Create journal.py

journal.py

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+# journal.py
+import os
+import csv
+import pandas as pd
+import datetime
+
+JOURNAL_FILE = "./lab_journal.csv"
+JOURNAL_CATEGORIES = [
+    # S1-A Genomics
+    "S1-A·R1a",  # Real Variant Lookup
+    "S1-A·R1b",  # Variant Concepts
+    "S1-A·R2a",  # Gray Zones Explorer
+    "S1-A·R2b",  # Understudied Target Finder
+    "S1-A·R2c",  # Literature Gap Finder
+    "S1-A·R2d",  # Druggable Orphans
+    "S1-A·R2e",  # Research Assistant
+    # S1-C Drug Discovery
+    "S1-C·R1a",  # FGFR3 RNA Drug
+    "S1-C·R1b",  # SL Drug Mapping
+    "S1-C·R2a",  # m6A × Ferroptosis × Circadian
+    # S1-D LNP
+    "S1-D·R1a",  # LNP Corona ML
+    "S1-D·R2a",  # Flow Corona
+    "S1-D·R3a",  # LNP Brain / BBB
+    "S1-D·R4a",  # AutoCorona NLP
+    "S1-D·R5a",  # CSF/Vitreous/BM
+    "S1-D·R6a",  # Corona Database
+    # S1-E Biomarkers
+    "S1-E·R1a",  # Liquid Biopsy Classifier
+    "S1-E·R1b",  # Protein Panel Validator
+    "S1-E·R2a",  # Multi-protein Biomarkers
+    # S1-F Rare Cancers
+    "S1-F·R1a",  # DIPG Toolkit
+    "S1-F·R2a",  # UVM Toolkit
+    "S1-F·R3a",  # pAML Toolkit
+    # Learning Sandbox
+    "S1-B·R1a",  # miRNA Explorer
+    "S1-B·R2a",  # siRNA Targets
+    "S1-G·General",  # 3D Models
+    "Manual"
+]
+
+def journal_log(category: str, action: str, result: str, note: str = ""):
+    """Log an entry with category."""
+    ts = datetime.datetime.utcnow().isoformat()
+    row = [ts, category, action, result[:200], note]
+    write_header = not os.path.exists(JOURNAL_FILE)
+    with open(JOURNAL_FILE, "a", newline="", encoding="utf-8") as f:
+        w = csv.writer(f)
+        if write_header:
+            w.writerow(["timestamp", "category", "action", "result_summary", "note"])
+        w.writerow(row)
+    return ts
+
+def journal_read(category: str = "All") -> str:
+    """Read journal entries, optionally filtered by category. Returns markdown."""
+    if not os.path.exists(JOURNAL_FILE):
+        return "No entries yet."
+    try:
+        df = pd.read_csv(JOURNAL_FILE)
+        if df.empty:
+            return "No entries yet."
+        if category != "All":
+            df = df[df["category"] == category]
+        if df.empty:
+            return f"No entries for category: {category}"
+        df_display = df[["timestamp", "category", "action", "result_summary"]].tail(50)
+        return df_display.to_markdown(index=False)
+    except Exception as e:
+        print(f"Journal read error: {e}")
+        return "Error reading journal."
+
+def clear_journal():
+    try:
+        if os.path.exists(JOURNAL_FILE):
+            os.remove(JOURNAL_FILE)
+        return "Journal cleared."
+    except Exception as e:
+        print(f"Clear journal error: {e}")
+        return "Error clearing journal."