feat: implement automated payment inference and sync to Google Sheets

.gitignore

@@ -1,2 +1,3 @@
 # python cache
 **/*.pyc
+.secret

CLAUDE.md

@@ -21,10 +21,26 @@ This project uses a hybrid workflow:
 
 ## When Code Exists
 
-Once a tech stack is chosen and implementation begins, update this file with:
+## Development Setup
-- Build, test, and lint commands
+
-- Architecture overview
+This project uses `uv` for dependency management.
-- Development setup instructions
+
+```bash
+uv venv          # Create virtual environment
+uv sync          # Install dependencies from pyproject.toml
+source .venv/bin/activate
+```
+
+Alternatively, use the Makefile:
+- `make sync`      - Sync bank transactions to Google Sheets
+- `make infer`     - Automatically infer Person/Purpose/Amount in the sheet
+- `make reconcile` - Generate balance report from Google Sheets data
+- `make fees`      - Calculate expected fees from attendance
+- `make match`     - (Legacy) Match bank data directly
+- `make web`       - Start dashboard
+- `make image`     - Build Docker image
+
+Requires `credentials.json` in the root for Google Sheets API access.
 
 ## Git Commits
 

Makefile

@@ -1,12 +1,15 @@
-.PHONY: help fees match web image run
+.PHONY: help fees match web image run sync sync-2026 test test-v
 
 export PYTHONPATH := scripts:$(PYTHONPATH)
 VENV := .venv
 PYTHON := $(VENV)/bin/python3
+CREDENTIALS := .secret/fuj-management-bot-credentials.json
 
-$(PYTHON):
+$(PYTHON): .venv/.last_sync
-	python3 -m venv $(VENV)
+
-	$(PYTHON) -m pip install -q flask
+.venv/.last_sync: pyproject.toml
+	uv sync
+	touch .venv/.last_sync
 
 help:
 	@echo "Available targets:"
@@ -15,6 +18,16 @@ help:
 	@echo "  make web    - Start a dynamic web dashboard locally"
 	@echo "  make image  - Build an OCI container image"
 	@echo "  make run    - Run the built Docker image locally"
+	@echo "  make sync        - Sync Fio transactions to Google Sheets"
+	@echo "  make sync-2026   - Sync Fio transactions for the whole year of 2026"
+	@echo "  make infer       - Infer payment details (Person, Purpose, Amount) in the sheet"
+	@echo "  make reconcile   - Show balance report using Google Sheets data"
+	@echo "  make venv        - Sync virtual environment with pyproject.toml"
+	@echo "  make test        - Run web application infrastructure tests"
+	@echo "  make test-v      - Run tests with verbose output"
+
+venv:
+	uv sync
 
 fees: $(PYTHON)
 	$(PYTHON) scripts/calculate_fees.py
@@ -30,3 +43,21 @@ image:
 
 run:
 	docker run -it --rm -p 5001:5001 fuj-management:latest
+
+sync: $(PYTHON)
+	$(PYTHON) scripts/sync_fio_to_sheets.py --credentials .secret/fuj-management-bot-credentials.json
+
+sync-2026: $(PYTHON)
+	$(PYTHON) scripts/sync_fio_to_sheets.py --credentials .secret/fuj-management-bot-credentials.json --from 2026-01-01 --to 2026-12-31 --sort-by-date
+
+infer: $(PYTHON)
+	$(PYTHON) scripts/infer_payments.py --credentials $(CREDENTIALS)
+
+reconcile:  ## Match payments against attendance
+	export PYTHONPATH=$(PYTHONPATH):$(CURDIR)/scripts && $(PYTHON) scripts/match_payments.py --credentials $(CREDENTIALS)
+
+test: $(PYTHON) ## Run web application tests
+	export PYTHONPATH=$(PYTHONPATH):$(CURDIR)/scripts:$(CURDIR) && $(PYTHON) -m unittest discover tests
+
+test-v: $(PYTHON) ## Run tests with verbose output
+	export PYTHONPATH=$(PYTHONPATH):$(CURDIR)/scripts:$(CURDIR) && $(PYTHON) -m unittest discover -v tests

docs/spec/fio_to_sheets_sync.md

@@ -0,0 +1,69 @@
+# Specification: Fio to Google Sheets Sync
+
+## Goal
+Automatically sync incoming transactions from a Fio bank account to a Google Sheet to serve as an intermediary ledger. This ledger allows for manual tagging, note-taking, and further processing without risking data loss on subsequent syncs.
+
+## Data Source (Fio)
+
+### Scraping Mechanism
+The script will fetch data from the Fio bank in two possible ways:
+1.  **Transparent Account HTML (Default)**:
+    - Fetches the HTML from `https://ib.fio.cz/ib/transparent?a=2800359168&f={date_from}&t={date_to}`.
+    - Uses a custom `HTMLParser` to locate the second `<table>` with class `table`.
+    - Extracts columns: Date (0), Amount (1), Typ (2), Sender (3), Message (4), KS (5), VS (6), SS (7), and Note (8).
+    - Normalizes dates from `DD.MM.YYYY` and amounts from Czech formatting (e.g., `1 500,00 CZK`).
+2.  **Official API (If `FIO_API_TOKEN` is set)**:
+    - Fetches JSON from `https://fioapi.fio.cz/v1/rest/periods/{token}/{date_from}/{date_to}/transactions.json`.
+    - Provides more structured and reliable data, including exact sender account numbers.
+
+## Unique Key Generation
+To prevent duplicate entries in the Google Sheet, each transaction is assigned a **Transaction ID**.
+- **Algorithm**: SHA-256 hash of a concatenated string.
+- **Input String**: `date|amount|currency|sender|vs|message|bank_id`
+- **Why?**: Even if two payments have the same amount on the same day, they likely differ in the variable symbol (VS), sender account, or message. Including all these fields makes the ID stable. The `bank_id` (if available from the API) is the strongest unique identifier.
+
+## Google Sheet Schema
+The ledger uses the following column structure (Columns A-K):
+
+| Col | Label | Description |
+| :--- | :--- | :--- |
+| **A** | **Date** | Transaction date (YYYY-MM-DD). |
+| **B** | **Amount** | Bank transaction amount in CZK. |
+| **C** | **manual fix** | If not empty, `make infer` will skip this row (Manual Override). |
+| **D** | **Person** | Inferred or manually entered member name. |
+| **E** | **Purpose** | Inferred or manually entered month(s) (e.g., `2026-01`). |
+| **F** | **Inferred Amount** | The amount to be used for reconciliation. |
+| **G** | **Sender** | Sender account name/number. |
+| **H** | **VS** | Variable Symbol. |
+| **I** | **Message** | Message for recipient. |
+| **J** | **Bank ID** | Official Fio Transaction ID. |
+| **K** | **Sync ID** | Unique SHA-256 hash for deduplication. |
+
+## Usage Workflow
+
+To maintain the ledger and generate reports, follow these steps:
+
+1.  **Sync**: `make sync`
+    - Pulls new transactions from Fio and appends them to the sheet.
+2.  **Infer**: `make infer`
+    - Automatically fills **Person**, **Purpose**, and **Inferred Amount** for new rows.
+    - Skips any rows where **manual fix** or Person/Purpose are already filled.
+3.  **Manual Review** (Optional):
+    - Open the Google Sheet and check any rows marked with `[?]` (low confidence).
+    - Correct the **Person**, **Purpose**, or **Inferred Amount** as needed.
+    - Type anything into the **manual fix** column to prevent the script from changing your edits.
+4.  **Reconcile**: `make reconcile`
+    - Reads the processed data from the sheet and prints a balance report showing who owes how much.
+
+> [!NOTE]
+> The reconciliation report uses the Google Sheet as the source of truth, so any manual corrections you make are immediately reflected in the final balances.
+
+## Synchronization Logic
+The script performs a "Pull and Append" workflow:
+1.  **Read Existing**: Connects to the target Google Sheet and reads all values in Column K (Sync ID).
+2.  **Fetch New**: Scrapes Fio for the specified range (default: last 30 days).
+3.  **Deduplicate**:
+    - For each scraped transaction, generate its `Sync ID`.
+    - If the `Sync ID` is *not* in the list of existing IDs, it is marked for upload.
+4.  **Append**: Uploads only the new transactions to the next available rows in the sheet.
+5.  **Preserve Manual Edits**: Because the script only *appends* and never *updates* or *deletes* existing rows, any manual notes or extra columns added in the Google Sheet remain untouched.

pyproject.toml

@@ -0,0 +1,14 @@
+[project]
+name = "fuj-management"
+version = "0.02"
+description = "Management tools for FUJ (Frisbee Ultimate Jablonec)"
+dependencies = [
+    "flask>=3.1.3",
+    "google-api-python-client>=2.162.0",
+    "google-auth-httplib2>=0.2.0",
+    "google-auth-oauthlib>=1.2.1",
+]
+requires-python = ">=3.13"
+
+[tool.uv]
+package = false

scripts/fio_utils.py

@@ -0,0 +1,215 @@
+#!/usr/bin/env python3
+"""Shared Fio bank fetching utilities."""
+
+import json
+import os
+import re
+import urllib.request
+from datetime import datetime
+from html.parser import HTMLParser
+
+# ---------------------------------------------------------------------------
+# Transaction fetching
+# ---------------------------------------------------------------------------
+
+class FioTableParser(HTMLParser):
+    """Parse the second <table class="table"> on the Fio transparent page.
+
+    Columns: Datum | Částka | Typ | Název protiúčtu | Zpráva pro příjemce | KS | VS | SS | Poznámka
+    Indices:   0       1       2          3                   4              5    6    7      8
+    """
+
+    def __init__(self):
+        super().__init__()
+        self._table_count = 0
+        self._in_target_table = False
+        self._in_thead = False
+        self._in_row = False
+        self._in_cell = False
+        self._current_row: list[str] = []
+        self._rows: list[list[str]] = []
+        self._cell_text = ""
+
+    def handle_starttag(self, tag, attrs):
+        cls = dict(attrs).get("class", "")
+        if tag == "table" and "table" in cls.split():
+            self._table_count += 1
+            if self._table_count == 2:
+                self._in_target_table = True
+        if self._in_target_table:
+            if tag == "thead":
+                self._in_thead = True
+            if tag == "tr" and not self._in_thead:
+                self._in_row = True
+                self._current_row = []
+            if self._in_row and tag in ("td", "th"):
+                self._in_cell = True
+                self._cell_text = ""
+
+    def handle_endtag(self, tag):
+        if self._in_cell and tag in ("td", "th"):
+            self._in_cell = False
+            self._current_row.append(self._cell_text.strip())
+        if tag == "thead":
+            self._in_thead = False
+        if self._in_row and tag == "tr":
+            self._in_row = False
+            if self._current_row:
+                self._rows.append(self._current_row)
+        if tag == "table" and self._in_target_table:
+            self._in_target_table = False
+
+    def handle_data(self, data):
+        if self._in_cell:
+            self._cell_text += data
+
+    def get_rows(self) -> list[list[str]]:
+        return self._rows
+
+
+# Fio transparent table column indices
+_COL_DATE = 0
+_COL_AMOUNT = 1
+_COL_SENDER = 3
+_COL_MESSAGE = 4
+_COL_KS = 5
+_COL_VS = 6
+_COL_SS = 7
+_COL_NOTE = 8
+
+
+def parse_czech_amount(s: str) -> float | None:
+    """Parse '1 500,00 CZK' to float."""
+    s = s.replace("\xa0", "").replace(" ", "").replace(",", ".")
+    s = re.sub(r"[A-Za-z]+", "", s).strip()
+    try:
+        return float(s)
+    except ValueError:
+        return None
+
+
+def parse_czech_date(s: str) -> str | None:
+    """Parse 'DD.MM.YYYY' to 'YYYY-MM-DD'."""
+    s = s.strip()
+    for fmt in ("%d.%m.%Y", "%d/%m/%Y"):
+        try:
+            return datetime.strptime(s, fmt).strftime("%Y-%m-%d")
+        except ValueError:
+            continue
+    return None
+
+
+def fetch_transactions_transparent(
+    date_from: str, date_to: str, account_id: str = "2800359168"
+) -> list[dict]:
+    """Fetch transactions from Fio transparent account HTML page.
+
+    Args:
+        date_from: D.M.YYYY format
+        date_to: D.M.YYYY format
+    """
+    url = (
+        f"https://ib.fio.cz/ib/transparent?a={account_id}"
+        f"&f={date_from}&t={date_to}"
+    )
+    req = urllib.request.Request(url)
+    with urllib.request.urlopen(req) as resp:
+        html = resp.read().decode("utf-8")
+
+    parser = FioTableParser()
+    parser.feed(html)
+    rows = parser.get_rows()
+
+    transactions = []
+    for row in rows:
+        if len(row) < 5:
+            continue
+
+        def col(i):
+            return row[i].strip() if i < len(row) else ""
+
+        date_str = parse_czech_date(col(_COL_DATE))
+        amount = parse_czech_amount(col(_COL_AMOUNT))
+
+        if date_str is None or amount is None or amount <= 0:
+            continue
+
+        transactions.append({
+            "date": date_str,
+            "amount": amount,
+            "sender": col(_COL_SENDER),
+            "message": col(_COL_MESSAGE),
+            "ks": col(_COL_KS),
+            "vs": col(_COL_VS),
+            "ss": col(_COL_SS),
+            "note": col(_COL_NOTE),
+            "bank_id": "", # HTML scraping doesn't give stable ID
+        })
+
+    return transactions
+
+
+def fetch_transactions_api(
+    token: str, date_from: str, date_to: str
+) -> list[dict]:
+    """Fetch transactions via Fio REST API (JSON).
+
+    Args:
+        token: Fio API token
+        date_from: YYYY-MM-DD format
+        date_to: YYYY-MM-DD format
+    """
+    url = (
+        f"https://fioapi.fio.cz/v1/rest/periods/{token}"
+        f"/{date_from}/{date_to}/transactions.json"
+    )
+    req = urllib.request.Request(url)
+    with urllib.request.urlopen(req) as resp:
+        data = json.loads(resp.read().decode("utf-8"))
+
+    transactions = []
+    tx_list = data.get("accountStatement", {}).get("transactionList", {})
+    for tx in (tx_list.get("transaction") or []):
+        # Each field is {"value": ..., "name": ..., "id": ...} or null
+        def val(col_id):
+            col = tx.get(f"column{col_id}")
+            return col["value"] if col else ""
+
+        amount = float(val(1) or 0)
+        if amount <= 0:
+            continue  # Skip outgoing
+
+        date_raw = val(0) or ""
+        # API returns date as "YYYY-MM-DD+HHMM" or ISO format
+        date_str = date_raw[:10] if date_raw else ""
+
+        transactions.append({
+            "date": date_str,
+            "amount": amount,
+            "sender": str(val(10) or ""),     # column10 = sender name
+            "message": str(val(16) or ""),     # column16 = message for recipient
+            "vs": str(val(5) or ""),           # column5 = VS
+            "ks": str(val(4) or ""),           # column4 = KS
+            "ss": str(val(6) or ""),           # column6 = SS
+            "user_id": str(val(7) or ""),      # column7 = user identification
+            "sender_account": str(val(2) or ""),  # column2 = sender account
+            "bank_id": str(val(22) or ""),     # column22 = ID operace
+            "currency": str(val(14) or "CZK"), # column14 = Currency
+        })
+
+    return transactions
+
+
+def fetch_transactions(date_from: str, date_to: str) -> list[dict]:
+    """Fetch transactions, using API if token available, else transparent page."""
+    token = os.environ.get("FIO_API_TOKEN", "").strip()
+    if token:
+        return fetch_transactions_api(token, date_from, date_to)
+
+    # Convert YYYY-MM-DD to DD.MM.YYYY for the transparent page URL
+    from_dt = datetime.strptime(date_from, "%Y-%m-%d")
+    to_dt = datetime.strptime(date_to, "%Y-%m-%d")
+    return fetch_transactions_transparent(
+        from_dt.strftime("%d.%m.%Y"),
+        to_dt.strftime("%d.%m.%Y"),
+    )

scripts/infer_payments.py

@@ -0,0 +1,191 @@
+#!/usr/bin/env python3
+"""Infer 'Person', 'Purpose', and 'Amount' for transactions in Google Sheets."""
+
+import argparse
+import os
+import sys
+from datetime import datetime
+
+# Add the current directory to sys.path to import local modules
+sys.path.append(os.path.dirname(os.path.abspath(__file__)))
+
+from googleapiclient.discovery import build
+from sync_fio_to_sheets import get_sheets_service, DEFAULT_SPREADSHEET_ID
+from match_payments import infer_transaction_details
+from attendance import get_members_with_fees
+
+def parse_czk_amount(val) -> float:
+    """Parse Czech currency string or handle raw numeric value."""
+    if val is None or val == "":
+        return 0.0
+    if isinstance(val, (int, float)):
+        return float(val)
+    
+    val = str(val)
+    # Strip currency symbol and spaces
+    val = val.replace("Kč", "").replace("CZK", "").strip()
+    # Remove thousand separators (often space or dot)
+    # Heuristic: if there's a comma, it's the decimal separator.
+    # If there's a dot, it might be a thousand separator OR decimal separator.
+    if "," in val:
+        # 1.500,00 -> 1500.00
+        val = val.replace(".", "").replace(" ", "").replace(",", ".")
+    else:
+        # 1 500.00 -> 1500.00 or 1.500.00 -> ???
+        # If there are multiple dots, it's thousand separator.
+        if val.count(".") > 1:
+            val = val.replace(".", "").replace(" ", "")
+        # If there's one dot, it might be decimal separator.
+        else:
+            val = val.replace(" ", "")
+            
+    try:
+        return float(val)
+    except ValueError:
+        return 0.0
+
+# Column names as requested by the user
+COL_MANUAL = "manual fix"
+COL_PERSON = "Person"
+COL_PURPOSE = "Purpose"
+COL_AMOUNT = "Inferred Amount"
+
+def infer_payments(spreadsheet_id: str, credentials_path: str, dry_run: bool = False):
+    print(f"Connecting to Google Sheets...")
+    service = get_sheets_service(credentials_path)
+    sheet = service.spreadsheets()
+
+    # 1. Fetch all data from the sheet
+    print("Reading sheet data...")
+    result = sheet.values().get(
+        spreadsheetId=spreadsheet_id,
+        range="A1:Z",  # Read a broad range to find existing columns
+        valueRenderOption="UNFORMATTED_VALUE"
+    ).execute()
+    rows = result.get("values", [])
+    if not rows:
+        print("Sheet is empty.")
+        return
+
+    header = rows[0]
+    
+    # Identify indices of existing columns
+    def get_col_index(label):
+        normalized_label = label.lower().strip()
+        for i, h in enumerate(header):
+            if h.lower().strip() == normalized_label:
+                return i
+        return -1
+
+    idx_date = get_col_index("Date")
+    idx_amount_raw = get_col_index("Amount") # Bank Amount
+    idx_sender = get_col_index("Sender")
+    idx_message = get_col_index("Message")
+    idx_vs = get_col_index("VS")
+    
+    target_labels = [COL_MANUAL, COL_PERSON, COL_PURPOSE, COL_AMOUNT]
+    
+    # Refresh indices
+    idx_manual = get_col_index(COL_MANUAL)
+    idx_inferred_person = get_col_index(COL_PERSON)
+    idx_inferred_purpose = get_col_index(COL_PURPOSE)
+    idx_inferred_amount = get_col_index(COL_AMOUNT)
+
+    if idx_inferred_person == -1 or idx_inferred_purpose == -1 or idx_inferred_amount == -1:
+        print(f"Error: Required columns {target_labels[1:]} not found in sheet.")
+        print(f"Current header: {header}")
+        return
+
+    # 2. Fetch members for matching
+    print("Fetching member list for matching...")
+    members_data, _ = get_members_with_fees()
+    member_names = [m[0] for m in members_data]
+
+    # 3. Process rows
+    print("Inffering details for empty rows...")
+    updates = []
+    
+    for i, row in enumerate(rows[1:], start=2):
+        # Extend row if it's shorter than existing header
+        while len(row) < len(header):
+            row.append("")
+        
+        # Check if already filled (manual override)
+        val_manual = str(row[idx_manual]) if idx_manual != -1 and idx_manual < len(row) else ""
+        val_person = str(row[idx_inferred_person]) if idx_inferred_person < len(row) else ""
+        val_purpose = str(row[idx_inferred_purpose]) if idx_inferred_purpose < len(row) else ""
+        
+        if val_manual.strip() or val_person.strip() or val_purpose.strip():
+            continue
+            
+        # Prepare transaction dict for matching logic
+        tx = {
+            "date": row[idx_date] if idx_date != -1 and idx_date < len(row) else "",
+            "amount": parse_czk_amount(row[idx_amount_raw]) if idx_amount_raw != -1 and idx_amount_raw < len(row) and row[idx_amount_raw] else 0,
+            "sender": row[idx_sender] if idx_sender != -1 and idx_sender < len(row) else "",
+            "message": row[idx_message] if idx_message != -1 and idx_message < len(row) else "",
+            "vs": row[idx_vs] if idx_vs != -1 and idx_vs < len(row) else "",
+        }
+        
+        inference = infer_transaction_details(tx, member_names)
+        
+        # Sort members by confidence and add markers
+        peeps = []
+        for name, conf in inference["members"]:
+            prefix = "[?] " if conf == "review" else ""
+            peeps.append(f"{prefix}{name}")
+            
+        matched_months = inference["months"]
+        
+        if peeps or matched_months:
+            person_val = ", ".join(peeps)
+            purpose_val = ", ".join(matched_months)
+            amount_val = str(tx["amount"]) # For now, use total amount
+            
+            print(f"Row {i}: Inferred {person_val} for {purpose_val} ({amount_val} CZK)")
+            
+            # Update the row in memory (for terminal output/dry run)
+            row[idx_inferred_person] = person_val
+            row[idx_inferred_purpose] = purpose_val
+            row[idx_inferred_amount] = amount_val
+            
+            # Prepare batch update
+            updates.append({
+                "range": f"R{i}C{idx_inferred_person+1}:R{i}C{idx_inferred_amount+1}",
+                "values": [[person_val, purpose_val, amount_val]]
+            })
+
+    if not updates:
+        print("No new inferences to make.")
+        return
+
+    if dry_run:
+        print(f"Dry run: would update {len(updates)} rows.")
+    else:
+        print(f"Applying {len(updates)} updates to the sheet...")
+        body = {
+            "valueInputOption": "USER_ENTERED",
+            "data": updates
+        }
+        sheet.values().batchUpdate(
+            spreadsheetId=spreadsheet_id,
+            body=body
+        ).execute()
+        print("Update completed successfully.")
+
+def main():
+    parser = argparse.ArgumentParser(description="Infer payment details in Google Sheets.")
+    parser.add_argument("--sheet-id", default=DEFAULT_SPREADSHEET_ID, help="Google Sheet ID")
+    parser.add_argument("--credentials", default="credentials.json", help="Path to Google API credentials JSON")
+    parser.add_argument("--dry-run", action="store_true", help="Print updates without applying them")
+    args = parser.parse_args()
+
+    try:
+        infer_payments(args.sheet_id, args.credentials, args.dry_run)
+    except Exception as e:
+        print(f"Inference failed: {e}")
+        import traceback
+        traceback.print_exc()
+
+if __name__ == "__main__":
+    main()

scripts/match_payments.py

@@ -11,205 +11,7 @@ from html.parser import HTMLParser
 
 from attendance import get_members_with_fees
 from czech_utils import normalize, parse_month_references
-
+from sync_fio_to_sheets import get_sheets_service, DEFAULT_SPREADSHEET_ID
-
-# ---------------------------------------------------------------------------
-# Transaction fetching
-# ---------------------------------------------------------------------------
-
-class _FioTableParser(HTMLParser):
-    """Parse the second <table class="table"> on the Fio transparent page.
-
-    Columns: Datum | Částka | Typ | Název protiúčtu | Zpráva pro příjemce | KS | VS | SS | Poznámka
-    Indices:   0       1       2          3                   4              5    6    7      8
-    """
-
-    def __init__(self):
-        super().__init__()
-        self._table_count = 0
-        self._in_target_table = False
-        self._in_thead = False
-        self._in_row = False
-        self._in_cell = False
-        self._current_row: list[str] = []
-        self._rows: list[list[str]] = []
-        self._cell_text = ""
-
-    def handle_starttag(self, tag, attrs):
-        cls = dict(attrs).get("class", "")
-        if tag == "table" and "table" in cls.split():
-            self._table_count += 1
-            if self._table_count == 2:
-                self._in_target_table = True
-        if self._in_target_table:
-            if tag == "thead":
-                self._in_thead = True
-            if tag == "tr" and not self._in_thead:
-                self._in_row = True
-                self._current_row = []
-            if self._in_row and tag in ("td", "th"):
-                self._in_cell = True
-                self._cell_text = ""
-
-    def handle_endtag(self, tag):
-        if self._in_cell and tag in ("td", "th"):
-            self._in_cell = False
-            self._current_row.append(self._cell_text.strip())
-        if tag == "thead":
-            self._in_thead = False
-        if self._in_row and tag == "tr":
-            self._in_row = False
-            if self._current_row:
-                self._rows.append(self._current_row)
-        if tag == "table" and self._in_target_table:
-            self._in_target_table = False
-
-    def handle_data(self, data):
-        if self._in_cell:
-            self._cell_text += data
-
-    def get_rows(self) -> list[list[str]]:
-        return self._rows
-
-
-# Fio transparent table column indices
-_COL_DATE = 0
-_COL_AMOUNT = 1
-_COL_SENDER = 3
-_COL_MESSAGE = 4
-_COL_KS = 5
-_COL_VS = 6
-_COL_SS = 7
-_COL_NOTE = 8
-
-
-def _parse_czech_amount(s: str) -> float | None:
-    """Parse '1 500,00 CZK' to float."""
-    s = s.replace("\xa0", "").replace(" ", "").replace(",", ".")
-    s = re.sub(r"[A-Za-z]+", "", s).strip()
-    try:
-        return float(s)
-    except ValueError:
-        return None
-
-
-def _parse_czech_date(s: str) -> str | None:
-    """Parse 'DD.MM.YYYY' to 'YYYY-MM-DD'."""
-    s = s.strip()
-    for fmt in ("%d.%m.%Y", "%d/%m/%Y"):
-        try:
-            return datetime.strptime(s, fmt).strftime("%Y-%m-%d")
-        except ValueError:
-            continue
-    return None
-
-
-def fetch_transactions_transparent(
-    date_from: str, date_to: str
-) -> list[dict]:
-    """Fetch transactions from Fio transparent account HTML page.
-
-    Args:
-        date_from: D.M.YYYY format
-        date_to: D.M.YYYY format
-    """
-    url = (
-        f"https://ib.fio.cz/ib/transparent?a=2800359168"
-        f"&f={date_from}&t={date_to}"
-    )
-    req = urllib.request.Request(url)
-    with urllib.request.urlopen(req) as resp:
-        html = resp.read().decode("utf-8")
-
-    parser = _FioTableParser()
-    parser.feed(html)
-    rows = parser.get_rows()
-
-    transactions = []
-    for row in rows:
-        if len(row) < 5:
-            continue
-
-        def col(i):
-            return row[i].strip() if i < len(row) else ""
-
-        date_str = _parse_czech_date(col(_COL_DATE))
-        amount = _parse_czech_amount(col(_COL_AMOUNT))
-
-        if date_str is None or amount is None or amount <= 0:
-            continue
-
-        transactions.append({
-            "date": date_str,
-            "amount": amount,
-            "sender": col(_COL_SENDER),
-            "message": col(_COL_MESSAGE),
-            "vs": col(_COL_VS),
-        })
-
-    return transactions
-
-
-def fetch_transactions_api(
-    token: str, date_from: str, date_to: str
-) -> list[dict]:
-    """Fetch transactions via Fio REST API (JSON).
-
-    Args:
-        token: Fio API token
-        date_from: YYYY-MM-DD format
-        date_to: YYYY-MM-DD format
-    """
-    url = (
-        f"https://fioapi.fio.cz/v1/rest/periods/{token}"
-        f"/{date_from}/{date_to}/transactions.json"
-    )
-    req = urllib.request.Request(url)
-    with urllib.request.urlopen(req) as resp:
-        data = json.loads(resp.read().decode("utf-8"))
-
-    transactions = []
-    tx_list = data.get("accountStatement", {}).get("transactionList", {})
-    for tx in (tx_list.get("transaction") or []):
-        # Each field is {"value": ..., "name": ..., "id": ...} or null
-        def val(col_id):
-            col = tx.get(f"column{col_id}")
-            return col["value"] if col else ""
-
-        amount = float(val(1) or 0)
-        if amount <= 0:
-            continue  # Skip outgoing
-
-        date_raw = val(0) or ""
-        # API returns date as "YYYY-MM-DD+HHMM" or ISO format
-        date_str = date_raw[:10] if date_raw else ""
-
-        transactions.append({
-            "date": date_str,
-            "amount": amount,
-            "sender": str(val(10) or ""),     # column10 = sender name
-            "message": str(val(16) or ""),     # column16 = message for recipient
-            "vs": str(val(5) or ""),           # column5 = VS
-            "user_id": str(val(7) or ""),      # column7 = user identification
-            "sender_account": str(val(2) or ""),  # column2 = sender account
-        })
-
-    return transactions
-
-
-def fetch_transactions(date_from: str, date_to: str) -> list[dict]:
-    """Fetch transactions, using API if token available, else transparent page."""
-    token = os.environ.get("FIO_API_TOKEN", "").strip()
-    if token:
-        return fetch_transactions_api(token, date_from, date_to)
-
-    # Convert YYYY-MM-DD to DD.MM.YYYY for the transparent page URL
-    from_dt = datetime.strptime(date_from, "%Y-%m-%d")
-    to_dt = datetime.strptime(date_to, "%Y-%m-%d")
-    return fetch_transactions_transparent(
-        from_dt.strftime("%-d.%-m.%Y"),
-        to_dt.strftime("%-d.%-m.%Y"),
-    )
 
 
 # ---------------------------------------------------------------------------
@@ -255,35 +57,58 @@ def match_members(
 
     for name in member_names:
         variants = _build_name_variants(name)
-        # Full name match = high confidence
         full_name = variants[0] if variants else ""
+        parts = full_name.split()
+        
+        # 1. Full name match (exact sequence) = high confidence
         if full_name and full_name in normalized_text:
             matches.append((name, "auto"))
             continue
 
-        # Last name + first name both present = high confidence
+        # 2. Both first and last name present (any order) = high confidence
-        parts = full_name.split()
         if len(parts) >= 2:
             if parts[0] in normalized_text and parts[-1] in normalized_text:
                 matches.append((name, "auto"))
                 continue
 
-        # Nickname match = high confidence
+        # 3. Nickname + one part of the name = high confidence
-        if len(variants) > 1 and variants[1] in normalized_text:
+        nickname = ""
+        nickname_match = re.search(r"\(([^)]+)\)", name)
+        if nickname_match:
+            nickname = normalize(nickname_match.group(1))
+            if nickname and nickname in normalized_text:
+                # Nickname alone is often enough, but let's check if it's combined with a name part
                 matches.append((name, "auto"))
                 continue
 
-        # Last name only = lower confidence, but skip very common Czech surnames
+        # 4. Partial matches = review confidence
+        if len(parts) >= 2:
+            first_name = parts[0]
+            last_name = parts[-1]
             _COMMON_SURNAMES = {"novak", "novakova", "prach"}
-        if (
+            
-            len(parts) >= 2
+            # Match last name
-            and len(parts[-1]) >= 4
+            if len(last_name) >= 4 and last_name not in _COMMON_SURNAMES and last_name in normalized_text:
-            and parts[-1] not in _COMMON_SURNAMES
-            and parts[-1] in normalized_text
-        ):
                 matches.append((name, "review"))
                 continue
             
+            # Match first name (if not too short)
+            if len(first_name) >= 3 and first_name in normalized_text:
+                matches.append((name, "review"))
+                continue
+        elif len(parts) == 1:
+            # Single name member
+            if len(parts[0]) >= 4 and parts[0] in normalized_text:
+                matches.append((name, "review"))
+                continue
+
+    # --- Filtering ---
+    # If we have any "auto" matches, discard all "review" matches
+    auto_matches = [m for m in matches if m[1] == "auto"]
+    if auto_matches:
+        # If multiple auto matches, keep them (ambiguous but high priority)
+        return auto_matches
+
     return matches
 
 
@@ -291,6 +116,102 @@ def match_members(
 # Reconciliation
 # ---------------------------------------------------------------------------
 
+def infer_transaction_details(tx: dict, member_names: list[str]) -> dict:
+    """Infer member(s) and month(s) for a single transaction.
+    
+    Returns:
+        {
+            'members': [(name, confidence)],
+            'months': [YYYY-MM],
+            'matched_text': str
+        }
+    """
+    # Combine sender + message for searching
+    search_text = f"{tx.get('sender', '')} {tx.get('message', '')} {tx.get('user_id', '')}"
+    matched_members = match_members(search_text, member_names)
+    matched_months = parse_month_references(
+        tx.get("message", "") + " " + tx.get("user_id", "")
+    )
+
+    if not matched_members:
+        # Try matching sender name alone with more lenient matching
+        matched_members = match_members(tx.get("sender", ""), member_names)
+
+    if not matched_months:
+        # If no month specified, try to infer from payment date
+        tx_date = tx.get("date")
+        if tx_date:
+            try:
+                if isinstance(tx_date, (int, float)):
+                    # Handle Google Sheets serial date
+                    dt = datetime(1899, 12, 30) + timedelta(days=tx_date)
+                else:
+                    dt = datetime.strptime(str(tx_date), "%Y-%m-%d")
+                # Assume payment is for the current month
+                matched_months = [dt.strftime("%Y-%m")]
+            except (ValueError, TypeError):
+                pass
+
+    return {
+        "members": matched_members,
+        "months": matched_months,
+        "search_text": search_text
+    }
+
+
+def fetch_sheet_data(spreadsheet_id: str, credentials_path: str) -> list[dict]:
+    """Fetch all rows from the Google Sheet and convert to a list of dicts."""
+    service = get_sheets_service(credentials_path)
+    sheet = service.spreadsheets()
+    
+    result = sheet.values().get(
+        spreadsheetId=spreadsheet_id,
+        range="A1:Z",
+        valueRenderOption="UNFORMATTED_VALUE"
+    ).execute()
+    rows = result.get("values", [])
+    if not rows:
+        return []
+    
+    header = rows[0]
+    def get_col_index(label):
+        normalized_label = label.lower().strip()
+        for i, h in enumerate(header):
+            if h.lower().strip() == normalized_label:
+                return i
+        return -1
+
+    idx_date = get_col_index("Date")
+    idx_amount = get_col_index("Amount") 
+    idx_manual = get_col_index("manual fix")
+    idx_person = get_col_index("Person")
+    idx_purpose = get_col_index("Purpose")
+    idx_inferred_amount = get_col_index("Inferred Amount")
+    idx_sender = get_col_index("Sender")
+    idx_message = get_col_index("Message")
+    idx_bank_id = get_col_index("Bank ID")
+
+    transactions = []
+    for row in rows[1:]:
+        def get_val(idx):
+            return row[idx] if idx != -1 and idx < len(row) else ""
+
+        tx = {
+            "date": get_val(idx_date),
+            "amount": get_val(idx_amount),
+            "manual_fix": get_val(idx_manual),
+            "person": get_val(idx_person),
+            "purpose": get_val(idx_purpose),
+            "inferred_amount": get_val(idx_inferred_amount),
+            "sender": get_val(idx_sender),
+            "message": get_val(idx_message),
+            "bank_id": get_val(idx_bank_id),
+        }
+        transactions.append(tx)
+    
+    return transactions
+
+
 def reconcile(
     members: list[tuple[str, str, dict[str, int]]],
     sorted_months: list[str],
@@ -322,41 +243,54 @@ def reconcile(
     credits: dict[str, int] = {}
 
     for tx in transactions:
-        # Combine sender + message for searching
+        # Use sheet columns if they exist, otherwise fallback to inference
-        search_text = f"{tx['sender']} {tx['message']} {tx.get('user_id', '')}"
+        person_str = str(tx.get("person", "")).strip()
-        matched_members = match_members(search_text, member_names)
+        purpose_str = str(tx.get("purpose", "")).strip()
-        matched_months = parse_month_references(
-            tx["message"] + " " + tx.get("user_id", "")
-        )
         
-        if not matched_members:
+        # Strip markers like [?]
-            # Try matching sender name alone with more lenient matching
+        person_str = re.sub(r"\[\?\]\s*", "", person_str)
-            matched_members = match_members(tx["sender"], member_names)
         
-        if not matched_members:
+        if person_str and purpose_str:
-            unmatched.append(tx)
+            # We have pre-matched data (either from script or manual)
-            continue
+            # Support multiple people/months in the comma-separated string
+            matched_members = [(p.strip(), "auto") for p in person_str.split(",") if p.strip()]
+            matched_months = [m.strip() for m in purpose_str.split(",") if m.strip()]
             
-        if not matched_months:
+            # Use Inferred Amount if available, otherwise bank Amount
-            # If no month specified, try to infer from payment date
+            amount = tx.get("inferred_amount")
-            tx_date = tx["date"]
+            if amount is None or amount == "":
-            if tx_date:
+                amount = tx.get("amount", 0)
             try:
-                    dt = datetime.strptime(tx_date, "%Y-%m-%d")
+                amount = float(amount)
-                    # Assume payment is for the current month
+            except (ValueError, TypeError):
-                    matched_months = [dt.strftime("%Y-%m")]
+                amount = 0
-                except ValueError:
+        else:
-                    pass
+            # Fallback to inference (for rows not yet processed by infer_payments.py)
+            inference = infer_transaction_details(tx, member_names)
+            matched_members = inference["members"]
+            matched_months = inference["months"]
+            amount = tx.get("amount", 0)
+            try:
+                amount = float(amount)
+            except (ValueError, TypeError):
+                amount = 0
 
-        if not matched_months:
+        if not matched_members or not matched_months:
             unmatched.append(tx)
             continue
 
         # Allocate payment across matched members and months
         num_allocations = len(matched_members) * len(matched_months)
-        per_allocation = tx["amount"] / num_allocations if num_allocations > 0 else 0
+        per_allocation = amount / num_allocations if num_allocations > 0 else 0
 
         for member_name, confidence in matched_members:
+            # If we matched via sheet 'Person' column, name might be partial or have markers
+            # but usually it's the exact member name from get_members_with_fees.
+            # Let's ensure it exists in our ledger.
+            if member_name not in ledger:
+                # Try matching by base name if it was Jan Novak (Kačerr) etc.
+                pass
+
             for month_key in matched_months:
                 entry = {
                     "amount": per_allocation,
@@ -372,16 +306,26 @@ def reconcile(
                     # Future month — track as credit
                     credits[member_name] = credits.get(member_name, 0) + int(per_allocation)
 
+    # Calculate final total balances (window + off-window credits)
+    final_balances: dict[str, int] = {}
+    for name in member_names:
+        window_balance = sum(
+            int(mdata["paid"]) - mdata["expected"] 
+            for mdata in ledger[name].values()
+        )
+        final_balances[name] = window_balance + credits.get(name, 0)
+
     return {
         "members": {
             name: {
                 "tier": member_tiers[name],
                 "months": ledger[name],
+                "total_balance": final_balances[name]
             }
             for name in member_names
         },
         "unmatched": unmatched,
-        "credits": credits,
+        "credits": final_balances, # Redefine credits as any positive total balance
     }
 
 
@@ -452,12 +396,30 @@ def print_report(result: dict, sorted_months: list[str]):
     balance = total_paid - total_expected
     print(f" | {f'Expected: {total_expected}, Paid: {int(total_paid)}, Balance: {balance:+d}'}")
 
-    # --- Credits ---
+    # --- Credits (Total Surplus) ---
-    if result["credits"]:
+    all_credits = {
-        print(f"\n{'CREDITS (advance payments for future months)':}")
+        name: data["total_balance"]
-        for name, amount in sorted(result["credits"].items()):
+        for name, data in result["members"].items()
+        if data["total_balance"] > 0
+    }
+    
+    if all_credits:
+        print(f"\n{'TOTAL CREDITS (advance payments or surplus):'}")
+        for name, amount in sorted(all_credits.items()):
             print(f"  {name}: {amount} CZK")
 
+    # --- Debts (Missing Payments) ---
+    all_debts = {
+        name: data["total_balance"]
+        for name, data in result["members"].items()
+        if data["total_balance"] < 0
+    }
+
+    if all_debts:
+        print(f"\n{'TOTAL DEBTS (missing payments):'}")
+        for name, amount in sorted(all_debts.items()):
+            print(f"  {name}: {abs(amount)} CZK")
+
     # --- Unmatched transactions ---
     if result["unmatched"]:
         print(f"\n{'UNMATCHED TRANSACTIONS (need manual review)':}")
@@ -499,13 +461,14 @@ def main():
         description="Match bank payments against expected attendance fees."
     )
     parser.add_argument(
-        "--from", dest="date_from", default="2025-12-01",
+        "--sheet-id", default=DEFAULT_SPREADSHEET_ID, help="Google Sheet ID"
-        help="Start date YYYY-MM-DD (default: 2025-12-01)",
     )
     parser.add_argument(
-        "--to", dest="date_to",
+        "--credentials", default=".secret/fuj-management-bot-credentials.json",
-        default=datetime.now().strftime("%Y-%m-%d"),
+        help="Path to Google API credentials JSON"
-        help="End date YYYY-MM-DD (default: today)",
+    )
+    parser.add_argument(
+        "--bank", action="store_true", help="Scrape bank instead of using Sheet data"
     )
     args = parser.parse_args()
 
@@ -515,9 +478,15 @@ def main():
         print("No attendance data found.")
         return
 
-    print(f"Fetching transactions from {args.date_from} to {args.date_to}...")
+    if args.bank:
+        print(f"Fetching transactions from Fio bank ({args.date_from} to {args.date_to})...")
+        from fio_utils import fetch_transactions
         transactions = fetch_transactions(args.date_from, args.date_to)
-    print(f"Found {len(transactions)} incoming transactions.\n")
+    else:
+        print(f"Fetching transactions from Google Sheet ({args.sheet_id})...")
+        transactions = fetch_sheet_data(args.sheet_id, args.credentials)
+    
+    print(f"Processing {len(transactions)} transactions.\n")
 
     result = reconcile(members, sorted_months, transactions)
     print_report(result, sorted_months)

scripts/sync_fio_to_sheets.py

@@ -0,0 +1,210 @@
+#!/usr/bin/env python3
+"""Sync Fio bank transactions to a Google Sheet intermediary ledger."""
+
+import argparse
+import hashlib
+import os
+import pickle
+from datetime import datetime, timedelta
+
+from google.auth.transport.requests import Request
+from google_auth_oauthlib.flow import InstalledAppFlow
+from google.oauth2 import service_account
+from googleapiclient.discovery import build
+
+from fio_utils import fetch_transactions
+
+# Configuration
+DEFAULT_SPREADSHEET_ID = "1Om0YPoDVCH5cV8BrNz5LG5eR5MMU05ypQC7UMN1xn_Y"
+SCOPES = ["https://www.googleapis.com/auth/spreadsheets"]
+TOKEN_FILE = "token.pickle"
+COLUMN_LABELS = ["Date", "Amount", "manual fix", "Person", "Purpose", "Inferred Amount", "Sender", "VS", "Message", "Bank ID", "Sync ID"]
+def get_sheets_service(credentials_path: str):
+    """Authenticate and return the Google Sheets API service."""
+    if not os.path.exists(credentials_path):
+        raise FileNotFoundError(f"Credentials file not found: {credentials_path}")
+
+    # Check if it's a service account
+    import json
+    with open(credentials_path, "r") as f:
+        creds_data = json.load(f)
+    
+    if creds_data.get("type") == "service_account":
+        creds = service_account.Credentials.from_service_account_file(
+            credentials_path, scopes=SCOPES
+        )
+    else:
+        # Fallback to OAuth2 flow
+        creds = None
+        if os.path.exists(TOKEN_FILE):
+            with open(TOKEN_FILE, "rb") as token:
+                creds = pickle.load(token)
+
+        if not creds or not creds.valid:
+            if creds and creds.expired and creds.refresh_token:
+                creds.refresh(Request())
+            else:
+                flow = InstalledAppFlow.from_client_secrets_file(credentials_path, SCOPES)
+                creds = flow.run_local_server(port=0)
+
+            with open(TOKEN_FILE, "wb") as token:
+                pickle.dump(creds, token)
+
+    return build("sheets", "v4", credentials=creds)
+
+
+def generate_sync_id(tx: dict) -> str:
+    """Generate a unique SHA-256 hash for a transaction.
+    
+    Hash components: date|amount|currency|sender|vs|message|bank_id
+    """
+    components = [
+        str(tx.get("date", "")),
+        str(tx.get("amount", "")),
+        str(tx.get("currency", "CZK")),
+        str(tx.get("sender", "")),
+        str(tx.get("vs", "")),
+        str(tx.get("message", "")),
+        str(tx.get("bank_id", "")),
+    ]
+    raw_str = "|".join(components).lower()
+    return hashlib.sha256(raw_str.encode("utf-8")).hexdigest()
+
+
+def sort_sheet_by_date(service, spreadsheet_id):
+    """Sort the sheet by the Date column (Column B)."""
+    # Get the sheet ID (gid) of the first sheet
+    spreadsheet = service.spreadsheets().get(spreadsheetId=spreadsheet_id).execute()
+    sheet_id = spreadsheet['sheets'][0]['properties']['sheetId']
+
+    requests = [{
+        "sortRange": {
+            "range": {
+                "sheetId": sheet_id,
+                "startRowIndex": 1, # Skip header
+                "endRowIndex": 10000 
+            },
+            "sortSpecs": [{
+                "dimensionIndex": 0, # Column A (Date)
+                "sortOrder": "ASCENDING"
+            }]
+        }
+    }]
+    
+    service.spreadsheets().batchUpdate(
+        spreadsheetId=spreadsheet_id,
+        body={"requests": requests}
+    ).execute()
+    print("Sheet sorted by date.")
+
+
+def sync_to_sheets(spreadsheet_id: str, credentials_path: str, days: int = None, date_from_str: str = None, date_to_str: str = None, sort_by_date: bool = False):
+    print(f"Connecting to Google Sheets using {credentials_path}...")
+    service = get_sheets_service(credentials_path)
+    sheet = service.spreadsheets()
+
+    # 1. Fetch existing IDs from Column G (last column in A-G range)
+    print(f"Reading existing sync IDs from sheet...")
+    try:
+        result = sheet.values().get(
+            spreadsheetId=spreadsheet_id,
+            range="A1:K" # Include header and all columns to check Sync ID
+        ).execute()
+        values = result.get("values", [])
+        
+        # Check and insert labels if missing
+        if not values or values[0] != COLUMN_LABELS:
+            print("Inserting column labels...")
+            sheet.values().update(
+                spreadsheetId=spreadsheet_id,
+                range="A1",
+                valueInputOption="USER_ENTERED",
+                body={"values": [COLUMN_LABELS]}
+            ).execute()
+            existing_ids = set()
+        else:
+            # Sync ID is now the last column (index 10)
+            existing_ids = {row[10] for row in values[1:] if len(row) > 10}
+    except Exception as e:
+        print(f"Error reading sheet (maybe empty?): {e}")
+        existing_ids = set()
+
+    # 2. Fetch Fio transactions
+    if date_from_str and date_to_str:
+        df_str = date_from_str
+        dt_str = date_to_str
+    else:
+        now = datetime.now()
+        date_to = now
+        date_from = now - timedelta(days=days or 30)
+        df_str = date_from.strftime("%Y-%m-%d")
+        dt_str = date_to.strftime("%Y-%m-%d")
+
+    print(f"Fetching Fio transactions from {df_str} to {dt_str}...")
+    transactions = fetch_transactions(df_str, dt_str)
+    print(f"Found {len(transactions)} transactions.")
+
+    # 3. Filter for new transactions
+    new_rows = []
+    for tx in transactions:
+        sync_id = generate_sync_id(tx)
+        if sync_id not in existing_ids:
+            # Schema: Date | Amount | Manual | Person | Purpose | Inferred Amount | Sender | VS | Message | Bank ID | Sync ID
+            new_rows.append([
+                tx.get("date", ""),
+                tx.get("amount", ""),
+                "", # Manual
+                "", # Person
+                "", # Purpose
+                "", # Inferred Amount
+                tx.get("sender", ""),
+                tx.get("vs", ""),
+                tx.get("message", ""),
+                tx.get("bank_id", ""),
+                sync_id,
+            ])
+
+    if not new_rows:
+        print("No new transactions to sync.")
+        return
+
+    # 4. Append to sheet
+    print(f"Appending {len(new_rows)} new transactions to the sheet...")
+    body = {"values": new_rows}
+    sheet.values().append(
+        spreadsheetId=spreadsheet_id,
+        range="A2", # Appends to the end of the sheet
+        valueInputOption="USER_ENTERED",
+        body=body
+    ).execute()
+    print("Sync completed successfully.")
+
+    if sort_by_date:
+        sort_sheet_by_date(service, spreadsheet_id)
+
+
+def main():
+    parser = argparse.ArgumentParser(description="Sync Fio transactions to Google Sheets.")
+    parser.add_argument("--days", type=int, default=30, help="Days to look back (default: 30)")
+    parser.add_argument("--sheet-id", default=DEFAULT_SPREADSHEET_ID, help="Google Sheet ID")
+    parser.add_argument("--credentials", default="credentials.json", help="Path to Google API credentials JSON")
+    parser.add_argument("--from", dest="date_from", help="Start date YYYY-MM-DD")
+    parser.add_argument("--to", dest="date_to", help="End date YYYY-MM-DD")
+    parser.add_argument("--sort-by-date", action="store_true", help="Sort the sheet by date after sync")
+    args = parser.parse_args()
+
+    try:
+        sync_to_sheets(
+            spreadsheet_id=args.sheet_id, 
+            credentials_path=args.credentials,
+            days=args.days,
+            date_from_str=args.date_from,
+            date_to_str=args.date_to,
+            sort_by_date=args.sort_by_date
+        )
+    except Exception as e:
+        print(f"Sync failed: {e}")
+
+
+if __name__ == "__main__":
+    main()

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