Gemma 4 31B Instruct (Venice) (thinking on) on Rebalance to target weights with whole shares and highest-cost-first tax lots

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        "reasoning_content": "The objective is to create a Python script `solve.py` that calculates a rebalancing plan for a portfolio based on target weights, using a specific lot selection strategy (highest-cost-first) and calculating tax implications.\n\n    *   `as_of`: ISO date.\n    *   `cash`: Initial cash.\n    *   `prices`: Symbol to price mapping.\n    *   `targets`: Symbol to target weight mapping.\n    *   `lots`: List of tax lots (id, symbol, shares, cost_per_share, acquired).\n    *   `short_term_rate`: Tax rate for short-term gains.\n    *   `long_term_rate`: Tax rate for long-term gains.\n\n    *   Use `decimal.Decimal` for all monetary calculations.\n    *   `total_value` = `cash` + sum of (shares * price) for all symbols.\n    *   `target_value[symbol]` = `target_weight[symbol] * total_value`.\n    *   Symbols processed in alphabetical order.\n    *   **Sells first**:\n        *   If `current_value > target_value`, sell `floor((current_value - target_value) / price)` shares.\n        *   Cannot sell more than held.\n        *   Lot selection: Highest `cost_per_share` first, then earliest `acquired`, then `id`.\n        *   Gain = `(price - cost_per_share) * shares_sold`.\n        *   Term: Long-term if `(as_of - acquired) > 365 days`, else short-term.\n    *   **Buys second**:\n        *   If `target_value > current_value`, buy `floor(min(target_value - current_value, cash_available) / price)` shares.\n        *   `cash_available` includes proceeds from all sells.\n    *   **Tax Calculation**:\n        *   `realized_short_term` = sum of short-term gains.\n        *   `realized_long_term` = sum of long-term gains.\n        *   `estimated_tax` = `max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`.\n    *   **Weights After**:\n        *   `weights_after[symbol] = (shares_after * price) / total_value`.\n        *   Include all symbols that were either held or targeted.\n\n    *   `total_value`: Decimal.\n    *   `trades`: List of `{\"symbol\", \"side\", \"shares\"}` sorted by symbol then side.\n    *   `lot_sales`: List of `{\"lot_id\", \"shares\", \"gain\", \"term\"}` in order of use.\n    *   `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after`: Decimals.\n    *   `weights_after`: Symbol to weight mapping.\n\n    *   `datetime.date.fromisoformat` for dates.\n    *   `decimal.Decimal` for precision.\n    *   `math.floor` or `Decimal`'s floor method.\n    *   `json` for input/output.\n\n    *   Read `input.json`.\n    *   Calculate `total_value`.\n    *   Identify all symbols (from `prices`, `targets`, and `lots`).\n    *   Sort symbols alphabetically.\n    *   Perform sells:\n        *   For each symbol in alphabetical order:\n            *   Calculate `current_value` and `target_value`.\n            *   If `current_value > target_value`:\n                *   Calculate shares to sell: `floor((current_value - target_value) / price)`.\n                *   Ensure shares to sell <= total shares held.\n                *   Select lots based on criteria (highest cost, then earliest acquired, then id).\n                *   Update cash, record trades, record lot sales, update realized gains.\n    *   Perform buys:\n        *   For each symbol in alphabetical order:\n            *   Calculate `current_value` (after sells) and `target_value`.\n            *   If `target_value > current_value`:\n                *   Calculate shares to buy: `floor(min(target_value - current_value, cash_available) / price)`.\n                *   Update cash, record trades.\n    *   Calculate `estimated_tax`.\n    *   Calculate `weights_after`.\n    *   Format and write `answer.json`.\n\n    *   `total_value` is computed *once* at the beginning.\n    *   `current_value` and `target_value` for each symbol are computed *once* before any trade.\n    *   Wait, the rules say: \"Current value and target value (= weight * total_value) of each symbol are computed once, before any trade.\"\n    *   Let's re-read: \"Sells first: if current > target, sell floor((current - target) / price) shares... Then buys, again alphabetically: if target > current, buy floor(min(target - current, cash available now) / price) shares\".\n    *   This means `current` and `target` are fixed based on the initial state.\n    *   Wait, \"where cash available includes all sale proceeds and decreases with each buy.\"\n    *   So:\n        1.  `total_value` = `cash` + sum(shares * price).\n        2.  For each symbol: `current_val = shares * price`, `target_val = weight * total_value`.\n        3.  Sells (alphabetical):\n            If `current_val > target_val`:\n                `shares_to_sell = floor((current_val - target_val) / price)`\n                `shares_to_sell = min(shares_to_sell, total_shares_held)`\n                Sell these shares using the lot selection rules.\n                `cash += shares_to_sell * price`\n        4.  Buys (alphabetical):\n            If `target_val > current_val`:\n                `shares_to_buy = floor(min(target_val - current_val, cash) / price)`\n                Buy these shares.\n                `cash -= shares_to_buy * price`\n\n    *   Lot selection: \"highest `cost_per_share` first, ties by earlier `acquired`, then by `id`\".\n    *   Sort lots for a symbol: `(-cost_per_share, acquired, id)`.\n\n    *   Date difference: `(as_of - acquired).days > 365` is long-term.\n\n    *   `weights_after[symbol] = shares_held_after * price / total_value`.\n    *   Include all symbols held or targeted.\n\n    *   `ROUND_HALF_UP` to cents for money.\n    *   Weights to 6 decimals.\n\n    *   `total_value` is a Decimal.\n    *   `cash` is a Decimal.\n    *   `prices` are Decimals.\n    *   `targets` are Decimals.\n    *   `lots` shares are Decimals (though they are whole shares, let's use Decimal for consistency).\n    *   `cost_per_share` is Decimal.\n\n    *   `trades` sorted by symbol then side.\n    *   `lot_sales` in order of use.\n    *   `weights_after` for every symbol held or targeted.\n\n    *   `total_value` is computed once.\n    *   `current_value` and `target_value` are computed once.\n    *   Sells are processed alphabetically.\n    *   Buys are processed alphabetically.\n    *   Cash is updated after each trade.\n    *   Lot selection is correct.\n    *   Tax calculation is correct.\n    *   Weights are calculated based on final shares.\n\n    *   `total_value` = `cash` + sum(shares * price).\n    *   `current_value[symbol]` = `shares_held[symbol] * price[symbol]`.\n    *   `target_value[symbol]` = `targets[symbol] * total_value`.\n    *   Sells:\n        For symbol in sorted(all_symbols):\n            if `current_value[symbol] > target_value[symbol]`:\n                `shares_to_sell = floor((current_value[symbol] - target_value[symbol]) / price[symbol])`\n                `shares_to_sell = min(shares_to_sell, shares_held[symbol])`\n                ... sell shares ...\n    *   Buys:\n        For symbol in sorted(all_symbols):\n            if `target_value[symbol] > current_value[symbol]`:\n                `shares_to_buy = floor(min(target_value[symbol] - current_value[symbol], cash) / price[symbol])`\n                ... buy shares ...\n\n    *   Wait, \"a held symbol missing from `targets` has target 0; a target symbol may have no lots\".\n    *   So `all_symbols` should be the union of symbols in `prices`, `targets`, and `lots`.\n\n    *   `realized_short_term` = sum of gains for lots where `(as_of - acquired).days <= 365`.\n    *   `realized_long_term` = sum of gains for lots where `(as_of - acquired).days > 365`.\n    *   `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`.\n\n    *   \"round with ROUND_HALF_UP to cents when writing.\"\n    *   This applies to `total_value`, `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after`, and `gain` in `lot_sales`.\n    *   Weights are 6 decimals.\n\n    *   `trades` sorted by symbol then side.\n    *   Wait, \"sorted by symbol then side\". If symbol is \"AAPL\", and we have both buy and sell? (Not possible in this logic, but the rule says so).\n    *   Actually, the rules say \"Sells first... Then buys\". So for a single symbol, we can't have both a buy and a sell. But we should still sort them.\n\n    *   `lot_sales` in the order lots are used (symbols alphabetically).\n    *   This means as we iterate through symbols alphabetically and perform sells, we append to `lot_sales`.\n\n    *   `weights_after` for every symbol that is held or targeted.\n\n    *   `Decimal(str(x))` for all numbers.\n    *   `ROUND_HALF_UP` for cents.\n    *   `floor` for shares.\n\n    *   `as_of`: \"2023-01-01\"\n    *   `acquired`: \"2022-01-01\"\n    *   `diff = (date(2023,1,1) - date(2022,1,1)).days`\n    *   `diff` is 365.\n    *   Rule: \"long-term if (as_of - acquired) in days is greater than 365, otherwise short-term.\"\n    *   So 365 days is short-term. 366 days is long-term.\n\n    *   `total_value` is computed once.\n    *   `current_value` and `target_value` are computed once.\n    *   Sells are processed alphabetically.\n    *   Buys are processed alphabetically.\n    *   Cash is updated.\n    *   Lot selection: highest cost, then earliest acquired, then id.\n    *   Tax: no netting between short and long term.\n    *   Weights: 6 decimals.\n    *   Money: ROUND_HALF_UP to 2 decimals.\n\n    *   `Decimal` doesn't have a `floor` method that returns an integer directly in the same way `math.floor` does, but `Decimal(x).quantize(Decimal('1'), rounding=ROUND_FLOOR)` works. Or just `int(x // 1)`.\n    *   Wait, `(current_value - target_value) / price` might be something like `10.9999999999`. `floor` should be `10`.\n    *   Using `(current_value - target_value) / price` with `Decimal` and then `math.floor()` should be fine.\n\n    *   `total_value`: `Decimal`\n    *   `trades`: `list` of `dict`\n    *   `lot_sales`: `list` of `dict`\n    *   `realized_short_term`: `Decimal`\n    *   `realized_long_term`: `Decimal`\n    *   `estimated_tax`: `Decimal`\n    *   `cash_after`: `Decimal`\n    *   `weights_after`: `dict` of `Decimal` (6 decimals)\n\n    *   `total_value` = `cash` + sum(shares * price)\n    *   `current_value[symbol]` = `shares_held[symbol] * price[symbol]`\n    *   `target_value[symbol]` = `targets[symbol] * total_value`\n    *   Sells:\n        For symbol in sorted(all_symbols):\n            if `current_value[symbol] > target_value[symbol]`:\n                `shares_to_sell = floor((current_value[symbol] - target_value[symbol]) / price[symbol])`\n                `shares_to_sell = min(shares_to_sell, shares_held[symbol])`\n                ...\n    *   Buys:\n        For symbol in sorted(all_symbols):\n            if `target_value[symbol] > current_value[symbol]`:\n                `shares_to_buy = floor(min(target_value[symbol] - current_value[symbol], cash) / price[symbol])`\n                ...\n\n    *   Wait, if `target_value` is `100.00` and `current_value` is `90.00`, `target_value - current_value` is `10.00`. If `price` is `3.00`, `shares_to_buy` is `floor(10.00 / 3.00) = 3`.\n    *   If `cash` is `5.00`, `shares_to_buy` is `floor(min(10.00, 5.00) / 3.00) = floor(5.00 / 3.00) = 1`.\n    *   This matches the rules.\n\n    *   `lot_sales` should contain `lot_id`, `shares`, `gain`, `term`.\n    *   `gain` = `(price - cost_per_share) * shares_sold`.\n    *   `term` = \"short\" or \"long\".\n\n    *   `weights_after[symbol] = shares_held_after * price / total_value`.\n    *   Include all symbols that were either held or targeted.\n\n    *   `Decimal(str(x)).quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)` for money.\n    *   `Decimal(str(x)).quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)` for weights? The rule says \"6 decimals\", usually this means rounding or formatting. Let's use `quantize` with `ROUND_HALF_UP` for weights too, or just format them. Wait, the rule says \"weights_after[symbol] = shares held after trades * price / total_value (6 decimals)\". Let's use `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`.\n\n    *   `total_value` is computed once.\n    *   `current_value` and `target_value` are computed once.\n    *   Sells are processed alphabetically.\n    *   Buys are processed alphabetically.\n    *   Cash is updated.\n    *   Lot selection: highest cost, then earliest acquired, then id.\n    *   Tax: no netting between short and long term.\n    *   Weights: 6 decimals.\n    *   Money: ROUND_HALF_UP to 2 decimals.\n\n    *   Wait, \"a target symbol may have no lots\". This means we need to handle symbols that are in `targets` but not in `lots`.\n    *   `all_symbols` = set(prices.keys()) | set(targets.keys()) | set(lot.symbol for lot in lots).\n\n    *   `total_value` is computed once.\n    *   `current_value` and `target_value` are computed once.\n    *   Sells are processed alphabetically.\n    *   Buys are processed alphabetically.\n    *   Cash is updated.\n    *   Lot selection: highest cost, then earliest acquired, then id.\n    *   Tax: no netting between short and long term.\n    *   Weights: 6 decimals.\n    *   Money: ROUND_HALF_UP to 2 decimals.\n\n    *   Wait, \"Sells first: if current > target, sell floor((current - target) / price) shares (never more than held).\"\n    *   \"Then buys, again alphabetically: if target > current, buy floor(min(target - current, cash available now) / price) shares\".\n    *   This means we use the *initial* `current` and `target` values for both sells and buys.\n\n    *   Let's double check the lot selection: \"highest `cost_per_share` first, ties by earlier `acquired`, then by `id`\".\n    *   So we sort lots by `(-cost_per_share, acquired, id)`.\n\n    *   Let's double check the tax: \"estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate\".\n    *   This means if `realized_short_term` is negative, it doesn't offset `realized_long_term`.\n\n    *   Let's double check the weights: \"weights_after[symbol] = shares held after trades * price / total_value (6 decimals), for every symbol that is held or targeted.\"\n    *   This means any symbol that was in `lots` or in `targets`.\n\n    *   Let's double check the `total_value` calculation: `total_value = cash + sum over symbols of (shares held * price)`.\n    *   This is the initial total value.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after = initial_cash + sum(shares_sold * price) - sum(shares_bought * price)`.\n\n    *   Wait, the `estimated_tax` is not subtracted from `cash_after`. The rules say \"estimated_tax = ...\", but it doesn't say to subtract it from `cash_after`. \"cash_after\" should be the cash after the trades.\n\n    *   Let's double check the `lot_sales` order: \"in the order lots are used (symbols alphabetically)\".\n    *   Since we process symbols alphabetically and then sell lots within each symbol, this is straightforward.\n\n    *   Let's double check the `trades` sorting: \"sorted by symbol then side\".\n    *   Since we have only one trade per symbol (either buy or sell), sorting by symbol is enough. But let's sort by symbol and then side just in case.\n\n    *   Wait, \"a lot can be partly sold\".\n    *   So if we need to sell 10 shares and the first lot has 6, we take all 6 and then 4 from the next lot.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`: they should be integers (whole shares).\n\n    *   Let's double check the `gain` in `lot_sales`: `(price - cost_per_share) * shares_sold`. This should be a Decimal rounded to 2 decimals.\n\n    *   Let's double check the `total_value` in the output: \"total_value: ..., trades: ...\". It should be rounded to 2 decimals.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` in the output: all rounded to 2 decimals.\n\n    *   Wait, \"weights_after[symbol] = shares held after trades * price / total_value (6 decimals)\".\n    *   Let's use `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`.\n\n    *   One last thing: \"a held symbol missing from `targets` has target 0\".\n    *   So `target_weight = targets.get(symbol, Decimal('0'))`.\n\n    *   Let's refine the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n\n    *   Wait, the `prices` dictionary might not have all the symbols. But the rules say \"prices (symbol -> price)\". If a symbol is in `targets` or `lots` but not in `prices`, what should we do? The problem says \"prices (symbol -> price)\", implying all necessary prices are provided.\n\n    *   Let's refine the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n\n    *   Let's refine the `lot_selection` process:\n        For each symbol, sort its lots:\n        `symbol_lots = [lot for lot in lots if lot['symbol'] == symbol]`\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), x['acquired'], x['id']))`\n\n    *   Wait, the `acquired` date is a string. We should convert it to a `date` object for sorting and for the 365-day check.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = floor((current_value - target_value) / price)`\n        `shares_to_sell = min(shares_to_sell, shares_held[symbol])`\n        If `shares_to_sell > 0`:\n            ... sell ...\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = floor(min(target_value - current_value, cash) / price)`\n        If `shares_to_buy > 0`:\n            ... buy ...\n\n    *   Wait, the `cash` used in `shares_to_buy` is the `cash` *after* all sells have been processed.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (price - cost_per_share) * shares_sold`\n        This should be rounded to 2 decimals.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term`:\n        These are the sums of the gains. Should they be rounded at the end or should each gain be rounded first?\n        \"realized_short_term and realized_long_term are the sums of gains (can be negative).\"\n        Usually, this means you sum the exact gains and then round the final result. Let's do that.\n\n    *   Wait, the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This should also be rounded to 2 decimals.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held_after * price) / total_value`\n        This should be rounded to 6 decimals.\n\n    *   Let's double check the `total_value` in the output:\n        `total_value` should be rounded to 2 decimals.\n\n    *   Let's double check the `cash_after` in the output:\n        `cash_after` should be rounded to 2 decimals.\n\n    *   Let's double check the `trades` sorting:\n        \"sorted by symbol then side\".\n        If we have a trade for \"AAPL\" and \"MSFT\", \"AAPL\" comes first.\n        If we have \"AAPL\" buy and \"AAPL\" sell (not possible here), \"AAPL\" buy would come before \"AAPL\" sell? No, \"buy\" comes before \"sell\" alphabetically. But we only have one trade per symbol.\n\n    *   Wait, the `lot_sales` order: \"in the order lots are used (symbols alphabetically)\".\n        This means we iterate through symbols alphabetically, and for each symbol, we sell lots in the specified order.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n\n    *   Let's double check the `total_value` calculation again:\n        `total_value = cash + sum(shares_held[symbol] * prices[symbol] for symbol in all_symbols)`\n        Wait, `prices` might not have all symbols. Let's use `prices.get(symbol, Decimal('0'))`. But the problem says `prices` is `symbol -> price`, so it should have them.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = floor((current_value - target_value) / prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, shares_held[symbol])`\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = floor(min(target_value - current_value, cash) / prices[symbol])`\n\n    *   Wait, if `prices[symbol]` is 0, we might have a division by zero. But prices should be positive.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - acquired_date).days`\n        `term = \"long\" if days > 365 else \"short\"`\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        `all_symbols` is the union of symbols in `prices`, `targets`, and `lots`. This should cover it.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n\n    *   Let's double check the `cash_after` in the output:\n        It should be the final `cash` after all trades.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax` in the output:\n        They should be rounded to 2 decimals.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n\n    *   Let's double check the `weights_after` rounding:\n        `weights_after[symbol] = (shares_held_after * prices[symbol] / total_value).quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `total_value` rounding:\n        `total_value.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `cash_after` rounding:\n        `cash_after.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `realized_short_term` rounding:\n        `realized_short_term.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `realized_long_term` rounding:\n        `realized_long_term.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `estimated_tax` rounding:\n        `estimated_tax.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n\n    *   Wait, the `shares` in `trades` and `lot_sales` should be integers. Let's make sure they are.\n\n    *   Let's double check the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is a safer way to do `floor`.\n\n    *   Let's double check the `total_value` calculation again:\n        `total_value = cash + sum(shares_held[symbol] * prices[symbol] for symbol in all_symbols)`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Wait, the `shares_held` should be updated after each trade.\n        For sells: `shares_held[symbol] -= shares_to_sell`\n        For buys: `shares_held[symbol] += shares_to_buy`\n\n    *   Let's double check the `lot_sales` shares:\n        If we sell 10 shares and the first lot has 6, the first `lot_sale` has 6 shares and the second has 4.\n\n    *   Let's double check the `lot_sales` gain:\n        For the first lot: `gain = (price - cost_per_share) * 6`\n        For the second lot: `gain = (price - cost_per_share) * 4`\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        They should be the sum of these gains.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n\n    *   Wait, the `total_value` is used in the denominator for `weights_after`. Should it be the initial `total_value` or the final `total_value`?\n        \"weights_after[symbol] = shares held after trades * price / total_value\"\n        The `total_value` is computed once, before any trade. So we use the initial `total_value`.\n\n    *   Let's double check the `total_value` in the output:\n        \"total_value: ..., trades: ...\"\n        This should be the initial `total_value`.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), x['acquired'], x['id']))`\n        Wait, `x['acquired']` is a string. We should convert it to a `date` object for sorting.\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is correct.\n\n    *   Let's double check the `total_value` in the output:\n        It should be the initial `total_value`.\n        This is correct.\n\n    *   Let's double check the `trades` sorting:\n        `trades.sort(key=lambda x: (x['symbol'], x['side']))`\n        This is correct.\n\n    *   Let's double check the `lot_sales` order:\n        They are added as we process symbols alphabetically and then lots within each symbol.\n        This is correct.\n\n    *   Let's double check the `weights_after` symbols:\n        \"for every symbol that is held or targeted.\"\n        This is correct.\n\n    *   Let's double check the `shares` in `trades` and `lot_sales`:\n        They should be integers.\n        This is correct.\n\n    *   Let's double check the `gain` in `lot_sales` rounding:\n        `gain.quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `realized_short_term`, `realized_long_term`, `estimated_tax`, `cash_after` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `total_value` rounding:\n        `quantize(Decimal('0.01'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Let's double check the `weights_after` rounding:\n        `quantize(Decimal('0.000001'), rounding=ROUND_HALF_UP)`\n        This is correct.\n\n    *   Wait, the `shares_to_sell` and `shares_to_buy` calculations:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_selection` sorting:\n        `symbol_lots.sort(key=lambda x: (-Decimal(str(x['cost_per_share'])), date.fromisoformat(x['acquired']), x['id']))`\n        This is correct.\n\n    *   Let's double check the `term` calculation:\n        `days = (as_of_date - date.fromisoformat(lot['acquired'])).days`\n        `term = \"long\" if days > 365 else \"short\"`\n        This is correct.\n\n    *   Let's double check the `all_symbols` list:\n        `all_symbols = sorted(list(set(prices.keys()) | set(targets.keys()) | {lot['symbol'] for lot in lots}))`\n        This is correct.\n\n    *   Let's double check the `shares_held` dictionary:\n        `shares_held = {symbol: Decimal('0') for symbol in all_symbols}`\n        `for lot in lots: shares_held[lot['symbol']] += Decimal(str(lot['shares']))`\n        This is correct.\n\n    *   Let's double check the `current_value` and `target_value` calculation:\n        `current_value = shares_held[symbol] * prices[symbol]`\n        `target_value = targets.get(symbol, Decimal('0')) * total_value`\n        This is correct.\n\n    *   Let's double check the `shares_to_sell` calculation:\n        `shares_to_sell = int((current_value - target_value) // prices[symbol])`\n        `shares_to_sell = min(shares_to_sell, int(shares_held[symbol]))`\n        This is correct.\n\n    *   Let's double check the `shares_to_buy` calculation:\n        `shares_to_buy = int(min(target_value - current_value, cash) // prices[symbol])`\n        This is correct.\n\n    *   Let's double check the `lot_sales` gain:\n        `gain = (prices[symbol] - cost_per_share) * shares_sold`\n        This is correct.\n\n    *   Let's double check the `realized_short_term` and `realized_long_term` sums:\n        `realized_short_term += gain`\n        `realized_long_term += gain`\n        This is correct.\n\n    *   Let's double check the `estimated_tax` calculation:\n        `estimated_tax = max(realized_short_term, 0) * short_term_rate + max(realized_long_term, 0) * long_term_rate`\n        This is correct.\n\n    *   Let's double check the `weights_after` calculation:\n        `weights_after[symbol] = (shares_held[symbol] * prices[symbol]) / total_value`\n        This is correct.\n\n    *   Let's double check the `cash_after` calculation:\n        `cash_after` is the final `cash` after all trades.\n        This is",
        "name": null,
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     "usage": {
      "prompt_tokens": 1094,
      "completion_tokens": 16000,
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     "venice_parameters": {
      "strip_thinking_response": false,
      "disable_thinking": false,
      "enable_e2ee": true,
      "enable_web_search": "off",
      "enable_web_scraping": false,
      "enable_web_citations": false,
      "include_search_results_in_stream": false,
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