Added all

.gitignore

@@ -0,0 +1,177 @@
+# Created by https://www.toptal.com/developers/gitignore/api/intellij+all,zsh
+# Edit at https://www.toptal.com/developers/gitignore?templates=intellij+all,zsh
+media/downloads
+media/xhs_videos
+### Intellij+all ###
+# Covers JetBrains IDEs: IntelliJ, RubyMine, PhpStorm, AppCode, PyCharm, CLion, Android Studio, WebStorm and Rider
+# Reference: https://intellij-support.jetbrains.com/hc/en-us/articles/206544839
+.DS_Store
+# User-specific stuff
+.idea/**/workspace.xml
+.idea/**/tasks.xml
+.idea/**/usage.statistics.xml
+.idea/**/dictionaries
+.idea/**/shelf
+
+# AWS User-specific
+.idea/**/aws.xml
+
+*.txt
+*.csv
+*.xlsx
+*.xls
+.env
+*.env
+
+# Generated files
+.idea/**/contentModel.xml
+
+# Sensitive or high-churn files
+.idea/**/dataSources/
+.idea/**/dataSources.ids
+.idea/**/dataSources.local.xml
+.idea/**/sqlDataSources.xml
+.idea/**/dynamic.xml
+.idea/**/uiDesigner.xml
+.idea/**/dbnavigator.xml
+
+# Gradle
+.idea/**/gradle.xml
+.idea/**/libraries
+
+# Gradle and Maven with auto-import
+# When using Gradle or Maven with auto-import, you should exclude module files,
+# since they will be recreated, and may cause churn.  Uncomment if using
+# auto-import.
+# .idea/artifacts
+# .idea/compiler.xml
+# .idea/jarRepositories.xml
+# .idea/modules.xml
+# .idea/*.iml
+# .idea/modules
+# *.iml
+# *.ipr
+
+# CMake
+cmake-build-*/
+
+# Mongo Explorer plugin
+.idea/**/mongoSettings.xml
+
+# File-based project format
+*.iws
+
+# IntelliJ
+out/
+
+# mpeltonen/sbt-idea plugin
+.idea_modules/
+
+# JIRA plugin
+atlassian-ide-plugin.xml
+
+# Cursive Clojure plugin
+.idea/replstate.xml
+
+# SonarLint plugin
+.idea/sonarlint/
+
+# Crashlytics plugin (for Android Studio and IntelliJ)
+com_crashlytics_export_strings.xml
+crashlytics.properties
+crashlytics-build.properties
+fabric.properties
+
+# Editor-based Rest Client
+.idea/httpRequests
+
+# Android studio 3.1+ serialized cache file
+.idea/caches/build_file_checksums.ser
+
+### Intellij+all Patch ###
+# Ignore everything but code style settings and run configurations
+# that are supposed to be shared within teams.
+
+.idea/*
+
+!.idea/codeStyles
+!.idea/runConfigurations
+
+### Zsh ###
+# Zsh compiled script + zrecompile backup
+*.zwc
+*.zwc.old
+
+# Zsh completion-optimization dumpfile
+*zcompdump*
+
+# Zsh history
+.zsh_history
+
+# Zsh sessions
+.zsh_sessions
+
+# Zsh zcalc history
+.zcalc_history
+
+# A popular plugin manager's files
+._zinit
+.zinit_lstupd
+
+# zdharma/zshelldoc tool's files
+zsdoc/data
+
+# robbyrussell/oh-my-zsh/plugins/per-directory-history plugin's files
+# (when set-up to store the history in the local directory)
+.directory_history
+
+# MichaelAquilina/zsh-autoswitch-virtualenv plugin's files
+# (for Zsh plugins using Python)
+.venv
+
+# Zunit tests' output
+/tests/_output/*
+!/tests/_output/.gitkeep
+
+# End of https://www.toptal.com/developers/gitignore/api/intellij+all,zsh
+
+downloads/
+
+# Created by https://www.toptal.com/developers/gitignore/api/macos
+# Edit at https://www.toptal.com/developers/gitignore?templates=macos
+
+### macOS ###
+# General
+.DS_Store
+.AppleDouble
+.LSOverride
+
+# Icon must end with two \r
+Icon
+
+
+# Thumbnails
+._*
+
+# Files that might appear in the root of a volume
+.DocumentRevisions-V100
+.fseventsd
+.Spotlight-V100
+.TemporaryItems
+.Trashes
+.VolumeIcon.icns
+.com.apple.timemachine.donotpresent
+
+# Directories potentially created on remote AFP share
+.AppleDB
+.AppleDesktop
+Network Trash Folder
+Temporary Items
+.apdisk
+
+### macOS Patch ###
+# iCloud generated files
+*.icloud
+*.csv 
+
+# End of https://www.toptal.com/developers/gitignore/api/macos

README.md

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+# scripts

file-management/buscar_grandes.sh

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+#!/bin/bash
+
+# Directorio base desde donde buscar (puedes cambiarlo o usar el argumento del script)
+DIRECTORIO=${1:-.}
+
+# Encuentra archivos mayores a 1GB y muestra su tamaño ordenado
+echo "Archivos mayores a 1GB en el directorio: $DIRECTORIO"
+find "$DIRECTORIO" -type f -size +1G -exec du -h {} + | sort -hr
+echo "Búsqueda completada."

file-management/filtrar_excel_per_csv.py

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+import pandas as pd
+import os
+import sys
+
+print("🔍 --- Filtrant Excel segons usuaris actius del CSV ---")
+
+# Noms dels fitxers
+fitxer_csv = "Newsletter_Combinat_Final_Actius.csv"
+fitxer_excel = "Contactos_Unificats.xlsx"
+fitxer_resultat = "Contactos_Unificats_Filtrats.xlsx"
+
+# Comprovem que existeixen
+if not os.path.exists(fitxer_csv) or not os.path.exists(fitxer_excel):
+    print("❌ Error: Assegura't que els fitxers CSV i Excel són a la mateixa carpeta.")
+    sys.exit(1)
+
+try:
+    print("⏳ Llegint els usuaris actius del CSV...")
+    # Llegim el CSV (sabem que està separat per punt i coma)
+    df_csv = pd.read_csv(fitxer_csv, sep=';', encoding='utf-8')
+    
+    # Extraiem els correus de la columna 'Email_ID', els passem a minúscules i traiem espais en blanc
+    # per assegurar-nos que coincideixen perfectament
+    correus_actius = set(df_csv['Email_ID'].dropna().astype(str).str.lower().str.strip())
+    print(f"✅ S'han carregat {len(correus_actius)} correus únics del CSV.")
+
+    print("⏳ Processant l'Excel pestanya per pestanya...")
+    # Obrim l'Excel original i preparem el nou per escriure
+    excel_original = pd.ExcelFile(fitxer_excel)
+    
+    with pd.ExcelWriter(fitxer_resultat, engine='openpyxl') as writer:
+        for nom_pestanya in excel_original.sheet_names:
+            # Llegim la pestanya actual
+            df_pestanya = pd.read_excel(excel_original, sheet_name=nom_pestanya)
+            total_inicial = len(df_pestanya)
+            
+            # Normalitzem la columna 'email' de l'Excel per poder comparar-la
+            if 'email' in df_pestanya.columns:
+                correus_excel = df_pestanya['email'].astype(str).str.lower().str.strip()
+                
+                # Filtrem: ens quedem només amb les files on el correu estigui a la nostra llista d'actius
+                df_filtrat = df_pestanya[correus_excel.isin(correus_actius)]
+                total_final = len(df_filtrat)
+                
+                print(f"   👉 Pestanya '{nom_pestanya}': s'han mantingut {total_final} de {total_inicial} contactes.")
+            else:
+                print(f"   ⚠️ Avís: La pestanya '{nom_pestanya}' no té cap columna anomenada 'email'. Es deixa intacta.")
+                df_filtrat = df_pestanya
+                
+            # Guardem el resultat a la mateixa pestanya del nou fitxer
+            df_filtrat.to_excel(writer, sheet_name=nom_pestanya, index=False)
+
+    print(f"\n🎉 Procés completat amb èxit!")
+    print(f"📄 S'ha creat el fitxer amb els contactes filtrats: {fitxer_resultat}")
+
+except Exception as e:
+    print(f"❌ S'ha produït un error: {e}")

file-management/juntar_csv.py

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+import csv
+import glob
+import os
+import sys
+
+# 1. Comprovem si s'ha passat la ruta com a argument
+if len(sys.argv) < 2:
+    print("❌ Error: Has d'indicar la ruta de la carpeta.")
+    print("💡 Ús correcte: python juntar_csv.py /ruta/de/la/carpeta")
+    sys.exit(1)
+
+# 2. Agafem la ruta (el primer argument després del nom de l'script)
+carpeta_origen = sys.argv[1]
+
+# Netegem possibles cometes que la terminal hagi afegit
+carpeta_origen = carpeta_origen.strip("'").strip('"').strip()
+
+# 3. Comprovem que la carpeta existeix
+if not os.path.isdir(carpeta_origen):
+    print(f"❌ Error: La ruta '{carpeta_origen}' no és vàlida o no és una carpeta.")
+    sys.exit(1)
+
+print(f"📁 Cercant fitxers CSV a: {carpeta_origen}")
+
+ruta_cerca = os.path.join(carpeta_origen, "*.csv")
+fitxers_csv = glob.glob(ruta_cerca)
+
+# Definim el nom del fitxer final
+fitxer_resultat = os.path.join(carpeta_origen, "Newsletter_Combinat_Final.csv")
+
+if not fitxers_csv:
+    print("⚠️ No s'han trobat fitxers CSV a la carpeta indicada.")
+else:
+    # Filtrem per no incloure el fitxer resultat si ja existeix d'una execució anterior
+    fitxers_a_processar = [f for f in fitxers_csv if f != fitxer_resultat]
+    
+    if not fitxers_a_processar:
+        print("⚠️ Només s'ha trobat el fitxer combinat anterior. No hi ha res de nou per unir.")
+        sys.exit(0)
+        
+    print(f"🔄 S'han trobat {len(fitxers_a_processar)} fitxers. Processant...")
+    
+    # 4. Unifiquem els fitxers
+    with open(fitxer_resultat, 'w', newline='', encoding='utf-8') as sortida:
+        escrivent = csv.writer(sortida, delimiter=';')
+        
+        fitxers_processats = 0
+        for nom_fitxer in fitxers_a_processar:
+            with open(nom_fitxer, 'r', encoding='utf-8') as f:
+                lector = csv.reader(f, delimiter=';')
+                try:
+                    capcalera = next(lector)
+                except StopIteration:
+                    continue # Saltem el fitxer si està completament buit
+                
+                # Escrivim la capçalera només pel primer fitxer vàlid
+                if fitxers_processats == 0:
+                    escrivent.writerow(capcalera)
+                    
+                # Escrivim la resta de dades
+                for fila in lector:
+                    escrivent.writerow(fila)
+                    
+            fitxers_processats += 1
+            
+    print(f"✅ Èxit! S'han combinat {fitxers_processats} fitxers.")
+    print(f"📄 Fitxer creat a: {fitxer_resultat}")

file-management/mautic.py

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+import pandas as pd
+import csv
+
+def filtrar_i_consolidar_etiquetes(tags_str):
+    """Filtra i agrupa les etiquetes segons les regles de negoci."""
+    if pd.isna(tags_str) or str(tags_str).strip().lower() == 'nan':
+        return ''
+    
+    # 1. Separem les etiquetes i les netegem
+    llista_tags = [t.strip().lower() for t in str(tags_str).split(',')]
+    
+    # Utilitzem un 'set' per evitar etiquetes duplicades al final
+    tags_finals = set()
+    
+    for t in llista_tags:
+        # 2. Regla de conservació directa: test_, int_ i rrhh
+        if t.startswith('test_') or t.startswith('int_') or t == 'rrhh':
+            tags_finals.add(t)
+            continue
+            
+        # 3. Regles d'agrupació (l'ordre és important per als prefixos llargs)
+        if t.startswith('skupspo2-') or t.startswith('pspo2-'):
+            tags_finals.add('pspo2')
+        elif t.startswith('pspo-'):
+            tags_finals.add('pspo')
+        elif t.startswith('psm2-'):
+            tags_finals.add('psm2')
+        elif t.startswith('psm-'):
+            tags_finals.add('psm')
+        elif t.startswith('psux-') or t.startswith('psu-'):
+            tags_finals.add('psu')
+        elif t.startswith('sps-'):
+            tags_finals.add('sps')
+        elif t.startswith('safe-'):
+            tags_finals.add('safe-ls')
+        elif t.startswith('pal_ebm-'):
+            tags_finals.add('pal_ebm')
+        elif t.startswith('pal-'):
+            tags_finals.add('pal')
+    
+    # 4. Si tenim etiquetes vàlides, les ordenem, les unim amb | i hi posem cometes
+    if tags_finals:
+        # Ordenar-les (sorted) fa que el resultat sigui més fàcil de llegir al CSV
+        tags_units = '|'.join(sorted(list(tags_finals)))
+        return f'"{tags_units}"'
+    else:
+        return ''
+
+# --- INICI DEL PROCÉS ---
+
+# 1. Carregar el fitxer original
+df = pd.read_excel('contactes_mautic/Contactos_2602026_7881pax.xlsx')
+
+# 2. Seleccionar només les columnes que ens interessen
+columnes_mautic = ['email', 'nombre_x', 'apellidos_x', '*ciudad_x', '*pais_x', 'etiquetas_x']
+df_net = df[columnes_mautic].copy()
+
+# 3. Reanomenar les columnes perquè Mautic les auto-detecti
+df_net.rename(columns={
+    'nombre_x': 'firstname',
+    'apellidos_x': 'lastname',
+    '*ciudad_x': 'city',
+    '*pais_x': 'country',
+    'etiquetas_x': 'etiquetes'
+}, inplace=True)
+
+# 4. APLICAR EL FILTRE I LA CONSOLIDACIÓ
+df_net['etiquetes'] = df_net['etiquetes'].apply(filtrar_i_consolidar_etiquetes)
+
+# 5. Guardar com a CSV llest per importar
+df_net.to_csv('Contactes_Mautic_Consolidats.csv', index=False, encoding='utf-8', quoting=csv.QUOTE_NONE, escapechar='\\')
+
+print("✅ Fitxer preparat! Les etiquetes s'han filtrat i agrupat correctament.")

file-management/mautic_tags.py

@@ -0,0 +1,84 @@
+import pandas as pd
+import os
+import csv
+
+def simplificar_etiqueta(tag):
+    """Filtra i redueix les etiquetes a la seva essència."""
+    tag = tag.strip().lower()
+    
+    # 1. Traducció dels noms llargs oficials
+    if 'professional-scrum-master' in tag: return 'psm'
+    if 'professional-scrum-product-owner' in tag: return 'pspo'
+    if 'professional-scrum-developer' in tag: return 'psd'
+    if 'professional-agile-leadership' in tag: return 'pal'
+    
+    # 2. Protecció de nivells avançats (Molt important posar-ho abans que els normals)
+    if 'psm2' in tag or 'psm-2' in tag: return 'psm2'
+    if 'pspo2' in tag or 'pspo-2' in tag: return 'pspo2'
+    if 'pspo-a' in tag: return 'pspo-a'
+    
+    # 3. Agrupació per paraula clau (Si conté la paraula, s'assigna a l'etiqueta base)
+    if 'psm' in tag: return 'psm'
+    if 'pspo' in tag: return 'pspo'
+    if 'psu' in tag: return 'psu'
+    if 'psd' in tag: return 'psd'
+    if 'aps' in tag: return 'aps'
+    if 'apk' in tag: return 'apk'
+    if 'pal' in tag: return 'pal'
+    if 'sps' in tag: return 'sps'
+    
+    # 4. Altres agrupacions útils que he detectat a la teva llista
+    if 'okr' in tag: return 'okr'
+    if 'scrumday' in tag or 'sd20' in tag or 'sd21' in tag: return 'scrumday'
+    
+    # 5. Si no és cap de les importants, la deixem tal qual (però neta de test_)
+    if tag.startswith('test_'):
+        return tag.replace('test_', 'int_', 1)
+        
+    return tag
+
+# --- INICI DEL PROCÉS ---
+
+nom_fitxer = 'contactes_mautic/Contactos_2602026_7881pax.xlsx'
+print(f"Llegint el fitxer {nom_fitxer}...")
+df = pd.read_excel(nom_fitxer)
+
+columnes = {
+    'email': 'email',
+    'nombre_x': 'firstname',
+    'apellidos_x': 'lastname',
+    '*ciudad_x': 'city',
+    '*pais_x': 'country',
+    'etiquetas_x': 'tags'
+}
+df_net = df[list(columnes.keys())].rename(columns=columnes)
+df_net = df_net.dropna(subset=['email', 'tags'])
+
+carpeta_sortida = 'Mautic_CSVs_per_Tag'
+os.makedirs(carpeta_sortida, exist_ok=True)
+
+# Apliquem la nostra súper funció de simplificació
+df_net['tag_individual'] = df_net['tags'].apply(
+    lambda x: [simplificar_etiqueta(tag) for tag in str(x).split(',') if tag.strip()]
+)
+
+# Expandim i eliminem duplicats
+df_exploded = df_net.explode('tag_individual')
+df_exploded = df_exploded.drop_duplicates(subset=['email', 'tag_individual'])
+
+etiquetes_uniques = df_exploded['tag_individual'].unique()
+print(f"🎉 Màgia feta! Hem reduït centenars d'etiquetes a només {len(etiquetes_uniques)} úniques.")
+
+for tag in etiquetes_uniques:
+    df_tag = df_exploded[df_exploded['tag_individual'] == tag].copy()
+    
+    df_tag['tags'] = tag 
+    df_tag = df_tag.rename(columns={'tags': tag})
+    df_tag = df_tag.drop(columns=['tag_individual'])
+    
+    nom_tag_net = str(tag).replace(' ', '_').replace('/', '_').replace(':', '')
+    ruta_fitxer = os.path.join(carpeta_sortida, f"etiqueta_{nom_tag_net}.csv")
+    
+    df_tag.to_csv(ruta_fitxer, index=False, encoding='utf-8', sep=',', quoting=csv.QUOTE_ALL)
+
+print(f"✅ Tots els fitxers nets estan a la carpeta '{carpeta_sortida}'.")

file-management/nan-mautic.py

@@ -0,0 +1,17 @@
+import pandas as pd
+
+# 1. Carregar el fitxer original
+df = pd.read_excel('contactes_mautic/Contactos_2602026_7881pax.xlsx')
+
+# 2. Quedar-nos només amb els emails vàlids
+df_net = df.dropna(subset=['email'])[['email']].copy()
+
+# 3. Ordre d'esborrat múltiple
+# Afegim el signe '-' davant de l'etiqueta estranya i també del 'nan' normal
+# La 'r' al davant indica a Python que llegeixi les barres invertides literalment
+df_net['etiquetes'] = r'-\"-nan\"|-nan'
+
+# 4. Guardem el CSV de manera natural (sense forçar paràmetres d'escapament)
+df_net.to_csv('Neteja_Definitiva_Tags.csv', index=False, encoding='utf-8')
+
+print("✅ Fitxer preparat! Les etiquetes errònies s'han marcat per ser esborrades.")

file-management/netejar_desuscrits.py

@@ -0,0 +1,53 @@
+import csv
+import sys
+import os
+
+# Comprovem que s'ha passat el fitxer com a argument
+if len(sys.argv) < 2:
+    print("❌ Error: Has d'indicar la ruta del fitxer CSV.")
+    print("💡 Ús correcte: python netejar_desuscrits.py /ruta/al/Newsletter_Combinat_Final.csv")
+    sys.exit(1)
+
+fitxer_origen = sys.argv[1].strip("'").strip('"').strip()
+
+if not os.path.isfile(fitxer_origen):
+    print(f"❌ Error: No s'ha trobat el fitxer '{fitxer_origen}'.")
+    sys.exit(1)
+
+fitxer_desti = fitxer_origen.replace(".csv", "_Actius.csv")
+
+usuaris_eliminats = 0
+usuaris_actius = 0
+
+print(f"🔍 Analitzant el fitxer: {fitxer_origen}")
+
+with open(fitxer_origen, 'r', encoding='utf-8') as f_in, \
+     open(fitxer_desti, 'w', newline='', encoding='utf-8') as f_out:
+    
+    lector = csv.reader(f_in, delimiter=';')
+    escrivent = csv.writer(f_out, delimiter=';')
+    
+    # Llegim i escrivim la capçalera
+    capcalera = next(lector)
+    escrivent.writerow(capcalera)
+    
+    # Busquem l'índex de la columna de desuscripció
+    try:
+        index_unsub = capcalera.index("Unsubscribe_Date")
+    except ValueError:
+        print("❌ Error: No s'ha trobat la columna 'Unsubscribe_Date' al fitxer.")
+        sys.exit(1)
+        
+    # Filtrem les files
+    for fila in lector:
+        # Si la columna està buida, l'usuari és actiu
+        if len(fila) > index_unsub and not fila[index_unsub].strip():
+            escrivent.writerow(fila)
+            usuaris_actius += 1
+        else:
+            usuaris_eliminats += 1
+
+print("✅ Neteja completada amb èxit!")
+print(f"📉 Usuaris desuscrits eliminats: {usuaris_eliminats}")
+print(f"📈 Usuaris actius conservats: {usuaris_actius}")
+print(f"📄 Nou fitxer creat a: {fitxer_desti}")

file-management/netejar_excel.py

@@ -0,0 +1,32 @@
+import pandas as pd
+
+# 1. Definir los nombres de los archivos
+archivo_entrada = 'Contactos_2602026_totales.xlsx'
+archivo_salida = 'Contactos_2602026_Limpios.xlsx'
+
+print(f"Cargando el archivo: {archivo_entrada}...")
+
+# 2. Leer el archivo Excel
+# Asumimos que los datos están en la primera hoja (Sheet1)
+df = pd.read_excel(archivo_entrada)
+
+# Contar cuántos registros hay inicialmente
+total_inicial = len(df)
+print(f"Registros iniciales encontrados: {total_inicial}")
+
+# 3. Eliminar duplicados basados en la columna 'email'
+# keep='first' conserva la primera aparición del correo y elimina las siguientes
+df_limpio = df.drop_duplicates(subset=['email'], keep='first')
+
+# Contar cuántos registros quedaron y cuántos se eliminaron
+total_final = len(df_limpio)
+duplicados_eliminados = total_inicial - total_final
+
+print(f"Se han eliminado {duplicados_eliminados} contactos duplicados.")
+print(f"Registros finales únicos: {total_final}")
+
+# 4. Exportar el resultado a un nuevo archivo Excel
+print("Guardando el nuevo archivo limpio...")
+df_limpio.to_excel(archivo_salida, index=False)
+
+print(f"¡Proceso completado! Archivo guardado como: {archivo_salida}")

file-management/split_excel.py

@@ -0,0 +1,46 @@
+import pandas as pd
+import numpy as np
+import math
+
+# Load the Excel file
+file_name = 'Contactos_2602026_7881pax.xlsx'
+
+print("Llegint el fitxer Excel...")
+
+# --- CORRECCIÓ AQUÍ ---
+# Fem servir read_excel en lloc de read_csv
+df = pd.read_excel(file_name) 
+# ----------------------
+
+# Display head and info to understand the structure
+print(df.head())
+print(df.info())
+
+# Total number of rows
+total_rows = len(df)
+print(f"Total rows: {total_rows}")
+
+# Number of splits
+n = 6
+# Fem servir math.ceil o np.ceil per assegurar que no deixem files fora
+chunk_size = int(np.ceil(total_rows / n))
+
+# Split and save
+output_files = []
+print(f"Dividint en {n} parts...")
+
+for i in range(n):
+    start_row = i * chunk_size
+    end_row = min((i + 1) * chunk_size, total_rows)
+    
+    # Si per algun motiu start_row supera el total, parem
+    if start_row >= total_rows:
+        break
+        
+    chunk = df.iloc[start_row:end_row]
+    
+    output_filename = f'Contactos_linkedin_part_{i+1}.xlsx'
+    chunk.to_excel(output_filename, index=False)
+    output_files.append(output_filename)
+
+print(f"Files created: {output_files}")

file-management/teams.py

@@ -0,0 +1,104 @@
+import pandas as pd
+import glob
+import re
+import os
+import csv
+
+def extreure_minuts(temps_str):
+    """Converteix cadenes de text com '2h 15m', '45m' o '1h' a minuts totals."""
+    if pd.isna(temps_str):
+        return 0
+    temps_str = str(temps_str).lower()
+    hores = 0
+    minuts = 0
+    
+    match_h = re.search(r'(\d+)\s*h', temps_str)
+    if match_h:
+        hores = int(match_h.group(1))
+        
+    match_m = re.search(r'(\d+)\s*m', temps_str)
+    if match_m:
+        minuts = int(match_m.group(1))
+        
+    return (hores * 60) + minuts
+
+fitxers = glob.glob("*.csv")
+dades_alumnes = {}
+
+if not fitxers:
+    print("⚠️ No s'han trobat fitxers CSV a la carpeta actual.")
+else:
+    print(f"S'han trobat {len(fitxers)} fitxers. Processant dades...\n")
+
+for fitxer in fitxers:
+    try:
+        # 1. Obrim el fitxer manualment per buscar a quina fila comencen les dades
+        with open(fitxer, 'r', encoding='utf-16') as f:
+            linies = f.readlines()
+            
+        fila_capcalera = -1
+        separador = '\t'
+        
+        # Busquem la línia que conté "Nom" o "Nombre" o "Name"
+        for i, linia in enumerate(linies):
+            if 'Nom' in linia or 'Nombre' in linia or 'Name' in linia:
+                fila_capcalera = i
+                # Detectem si fa servir tabulacions o comes
+                if ',' in linia and '\t' not in linia:
+                    separador = ','
+                break
+                
+        if fila_capcalera == -1:
+            print(f"⚠️ Saltant '{fitxer}': No s'ha trobat cap fila amb la paraula 'Nom'.")
+            continue
+
+        # 2. Llegim el CSV dient-li exactament on comença
+        df = pd.read_csv(fitxer, sep=separador, encoding='utf-16', skiprows=fila_capcalera)
+        
+        # 3. Busquem les columnes dinàmicament
+        col_durada = next((col for col in df.columns if 'durada' in col.lower() or 'duración' in col.lower() or 'duration' in col.lower()), None)
+        col_nom = next((col for col in df.columns if 'nom' in col.lower() or 'nombre' in col.lower() or 'name' in col.lower()), None)
+
+        if not col_nom or not col_durada:
+            print(f"⚠️ Saltant '{fitxer}': Columnes invàlides. Trobades: {list(df.columns)}")
+            continue
+
+        for index, row in df.iterrows():
+            nom = row[col_nom]
+            if pd.isna(nom):
+                continue
+                
+            minuts = extreure_minuts(row[col_durada]) 
+            
+            # Apliquem la regla del 5 de febrer (límit de 205 minuts)
+            if "2-05-26" in fitxer and minuts > 205:
+                minuts = 205
+                
+            if nom in dades_alumnes:
+                dades_alumnes[nom] += minuts
+            else:
+                dades_alumnes[nom] = minuts
+                
+    except UnicodeError:
+        print(f"❌ Error de codificació al fitxer '{fitxer}'. Intenta obrir-lo i guardar-lo de nou.")
+    except Exception as e:
+        print(f"❌ Error processant el fitxer '{fitxer}': {e}")
+
+# 4. Resultats
+if dades_alumnes:
+    print("="*50)
+    print("📊 RESULTATS D'ASSISTÈNCIA (Mínim requerit: 1581 min)")
+    print("="*50)
+
+    for nom in sorted(dades_alumnes.keys()):
+        minuts_totals = dades_alumnes[nom]
+        
+        if minuts_totals >= 1581:
+            estat = "✅ Supera el 80%"
+        else:
+            estat = "❌ No arriba"
+            
+        h = minuts_totals // 60
+        m = minuts_totals % 60
+        
+        print(f"{nom}: {minuts_totals} minuts ({h}h {m}m) -> {estat}")

file-management/treure_etiquetes_mautic.py

@@ -0,0 +1,40 @@
+import pandas as pd
+import csv
+
+def preparar_etiquetes_per_esborrar(tags_str):
+    """Afegeix un '-' a cada etiqueta, les uneix amb | i les tanca entre cometes."""
+    # 1. Si la cel·la està buida, la deixem en blanc
+    if pd.isna(tags_str) or str(tags_str).strip().lower() == 'nan':
+        return ''
+    
+    # 2. Separem les etiquetes originals per coma i traiem espais
+    llista_tags = [t.strip() for t in str(tags_str).split(',')]
+    
+    # 3. Afegim el signe '-' davant de CADA etiqueta (excepte si està buida)
+    tags_per_esborrar = [f"-{t}" for t in llista_tags if t]
+    
+    # 4. Les unim amb | i hi afegim les cometes dobles manualment
+    if tags_per_esborrar:
+        tags_units = '|'.join(tags_per_esborrar)
+        return f'"{tags_units}"'
+    else:
+        return ''
+
+# --- INICI DEL PROCÉS ---
+
+# 1. Carregar el fitxer original
+df = pd.read_excel('contactes_mautic/Contactos_2602026_7881pax.xlsx')
+
+# 2. Seleccionar només l'email i les etiquetes
+df_esborrar = df[['email', 'etiquetas_x']].copy()
+
+# 3. Reanomenar la columna
+df_esborrar.rename(columns={'etiquetas_x': 'etiquetes'}, inplace=True)
+
+# 4. APLICAR LA TRANSFORMACIÓ
+df_esborrar['etiquetes'] = df_esborrar['etiquetes'].apply(preparar_etiquetes_per_esborrar)
+
+# 5. Guardar el CSV respectant les nostres cometes literals
+df_esborrar.to_csv('Contactes_Mautic_Esborrar_Etiquetes.csv', index=False, encoding='utf-8', quoting=csv.QUOTE_NONE, escapechar='\\')
+
+print("✅ Fitxer preparat! Les etiquetes tenen el '-' i estan entre cometes dobles.")

file-management/unificar_excels.py

@@ -0,0 +1,19 @@
+import pandas as pd
+
+# 1. Cargar el primer archivo (tiene encabezados)
+df1 = pd.read_excel('Contactos_linkedin_120126_agile_6589pax_filtrado.xlsx')
+
+# 2. Cargar el segundo archivo (sin encabezados, asignamos los principales)
+# Asumimos que las primeras 3 columnas son email, apellidos y nombre
+df2 = pd.read_excel('lista_contactos_brevo_20251023_1394pax_AGILE611.xlsx', header=None)
+df2.rename(columns={0: 'email', 1: 'apellidos_x', 2: 'nombre_x'}, inplace=True)
+
+# 3. Unir ambos archivos (apilarlos uno debajo del otro)
+df_final = pd.concat([df1, df2], ignore_index=True)
+
+# 4. Eliminar contactos duplicados basados en la columna 'email'
+df_final.drop_duplicates(subset=['email'], keep='first', inplace=True)
+
+# 5. Exportar el resultado a un nuevo archivo Excel
+df_final.to_excel('Contactos_Unificados_Agile611.xlsx', index=False)
+print("¡Archivo unificado creado con éxito!")

file-management/unir_excels_pestanyes.py

@@ -0,0 +1,40 @@
+import pandas as pd
+import os
+import sys
+
+print("📊 --- Unificador de fitxers Excel ---")
+
+# Definim els noms dels fitxers d'entrada i el de sortida
+fitxer1 = "Contactos_rrhh_040226.xlsx"
+fitxer2 = "Contactos_2602026_7881pax.xlsx"
+fitxer_resultat = "Contactos_Unificats.xlsx"
+
+# Comprovem que els fitxers existeixen a la carpeta actual
+if not os.path.exists(fitxer1):
+    print(f"❌ Error: No s'ha trobat el fitxer '{fitxer1}'.")
+    sys.exit(1)
+
+if not os.path.exists(fitxer2):
+    print(f"❌ Error: No s'ha trobat el fitxer '{fitxer2}'.")
+    sys.exit(1)
+
+print("⏳ Llegint els fitxers... (això pot trigar uns segons depenent de la mida)")
+
+try:
+    # Llegim els dos fitxers Excel
+    df1 = pd.read_excel(fitxer1)
+    df2 = pd.read_excel(fitxer2)
+    
+    # Creem el nou fitxer Excel amb múltiples pestanyes
+    with pd.ExcelWriter(fitxer_resultat, engine='openpyxl') as writer:
+        # Escrivim cada DataFrame en una pestanya diferent
+        df1.to_excel(writer, sheet_name='RRHH', index=False)
+        df2.to_excel(writer, sheet_name='Contactos_7881', index=False)
+        
+    print(f"✅ Procés completat amb èxit!")
+    print(f"📄 S'ha creat el fitxer: {fitxer_resultat}")
+    print("   - Pestanya 1: 'RRHH'")
+    print("   - Pestanya 2: 'Contactos_7881'")
+
+except Exception as e:
+    print(f"❌ S'ha produït un error durant el procés: {e}")

linkedin/linkedin-posts.py

@@ -0,0 +1,81 @@
+import os
+import requests
+from dotenv import load_dotenv
+
+# 1. Load the environment variables
+load_dotenv()
+
+ACCESS_TOKEN = os.getenv('LINKEDIN_ACCESS_TOKEN')
+ORGANIZATION_ID = os.getenv('LINKEDIN_ORG_ID')
+
+# LinkedIn requires a version header (Format: YYYYMM)
+API_VERSION = '202602' 
+
+def get_all_linkedin_posts(access_token, org_id):
+    """
+    Fetches ALL posts from a specific LinkedIn Organization Page using pagination.
+    """
+    if not access_token or not org_id:
+        print("🚨 Error: Missing credentials. Please check your .env file.")
+        return []
+
+    url = "https://api.linkedin.com/rest/posts"
+    
+    headers = {
+        "Authorization": f"Bearer {access_token}",
+        "LinkedIn-Version": API_VERSION,
+        "X-Restli-Protocol-Version": "2.0.0"
+    }
+    
+    all_posts = []
+    start = 0
+    count = 100 # Maximum allowed by LinkedIn per request
+    
+    print(f"📥 Starting to fetch posts for Organization ID: {org_id}...")
+    
+    while True:
+        params = {
+            "q": "author",
+            "author": f"urn:li:organization:{org_id}",
+            "count": count,
+            "start": start
+        }
+        
+        try:
+            response = requests.get(url, headers=headers, params=params)
+            response.raise_for_status()
+            
+            data = response.json()
+            elements = data.get('elements', [])
+            
+            # If no more posts are returned, we've reached the end!
+            if not elements:
+                break
+                
+            all_posts.extend(elements)
+            print(f"✅ Fetched posts {start + 1} to {start + len(elements)}...")
+            
+            # Increment the starting point for the next page
+            start += count
+            
+        except requests.exceptions.RequestException as e:
+            print(f"❌ Error fetching posts at offset {start}: {e}")
+            if response.text:
+                print(f"LinkedIn API Response: {response.text}")
+            break
+
+    print(f"\n🎉 Finished! Successfully retrieved a total of {len(all_posts)} posts.")
+    return all_posts
+
+# --- Run the application ---
+if __name__ == "__main__":
+    posts = get_all_linkedin_posts(ACCESS_TOKEN, ORGANIZATION_ID)
+    
+    # Print a quick preview of the first 3 posts
+    if posts:
+        print("\n--- Preview of latest 3 posts ---")
+        for post in posts[:3]:
+            # Safely extract the text content
+            text = post.get('commentary', {}).get('text', 'No text content')
+            print(f"ID: {post.get('id')}")
+            print(f"Content: {text[:100]}...\n")

media/audio-extractor.sh

@@ -0,0 +1,36 @@
+#!/bin/bash
+
+
+# Check if ffmpeg is installed
+if ! command -v ffmpeg &> /dev/null
+then
+    echo "ffmpeg could not be found. Please install ffmpeg first."
+    exit 1
+fi
+
+# Check for correct number of arguments
+if [ "$#" -ne 2 ]; then
+    echo "Usage: $0 <input_mp4_file> <output_mp3_file>"
+    exit 1
+fi
+
+# Input and output files
+INPUT_FILE="$1"
+OUTPUT_FILE="$2"
+
+# Check if the input file exists
+if [ ! -f "$INPUT_FILE" ]; then
+    echo "Input file '$INPUT_FILE' does not exist."
+    exit 1
+fi
+
+# Extract MP3 from MP4
+ffmpeg -i "$INPUT_FILE" -q:a 0 -map a "$OUTPUT_FILE"
+
+# Check if the operation was successful
+if [ $? -eq 0 ]; then
+    echo "MP3 file successfully created: $OUTPUT_FILE"
+else
+    echo "Failed to extract MP3 from $INPUT_FILE."
+    exit 1
+fi

media/convert_mp4_to_webm.sh

@@ -0,0 +1,45 @@
+#!/bin/bash
+
+# Function to convert MP4 to WebM
+convert_mp4_to_webm() {
+    input_file="$1"
+    output_file="$2"
+
+    # Check if input file exists
+    if [ ! -f "$input_file" ]; then
+        echo "Error: File '$input_file' does not exist."
+        exit 1
+    fi
+
+    # Check if the input file is an MP4
+    if [[ "$input_file" != *.mp4 ]]; then
+        echo "Error: Input file must be an MP4 file."
+        exit 1
+    fi
+
+    # Set output file name if not provided
+    if [ -z "$output_file" ]; then
+        output_file="${input_file%.mp4}.webm"
+    fi
+
+    # Convert the MP4 to WebM using ffmpeg
+    ffmpeg -i "$input_file" -c:v libvpx -c:a libvorbis "$output_file"
+
+    # Check if conversion was successful
+    if [ $? -eq 0 ]; then
+        echo "Successfully converted to '$output_file'."
+    else
+        echo "Error: Conversion failed."
+        exit 1
+    fi
+}
+
+# Check for input arguments
+if [ $# -lt 1 ]; then
+    echo "Usage: $0 <input_file> [output_file]"
+    exit 1
+fi
+
+# Call the function with arguments
+convert_mp4_to_webm "$1" "$2"
+

media/copy_cbr_files.sh

@@ -0,0 +1,12 @@
+#!/bin/bash
+
+# Destination directory for .cbr files
+DEST_DIR="cbr_files"
+
+# Create the destination directory if it doesn't exist
+mkdir -p "$DEST_DIR"
+
+# Find all .cbr files recursively in volum_* directories and copy them to cbr_files
+find volum_* -type f -name "*.cbr" -exec cp {} "$DEST_DIR" \;
+
+echo "All .cbr files have been copied to $DEST_DIR."

media/download_instagram_images.sh

@@ -0,0 +1,48 @@
+#!/bin/bash
+
+# Script to download images from an Instagram post
+# Requires: curl, jq
+
+# Function to display usage
+function usage() {
+    echo "Usage: $0 <instagram_post_url>"
+    exit 1
+}
+
+# Check if URL is provided
+if [ $# -ne 1 ]; then
+    usage
+fi
+
+# Instagram post URL
+POST_URL=$1
+
+# Fetch the HTML of the Instagram post
+echo "Fetching post data..."
+HTML=$(curl -s -L "$POST_URL")
+
+# Extract image URLs from the HTML
+echo "Extracting image URLs..."
+IMAGE_URLS=$(echo "$HTML" | sed -n 's/.*"display_url":"\([^"]*\)".*/\1/p')
+
+# Check if any image URLs were found
+if [ -z "$IMAGE_URLS" ]; then
+    echo "Failed to extract image URLs. Make sure the URL is valid and public."
+    exit 1
+fi
+
+# Create a directory to save images
+SAVE_DIR="instagram_images"
+mkdir -p "$SAVE_DIR"
+
+# Download each image
+echo "Downloading images..."
+COUNT=1
+for URL in $IMAGE_URLS; do
+    FILE_NAME="$SAVE_DIR/image_$COUNT.jpg"
+    curl -s -o "$FILE_NAME" "$URL"
+    echo "Downloaded: $FILE_NAME"
+    ((COUNT++))
+done
+
+echo "All images downloaded to $SAVE_DIR."

media/export_instagram_cookies.py

@@ -0,0 +1,22 @@
+# export_instagram_cookies.py
+import browser_cookie3
+
+cj = browser_cookie3.chrome(domain_name='instagram.com')
+
+with open('cookies.txt', 'w') as f:
+    f.write("# Netscape HTTP Cookie File\n")
+    f.write("# This file was generated by browser-cookie3\n")
+    f.write("# https://curl.se/docs/http-cookies.html\n\n")
+    for cookie in cj:
+        # domain, flag, path, secure, expiration, name, value
+        f.write(
+            f"{cookie.domain}\t"
+            f"{'TRUE' if cookie.domain.startswith('.') else 'FALSE'}\t"
+            f"{cookie.path}\t"
+            f"{'TRUE' if cookie.secure else 'FALSE'}\t"
+            f"{int(cookie.expires) if cookie.expires else 0}\t"
+            f"{cookie.name}\t"
+            f"{cookie.value}\n"
+        )
+print("cookies.txt exported!")
+# This script exports Instagram cookies from Chrome to a cookies.txt file.

media/image-instagram-downloader.sh

@@ -0,0 +1,57 @@
+#!/bin/bash
+
+# Directory to save downloaded images
+OUTPUT_DIR="./downloads"
+mkdir -p "$OUTPUT_DIR"
+
+# Instagram Full Image Downloader
+# Usage: ./image-instagram-downloader.sh <instagram_image_url>
+
+if [ $# -ne 1 ]; then
+    echo "Usage: $0 <instagram_image_url>"
+    exit 1
+fi
+
+URL="$1"
+
+# Fetch HTML content of the Instagram post
+HTML_DATA=$(curl -s "$URL")
+
+if [ -z "$HTML_DATA" ]; then
+    echo "Could not fetch HTML data."
+    exit 2
+fi
+
+# Extract JSON data containing the full-resolution image URL
+JSON_DATA=$(echo "$HTML_DATA" | grep -oE '<script type="application/ld\+json">[^<]+' | sed 's/<script type="application\/ld+json">//')
+
+if [ -z "$JSON_DATA" ]; then
+    echo "Could not find JSON data. Falling back to thumbnail."
+    # Extract thumbnail image URL
+    ENCODED_IMG_URL=$(echo "$HTML_DATA" | awk -F'<meta property="og:image" content="' '{print $2}' | awk -F'"' '{print $1}')
+    FULL_IMG_URL=$(echo "$ENCODED_IMG_URL" | sed 's/&amp;/\&/g')
+else
+    # Parse JSON data to extract full-resolution image URL
+    FULL_IMG_URL=$(echo "$JSON_DATA" | grep -oE '"url":"https:[^"]+' | sed 's/"url":"//')
+fi
+
+if [ -z "$FULL_IMG_URL" ]; then
+    echo "Could not find full image URL."
+    exit 3
+fi
+
+echo "Extracted Full Image URL: $FULL_IMG_URL"
+
+# Download the image
+FILENAME=$(basename "$FULL_IMG_URL" | cut -d'?' -f1)
+curl -L -A "Mozilla/5.0 (Windows NT 10.0; Win64; x64) AppleWebKit/537.36 (KHTML, like Gecko) Chrome/91.0.4472.124 Safari/537.36" "$FULL_IMG_URL" -o "$OUTPUT_DIR/$FILENAME"
+
+# Check if the file is a valid image
+FILE_TYPE=$(file "$OUTPUT_DIR/$FILENAME" | grep -oE 'image|HTML')
+
+if [[ "$FILE_TYPE" == "HTML" ]]; then
+    echo "Downloaded file is not an image. Please check the extracted URL."
+    exit 4
+fi
+
+echo "Downloaded: $OUTPUT_DIR/$FILENAME"

media/instagram-downloader.sh

@@ -0,0 +1,33 @@
+#!/bin/bash
+
+OUTPUT_DIR="./downloads"
+mkdir -p "$OUTPUT_DIR"
+
+if [ -z "$1" ]; then
+    echo "Usage: $0 <INSTAGRAM_REEL_URL>"
+    exit 1
+fi
+
+URL="$1"
+
+if ! command -v yt-dlp &> /dev/null; then
+    echo "yt-dlp is required. Install it with: pip install yt-dlp"
+    exit 2
+fi
+
+if ! command -v python3 &> /dev/null; then
+    echo "Python3 is required. Please install it."
+    exit 3
+fi
+
+# Export cookies.txt using Python script
+python3 export_instagram_cookies.py
+if [ ! -f cookies.txt ]; then
+    echo "Failed to export cookies.txt. Aborting."
+    exit 4
+fi
+
+# Use cookies.txt to handle private reels
+yt-dlp --cookies cookies.txt "$URL" -o "$OUTPUT_DIR/%(title)s.%(ext)s"
+echo "Download completed. Files are saved in $OUTPUT_DIR"
+#rm cookies.txt

media/spotify-rss.py

@@ -0,0 +1,61 @@
+import spotipy
+from spotipy.oauth2 import SpotifyClientCredentials
+import requests
+import urllib.parse
+
+# --- Configuration ---
+# Replace these with your actual Spotify Developer credentials
+SPOTIPY_CLIENT_ID = '3756ae92386d45e9971aa03d2f4b1eca'
+SPOTIPY_CLIENT_SECRET = '6c8ea8c409d944cc895571f3f49985df'
+
+# The ID from your link: https://open.spotify.com/show/13Gs651PIKKI7zRF0p3PcJ
+SHOW_ID = '13Gs651PIKKI7zRF0p3PcJ'
+
+def find_real_rss_feed():
+    # Step 1: Authenticate with Spotify
+    auth_manager = SpotifyClientCredentials(
+        client_id=SPOTIPY_CLIENT_ID, 
+        client_secret=SPOTIPY_CLIENT_SECRET
+    )
+    sp = spotipy.Spotify(auth_manager=auth_manager)
+
+    # Step 2: Get the Show Name from Spotify
+    print(f"Fetching details for Spotify Show ID: {SHOW_ID}...")
+    try:
+        show = sp.show(SHOW_ID)
+        show_name = show['name']
+        publisher = show['publisher']
+        print(f"Found Show: '{show_name}' by {publisher}")
+    except Exception as e:
+        print(f"Error fetching from Spotify: {e}")
+        return
+
+    # Step 3: Search the iTunes API for that Show Name
+    print("\nSearching public directories (iTunes) for the real RSS feed...")
+    # We encode the name so it can be safely used in a URL (e.g., spaces become %20)
+    encoded_name = urllib.parse.quote(show_name)
+    itunes_api_url = f"https://itunes.apple.com/search?term={encoded_name}&entity=podcast&limit=3"
+    
+    try:
+        response = requests.get(itunes_api_url)
+        data = response.json()
+        
+        if data['resultCount'] > 0:
+            # Grab the first result's RSS feed URL
+            # We check the first few results to ensure the author matches, but usually the first is correct
+            real_rss_url = data['results'][0].get('feedUrl')
+            
+            print("\n✅ SUCCESS! Found the public RSS feed:")
+            print("-" * 50)
+            print(real_rss_url)
+            print("-" * 50)
+            print("You can copy and paste this URL directly into Apple Podcasts, Pocket Casts, or any standard RSS reader. It contains all the real .mp3 files!")
+        else:
+            print("\n❌ Could not find this show in public directories.")
+            print("This usually means the podcast is a 'Spotify Exclusive' and does not have a public RSS feed.")
+            
+    except Exception as e:
+        print(f"Error searching iTunes: {e}")
+
+if __name__ == '__main__':
+    find_real_rss_feed()

media/url-video-downloader.sh

@@ -0,0 +1,33 @@
+#!/bin/bash
+
+# Script to download videos from URLs shared on Bluesky
+# Requires yt-dlp and ffmpeg to be installed
+
+# Directory to save downloaded videos
+OUTPUT_DIR="./downloads"
+mkdir -p "$OUTPUT_DIR"
+
+# Check if yt-dlp is installed
+if ! command -v yt-dlp &>/dev/null; then
+    echo "yt-dlp is not installed. Please install it and try again."
+    exit 1
+fi
+
+# Check if the URL is passed as an argument
+if [[ -z "$1" ]]; then
+    echo "No URL provided as an argument. Usage: ./script.sh <video_url>"
+    exit 1
+fi
+
+VIDEO_URL="$1"
+
+# Download the video with a shortened filename (using video ID)
+echo "Downloading video from $VIDEO_URL..."
+yt-dlp -k -o "$OUTPUT_DIR/%(id)s.%(ext)s" "$VIDEO_URL"
+
+if [[ $? -eq 0 ]]; then
+    echo "Video downloaded successfully to $OUTPUT_DIR."
+else
+    echo "Failed to download the video. Please check the URL and try again."
+    exit 1
+fi

media/video-downloader.sh

@@ -0,0 +1,34 @@
+#!/bin/bash
+
+# Script to download videos from URLs shared on Bluesky
+# Requires yt-dlp and ffmpeg to be installed
+
+# Directory to save downloaded videos
+OUTPUT_DIR="./downloads"
+mkdir -p "$OUTPUT_DIR"
+
+# Check if yt-dlp is installed
+if ! command -v yt-dlp &>/dev/null; then
+    echo "yt-dlp is not installed. Please install it and try again."
+    exit 1
+fi
+
+# Prompt for the video URL
+read -p "Enter the video URL: " VIDEO_URL
+
+# Validate the URL
+if [[ -z "$VIDEO_URL" ]]; then
+    echo "No URL entered. Exiting."
+    exit 1
+fi
+
+# Download the video
+echo "Downloading video from $VIDEO_URL..."
+yt-dlp -o "$OUTPUT_DIR/%(title)s.%(ext)s" "$VIDEO_URL"
+
+if [[ $? -eq 0 ]]; then
+    echo "Video downloaded successfully to $OUTPUT_DIR."
+else
+    echo "Failed to download the video. Please check the URL and try again."
+    exit 1
+fi

media/webm-to-mp4-converter.sh

@@ -0,0 +1,44 @@
+#!/bin/bash
+
+# Script to convert a .webm file to .mp4 using ffmpeg
+
+# Check if ffmpeg is installed
+if ! command -v ffmpeg &> /dev/null
+then
+    echo "ffmpeg could not be found. Please install ffmpeg first."
+    exit 1
+fi
+
+# Check if input file is provided
+if [ "$#" -lt 1 ]; then
+    echo "Usage: $0 input_file.webm [output_file.mp4]"
+    exit 1
+fi
+
+# Input file
+input_file="$1"
+
+# Check if the input file exists
+if [ ! -f "$input_file" ]; then
+    echo "Input file '$input_file' not found."
+    exit 1
+fi
+
+# Set output file name
+if [ "$#" -ge 2 ]; then
+    output_file="$2"
+else
+    output_file="${input_file%.*}.mp4"
+fi
+
+# Convert .webm to .mp4 using ffmpeg
+ffmpeg -i "$input_file" -c:v libx264 -preset slow -crf 23 -c:a aac "$output_file"
+
+# Check if conversion was successful
+if [ $? -eq 0 ]; then
+    echo "Conversion successful. Output file: $output_file"
+else
+    echo "Conversion failed."
+    exit 1
+fi
+

media/zip_cbr_files.sh

@@ -0,0 +1,13 @@
+#!/bin/bash
+
+# Loop over a range of episode numbers
+for i in {1..27}; do
+    # Format the episode number with leading zeros if needed
+    episode_number=$(printf $i)
+    echo $episode_number
+    zip capitol_${episode_number}.cbr volume_1_episode_${episode_number}_*.jpg
+    echo "Created capitol_${episode_number}.cbr"
+done
+
+echo "All .cbr files have been created."
+

odilo/biblio_odilo.py

@@ -0,0 +1,31 @@
+import requests
+
+# 1. Definim les capçaleres
+headers = {
+    'Content-Type': 'application/json',
+    'User-Agent': 'ie',
+    'Host': 'odiloid.odilo.us'
+}
+
+url_api = 'https://odiloid.odilo.us/ClientId'
+
+try:
+    # 2. Fem la petició
+    print("⏳ Obtenint dades del servidor...")
+    response = requests.get(url_api, headers=headers)
+    response.raise_for_status()
+    
+    # 3. Convertim a JSON (llista de diccionaris)
+    bibliolist_response = response.json()
+    
+    # 4. Filtrem només les URLs
+    llista_urls = [biblio['url'] for biblio in bibliolist_response if 'url' in biblio]
+    
+    # 5. Mostrem el resultat per pantalla
+    print(f"✅ S'han trobat {len(llista_urls)} biblioteques. Aquí tens les URLs:\n")
+    
+    for url in llista_urls:
+        print(url)
+
+except requests.exceptions.RequestException as e:
+    print(f"❌ Hi ha hagut un error amb la petició: {e}")

odilo/recollir_epubs.sh

@@ -0,0 +1,21 @@
+#!/bin/bash
+
+# Comprovem que s'han passat exactament 2 paràmetres
+if [ "$#" -ne 2 ]; then
+    echo "❌ Error: Falten paràmetres."
+    echo "💡 Ús correcte: $0 <carpeta_origen> <carpeta_desti>"
+    exit 1
+fi
+
+# Assignem els paràmetres a les variables
+origen="$1"
+desti="$2"
+
+# Creem la carpeta destí si no existeix
+mkdir -p "$desti"
+
+# Executem la cerca i còpia
+echo "Cercant i copiant els arxius .epub..."
+find "$origen" -type f -name "*.epub" -exec cp {} "$desti" \;
+
+echo "✅ Procés completat! Tots els epubs estan a $desti"

outlook/email_login.py

@@ -0,0 +1,43 @@
+import imaplib
+
+# ==========================================
+# 1. CONFIGURATION
+# ==========================================
+EMAIL_ADDRESS = "marti@agile611.com"
+
+# ⚠️ Insert your generated App Password here (no spaces)
+PASSWORD = "fcztyfdwpfrgqjgl"  # Replace with your actual App Password
+
+IMAP_SERVER = "outlook.office365.com"
+IMAP_PORT = 993
+
+def test_app_password_login():
+    print(f"🔌 Connecting to {IMAP_SERVER} on port {IMAP_PORT}...")
+    
+    try:
+        # Connect to the server using SSL/TLS encryption
+        mail = imaplib.IMAP4_SSL(IMAP_SERVER, IMAP_PORT)
+        
+        # Attempt plaintext login using the App Password
+        print("🔐 Attempting login with App Password...")
+        mail.login(EMAIL_ADDRESS, PASSWORD)
+        
+        print("✅ Success! The App Password worked perfectly.")
+        
+        # Select the inbox to verify we can read data
+        status, messages = mail.select("INBOX")
+        if status == "OK":
+            message_count = messages[0].decode('utf-8')
+            print(f"📥 INBOX selected successfully. Total messages: {message_count}")
+        
+        # Safely log out
+        mail.logout()
+        print("👋 Logged out successfully.")
+        
+    except imaplib.IMAP4.error as e:
+        print("\n❌ Login failed!")
+        print(f"Error details: {e}")
+        print("\n⚠️ Note: If you see 'BasicAuthBlocked' again, your organization's global Azure settings have completely disabled basic authentication, overriding the App Password.")
+
+if __name__ == "__main__":
+    test_app_password_login()

outlook/get_token.py

@@ -0,0 +1,177 @@
+import msal
+import imaplib
+import os
+import csv
+import re
+import time
+import socket
+
+# 🚨 Force Python to drop the connection if Microsoft stops responding (tarpitting)
+socket.setdefaulttimeout(30)
+
+# ==========================================
+# 1. CONFIGURATION
+# ==========================================
+CLIENT_ID = "05332268-8149-449f-a1f8-1efadd17166f"  
+EMAIL_ADDRESS = "guillem@agile611.com"  
+
+AUTHORITY = "https://login.microsoftonline.com/884a3c53-8a5a-4d79-b0e0-a62ab5a794a1"
+# MSAL automatically requests offline_access, so we only list the IMAP scope here
+SCOPES = ["https://outlook.office.com/IMAP.AccessAsUser.All"]
+
+# ==========================================
+# 2. HELPER FUNCTION: GENERATE CSV
+# ==========================================
+def generate_user_csv(email_address, first_name="Guillem", last_name="Hernandez Sola"):
+    username = email_address.split("@")[0]
+    headers = [
+        "originUsername", "targetUsername", "password", "pop3enabled", 
+        "pop3password", "aliases", "forwards", "filters", 
+        "forename", "surname", "mailboxStatus"
+    ]
+    row_data = {
+        "originUsername": username, "targetUsername": username,
+        "password": "TempWebmailPassword123!", "pop3enabled": "true",
+        "pop3password": "", "aliases": "", "forwards": "", "filters": "",
+        "forename": first_name, "surname": last_name, "mailboxStatus": "premium"
+    }
+    csv_filename = f"{username}_import.csv"
+    with open(csv_filename, mode="w", newline="", encoding="utf-8") as file:
+        writer = csv.DictWriter(file, fieldnames=headers, delimiter=";")
+        writer.writeheader()
+        writer.writerow(row_data)
+    print(f"📝 Migration CSV generated: {csv_filename}")
+
+# ==========================================
+# 3. TOKEN & CONNECTION MANAGERS
+# ==========================================
+def get_valid_token(app):
+    """Checks the cache for a valid token, refreshes silently if needed, or prompts user."""
+    accounts = app.get_accounts()
+    if accounts:
+        result = app.acquire_token_silent(SCOPES, account=accounts[0])
+        if result and "access_token" in result:
+            return result["access_token"]
+
+    flow = app.initiate_device_flow(scopes=SCOPES)
+    if "user_code" not in flow:
+        raise ValueError("Failed to create device flow. Check your Client ID and Azure settings.")
+
+    print("\n🚨 ACTION REQUIRED 🚨")
+    print(flow["message"])
+    print("⏳ Waiting for browser authentication...")
+    
+    result = app.acquire_token_by_device_flow(flow)
+    if "access_token" not in result:
+        raise Exception(f"Failed to get token: {result.get('error_description')}")
+        
+    return result["access_token"]
+
+def connect_to_imap(email, token):
+    """Creates a fresh, authenticated connection to the IMAP server."""
+    auth_string = f"user={email}\x01auth=Bearer {token}\x01\x01"
+    mail = imaplib.IMAP4_SSL("outlook.office365.com", 993)
+    mail.authenticate("XOAUTH2", lambda x: auth_string.encode("utf-8"))
+    return mail
+
+# ==========================================
+# 4. MAIN EXECUTION
+# ==========================================
+def main():
+    print("🔄 Initializing Microsoft Authentication...")
+    app = msal.PublicClientApplication(CLIENT_ID, authority=AUTHORITY)
+    
+    try:
+        access_token = get_valid_token(app)
+        print("\n✅ Access Token Acquired Successfully!")
+        
+        print("\n🔌 Connecting to Outlook IMAP server...")
+        mail = connect_to_imap(EMAIL_ADDRESS, access_token)
+        print("✅ Successfully logged into IMAP via OAuth2!")
+    except Exception as e:
+        print(f"\n❌ Authentication failed: {e}")
+        return
+
+    try:
+        username = EMAIL_ADDRESS.split("@")[0]
+        base_download_dir = f"downloaded_emails_{username}"
+        os.makedirs(base_download_dir, exist_ok=True)
+
+        status, folders = mail.list()
+        if status == "OK":
+            print(f"📂 Found {len(folders)} folders. Starting full account backup...\n")
+            
+            for folder_data in folders:
+                folder_string = folder_data.decode('utf-8')
+                
+                if "\\Noselect" in folder_string:
+                    continue
+                
+                match = re.search(r'\"([^\"]+)\"$', folder_string)
+                folder_name = match.group(1) if match else folder_string.split()[-1].strip('"')
+                
+                print(f"📁 Scanning folder: {folder_name}")
+                
+                status, _ = mail.select(f'"{folder_name}"', readonly=True)
+                if status != "OK":
+                    print(f"   ⚠️ Could not open {folder_name}. Skipping.")
+                    continue
+                
+                status, data = mail.search(None, "ALL")
+                email_ids = data[0].split()
+                
+                if not email_ids:
+                    print("   ↳ Folder is empty.")
+                    continue
+                
+                print(f"   ↳ Found {len(email_ids)} emails. Downloading...")
+                
+                safe_folder_name = "".join([c for c in folder_name if c.isalnum() or c in (' ', '-', '_')]).strip()
+                folder_dir = os.path.join(base_download_dir, safe_folder_name)
+                os.makedirs(folder_dir, exist_ok=True)
+                
+                # Download loop with Reconnect & Timeout Logic
+                for e_id in email_ids:
+                    file_path = os.path.join(folder_dir, f"email_{e_id.decode('utf-8')}.eml")
+                    
+                    # 🚀 SKIP EXISTING: Don't re-download emails we already have!
+                    if os.path.exists(file_path):
+                        continue
+                    
+                    success = False
+                    while not success:
+                        try:
+                            status, msg_data = mail.fetch(e_id, "(RFC822)")
+                            for response_part in msg_data:
+                                if isinstance(response_part, tuple):
+                                    raw_email = response_part[1]
+                                    with open(file_path, "wb") as f:
+                                        f.write(raw_email)
+                            success = True
+                            
+                        # Catch token expiration, forced disconnects, AND silent timeouts
+                        except (imaplib.IMAP4.abort, imaplib.IMAP4.error, ConnectionResetError, socket.timeout, TimeoutError) as e:
+                            print(f"\n   ⚠️ Connection lost or timed out. Refreshing token and reconnecting...")
+                            try:
+                                access_token = get_valid_token(app)
+                                mail = connect_to_imap(EMAIL_ADDRESS, access_token)
+                                mail.select(f'"{folder_name}"', readonly=True) 
+                                print("   ✅ Reconnected! Resuming download...")
+                            except Exception as reconnect_error:
+                                print(f"   ❌ Reconnection failed: {reconnect_error}. Retrying in 5 seconds...")
+                                time.sleep(5)
+                                
+            print(f"\n🎉 All folders successfully downloaded to '{base_download_dir}'!")
+        
+        mail.logout()
+        print("👋 Logged out successfully.\n")
+
+        print("⚙️ Generating configuration files...")
+        generate_user_csv(EMAIL_ADDRESS)
+        print("🎉 Migration prep complete!")
+
+    except Exception as e:
+        print(f"\n❌ A critical error occurred: {e}")
+
+if __name__ == "__main__":
+    main()

outlook/marti.py

@@ -0,0 +1,142 @@
+import msal
+import imaplib
+import os
+import csv
+import re  # Added for parsing folder names safely
+
+# ==========================================
+# 1. CONFIGURATION
+# ==========================================
+CLIENT_ID = "05332268-8149-449f-a1f8-1efadd17166f"  
+EMAIL_ADDRESS = "marti@agile611.com"  
+
+AUTHORITY = "https://login.microsoftonline.com/884a3c53-8a5a-4d79-b0e0-a62ab5a794a1"
+SCOPES = ["https://outlook.office.com/IMAP.AccessAsUser.All"]
+
+# ==========================================
+# 2. HELPER FUNCTION: GENERATE CSV
+# ==========================================
+def generate_user_csv(email_address, first_name="Marti", last_name="Montfort Ruiz"):
+    username = email_address.split("@")[0]
+    headers = [
+        "originUsername", "targetUsername", "password", "pop3enabled", 
+        "pop3password", "aliases", "forwards", "filters", 
+        "forename", "surname", "mailboxStatus"
+    ]
+    row_data = {
+        "originUsername": username, "targetUsername": username,
+        "password": "TempWebmailPassword123!", "pop3enabled": "true",
+        "pop3password": "", "aliases": "", "forwards": "", "filters": "",
+        "forename": first_name, "surname": last_name, "mailboxStatus": "premium"
+    }
+    csv_filename = f"{username}_import.csv"
+    with open(csv_filename, mode="w", newline="", encoding="utf-8") as file:
+        writer = csv.DictWriter(file, fieldnames=headers, delimiter=";")
+        writer.writeheader()
+        writer.writerow(row_data)
+    print(f"📝 Migration CSV generated: {csv_filename}")
+
+def main():
+    # ==========================================
+    # 3. GETTING THE OAUTH2 TOKEN
+    # ==========================================
+    print("🔄 Initializing Microsoft Authentication...")
+    app = msal.PublicClientApplication(CLIENT_ID, authority=AUTHORITY)
+    flow = app.initiate_device_flow(scopes=SCOPES)
+    
+    if "user_code" not in flow:
+        raise ValueError("Failed to create device flow. Check your Client ID and Azure settings.")
+
+    print("\n🚨 ACTION REQUIRED 🚨")
+    print(flow["message"])
+    print("\n⏳ Waiting for browser authentication...")
+    
+    result = app.acquire_token_by_device_flow(flow)
+    if "access_token" not in result:
+        print("\n❌ Failed to get token:", result.get("error_description"))
+        return
+
+    access_token = result["access_token"]
+    print("\n✅ Access Token Acquired Successfully!")
+
+    # ==========================================
+    # 4. CONNECTING TO IMAP & DOWNLOADING ALL FOLDERS
+    # ==========================================
+    print("\n🔌 Connecting to Outlook IMAP server...")
+    auth_string = f"user={EMAIL_ADDRESS}\x01auth=Bearer {access_token}\x01\x01"
+
+    try:
+        mail = imaplib.IMAP4_SSL("outlook.office365.com", 993)
+        mail.authenticate("XOAUTH2", lambda x: auth_string.encode("utf-8"))
+        print("✅ Successfully logged into IMAP via OAuth2!")
+        
+        # Base directory for this user
+        username = EMAIL_ADDRESS.split("@")[0]
+        base_download_dir = f"downloaded_emails_{username}"
+        os.makedirs(base_download_dir, exist_ok=True)
+
+        # Fetch all folders in the mailbox
+        status, folders = mail.list()
+        if status == "OK":
+            print(f"📂 Found {len(folders)} folders. Starting full account backup...\n")
+            
+            for folder_data in folders:
+                folder_string = folder_data.decode('utf-8')
+                
+                # Skip unselectable folders (like root directory markers)
+                if "\\Noselect" in folder_string:
+                    continue
+                
+                # Safely extract the folder name (handles spaces and quotes)
+                match = re.search(r'\"([^\"]+)\"$', folder_string)
+                folder_name = match.group(1) if match else folder_string.split()[-1].strip('"')
+                
+                print(f"📁 Scanning folder: {folder_name}")
+                
+                # Select the folder (readonly to prevent accidental modifications)
+                status, _ = mail.select(f'"{folder_name}"', readonly=True)
+                if status != "OK":
+                    print(f"   ⚠️ Could not open {folder_name}. Skipping.")
+                    continue
+                
+                status, data = mail.search(None, "ALL")
+                email_ids = data[0].split()
+                
+                if not email_ids:
+                    print("   ↳ Folder is empty.")
+                    continue
+                
+                print(f"   ↳ Found {len(email_ids)} emails. Downloading...")
+                
+                # Create a safe subfolder name for the OS
+                safe_folder_name = "".join([c for c in folder_name if c.isalnum() or c in (' ', '-', '_')]).strip()
+                folder_dir = os.path.join(base_download_dir, safe_folder_name)
+                os.makedirs(folder_dir, exist_ok=True)
+                
+                # Download each email into its respective folder
+                for e_id in email_ids:
+                    status, msg_data = mail.fetch(e_id, "(RFC822)")
+                    for response_part in msg_data:
+                        if isinstance(response_part, tuple):
+                            raw_email = response_part[1]
+                            file_path = os.path.join(folder_dir, f"email_{e_id.decode('utf-8')}.eml")
+                            with open(file_path, "wb") as f:
+                                f.write(raw_email)
+                                
+            print(f"\n🎉 All folders successfully downloaded to '{base_download_dir}'!")
+        
+        mail.logout()
+        print("👋 Logged out successfully.\n")
+
+        # ==========================================
+        # 5. GENERATE THE CSV
+        # ==========================================
+        print("⚙️ Generating configuration files...")
+        generate_user_csv(EMAIL_ADDRESS)
+        print("🎉 Migration prep complete!")
+
+    except imaplib.IMAP4.error as e:
+        print(f"\n❌ IMAP Authentication failed: {e}")
+
+if __name__ == "__main__":
+    main()

pdfs/split_pdf_pages.sh

@@ -0,0 +1,33 @@
+#!/bin/bash
+
+# Check if the input file is provided
+if [ "$#" -ne 1 ]; then
+    echo "Usage: $0 input.pdf"
+    exit 1
+fi
+
+# Input PDF file
+input_pdf="$1"
+
+# Check if the file exists
+if [ ! -f "$input_pdf" ]; then
+    echo "Error: File '$input_pdf' not found."
+    exit 1
+fi
+
+# Create an output directory
+output_dir="${input_pdf%.pdf}_pages"
+mkdir -p "$output_dir"
+
+# Get the number of pages in the PDF
+total_pages=$(pdftk "$input_pdf" dump_data | grep NumberOfPages | awk '{print $2}')
+
+# Split each page into a separate PDF
+echo "Splitting '$input_pdf' into separate pages..."
+for ((i=1; i<=total_pages; i++)); do
+    output_file="$output_dir/page_$i.pdf"
+    pdftk "$input_pdf" cat "$i" output "$output_file"
+    echo "Created $output_file"
+done
+
+echo "All pages have been split and saved in '$output_dir'."

replace_remove/fix-all-special-characters.sh

@@ -0,0 +1,7 @@
+#!/bin/bash
+
+./remove_parentheses_files_folders.sh $1
+./replace_hyphen_with_underscores.sh $1
+./replace_spaces_with_underscores.sh $1
+./replace_under_hyphen_under_with_underscores.sh $1
+./replace_triple_with_underscores.sh $1

replace_remove/remove_parentheses_files_folders.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename files and folders recursively
+rename_files_and_folders() {
+    find "$1" -depth | while read -r item; do
+        # Remove parentheses from names
+        new_item=$(echo "$item" | sed 's/[()]//g')
+        
+        # Rename item if the new name is different
+        if [ "$item" != "$new_item" ]; then
+            mv "$item" "$new_item"
+            echo "Renamed: $item -> $new_item"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+rename_files_and_folders "$start_dir"
+
+echo "Done!"

replace_remove/remove_parentheses_folders.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename folders recursively
+rename_folders() {
+    find "$1" -depth -type d | while read -r dir; do
+        # Remove parentheses from folder names
+        new_dir=$(echo "$dir" | sed 's/[()]//g')
+        
+        # Rename folder if the new name is different
+        if [ "$dir" != "$new_dir" ]; then
+            mv "$dir" "$new_dir"
+            echo "Renamed: $dir -> $new_dir"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+rename_folders "$start_dir"
+
+echo "Done!"

replace_remove/replace_hyphen_with_underscores.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename files and folders recursively
+replace_spaces_with_underscores() {
+    find "$1" -depth | while read -r item; do
+        # Replace spaces with underscores in names
+        new_item=$(echo "$item" | sed 's/-/_/g')
+        
+        # Rename item if the new name is different
+        if [ "$item" != "$new_item" ]; then
+            mv "$item" "$new_item"
+            echo "Renamed: $item -> $new_item"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+replace_spaces_with_underscores "$start_dir"
+
+echo "Done!"

replace_remove/replace_spaces_with_underscores.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename files and folders recursively
+replace_spaces_with_underscores() {
+    find "$1" -depth | while read -r item; do
+        # Replace spaces with underscores in names
+        new_item=$(echo "$item" | sed 's/ /_/g')
+        
+        # Rename item if the new name is different
+        if [ "$item" != "$new_item" ]; then
+            mv "$item" "$new_item"
+            echo "Renamed: $item -> $new_item"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+replace_spaces_with_underscores "$start_dir"
+
+echo "Done!"

replace_remove/replace_triple_with_underscores.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename files and folders recursively
+replace_spaces_with_underscores() {
+    find "$1" -depth | while read -r item; do
+        # Replace spaces with underscores in names
+        new_item=$(echo "$item" | sed 's/___/_/g')
+        
+        # Rename item if the new name is different
+        if [ "$item" != "$new_item" ]; then
+            mv "$item" "$new_item"
+            echo "Renamed: $item -> $new_item"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+replace_spaces_with_underscores "$start_dir"
+
+echo "Done!"

replace_remove/replace_under_hyphen_under_with_underscores.sh

@@ -0,0 +1,23 @@
+#!/bin/bash
+
+# Function to rename files and folders recursively
+replace_spaces_with_underscores() {
+    find "$1" -depth | while read -r item; do
+        # Replace spaces with underscores in names
+        new_item=$(echo "$item" | sed 's/_-_/_/g')
+        
+        # Rename item if the new name is different
+        if [ "$item" != "$new_item" ]; then
+            mv "$item" "$new_item"
+            echo "Renamed: $item -> $new_item"
+        fi
+    done
+}
+
+# Starting directory (default is current directory if no argument is provided)
+start_dir="${1:-.}"
+
+echo "Starting from directory: $start_dir"
+replace_spaces_with_underscores "$start_dir"
+
+echo "Done!"

wordpress/export-articles.py

@@ -0,0 +1,29 @@
+import requests
+import csv
+
+posts = []
+page = 1
+
+while True:
+    r = requests.get(f"https://www.agile611.com/wp-json/wp/v2/posts?per_page=100&page={page}")
+    r.encoding = 'utf-8'
+    data = r.json()
+    if not isinstance(data, list) or not data:
+        break
+    for post in data:
+        if isinstance(post, dict) and 'title' in post and isinstance(post['title'], dict):
+            title = post['title']['rendered']
+        else:
+            title = str(post.get('title', ''))
+        title = title.replace(',', '')  # Remove commas from the title
+        date = post.get('date', '')
+        link = post.get('link', '')
+        posts.append([title, date, link])
+    page += 1
+
+with open('agile611_posts.csv', 'w', newline='', encoding='utf-8-sig') as f:
+    writer = csv.writer(f)
+    writer.writerow(['Title', 'Date', 'URL'])
+    writer.writerows(posts)
+
+print(f"Saved {len(posts)} posts to agile611_posts.csv")