio_data.get('ops:world-patent-data', {}).get('exchange-documents', {}).get('exchange-document', {}).get(
+                'bibliographic-data', {}).get('publication-reference', {}).get('document-id', [{}])[0].get('date')
+            if date_raw:
+                pub_date = date_raw
+        except Exception:
+            pass
+
+    return {
+        'forward_cites': forward_cites,
+        'backward_cites': backward_cites,
+        'pub_date': pub_date
+    }
+
+
+# --- 3. FUNÇÃO PARA EXTRAIR MÉTRICAS DO PORTFÓLIO DO INVENTOR ---
+def get_inventor_portfolio_metrics(inventor_name: str) -> Dict[str, Any]:
+    """
+    Calcula Recência (Taxa de Crescimento Refinada), Qualidade e Cobertura do Inventor.
+    """
+    if not inventor_name or not ACCESS_TOKEN:
+        return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Consulta de busca (in= para Inventor) - usa o nome já limpo (SOBRENOME, NOME)
+    search_url = f"{base_url}/rest-services/published-data/search/biblio?query=in%3D%22{requests.utils.quote(inventor_name)}%22&range=1-{PORTFOLIO_SAMPLE_SIZE}"
+
+    print(
+        f"   [BUSCA PORTFÓLIO]: Buscando amostra de {PORTFOLIO_SAMPLE_SIZE} patentes para o Inventor '{inventor_name}'...")
+
+    search_response = make_ops_request(search_url, headers, f"Busca {inventor_name}")
+
+    total_patents_found = 0
+    patent_ids = []
+
+    if search_response and search_response.status_code == 200:
+        try:
+            search_data = xmltodict.parse(search_response.text)
+
+            total_patents_found = int(
+                search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {}).get('@total-result-count', 0))
+
+            biblio_search = search_data.get('ops:world-patent-data', {}).get('ops:biblio-search', {})
+            hits = biblio_search.get('ops:search-result', {}).get('ops:publication-reference', [])
+
+            if isinstance(hits, dict):
+                hits = [hits]
+
+            for hit in hits:
+                doc_id_list = hit.get('document-id', [])
+                if isinstance(doc_id_list, dict): doc_id_list = [doc_id_list]
+
+                for doc_id in doc_id_list:
+                    if doc_id.get('doc-number'):
+                        patent_ids.append(doc_id.get('doc-number'))
+                        break
+
+        except Exception as e:
+            print(f"   [ERRO PARSING BUSCA]: Falha ao processar a busca para {inventor_name}: {e}")
+            return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+    if not patent_ids:
+        print(f"   [ALERTA PORTFÓLIO]: Nenhuma patente encontrada na amostra para o Inventor '{inventor_name}'.")
+        return {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': total_patents_found}
+
+    # ----------------------------------------------------------------------
+    # ITERAÇÃO SOBRE A AMOSTRA E AGREGAÇÃO DE DADOS
+    # ----------------------------------------------------------------------
+
+    total_forward_cites = 0
+    total_backward_cites = 0
+    total_family_size = 0
+    publication_years = {}  # {year: count}
+
+    current_year = datetime.datetime.now().year
+
+    print(f"   [CALC. MÉTRICAS]: Processando amostra de {len(patent_ids)} patentes do Inventor...")
+
+    for pub_id in patent_ids:
+
+        # Coleta de Citações e Data
+        metrics = get_citation_and_date(pub_id, headers)
+
+        total_forward_cites += metrics['forward_cites']
+        total_backward_cites += metrics['backward_cites']
+
+        if metrics['pub_date']:
+            try:
+                year = int(metrics['pub_date'][:4])
+                publication_years[year] = publication_years.get(year, 0) + 1
+            except (ValueError, TypeError):
+                pass
+
+        # Coleta de Tamanho da Família
+        family_url = f"{base_url}/family/publication/epodoc/{pub_id}"
+        family_response = make_ops_request(family_url, headers, f"Família {pub_id}")
+
+        family_count = 0
+        if family_response and family_response.status_code == 200:
+            try:
+                family_data = xmltodict.parse(family_response.text)
+                family_members_raw = family_data.get('ops:world-patent-data', {}).get('ops:patent-family', {}).get(
+                    'ops:family-member', [])
+
+                if isinstance(family_members_raw, dict): family_members_raw = [family_members_raw]
+
+                family_count = len(family_members_raw)
+                total_family_size += family_count
+            except Exception:
+                pass
+
+        time.sleep(1)  # Pausa curta
+
+    # ----------------------------------------------------------------------
+    # CÁLCULO DAS MÉTRICAS FINAIS
+    # ----------------------------------------------------------------------
+
+    sample_count = len(patent_ids)
+
+    # 1. Qualidade do Inventor (Média de Citações)
+    total_cites = total_forward_cites + total_backward_cites
+    quality = round(total_cites / sample_count, 2) if sample_count > 0 else 0
+
+    # 2. Cobertura do Inventor (Média de Membros da Família)
+    coverage = round(total_family_size / sample_count, 2) if sample_count > 0 else 0
+
+    # 3. Recência do Inventor (Taxa de Crescimento em 5 anos) - Lógica Refinada
+
+    # Define os anos dos períodos
+    year_end_A = current_year
+    year_start_A = year_end_A - RECENCY_YEARS_PERIOD + 1
+    year_start_B = year_start_A - RECENCY_YEARS_PERIOD
+
+    # Soma as patentes em cada período
+    patents_A = sum(
+        count for year, count in publication_years.items()
+        if year >= year_start_A and year <= year_end_A
+    )
+    patents_B = sum(
+        count for year, count in publication_years.items()
+        if year >= year_start_B and year < year_start_A
+    )
+
+    recency_growth_rate = 0.0
+    if patents_B > 0:
+        # Crescimento percentual normal
+        recency_growth_rate = round((patents_A - patents_B) / patents_B, 4)
+    elif patents_A > 0:
+        # TRATAMENTO REFINADO para INÍCIO DE ATIVIDADE (P_B = 0, P_A > 0)
+
+        # Encontra o ano mais antigo de publicação no Período A
+        recent_years_with_patents = [year for year in publication_years.keys()
+                                     if year >= year_start_A and year <= year_end_A]
+
+        min_recent_year = min(recent_years_with_patents) if recent_years_with_patents else year_end_A
+
+        # Calcula o número de anos ativos (inclui o ano atual)
+        years_active = current_year - min_recent_year + 1
+
+        # Métrica: Volume Médio Anual no período A (resolve a "explosão")
+        recency_growth_rate = round(patents_A / years_active, 4)
+
+    # Se P_A=0 e P_B=0, a taxa é 0.
+
+    print(
+        f"   [MÉTRICAS INVENTOR]: Qualidade Média: {quality}, Cobertura Média: {coverage}, Recência (Taxa Cresc.): {recency_growth_rate}")
+
+    return {
+        'recency_growth_rate': recency_growth_rate,
+        'quality': quality,
+        'coverage': coverage,
+        'portfolio_size': total_patents_found
+    }
+
+
+# --- 4. FUNÇÃO DE EXTRAÇÃO DE DADOS BÁSICOS E INVENTOR ---
+def get_patent_data(publication_number: str) -> Optional[Dict[str, Any]]:
+    """Consulta OPS para obter Classes, Família, e o nome do PRIMEIRO Inventor."""
+    global ACCESS_TOKEN
+    if not ACCESS_TOKEN: return None
+
+    headers = {'Authorization': f'Bearer {ACCESS_TOKEN}'}
+    base_url = "https://ops.epo.org/rest-services"
+
+    # Inicializa variáveis
+    ipc_list, cpc_list = [], []
+    family_count = 'N/A'
+    biblio_success = False
+    family_members_list = []
+    ipc_diversity = 0
+    cpc_diversity = 0
+    inventor_name = None
+
+    # ----------------------------------------------------------------------
+    # A) REQUISIÇÃO PARA DADOS BIBLIOGRÁFICOS (IPC/CPC/Inventor)
+    # ----------------------------------------------------------------------
+    biblio_url = f"{base_url}/published-data/publication/epodoc/{publication_number}/biblio"
+    biblio_response = make_ops_request(biblio_url, headers, publication_number)
+
+    if biblio_response and biblio_response.status_code == 200:
+        try:
+            biblio_data = xmltodict.parse(biblio_response.text)
+            biblio_success = True
+
+            # Funções auxiliares
+            def safe_extract_text(data):
+                if isinstance(data, list):
+                    result = []
+                    for item in data:
+                        if isinstance(item, dict) and 'text' in item:
+                            result.append(item['text'].strip())
+                    return result
+                elif isinstance(data, dict) and 'text' in data:
+                    return [data['text'].strip()]
+                return []
+
+            def build_cpc_code(cpc_item):
+                if not isinstance(cpc_item, dict) or cpc_item.get('classification-scheme', {}).get('@scheme') not in [
+                    'CPCI', 'CPC']: return None
+                section = cpc_item.get('section', '')
+                class_ = cpc_item.get('class', '')
+                subclass = cpc_item.get('subclass', '')
+                main_group = cpc_item.get('main-group', '')
+                subgroup = cpc_item.get('subgroup', '')
+                if section and class_ and subclass and main_group and subgroup:
+                    return f"{section}{class_}{subclass} {main_group}/{subgroup}"
+                return None
+
+            exchange_docs_container = biblio_data.get('ops:world-patent-data', {}).get('exchange-documents')
+            if exchange_docs_container:
+                exchange_docs = exchange_docs_container.get('exchange-document')
+
+                if isinstance(exchange_docs, list):
+                    exchange_doc = exchange_docs[0]
+                else:
+                    exchange_doc = exchange_docs
+
+                if exchange_doc:
+                    bib_data = exchange_doc.get('bibliographic-data', {})
+
+                    # Extração e Limpeza do PRIMEIRO Inventor
+                    inventors = bib_data.get('parties', {}).get('inventors', {}).get('inventor', [])
+                    if isinstance(inventors, dict): inventors = [inventors]
+
+                    if inventors:
+                        first_inventor = inventors[0]
+                        addressbook = first_inventor.get('addressbook', {})
+                        last_name = addressbook.get('last-name')
+                        first_name = addressbook.get('first-name')
+
+
+                        if last_name and first_name:
+                            # Formato preferido para busca EPO: "SOBRENOME, NOME"
+                            inventor_name = f"{first_name}, {last_name}"
+                        else:
+                            # Fallback para o nome não estruturado e limpeza do código do país
+                            name_container = first_inventor.get('inventor-name', {}).get('name')
+                            if name_container:
+                                # Remove código de país tipo [US] e espaços extras
+                                inventor_name = re.sub(r'\s*\[[A-Z]{2,3}\]\s*', '', name_container).strip()
+                                partes = inventor_name.split()
+                                partes.append(partes.pop(0))
+                                inventor_name = ' '.join(partes)
+                                print(inventor_name)
+                                print("até aqui funciona")
+
+
+                    # Extração de IPC e CPC (mantido)
+                    ipc_parent = bib_data.get('classifications-ipcr', {})
+                    ipc_data = ipc_parent.get('classification-ipcr', [])
+                    ipc_list = safe_extract_text(ipc_data)
+
+                    patent_classes = bib_data.get('patent-classifications', {})
+                    cpc_items = patent_classes.get('patent-classification', [])
+                    if isinstance(cpc_items, dict): cpc_items = [cpc_items]
+                    for item in cpc_items:
+                        cpc_code = build_cpc_code(item)
+                        if cpc_code: cpc_list.append(cpc_code)
+
+                    ipc_list = list(set(ipc_list))
+                    cpc_list = list(set(cpc_list))
+
+                    ipc_diversity = len(set(ipc[:4] for ipc in ipc_list if len(ipc) >= 4))
+                    cpc_diversity = len(set(re.match(r'([A-Z]\d{2}[A-Z])', cpc).group(1) for cpc in cpc_list if
+                                            re.match(r'([A-Z]\d{2}[A-Z])', cpc)))
+
+
+        except Exception as e:
+            print(f"   [ERRO PROCESSAMENTO XML BIBLIO]: Falha ao processar XML de {publication_number}: {e}")
+            biblio_success = False
+
+    # ----------------------------------------------------------------------
+    # B) REQUISIÇÃO PARA DADOS DA FAMÍLIA (Lógica anterior)
+    # ----------------------------------------------------------------------
+    family_url = f"{base_url}/family/publication/epodoc/{publication_number}"
+    family_response = make_ops_request(family_url, headers, publication_number)
+
+    if family_response and family_response.status_code == 200:
+        try:
+            family_data = xmltodict.parse(family_response.text)
+            family_container = family_data.get('ops:world-patent-data', {}).get('ops:patent-family')
+
+            # Lógica de extração de Family Count e Members (mantida)
+            if family_container:
+                family_members_raw = family_container.get('ops:family-member')
+                if isinstance(family_members_raw, dict):
+                    members_to_process = [family_members_raw]
+                elif isinstance(family_members_raw, list):
+                    members_to_process = family_members_raw
+                else:
+                    members_to_process = []
+                family_count = len(members_to_process)
+                for member in members_to_process:
+                    try:
+                        pub_ref = member.get('ops:publication-reference', {})
+                        doc_ids = pub_ref.get('document-id')
+                        if isinstance(doc_ids, dict): doc_ids = [doc_ids]
+                        for doc_id in doc_ids:
+                            doc_num = doc_id.get('doc-number')
+                            if doc_num:
+                                family_members_list.append(doc_num)
+                                break
+                    except Exception:
+                        continue
+            else:
+                family_count = 0
+        except Exception:
+            family_count = 'ERRO'
+    else:
+        family_count = 'FALHA REQ'
+
+    if not biblio_success and family_count in ('ERRO', 'FALHA REQ', 0, 'N/A'):
+        return None
+
+    return {
+        'inventor_name': inventor_name,
+        'family_count': family_count,
+        'family_members': family_members_list,
+        'num_ipc': len(ipc_list),
+        'num_cpc': len(cpc_list),
+        'ipc_diversity': ipc_diversity,
+        'cpc_diversity': cpc_diversity,
+        'IPC': ipc_list,
+        'CPC': cpc_list
+    }
+
+
+# --- FLUXO PRINCIPAL DO SCRIPT ---
+if __name__ == "__main__":
+
+    if not get_access_token():
+        print("\nO script não pode continuar sem um Access Token válido.")
+    else:
+        try:
+            with open(INPUT_FILE, 'r', encoding='utf-8') as f:
+                links = [line.strip() for line in f.readlines() if line.strip()]
+
+        except FileNotFoundError:
+            print(f"\n❌ ERRO: Arquivo de entrada não encontrado: {INPUT_FILE}")
+            exit()
+
+        with open(OUTPUT_FILE, 'w', newline='', encoding='utf-8') as csvfile:
+
+            # --- COLUNAS ATUALIZADAS PARA INVENTOR E NOVA MÉTRICA DE RECÊNCIA ---
+            fieldnames = ['link', 'publication_number', 'inventor_name', 'inventor_portfolio_size',
+                          'inventor_recency_growth_rate', 'inventor_quality_avg_cites', 'inventor_coverage_avg_family',
+                          'family_count', 'family_members', 'num_ipc', 'num_cpc', 'ipc_diversity', 'cpc_diversity',
+                          'IPC', 'CPC']
+            writer = csv.DictWriter(csvfile, fieldnames=fieldnames)
+            writer.writeheader()
+
+            for i, link in enumerate(links, 1):
+                pub_number = extract_pub_number(link)
+                total_links = len(links)
+
+                if not pub_number:
+                    print(f"[{i}/{total_links}] ⚠️ Não extraído do link/número: {link}")
+                    fail_data = {f: 'N/A' for f in fieldnames}
+                    fail_data.update({'link': link, 'publication_number': 'N/A'})
+                    writer.writerow(fail_data)
+                    continue
+
+                print(f"[{i}/{total_links}] Processando {pub_number}...")
+
+                # 1. Extrai dados básicos e o NOME do PRIMEIRO Inventor (agora limpo)
+                basic_data = get_patent_data(pub_number)
+
+                if not basic_data:
+                    print(f"   [FALHA TOTAL]: Não foi possível obter dados básicos de {pub_number}.")
+                    fail_data = {f: 'FALHA' for f in fieldnames}
+                    fail_data.update({'link': link, 'publication_number': pub_number,
+                                      'num_ipc': 0, 'num_cpc': 0, 'ipc_diversity': 0, 'cpc_diversity': 0})
+                    writer.writerow(fail_data)
+                    time.sleep(3)
+                    continue
+
+                # 2. Extrai Características do Inventor (usando o nome limpo)
+                inventor_name = basic_data.get('inventor_name')
+                inventor_metrics = {}
+
+                if inventor_name:
+                    print(f"   [INVENTOR]: Extraindo características do Inventor principal: '{inventor_name}'.")
+                    inventor_metrics = get_inventor_portfolio_metrics(inventor_name)
+                else:
+                    print("   [ALERTA INVENTOR]: Inventor não encontrado na patente. Métricas setadas para 0/N/A.")
+                    inventor_metrics = {'recency_growth_rate': 0, 'quality': 0, 'coverage': 0, 'portfolio_size': 0}
+
+                # 3. CONSOLIDAÇÃO E ESCRITA
+
+                row_data = {
+                    'link': link,
+                    'publication_number': pub_number,
+                    'inventor_name': inventor_name if inventor_name else 'N/A',
+                    'inventor_portfolio_size': inventor_metrics['portfolio_size'],
+                    'inventor_recency_growth_rate': inventor_metrics['recency_growth_rate'],
+                    'inventor_quality_avg_cites': inventor_metrics['quality'],
+                    'inventor_coverage_avg_family': inventor_metrics['coverage'],
+                    'family_count': basic_data['family_count'],
+                    'family_members': ', '.join(basic_data['family_members']),
+                    'num_ipc': basic_data['num_ipc'],
+                    'num_cpc': basic_data['num_cpc'],
+                    'ipc_diversity': basic_data['ipc_diversity'],
+                    'cpc_diversity': basic_data['cpc_diversity'],
+                    'IPC': ', '.join(basic_data['IPC']),
+                    'CPC': ', '.join(basic_data['CPC'])
+                }
+
+                writer.writerow(row_data)
+
+                time.sleep(3)
+
+        print(f"\n✨ Processamento concluído. Resultados salvos em: {OUTPUT_FILE}")