Update README.md

README.md

@@ -745,6 +745,75 @@ print(dataset[:])
 
 </details>
 
+<details>
+  <summary> ✅ Encrypt, decrypt data at chunk/sample level</summary>
+&nbsp;
+
+Secure data by applying encryption to individual samples or chunks, ensuring sensitive information is protected during storage.
+
+This example shows how to use the `FernetEncryption` class for sample-level encryption with a data optimization function.
+
+```python
+from litdata import optimize
+from litdata.utilities.encryption import FernetEncryption
+import numpy as np
+from PIL import Image
+
+# Initialize FernetEncryption with a password for sample-level encryption
+fernet = FernetEncryption(password="your_secure_password", level="sample")
+data_dir = "s3://my-bucket/optimized_data"
+
+def random_image(index):
+    """Generate a random image for demonstration purposes."""
+    fake_img = Image.fromarray(np.random.randint(0, 255, (32, 32, 3), dtype=np.uint8))
+    return {"image": fake_img, "class": index}
+
+# Optimize data while applying encryption
+optimize(
+    fn=random_image,
+    inputs=list(range(5)),  # Example inputs: [0, 1, 2, 3, 4]
+    num_workers=1,
+    output_dir=data_dir,
+    chunk_bytes="64MB",
+    encryption=fernet,
+)
+
+# Save the encryption key to a file for later use
+fernet.save("fernet.pem")
+```
+
+Load the encrypted data using the `StreamingDataset` class as follows:
+
+```python
+from litdata import StreamingDataset
+from litdata.utilities.encryption import FernetEncryption
+
+# Load the encryption key
+fernet = FernetEncryption(password="your_secure_password", level="sample")
+fernet.load("fernet.pem")
+
+# Create a streaming dataset for reading the encrypted samples
+ds = StreamingDataset(input_dir=data_dir, encryption=fernet)
+```
+
+Implement your own encryption method: Subclass the `Encryption` class and define the necessary methods:
+
+```python
+from litdata.utilities.encryption import Encryption
+
+class CustomEncryption(Encryption):
+    def encrypt(self, data):
+        # Implement your custom encryption logic here
+        return data
+
+    def decrypt(self, data):
+        # Implement your custom decryption logic here
+        return data
+```
+
+This allows the data to remain secure while maintaining flexibility in the encryption method.
+</details>
+
 &nbsp;
 
 ## Features for transforming datasets
@@ -817,75 +886,6 @@ Explore an example setup of litdata with MinIO in the [LitData with MinIO](https
 
 </details>
 
-<details>
-  <summary> ✅ Supports encryption and decryption of data at chunk/sample level</summary>
-&nbsp;
-
-Secure your data by applying encryption to individual samples or chunks, ensuring sensitive information is protected during storage.
-
-This example demonstrates how to use the `FernetEncryption` class for sample-level encryption with a data optimization function.
-
-```python
-from litdata import optimize
-from litdata.utilities.encryption import FernetEncryption
-import numpy as np
-from PIL import Image
-
-# Initialize FernetEncryption with a password for sample-level encryption
-fernet = FernetEncryption(password="your_secure_password", level="sample")
-data_dir = "s3://my-bucket/optimized_data"
-
-def random_image(index):
-    """Generate a random image for demonstration purposes."""
-    fake_img = Image.fromarray(np.random.randint(0, 255, (32, 32, 3), dtype=np.uint8))
-    return {"image": fake_img, "class": index}
-
-# Optimize data while applying encryption
-optimize(
-    fn=random_image,
-    inputs=list(range(5)),  # Example inputs: [0, 1, 2, 3, 4]
-    num_workers=1,
-    output_dir=data_dir,
-    chunk_bytes="64MB",
-    encryption=fernet,
-)
-
-# Save the encryption key to a file for later use
-fernet.save("fernet.pem")
-```
-
-You can load the encrypted data using the `StreamingDataset` class as follows:
-
-```python
-from litdata import StreamingDataset
-from litdata.utilities.encryption import FernetEncryption
-
-# Load the encryption key
-fernet = FernetEncryption(password="your_secure_password", level="sample")
-fernet.load("fernet.pem")
-
-# Create a streaming dataset for reading the encrypted samples
-ds = StreamingDataset(input_dir=data_dir, encryption=fernet)
-```
-
-If you want to implement your own encryption method, you can subclass the `Encryption` class and define the necessary methods:
-
-```python
-from litdata.utilities.encryption import Encryption
-
-class CustomEncryption(Encryption):
-    def encrypt(self, data):
-        # Implement your custom encryption logic here
-        return data
-
-    def decrypt(self, data):
-        # Implement your custom decryption logic here
-        return data
-```
-
-With this setup, you can ensure that your data remains secure while maintaining flexibility in how you handle encryption.
-</details>
-
 &nbsp;
 
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