Refactor sequence preprocessing

src/preprocessing.py

@@ -22,19 +22,6 @@ def align_sequences(sequence, label) -> Tuple[str, str]:
     return aligned_seq, aligned_label
 
 
-def generate_example(sequence, label) -> bytes:
-    """
-    Create a binary-string for each sequence containing the sequence and the bases' counts
-    """
-    aligned_seq, aligned_label = align_sequences(sequence, label)
-    schema = {
-        "sequence": Feature(int64_list=Int64List(value=encode_sequence(aligned_seq))),
-        "label": Feature(int64_list=Int64List(value=encode_sequence(aligned_label))),
-    }
-    example = Example(features=Features(feature=schema))
-    return example.SerializeToString()
-
-
 def encode_sequence(sequence) -> List[int]:
     """
     Encode the DNA sequence using the indices of the BASES constant
@@ -43,6 +30,30 @@ def encode_sequence(sequence) -> List[int]:
     return encoded_sequence
 
 
+def prepare_sequences(sequence, label):
+    """
+    Align and encode the sequences to obtain a fixed length output in order to perform batching
+    """
+    encoded_sequences = []
+    aligned_seq, aligned_label = align_sequences(sequence, label)
+    for item in [aligned_seq, aligned_label]:
+        encoded_sequences.append(encode_sequence(item))
+    return encoded_sequences[0], encoded_sequences[1]
+
+
+def generate_example(sequence, label) -> bytes:
+    """
+    Create a binary-string for each sequence containing the sequence and the bases' counts
+    """
+    processed_seq, processed_label = prepare_sequences(sequence, label)
+    schema = {
+        "sequence": Feature(int64_list=Int64List(value=processed_seq)),
+        "label": Feature(int64_list=Int64List(value=processed_label)),
+    }
+    example = Example(features=Features(feature=schema))
+    return example.SerializeToString()
+
+
 def read_fastq(hyperparams) -> List[bytes]:
     """
     Parses a data and a label FASTQ files and generates a List of serialized Examples