diff --git a/snippets/assignClouds.py b/snippets/assignClouds.py
deleted file mode 100644
index 4eaf9553..00000000
--- a/snippets/assignClouds.py
+++ /dev/null
@@ -1,37 +0,0 @@
-import os
-import random
-from supabase import create_client, Client
-
-# Set up Supabase client
-supabase_url = 'https://hlufptwhzkpkkjztimzo.supabase.co'
-supabase_key = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImhsdWZwdHdoemtwa2tqenRpbXpvIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MTYyOTk3NTUsImV4cCI6MjAzMTg3NTc1NX0.v_NDVWjIU_lJQSPbJ_Y6GkW3axrQWKXfXVsBEAbFv_I'
-supabase: Client = create_client(supabase_url, supabase_key)
-
-# Fetch anomalies with anomalytype 'planet'
-anomalies_list = supabase.table("anomalies").select("id").eq("anomalytype", "planet").execute()
-
-# Get the list of image files from the directory
-image_directory = "../anomalies/clouds"
-image_files = [f for f in os.listdir(image_directory) if os.path.isfile(os.path.join(image_directory, f))]
-
-# Define a function to upload image to Supabase storage
-def upload_to_supabase(filepath, bucket_name, folder_name, file_name):
-    with open(filepath, 'rb') as f:
-        supabase.storage.from_(bucket_name).upload(f"{folder_name}/{file_name}", f.read(), file_options={"content-type": "image/png"})
-
-# Process each image file
-for image_file in image_files:
-    # Randomly select an anomaly
-    anomaly = random.choice(anomalies_list.data)
-    anomaly_id = anomaly['id']
-
-    # Define folder names
-    folder_name = f"{anomaly_id}/clouds"
-
-    # Define full file path
-    file_path = os.path.join(image_directory, image_file)
-
-    # Upload the image file to Supabase storage
-    upload_to_supabase(file_path, 'anomalies', folder_name, image_file)
-
-    print(f"Uploaded {image_file} to folder {folder_name} in Supabase storage.")
\ No newline at end of file
diff --git a/snippets/base.png b/snippets/base.png
deleted file mode 100644
index e55e39ef..00000000
Binary files a/snippets/base.png and /dev/null differ
diff --git a/snippets/base/graphsForBaseSet.py b/snippets/base/graphsForBaseSet.py
new file mode 100644
index 00000000..c45a7071
--- /dev/null
+++ b/snippets/base/graphsForBaseSet.py
@@ -0,0 +1,107 @@
+import os
+import shutil
+import lightkurve as lk
+import matplotlib.pyplot as plt
+from supabase import create_client, Client
+
+# Initialize Supabase client
+supabase_url = 'https://hlufptwhzkpkkjztimzo.supabase.co'
+supabase_key = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImhsdWZwdHdoemtwa2tqenRpbXpvIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MTYyOTk3NTUsImV4cCI6MjAzMTg3NTc1NX0.v_NDVWjIU_lJQSPbJ_Y6GkW3axrQWKXfXVsBEAbFv_I'
+supabase: Client = create_client(supabase_url, supabase_key)
+
+# Define the local folder path to save files
+local_folder = './graphs'
+
+# Function to upload images to Supabase storage
+def upload_to_supabase(filepath, bucket_name, folder_name, file_name):
+    # Check if the file already exists in the bucket
+    existing_files = supabase.storage.from_(bucket_name).list(folder_name)
+    if file_name in [file['name'] for file in existing_files]:
+        print(f"Skipping upload for {file_name} as it already exists.")
+        return
+    
+    with open(filepath, 'rb') as f:
+        supabase.storage.from_(bucket_name).upload(f"{folder_name}/{file_name}", f.read(), file_options={"content-type": "image/png"})
+
+# Function to generate light curves and save plots
+def generate_lightcurves(tic_id, output_dir):
+    # Search for lightcurve data
+    sector_data = lk.search_lightcurve(tic_id, author='SPOC')
+    select_sector = sector_data[0:4]
+    lc_collection = select_sector.download_all()
+
+    # Plot individual light curves
+    fig1, ax1 = plt.subplots()
+    lc = select_sector.download_all()
+    lc.plot(ax=ax1, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3)
+    fig1.savefig(os.path.join(output_dir, 'individual_light_curves.png'))
+    plt.close(fig1)
+
+    # Stitch the light curves
+    lc_collection_stitched = lc_collection.stitch()
+    fig2, ax2 = plt.subplots()
+    lc_collection_stitched.plot(ax=ax2, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3)
+    fig2.savefig(os.path.join(output_dir, 'stitched_light_curves.png'))
+    plt.close(fig2)
+
+    # Bin the light curves with a larger bin time
+    bin_time = 15 / 24 / 60  # 15-minute binning
+    lc_collection_binned = lc_collection_stitched.bin(bin_time)
+    fig3, ax3 = plt.subplots()
+    lc_collection_binned.plot(ax=ax3, linewidth=0, marker='o', markersize=4, color='red', alpha=0.7)
+    fig3.savefig(os.path.join(output_dir, 'binned_light_curves.png'))
+    plt.close(fig3)
+
+    # Plot stitched and binned light curves together
+    fig4, ax4 = plt.subplots(figsize=(10, 5))
+    lc_collection_stitched.plot(ax=ax4, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3, label='Unbinned')
+    lc_collection_binned.plot(ax=ax4, linewidth=0, marker='o', markersize=4, color='red', alpha=0.7, label='Binned')
+    ax4.legend()
+    fig4.savefig(os.path.join(output_dir, 'stitched_and_binned_light_curves.png'))
+    plt.close(fig4)
+
+    # Zoom in on a specific time range to highlight transits
+    fig5, ax5 = plt.subplots(figsize=(10, 5))
+    lc_collection_stitched.plot(ax=ax5, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3, label='Unbinned')
+    lc_collection_binned.plot(ax=ax5, linewidth=0, marker='o', markersize=4, color='red', alpha=0.7, label='Binned')
+    ax5.set_xlim(lc_collection_stitched.time.min().value, lc_collection_stitched.time.min().value + 5)  # Adjust zoom range here
+    ax5.legend()
+    fig5.savefig(os.path.join(output_dir, 'zoomed_light_curves.png'))
+    plt.close(fig5)
+
+    # Apply a smoothing filter to the light curve
+    smoothed_lc = lc_collection_stitched.flatten(window_length=301)
+    fig6, ax6 = plt.subplots(figsize=(10, 5))
+    smoothed_lc.plot(ax=ax6, linewidth=0, marker='.', markersize=1, color='midnightblue', alpha=0.3, label='Smoothed')
+    fig6.savefig(os.path.join(output_dir, 'smoothed_light_curves.png'))
+    plt.close(fig6)
+
+# Function to process each TIC ID, generate graphs, and upload to Supabase
+def process_and_upload(tic_id, anomaly_id):
+    output_dir = os.path.join(local_folder, str(anomaly_id))
+    if not os.path.exists(output_dir):
+        os.makedirs(output_dir)
+
+    generate_lightcurves(tic_id, output_dir)
+
+    for filename in os.listdir(output_dir):
+        file_path = os.path.join(output_dir, filename)
+        if os.path.isfile(file_path):
+            upload_to_supabase(file_path, 'anomalies', str(anomaly_id), filename)
+
+    print(f"Processed TIC ID {tic_id}, Anomaly ID: {anomaly_id}")
+
+# Main function
+def main():
+    tic_ids = ['KIC 8692861', 'KIC 8120608', 'KIC 4138008', 'KIC 10593636', 'EPIC 246199087', 'TIC 150428135']
+    anomaly_ids = [1, 2, 3, 4, 5, 6]
+
+    if os.path.exists(local_folder):
+        shutil.rmtree(local_folder)
+    os.makedirs(local_folder)
+
+    for tic_id, anomaly_id in zip(tic_ids, anomaly_ids):
+        process_and_upload(tic_id, anomaly_id)
+
+if __name__ == "__main__":
+    main()
diff --git a/snippets/clouds/assignClouds.py b/snippets/clouds/assignClouds.py
new file mode 100644
index 00000000..0c9af943
--- /dev/null
+++ b/snippets/clouds/assignClouds.py
@@ -0,0 +1,113 @@
+import os
+import random
+import time
+from supabase import create_client, Client
+
+# Set up Supabase client
+supabase_url = 'https://hlufptwhzkpkkjztimzo.supabase.co'
+supabase_key = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImhsdWZwdHdoemtwa2tqenRpbXpvIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MTYyOTk3NTUsImV4cCI6MjAzMTg3NTc1NX0.v_NDVWjIU_lJQSPbJ_Y6GkW3axrQWKXfXVsBEAbFv_I'
+supabase: Client = create_client(supabase_url, supabase_key)
+
+# Get the list of image files from the directory
+image_directory = "../anomalies/clouds"
+image_files = [f for f in os.listdir(image_directory) if os.path.isfile(os.path.join(image_directory, f))]
+
+# Define a function to upload image to Supabase storage
+def upload_to_supabase(filepath, bucket_name, folder_name, file_name, retries=3):
+    for attempt in range(retries):
+        try:
+            # Check if the file already exists in the bucket
+            existing_files = supabase.storage.from_(bucket_name).list(folder_name)
+            existing_file_names = [file['name'] for file in existing_files]
+            if file_name in existing_file_names:
+                print(f"File {file_name} already exists in {folder_name}. Trying a different folder.")
+                raise FileExistsError("File already exists")  # Trigger an exception to try a different folder
+            
+            # Upload the file
+            with open(filepath, 'rb') as f:
+                supabase.storage.from_(bucket_name).upload(f"{folder_name}/{file_name}", f.read(), file_options={"content-type": "image/png"})
+            print(f"Uploaded {file_name} to folder {folder_name} in Supabase storage.")
+            break  # Exit loop if upload is successful
+        
+        except FileExistsError:
+            # Generate a new folder name to avoid conflicts
+            new_anomaly_id = random.choice(anomaly_ids)
+            new_folder_name = f"{new_anomaly_id}/clouds"
+            print(f"Retrying with a new folder {new_folder_name} for file {file_name}.")
+            folder_name = new_folder_name  # Update folder name for retry
+            
+        except Exception as e:
+            print(f"Error during upload: {e}. Retrying ({attempt + 1}/{retries})...")
+            if attempt == retries - 1:
+                print(f"Failed to upload {file_name} after {retries} attempts.")
+            else:
+                time.sleep(2)  # Wait before retrying
+
+# Fetch anomalies with anomalytype 'planet'
+anomalies_list = supabase.table("anomalies").select("id").eq("anomalytype", "planet").execute()
+anomaly_ids = [anomaly['id'] for anomaly in anomalies_list.data]
+
+# Get existing folders from the `anomalies` bucket
+def list_folders(bucket_name):
+    """List all folders in the given bucket."""
+    folders = []
+    response = supabase.storage.from_(bucket_name).list("")  # List all items in the bucket
+    items = response
+    for item in items:
+        path_parts = item['name'].split('/')
+        if len(path_parts) > 1 and path_parts[1] == 'clouds':
+            continue  # Skip paths already under a clouds folder
+        if len(path_parts) == 1 and path_parts[0].isdigit():  # Check if it's a folder with an ID
+            folders.append(path_parts[0])
+    return folders
+
+# Identify folders that do not have a `clouds` directory
+def identify_folders_without_clouds(bucket_name):
+    """Identify folders without a `clouds` directory."""
+    folders = list_folders(bucket_name)
+    folders_without_clouds = []
+    for folder in folders:
+        clouds_dir_exists = any(clouds_dir['name'] == f"{folder}/clouds" for clouds_dir in supabase.storage.from_(bucket_name).list(folder))
+        if not clouds_dir_exists:
+            folders_without_clouds.append(folder)
+    return folders_without_clouds
+
+folders_without_clouds = identify_folders_without_clouds('anomalies')
+
+# Define a function to upload images to folders that do not have a `clouds` directory
+def upload_to_folders_without_clouds(image_files, folders):
+    """Upload images to folders that do not have a `clouds` directory."""
+    for image_file in image_files:
+        for folder in folders:
+            file_path = os.path.join(image_directory, image_file)
+            folder_name = f"{folder}/clouds"
+            upload_to_supabase(file_path, 'anomalies', folder_name, image_file)
+            break  # Ensure that we only upload to one folder per image
+
+# Upload images to folders that do not have a `clouds` directory
+upload_to_folders_without_clouds(image_files, folders_without_clouds)
+
+# Upload remaining images to existing `clouds` directories or new folders
+def upload_to_existing_or_new_folders(image_files):
+    """Upload images to existing or new folders."""
+    for image_file in image_files:
+        file_path = os.path.join(image_directory, image_file)
+        for _ in range(5):  # Retry up to 5 times to find a folder
+            # Randomly select an anomaly
+            anomaly_id = random.choice(anomaly_ids)
+
+            # Define folder names
+            folder_name = f"{anomaly_id}/clouds"
+
+            # Try to upload the image file to Supabase storage
+            try:
+                upload_to_supabase(file_path, 'anomalies', folder_name, image_file)
+                break  # Exit loop if upload is successful
+            except Exception as e:
+                print(f"Error during upload to {folder_name}: {e}")
+                time.sleep(2)  # Wait before retrying
+        else:
+            print(f"Failed to upload {image_file} after several attempts.")
+
+# Upload remaining images to existing or new folders
+upload_to_existing_or_new_folders(image_files)
\ No newline at end of file
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deleted file mode 100644
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diff --git a/snippets/output_1/zoomed_light_curves.png b/snippets/output_1/zoomed_light_curves.png
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diff --git a/snippets/createAnomalies.py b/snippets/planets/creation/createAnomalies.py
similarity index 80%
rename from snippets/createAnomalies.py
rename to snippets/planets/creation/createAnomalies.py
index 85f604de..5d75f3a5 100644
--- a/snippets/createAnomalies.py
+++ b/snippets/planets/creation/createAnomalies.py
@@ -12,11 +12,34 @@
 
 # Function to upload images to Supabase storage
 def upload_to_supabase(filepath, bucket_name, folder_name, file_name):
+    # Check if the file already exists in the bucket
+    existing_files = supabase.storage.from_(bucket_name).list(folder_name)
+    if file_name in [file['name'] for file in existing_files]:
+        print(f"Skipping upload for {file_name} as it already exists.")
+        return
+    
     with open(filepath, 'rb') as f:
         supabase.storage.from_(bucket_name).upload(f"{folder_name}/{file_name}", f.read(), file_options={"content-type": "image/png"})
 
+# Function to check if the anomaly already exists
+def anomaly_exists(tic_id):
+    match = re.search(r'\d+', tic_id)
+    tic_id_numeric = int(match.group()) if match else None
+    
+    if tic_id_numeric is None:
+        raise ValueError("TIC ID must contain a numeric value to be used as the anomaly ID.")
+    
+    response = supabase.table("anomalies").select("id").eq("id", tic_id_numeric).execute()
+    return len(response.data) > 0
+
 # Function to insert a new anomaly and get its ID
 def insert_anomaly(tic_id):
+    if anomaly_exists(tic_id):
+        print(f"Anomaly for {tic_id} already exists. Skipping...")
+        match = re.search(r'\d+', tic_id)
+        tic_id_numeric = int(match.group()) if match else None
+        return tic_id_numeric
+
     # Extract the numeric part of the TIC ID for use as the id
     match = re.search(r'\d+', tic_id)
     tic_id_numeric = int(match.group()) if match else None
@@ -109,6 +132,10 @@ def main(tic_ids):
     os.makedirs(output_dir)
 
     for tic_id in tic_ids:
+        if anomaly_exists(tic_id):
+            print(f"Anomaly for {tic_id} already exists. Skipping...")
+            continue
+
         anomaly_id = insert_anomaly(tic_id)
         anomaly_folder = str(anomaly_id)
 
@@ -121,5 +148,5 @@ def main(tic_ids):
         print(f"Processed TIC ID {tic_id}, Anomaly ID: {anomaly_id}")
 
 if __name__ == "__main__":
-    tic_ids_list = ['TIC 50365310', 'TIC 88863718']
+    tic_ids_list = ['TIC 50365310', 'TIC 88863718', 'TIC 124709665', 'TIC 106997505', 'TIC 238597883', 'TIC 169904935', 'TIC 156115721', 'TIC 65212867', 'TIC 440801822']
     main(tic_ids_list)
diff --git a/snippets/createCurvesAndUpload.py b/snippets/planets/creation/createCurvesAndUpload.py
similarity index 100%
rename from snippets/createCurvesAndUpload.py
rename to snippets/planets/creation/createCurvesAndUpload.py
diff --git a/snippets/zoomed_curves.py b/snippets/planets/creation/zoomed_curves.py
similarity index 100%
rename from snippets/zoomed_curves.py
rename to snippets/planets/creation/zoomed_curves.py
diff --git a/snippets/planets/downloadPlanetAnomalies.py b/snippets/planets/downloadPlanetAnomalies.py
new file mode 100644
index 00000000..c28ee29a
--- /dev/null
+++ b/snippets/planets/downloadPlanetAnomalies.py
@@ -0,0 +1,71 @@
+import os
+import requests
+from supabase import create_client, Client
+import logging
+
+# Initialize Supabase client
+supabase_url = 'https://hlufptwhzkpkkjztimzo.supabase.co'
+supabase_key = 'eyJhbGciOiJIUzI1NiIsInR5cCI6IkpXVCJ9.eyJpc3MiOiJzdXBhYmFzZSIsInJlZiI6ImhsdWZwdHdoemtwa2tqenRpbXpvIiwicm9sZSI6ImFub24iLCJpYXQiOjE3MTYyOTk3NTUsImV4cCI6MjAzMTg3NTc1NX0.v_NDVWjIU_lJQSPbJ_Y6GkW3axrQWKXfXVsBEAbFv_I'
+supabase: Client = create_client(supabase_url, supabase_key)
+
+# Define the initial folder path
+initial_folder = '../anomalies/planets'
+
+# Ensure the initial folder exists
+if not os.path.exists(initial_folder):
+    os.makedirs(initial_folder)
+
+# Set up logging
+logging.basicConfig(level=logging.INFO)
+logger = logging.getLogger(__name__)
+
+# Base URL for public access to the storage bucket
+public_base_url = f'{supabase_url}/storage/v1/object/public/anomalies/'
+
+# Function to download images from Supabase storage and save them to the local file system
+def download_images_from_supabase():
+    offset = 0
+    while True:
+        try:
+            # List objects in the 'anomalies' bucket with pagination
+            files = supabase.storage.from_('anomalies').list('', {'limit': 1000, 'offset': offset})
+            if not files:
+                logger.info("No more files to download.")
+                break
+        except Exception as e:
+            logger.error(f"Error listing files from Supabase: {e}")
+            break
+
+        for file in files:
+            file_path = file['name']
+            anomaly_id = file_path.split('/')[0]  # Extract the anomaly ID from the file path
+            file_name = file_path.split('/')[-1]  # Extract the file name
+
+            # Create a directory for the anomaly ID if it doesn't exist
+            anomaly_folder = os.path.join(initial_folder, anomaly_id)
+            if not os.path.exists(anomaly_folder):
+                os.makedirs(anomaly_folder)
+
+            # Construct the public URL for the file
+            public_file_url = f'{public_base_url}{file_path}'
+            local_file_path = os.path.join(anomaly_folder, file_name)
+
+            try:
+                # Download the file from Supabase storage
+                response = requests.get(public_file_url)
+                response.raise_for_status()  # Check for HTTP errors
+
+                # Save the file to the local directory
+                with open(local_file_path, 'wb') as f:
+                    f.write(response.content)
+
+                logger.info(f"Downloaded {file_name} to {local_file_path}")
+
+            except requests.RequestException as e:
+                logger.error(f"Error downloading {file_path}: {e}")
+
+        offset += 1000
+
+# Run the download function
+if __name__ == "__main__":
+    download_images_from_supabase()