refact

.gitignore

@@ -1 +1,3 @@
 env/
+__pycache__/
+*.pyc

app.py

@@ -1,220 +1,7 @@
 import gradio as gr
-import pandas as pd
 from io import StringIO
-from urllib.request import urlopen
-import re
-import xml.etree.ElementTree as ET
 
-
-def get_uniprot_data(uniprot_id):
-    """
-    Fetches protein sequence and annotation data from UniProt in XML format.
-
-    Args:
-        uniprot_id: The UniProt ID of the protein.
-
-    Returns:
-        A tuple containing:
-        - protein_sequence: The protein sequence as a string.
-        - annotations: A dictionary containing annotations.
-        - error_message: An error message if something goes wrong, otherwise None
-    """
-    # Fetch XML data
-    local_file_path = os.path.join("test", f"{uniprot_id}.xml")
-    if os.path.exists(local_file_path):
-        with open(local_file_path, "r", encoding="utf-8") as file:
-            response = file.read()
-    else:
-        # Fetch XML data from UniProt
-        url = f"https://www.uniprot.org/uniprot/{uniprot_id}.xml"
-        response = urlopen(url).read().decode("utf-8")
-
-    # Parse XML with namespace
-    root = ET.fromstring(response)
-    ns = {"up": "http://uniprot.org/uniprot"}
-
-    # Get sequence
-    sequence_elem = root.find("./up:entry/up:sequence", ns)
-    if sequence_elem is None:
-        return None, None, "Could not find sequence in UniProt response"
-    protein_sequence = sequence_elem.text.strip()
-
-    # Get feature annotations
-    annotations = {}
-    for feature in root.findall(".//up:feature", ns):
-        feature_type = feature.get("type")
-        description = feature.get("description", "")
-
-        # Get position information
-        location = feature.find("up:location", ns)
-        if location is None:
-            continue
-
-        # Handle different types of position elements
-        position = location.find("up:position", ns)
-        begin = location.find("up:begin", ns)
-        end_elem = location.find("up:end", ns)
-
-        if position is not None:
-            pos = int(position.get("position"))
-            # For single position features
-            if feature_type not in annotations:
-                annotations[feature_type] = []
-            annotations[feature_type].append(
-                {"position": pos, "description": description}
-            )
-        elif begin is not None and end_elem is not None:
-            start = int(begin.get("position"))
-            end = int(end_elem.get("position"))
-            # For range features and disulfide bonds
-            if feature_type not in annotations:
-                annotations[feature_type] = []
-            annotations[feature_type].append(
-                {"begin": start, "end": end, "description": description}
-            )
-
-    return protein_sequence, annotations
-
-
-def create_dataframe(protein_sequence, annotations):
-    """
-    Creates a Pandas DataFrame from protein sequence and annotations.
-    """
-    data = []
-    for i, residue in enumerate(protein_sequence):
-        residue_number = i + 1
-        row = {
-            "Residue Number": residue_number,
-            "Residue code": residue,
-            "Secondary structure": "",
-            "Domain": "",
-            "Pfam domain": "",
-            "Disorder": "",
-            "Disulfide bridges": "",
-            "Glycosylation sites": "",
-            "Phosphorylation sites": "",
-            "active sites": "",
-            "Binding sites": "",  # Combined binding sites column
-            "modified": "",
-        }
-        data.append(row)
-
-    df = pd.DataFrame(data)
-
-    # Map UniProt feature types to our column names
-    feature_mapping = {
-        "strand": "Secondary structure",
-        "helix": "Secondary structure",
-        "turn": "Secondary structure",
-        "domain": "Domain",
-        "disulfide bond": "Disulfide bridges",
-        "glycosylation site": "Glycosylation sites",
-        "modified residue": "modified",
-        "active site": "active sites",
-        "site": "Phosphorylation sites",
-    }
-
-    # Special mappings that need additional processing
-    region_mapping = {"pfam": "Pfam domain", "disorder": "Disorder"}
-
-    for feature_type, values in annotations.items():
-        feature_type = feature_type.lower()
-
-        # Handle disulfide bond pairs
-        if feature_type == "disulfide bond":
-            for item in values:
-                start = item["begin"]
-                end = item["end"]
-                desc = f"Cys-{end}"
-                df.at[start - 1, "Disulfide bridges"] = desc
-                desc = f"Cys-{start}"
-                df.at[end - 1, "Disulfide bridges"] = desc
-
-        # Handle glycosylation sites
-        elif feature_type == "glycosylation site":
-            for item in values:
-                pos = item["position"] - 1
-                df.at[pos, "Glycosylation sites"] = item["description"]
-
-        # Handle region features
-        elif feature_type == "region":
-            for item in values:
-                start = item.get("begin", item.get("position"))
-                end = item.get("end", item.get("position"))
-                if not start:
-                    continue
-
-                start = int(start)
-                end = int(end) if end else start
-                desc = item["description"].lower()
-
-                # Map to appropriate column based on description
-                column = None
-                if "pfam" in desc:
-                    column = "Pfam domain"
-                elif "disorder" in desc:
-                    column = "Disorder"
-
-                if column:
-                    for i in range(start - 1, end):
-                        if i >= len(df):
-                            continue
-                        current = df.at[i, column]
-                        if isinstance(current, str) and current != "" and desc:
-                            df.at[i, column] = f"{current}; {desc}"
-                        elif desc:
-                            df.at[i, column] = desc
-
-        # Handle binding site features
-        elif feature_type == "binding site":
-            for item in values:
-                start = item.get("begin", item.get("position"))
-                end = item.get("end", item.get("position"))
-                if not start:
-                    continue
-
-                start = int(start)
-                end = int(end) if end else start
-                desc = item["description"]
-
-                for i in range(start - 1, end):
-                    if i >= len(df):
-                        continue
-                    current = df.at[i, "Binding sites"]
-                    if isinstance(current, str) and current != "" and desc:
-                        df.at[i, "Binding sites"] = f"{current}; {desc}"
-                    elif desc:
-                        df.at[i, "Binding sites"] = desc
-
-        # Handle other features
-        else:
-            column = feature_mapping.get(feature_type)
-            if not column:
-                continue
-
-            for item in values:
-                start = item.get("begin", item.get("position"))
-                end = item.get("end", item.get("position"))
-                if not start:
-                    continue
-
-                start = int(start)
-                end = int(end) if end else start
-
-                for i in range(start - 1, end):
-                    if i >= len(df):
-                        continue
-                    if column == "Secondary structure":
-                        df.at[i, column] = feature_type.upper()
-                    else:
-                        current = df.at[i, column]
-                        desc = item["description"]
-                        if isinstance(current, str) and current != "" and desc:
-                            df.at[i, column] = f"{current}; {desc}"
-                        elif desc:
-                            df.at[i, column] = desc
-
-    return df
+from uniprot_data import create_dataframe, get_uniprot_data
 
 
 def process_uniprot_id(uniprot_id):
@@ -240,6 +27,9 @@ def process_uniprot_id(uniprot_id):
 with gr.Blocks() as demo:
     with gr.Column():
         gr.Markdown("# Protein Sequence Analysis")
+        gr.Markdown(
+            "This app fetches protein sequence and annotation data from UniProt using a UniProt ID and prints a copy-pasteable table for note-taking. **DO NOT TRUST, THIS IS A CODING EXPERIMENT**"
+        )
         input_text = gr.Textbox(
             label="UniProt ID",
             placeholder="Enter UniProt ID (e.g., P53_HUMAN)",

uniprot_data.py

@@ -0,0 +1,216 @@
+import os
+import xml.etree.ElementTree as ET
+from urllib.request import urlopen
+
+import pandas as pd
+
+
+def get_uniprot_data(uniprot_id):
+    """
+    Fetches protein sequence and annotation data from UniProt in XML format.
+
+    Args:
+        uniprot_id: The UniProt ID of the protein.
+
+    Returns:
+        A tuple containing:
+        - protein_sequence: The protein sequence as a string.
+        - annotations: A dictionary containing annotations.
+        - error_message: An error message if something goes wrong, otherwise None
+    """
+    # Fetch XML data
+    local_file_path = os.path.join("test", f"{uniprot_id}.xml")
+    if os.path.exists(local_file_path):
+        with open(local_file_path, "r", encoding="utf-8") as file:
+            response = file.read()
+    else:
+        # Fetch XML data from UniProt
+        url = f"https://www.uniprot.org/uniprot/{uniprot_id}.xml"
+        response = urlopen(url).read().decode("utf-8")
+
+    # Parse XML with namespace
+    root = ET.fromstring(response)
+    ns = {"up": "http://uniprot.org/uniprot"}
+
+    # Get sequence
+    sequence_elem = root.find("./up:entry/up:sequence", ns)
+    if sequence_elem is None:
+        return None, None, "Could not find sequence in UniProt response"
+    protein_sequence = sequence_elem.text.strip()
+
+    # Get feature annotations
+    annotations = {}
+    for feature in root.findall(".//up:feature", ns):
+        feature_type = feature.get("type")
+        description = feature.get("description", "")
+
+        # Get position information
+        location = feature.find("up:location", ns)
+        if location is None:
+            continue
+
+        # Handle different types of position elements
+        position = location.find("up:position", ns)
+        begin = location.find("up:begin", ns)
+        end_elem = location.find("up:end", ns)
+
+        if position is not None:
+            pos = int(position.get("position"))
+            # For single position features
+            if feature_type not in annotations:
+                annotations[feature_type] = []
+            annotations[feature_type].append(
+                {"position": pos, "description": description}
+            )
+        elif begin is not None and end_elem is not None:
+            start = int(begin.get("position"))
+            end = int(end_elem.get("position"))
+            # For range features and disulfide bonds
+            if feature_type not in annotations:
+                annotations[feature_type] = []
+            annotations[feature_type].append(
+                {"begin": start, "end": end, "description": description}
+            )
+
+    return protein_sequence, annotations
+
+
+def create_dataframe(protein_sequence, annotations):
+    """
+    Creates a Pandas DataFrame from protein sequence and annotations.
+    """
+    data = []
+    for i, residue in enumerate(protein_sequence):
+        residue_number = i + 1
+        row = {
+            "Residue Number": residue_number,
+            "Residue code": residue,
+            "Secondary structure": "",
+            "Domain": "",
+            "Pfam domain": "",
+            "Disorder": "",
+            "Disulfide bridges": "",
+            "Glycosylation sites": "",
+            "Phosphorylation sites": "",
+            "active sites": "",
+            "Binding sites": "",  # Combined binding sites column
+            "modified": "",
+        }
+        data.append(row)
+
+    df = pd.DataFrame(data)
+
+    # Map UniProt feature types to our column names
+    feature_mapping = {
+        "strand": "Secondary structure",
+        "helix": "Secondary structure",
+        "turn": "Secondary structure",
+        "domain": "Domain",
+        "disulfide bond": "Disulfide bridges",
+        "glycosylation site": "Glycosylation sites",
+        "modified residue": "modified",
+        "active site": "active sites",
+        "site": "Phosphorylation sites",
+    }
+
+    # Special mappings that need additional processing
+    region_mapping = {"pfam": "Pfam domain", "disorder": "Disorder"}
+
+    for feature_type, values in annotations.items():
+        feature_type = feature_type.lower()
+
+        # Handle disulfide bond pairs
+        if feature_type == "disulfide bond":
+            for item in values:
+                start = item["begin"]
+                end = item["end"]
+                desc = f"Cys-{end}"
+                df.at[start - 1, "Disulfide bridges"] = desc
+                desc = f"Cys-{start}"
+                df.at[end - 1, "Disulfide bridges"] = desc
+
+        # Handle glycosylation sites
+        elif feature_type == "glycosylation site":
+            for item in values:
+                pos = item["position"] - 1
+                df.at[pos, "Glycosylation sites"] = item["description"]
+
+        # Handle region features
+        elif feature_type == "region":
+            for item in values:
+                start = item.get("begin", item.get("position"))
+                end = item.get("end", item.get("position"))
+                if not start:
+                    continue
+
+                start = int(start)
+                end = int(end) if end else start
+                desc = item["description"].lower()
+
+                # Map to appropriate column based on description
+                column = None
+                if "pfam" in desc:
+                    column = "Pfam domain"
+                elif "disorder" in desc:
+                    column = "Disorder"
+
+                if column:
+                    for i in range(start - 1, end):
+                        if i >= len(df):
+                            continue
+                        current = df.at[i, column]
+                        if isinstance(current, str) and current != "" and desc:
+                            df.at[i, column] = f"{current}; {desc}"
+                        elif desc:
+                            df.at[i, column] = desc
+
+        # Handle binding site features
+        elif feature_type == "binding site":
+            for item in values:
+                start = item.get("begin", item.get("position"))
+                end = item.get("end", item.get("position"))
+                if not start:
+                    continue
+
+                start = int(start)
+                end = int(end) if end else start
+                desc = item["description"]
+
+                for i in range(start - 1, end):
+                    if i >= len(df):
+                        continue
+                    current = df.at[i, "Binding sites"]
+                    if isinstance(current, str) and current != "" and desc:
+                        df.at[i, "Binding sites"] = f"{current}; {desc}"
+                    elif desc:
+                        df.at[i, "Binding sites"] = desc
+
+        # Handle other features
+        else:
+            column = feature_mapping.get(feature_type)
+            if not column:
+                continue
+
+            for item in values:
+                start = item.get("begin", item.get("position"))
+                end = item.get("end", item.get("position"))
+                if not start:
+                    continue
+
+                start = int(start)
+                end = int(end) if end else start
+
+                for i in range(start - 1, end):
+                    if i >= len(df):
+                        continue
+                    if column == "Secondary structure":
+                        df.at[i, column] = feature_type.upper()
+                    else:
+                        current = df.at[i, column]
+                        desc = item["description"]
+                        if isinstance(current, str) and current != "" and desc:
+                            df.at[i, column] = f"{current}; {desc}"
+                        elif desc:
+                            df.at[i, column] = desc
+
+    return df