Add new handling of acquired/sold dates

Finalizing of 0.2.0 changes
Start of work on 0.2.0, add legacy compatible web view
2026-07-31 10:53:30 -04:00 · 2026-07-29 09:33:22 -04:00 · 2026-07-28 13:27:25 -04:00
14 changed files with 1111 additions and 33 deletions
--- a/README.md
+++ b/README.md
@ -8,6 +8,14 @@ Parse Kalshi transaction CSV files and generate IRS Form 8949 tax summaries for
 pip install kalshi-csv
 ```

+## What's New in 0.2.0
+
+- **Summary Cards**: View key metrics at a glance - Net Realized P&L, Win/Loss Record, Total Volume, and Best/Worst Single Trade
+- **Market Breakdown**: See performance by market category with trade counts, win rates, and net P&L
+- **Legacy Web Mode**: Browse your portfolio in a retro HTML 4.01 web interface compatible with older browsers (Netscape Navigator, IE 4+)
+- **Market Categorization**: Automatic categorization of tickers into 7 market types (Global Soccer, MLB, NPB, NBA Summer League, WNBA, S&P 500, Multivariate Events, Other Markets)
+- **Handling of Sold + Acquired Dates**: Instead of handling the aggregated Kalshi trades through approximated dates, we use `VARIOUS` to signal to the IRS that every single underlying transaction in that row independently satisfies the short-term holding period rule (one year or less), even though they were purchased at different times.
+
 ## Getting Your Transactions CSV

 Download your transaction history from Kalshi:
@ -32,7 +40,7 @@ Rows without `realized_pnl_without_fees_dollars` are automatically skipped.

 ## CLI Usage

-Parse a Kalshi transactions CSV and display the trade matrix with IRS summary:
+Parse a Kalshi transactions CSV and display the trade matrix with summary cards, market breakdown, and IRS summary:

 ```bash
 kalshi-csv Kalshi-Transactions-2026.csv
@ -56,6 +64,18 @@ Use ASCII characters instead of Unicode box-drawing (for terminals without UTF-8
 kalshi-csv Kalshi-Transactions-2026.csv --ascii
 ```

+Start a legacy web server to view your portfolio in a browser (HTML 4.01 compatible with older browsers):
+
+```bash
+kalshi-csv Kalshi-Transactions-2026.csv --legacy-web
+```
+
+Specify a custom port for the legacy web server:
+
+```bash
+kalshi-csv Kalshi-Transactions-2026.csv --legacy-web --legacy-web-port 3000
+```
+
 ### Sample Output

 Default mode (Unicode box-drawing):
@ -72,6 +92,27 @@ Total Transactions Parsed: 3
 Total Exchange Fees Paid:  $0.02
 Internal Tracked Net P&L:  $+0.26
 -----------------------------------------------------------------------------------
+
+┌────────────────────────────┬────────────────────────────┬────────────────────────────┬────────────────────────────┐
+│ NET REALIZED P&L           │ WIN / LOSS RECORD          │ TOTAL VOLUME               │ BEST/WORST SINGLE          │
+├────────────────────────────┼────────────────────────────┼────────────────────────────┼────────────────────────────┤
+│ $+0.26                     │ 2 - 1                      │ 3                          │ $+0.39 / $-0.10            │
+│ Includes $0.02 fees        │ 0 Pushes (66.7% Win)       │ Executed Contracts         │ MLB Baseball / S&P 500     │
+└────────────────────────────┴────────────────────────────┴────────────────────────────┴────────────────────────────┘
+
+┌─────────────────────────────────────┬────────────┬──────────────┬──────────────────┐
+│ ASSET CLASS / MARKET                │ TRADES     │ WIN RATE     │ NET P&L          │
+├─────────────────────────────────────┼────────────┼──────────────┼──────────────────┤
+│ Global Soccer / Football            │ 168        │ 54.8%        │ $+15.15          │
+│ S&P 500 (INXU Intraday)             │ 110        │ 50.9%        │ $-32.21          │
+│ Other Markets                       │ 87         │ 35.6%        │ $-28.63          │
+│ MLB Baseball                        │ 44         │ 40.9%        │ $-13.06          │
+│ NBA Summer League                   │ 43         │ 46.5%        │ $-7.09           │
+│ NPB Baseball (Japan)                │ 40         │ 47.5%        │ $-10.68          │
+│ Multivariate Events             │ 23         │ 8.7%         │ $-13.48          │
+│ WNBA Basketball                     │ 6          │ 0.0%         │ $-5.87           │
+└─────────────────────────────────────┴────────────┴──────────────┴──────────────────┘
+
 === IRS FORM 8949 / SCHEDULE D AGGREGATE SUMMARY ===
 Use these exact aggregates for a single-line summary entry:
  * Box to Check:            Box C (Short-term, not reported on Form 1099-B)
@ -98,18 +139,81 @@ Total Transactions Parsed: 3
 Total Exchange Fees Paid:  $0.02
 Internal Tracked Net P&L:  $+0.26
 -----------------------------------------------------------------------------------
+
+----------------------------+----------------------------+----------------------------+----------------------------+
+| NET REALIZED P&L           | WIN / LOSS RECORD          | TOTAL VOLUME               | BEST/WORST SINGLE          |
+----------------------------+----------------------------+----------------------------+----------------------------+
+| $+0.26                     | 2 - 1                      | 3                          | $+0.39 / $-0.10            |
+| Includes $0.02 fees        | 0 Pushes (66.7% Win)       | Executed Contracts         | MLB Baseball / S&P 500     |
+----------------------------+----------------------------+----------------------------+----------------------------+
+
+-------------------------------------+------------+--------------+------------------+
+| ASSET CLASS / MARKET                | TRADES     | WIN RATE     | NET P&L          |
+-------------------------------------+------------+--------------+------------------+
+| Global Soccer / Football            | 168        | 54.8%        | $+15.15          |
+| S&P 500 (INXU Intraday)             | 110        | 50.9%        | $-32.21          |
+| Other Markets                       | 87         | 35.6%        | $-28.63          |
+| MLB Baseball                        | 44         | 40.9%        | $-13.06          |
+| NBA Summer League                   | 43         | 46.5%        | $-7.09           |
+| NPB Baseball (Japan)                | 40         | 47.5%        | $-10.68          |
+| Multivariate Events             | 23         | 8.7%         | $-13.48          |
+| WNBA Basketball                     | 6          | 0.0%         | $-5.87           |
+-------------------------------------+------------+--------------+------------------+
+
 === IRS FORM 8949 / SCHEDULE D AGGREGATE SUMMARY ===
 Use these exact aggregates for a single-line summary entry:
  * Box to Check:            Box C (Short-term, not reported on Form 1099-B)
  * (a) Description:         Kalshi Event Contracts (Aggregate Summary)
-  * (b) Date Acquired:       07/07/2026
-  * (c) Date Sold:           07/08/2026
+  * (b) Date Acquired:       VARIOUS
+  * (c) Date Sold:           VARIOUS
  * (d) Gross Proceeds:      $+2.50
  * (e) Cost or Other Basis: $2.24
  * (h) Gain or (Loss):      $+0.26
 ====================================================
 ```

+## Legacy Web Mode
+
+View your portfolio in a web browser with a retro HTML 4.01 interface compatible with older browsers (Netscape Navigator, IE 4+):
+
+```bash
+kalshi-csv Kalshi-Transactions-2026.csv --legacy-web
+```
+
+This starts an HTTP server on `0.0.0.0:8080` by default. Access it from any machine on your network by navigating to `http://<your-ip>:8080`.
+
+To use a different port:
+
+```bash
+kalshi-csv Kalshi-Transactions-2026.csv --legacy-web --legacy-web-port 3000
+```
+
+### What's Displayed
+
+The web interface shows:
+
+- **Summary Cards**: Net Realized P&L, Win/Loss Record, Total Volume, Best/Worst Single Trade
+- **Market Breakdown**: Performance by category with trade counts, win rates, and net P&L
+- **Recent Closed Positions**: Last 20 trades with timestamps, tickers, sides, quantities, entry/exit prices, and P&L
+- **IRS Form 8949 Summary**: Tax reporting data including gross proceeds, cost basis, and gain/loss
+
+The interface uses pure HTML 4.01 table layout with no CSS or JavaScript, ensuring compatibility with legacy browsers.
+
+## Market Categorization
+
+The tool automatically categorizes market tickers into the following categories:
+
+- **Global Soccer / Football**: World Cup, Champions League, Europa League, Brasileirão, Argentino, Liga MX, and other soccer leagues
+- **MLB Baseball**: Major League Baseball games and derivatives
+- **NPB Baseball (Japan)**: Nippon Professional Baseball
+- **NBA Summer League**: NBA Summer League games
+- **WNBA Basketball**: Women's National Basketball Association
+- **S&P 500 (INXU Intraday)**: S&P 500 index intraday contracts
+- **Multivariate Events**: Multivariate Event (MVE) markets - parlay-style markets linking multiple individual event outcomes together
+- **Other Markets**: Weather, politics, crypto, and all other markets
+
+Categories are determined by analyzing ticker prefixes (e.g., `KXMLBGAME` → MLB Baseball, `KXINXU` → S&P 500).
+
 ## Library API

 Use `kalshi-csv` as a Python library in your own scripts:
@ -135,6 +239,16 @@ irs = kalshi.irs_summary()
 print(f"Gross Proceeds: ${irs['gross_proceeds']:.2f}")
 print(f"Cost Basis: ${irs['cost_basis']:.2f}")
 print(f"Gain/Loss: ${irs['gain_or_loss']:.2f}")
+
+# Get market breakdown by category
+breakdown = kalshi.market_breakdown()
+for item in breakdown:
+    print(f"{item['category']}: {item['trades']} trades, {item['win_rate']:.1f}% win, ${item['net_pnl']:+.2f}")
+
+# Get recent closed positions
+recent = kalshi.recent_closed_positions(10)
+for trade in recent:
+    print(f"{trade['close_timestamp']}: {trade['ticker']} ${trade['pnl_with_fees']:+.2f}")
 ```

 ### Data Structures
@ -149,6 +263,9 @@ print(f"Gain/Loss: ${irs['gain_or_loss']:.2f}")
 - `pnl_with_fees`: P&L including fees
 - `open_fees`: Opening fees
 - `close_fees`: Closing fees
+- `open_timestamp`: When the position was opened (datetime object or None)
+- `close_timestamp`: When the position was closed (datetime object or None)
+- `market_category`: Categorized market type (e.g., "MLB Baseball", "Global Soccer / Football")

 **Summary dict** (`kalshi.summary`):
 - `trade_count`: Number of trades parsed
@ -157,6 +274,11 @@ print(f"Gain/Loss: ${irs['gain_or_loss']:.2f}")
 - `total_pnl_with_fees`: Total P&L including fees
 - `total_tax_basis`: Total cost basis for IRS reporting
 - `total_tax_proceeds`: Total proceeds for IRS reporting
+- `wins`: Number of winning trades (pnl_with_fees > 0)
+- `losses`: Number of losing trades (pnl_with_fees < 0)
+- `pushes`: Number of break-even trades (pnl_with_fees == 0)
+- `best_trade`: Trade dict with highest pnl_with_fees (or None)
+- `worst_trade`: Trade dict with lowest pnl_with_fees (or None)

 **IRS summary dict** (`kalshi.irs_summary()`):
 - `box`: "C" (for Form 8949 Box C)
@ -165,6 +287,54 @@ print(f"Gain/Loss: ${irs['gain_or_loss']:.2f}")
 - `cost_basis`: Total cost basis
 - `gain_or_loss`: Net gain or loss

+## Development & Testing
+
+For developers who want to contribute or run the test suite:
+
+### Installing Dependencies
+
+```bash
+pip install -r requirements.txt
+```
+
+### Running Tests
+
+The project uses pytest for testing. Run the full test suite:
+
+```bash
+pytest
+```
+
+Or with verbose output:
+
+```bash
+pytest -v
+```
+
+### Sample Test Data
+
+The test suite uses sample data located at `tests/fixtures/sample.csv`. If you want to create this file manually or modify it for testing:
+
+**File location**: `tests/fixtures/sample.csv`
+
+```csv
+type,quantity_fp,market_ticker,side,entry_price_dollars,exit_price_dollars,open_fees_dollars,close_fees_dollars,realized_pnl_without_fees_dollars,realized_pnl_with_fees_dollars,close_timestamp,open_timestamp
+trade,1.00,TESTMARKET-WIN,yes,0.5000,1.0000,0.010000,0.020000,0.500000,0.470000,2026-07-07T12:19:57-04:00,2026-07-07T09:48:19-04:00
+trade,2.00,TESTMARKET-LOSS,yes,0.4000,0.0000,0.020000,0.000000,-0.800000,-0.820000,2026-07-07T12:56:23-04:00,2026-07-07T12:37:41-04:00
+trade,0.50,TESTMARKET-SMALL,no,0.6000,0.8000,0.010000,0.010000,0.100000,0.080000,2026-07-07T14:07:41-04:00,2026-07-07T12:26:45-04:00
+```
+
+This sample contains 3 trades:
+- **TESTMARKET-WIN**: A winning trade (+$0.47 P&L with fees)
+- **TESTMARKET-LOSS**: A losing trade (-$0.82 P&L with fees)
+- **TESTMARKET-SMALL**: A small winning trade (+$0.08 P&L with fees)
+
+You can also test this sample data directly with the CLI:
+
+```bash
+kalshi-csv tests/fixtures/sample.csv
+```
+
 ## IRS Form 8949

 Kalshi event contracts are typically reported on **IRS Form 8949, Box C** (short-term transactions not reported on Form 1099-B). The tool calculates:
@ -179,9 +349,9 @@ Use the aggregate summary for a single-line entry on Form 8949, or export to a f

 ## Source Code

-This project is hosted in two locations:
+This project is hosted in two locations, GitHub and my home Forgejo server, contributions are easiest through GitHub, but you are welcome to clone from my Forgejo as well:
 - **GitHub**: [https://github.com/MARKMENTAL/kalshi-csv](https://github.com/MARKMENTAL/kalshi-csv)
- **Codeberg**: [https://codeberg.org/markmental/kalshi-csv](https://codeberg.org/markmental/kalshi-csv)
+- **MentalNet Forgejo v2**: [https://mentalnet.xyz/forgejo-v2/markmental/kalshi-csv](https://mentalnet.xyz/forgejo-v2/markmental/kalshi-csv)

 ## License

--- a/kalshi-csv.jpg
+++ b/kalshi-csv.jpg
--- a/pyproject.toml
+++ b/pyproject.toml
@ -4,7 +4,7 @@ build-backend = "hatchling.build"

 [project]
 name = "kalshi-csv"
-version = "0.1.2"
+version = "0.2.0"
 description = "Parse Kalshi transaction CSV files and generate IRS Form 8949 tax summaries"
 readme = "README.md"
 license = "MIT"
@ -28,7 +28,7 @@ keywords = ["kalshi", "csv", "tax", "irs", "form-8949"]

 [project.urls]
 Homepage = "https://github.com/MARKMENTAL/kalshi-csv"
-Source = "https://codeberg.org/markmental/kalshi-csv"
+Source = "https://mentalnet.xyz/forgejo-v2/markmental/kalshi-csv"
 Issues = "https://github.com/MARKMENTAL/kalshi-csv/issues"

 [project.scripts]
--- a/requirements.txt
+++ b/requirements.txt
@ -0,0 +1,33 @@
+build==1.5.0
+certifi==2026.6.17
+cffi==2.1.0
+charset-normalizer==3.4.9
+cryptography==49.0.0
+docutils==0.23
+id==1.6.1
+idna==3.18
+iniconfig==2.3.0
+jaraco.classes==3.4.0
+jaraco.context==6.1.2
+jaraco.functools==4.6.0
+jeepney==0.9.0
+-e git+https://codeberg.org/markmental/kalshi-csv.git@f7171c025c23d8d46931042f6dba48c4e6beeda9#egg=kalshi_csv
+keyring==25.7.0
+markdown-it-py==4.2.0
+mdurl==0.1.2
+more-itertools==11.1.0
+nh3==0.3.6
+packaging==26.2
+pluggy==1.6.0
+pycparser==3.0
+Pygments==2.20.0
+pyproject_hooks==1.2.0
+pytest==9.1.1
+readme_renderer==45.0
+requests==2.34.2
+requests-toolbelt==1.0.0
+rfc3986==2.0.0
+rich==15.0.0
+SecretStorage==3.5.0
+twine==6.2.0
+urllib3==2.7.0
--- a/src/kalshi_csv/init.py
+++ b/src/kalshi_csv/init.py
@ -1,4 +1,4 @@
-__version__ = "0.1.2"
+__version__ = "0.2.0"

 from .parser import KalshiCSV

--- a/src/kalshi_csv/categories.py
+++ b/src/kalshi_csv/categories.py
@ -0,0 +1,44 @@
+TICKER_CATEGORY_MAP = {
+    "KXMLB": "MLB Baseball",
+    "KXMLBHR": "MLB Baseball",
+    "KXMLBMEN": "MLB Baseball",
+    "KXNPB": "NPB Baseball (Japan)",
+    "KXNBASUMMER": "NBA Summer League",
+    "KXNEXTTEAMNBA": "NBA Summer League",
+    "KXWNBA": "WNBA Basketball",
+    "KXINXU": "S&P 500 (INXU Intraday)",
+    "KXINX": "S&P 500 (INXU Intraday)",
+    "KXMVE": "Multivariate Events",
+}
+
+SOCCER_PREFIXES = [
+    "KXWC",
+    "KXUCL",
+    "KXUECL",
+    "KXBRASILEIRO",
+    "KXALLSVENSKAN",
+    "KXELITESERIEN",
+    "KXECULP",
+    "KXLIGAMX",
+    "KXLIGAEXP",
+    "KXKLEAGUE",
+    "KXCLUBF",
+    "KXSCOCUP",
+    "KXURYPD",
+    "KXDIMAYOR",
+    "KXARGPREM",
+    "KXBOLP",
+]
+
+
+def categorize_ticker(ticker):
+    """Maps a Kalshi market ticker to a human-readable category."""
+    for prefix, category in TICKER_CATEGORY_MAP.items():
+        if ticker.startswith(prefix):
+            return category
+
+    for prefix in SOCCER_PREFIXES:
+        if ticker.startswith(prefix):
+            return "Global Soccer / Football"
+
+    return "Other Markets"
--- a/src/kalshi_csv/cli.py
+++ b/src/kalshi_csv/cli.py
@ -1,4 +1,5 @@
 import argparse
+import os
 import sys

 from .parser import KalshiCSV
@ -13,9 +14,17 @@ from .formatter import (
    format_table_separator,
    format_table_row,
    get_box_chars,
+    pad_colored_text,
 )


+def truncate_text(text, max_len):
+    """Truncates text to max_len, using ellipsis if longer than max_len-3 chars."""
+    if len(text) > max_len:
+        return text[:max_len-3] + "..."
+    return text
+
+
 def main():
    parser = argparse.ArgumentParser(
        description="Parse Kalshi transaction CSV and generate IRS tax summary."
@ -35,6 +44,17 @@ def main():
        action="store_true",
        help="Use ASCII characters instead of Unicode box-drawing",
    )
+    parser.add_argument(
+        "--legacy-web",
+        action="store_true",
+        help="Start a legacy web server (HTML 4.01) to view portfolio in browser",
+    )
+    parser.add_argument(
+        "--legacy-web-port",
+        type=int,
+        default=8080,
+        help="Port for legacy web server (default: 8080)",
+    )

    args = parser.parse_args()
    no_color = args.no_color
@ -43,6 +63,13 @@ def main():
    kalshi = KalshiCSV(args.csv_path)
    kalshi.parse()

+    if args.legacy_web:
+        from .web import LegacyWebServer
+        csv_filename = os.path.basename(args.csv_path)
+        server = LegacyWebServer(kalshi, csv_filename, port=args.legacy_web_port)
+        server.serve()
+        return
+
    headers = ["Ticker", "Side", "Qty", "Entry", "Exit", "P&L (No Fees)", "Fees"]
    widths = [32, 4, 6, 6, 6, 14, 6]

@ -77,13 +104,79 @@ def main():
    )
    print("-" * 83)

+    # Summary cards section
+    print()
+    card_widths = [25, 25, 25, 25]
+    
+    best_pnl = kalshi.summary["best_trade"]["pnl_with_fees"] if kalshi.summary["best_trade"] else 0
+    worst_pnl = kalshi.summary["worst_trade"]["pnl_with_fees"] if kalshi.summary["worst_trade"] else 0
+    best_cat = kalshi.summary["best_trade"]["market_category"] if kalshi.summary["best_trade"] else "N/A"
+    worst_cat = kalshi.summary["worst_trade"]["market_category"] if kalshi.summary["worst_trade"] else "N/A"
+    
+    card_labels = ["NET REALIZED P&L", "WIN / LOSS RECORD", "TOTAL VOLUME", "BEST/WORST SINGLE"]
+    
+    best_worst_combined = format_currency_color(best_pnl, no_color) + " / " + format_currency_color(worst_pnl, no_color)
+    
+    card_values = [
+        format_currency_color_padded(kalshi.summary["total_pnl_with_fees"], 25, no_color),
+        truncate_text(f"{kalshi.summary['wins']} - {kalshi.summary['losses']}", 25),
+        truncate_text(str(kalshi.summary['trade_count']), 25),
+        pad_colored_text(best_worst_combined, 25, no_color),
+    ]
+    card_subtext = [
+        truncate_text(f"Includes ${kalshi.summary['total_fees']:.2f} fees", 25),
+        truncate_text(f"{kalshi.summary['pushes']} Push{'s' if kalshi.summary['pushes'] != 1 else ''} ({kalshi.summary['wins'] / kalshi.summary['trade_count'] * 100 if kalshi.summary['trade_count'] > 0 else 0:.1f}% Win)", 25),
+        truncate_text("Executed Contracts", 25),
+        truncate_text(f"{best_cat} / {worst_cat}", 25),
+    ]
+    
+    print(format_table_separator(card_widths, ascii_mode, "top"))
+    print(format_table_row(card_labels, card_widths, ascii_mode))
+    print(format_table_separator(card_widths, ascii_mode, "middle"))
+    
+    box = get_box_chars(ascii_mode)
+    value_row = (
+        f" {card_values[0]} "
+        f"{box['vertical']} {card_values[1]:<25} "
+        f"{box['vertical']} {card_values[2]:<25} "
+        f"{box['vertical']} {card_values[3]} "
+    )
+    print(box["vertical"] + value_row + box["vertical"])
+    
+    print(format_table_row(card_subtext, card_widths, ascii_mode))
+    print(format_table_separator(card_widths, ascii_mode, "bottom"))
+    print()
+    
+    # Market breakdown section
+    market_headers = ["ASSET CLASS / MARKET", "TRADES", "WIN RATE", "NET P&L"]
+    market_widths = [35, 10, 12, 16]
+    print(format_table_separator(market_widths, ascii_mode, "top"))
+    print(format_table_header(market_headers, market_widths, ascii_mode))
+    print(format_table_separator(market_widths, ascii_mode, "middle"))
+    
+    for item in kalshi.market_breakdown():
+        category = item["category"][:33] + ".." if len(item["category"]) > 35 else item["category"]
+        trades = str(item["trades"])
+        win_rate = f"{item['win_rate']:.1f}%"
+        net_pnl = format_currency_color_padded(item["net_pnl"], 16, no_color)
+        row = (
+            f" {category:<35} "
+            f"{get_box_chars(ascii_mode)['vertical']} {trades:<10} "
+            f"{get_box_chars(ascii_mode)['vertical']} {win_rate:<12} "
+            f"{get_box_chars(ascii_mode)['vertical']} {net_pnl} "
+        )
+        print(get_box_chars(ascii_mode)['vertical'] + row + get_box_chars(ascii_mode)['vertical'])
+    
+    print(format_table_separator(market_widths, ascii_mode, "bottom"))
+    print()
+
    irs = kalshi.irs_summary()
    print(color_yellow("=== IRS FORM 8949 / SCHEDULE D AGGREGATE SUMMARY ===", no_color))
    print("Use these exact aggregates for a single-line summary entry:")
    print(f"  * Box to Check:            {color_white('Box C', no_color)} (Short-term, not reported on Form 1099-B)")
    print(f"  * (a) Description:         {irs['description']}")
-    print(f"  * (b) Date Acquired:       {irs['date_acquired']}")
-    print(f"  * (c) Date Sold:           {irs['date_sold']}")
+    print(f"  * (b) Date Acquired:       VARIOUS")
+    print(f"  * (c) Date Sold:           VARIOUS")
    print(f"  * (d) Gross Proceeds:      {format_currency_color(irs['gross_proceeds'], no_color)}")
    print(f"  * (e) Cost or Other Basis: {color_cyan(f'${irs['cost_basis']:.2f}', no_color)}")
    print(f"  * (h) Gain or (Loss):      {format_currency_color(irs['gain_or_loss'], no_color)}")
@ -96,8 +189,8 @@ def main():
            f.write("Use these exact aggregates for a single-line summary entry:\n")
            f.write(f"  * Box to Check:            Box C (Short-term, not reported on Form 1099-B)\n")
            f.write(f"  * (a) Description:         {irs['description']}\n")
-            f.write(f"  * (b) Date Acquired:       {irs['date_acquired']}\n")
-            f.write(f"  * (c) Date Sold:           {irs['date_sold']}\n")
+            f.write(f"  * (b) Date Acquired:       VARIOUS\n")
+            f.write(f"  * (c) Date Sold:           VARIOUS\n")
            f.write(f"  * (d) Gross Proceeds:      ${irs['gross_proceeds']:.2f}\n")
            f.write(f"  * (e) Cost or Other Basis: ${irs['cost_basis']:.2f}\n")
            f.write(f"  * (h) Gain or (Loss):      ${irs['gain_or_loss']:.2f}\n")
--- a/src/kalshi_csv/formatter.py
+++ b/src/kalshi_csv/formatter.py
@ -46,6 +46,28 @@ def format_currency_color_padded(value, width, no_color=False):
    return color_green(padded_str, no_color) if value >= 0 else color_red(padded_str, no_color)


+def pad_colored_text(text, width, no_color=False):
+    """Pads a colored string to a specific visible width, accounting for ANSI codes."""
+    if no_color:
+        return f"{text:<{width}}"
+    
+    # Strip ANSI codes to get visible length
+    import re
+    ansi_escape = re.compile(r'\x1B(?:[@-Z\\-_]|\[[0-?]*[ -/]*[@-~])')
+    visible_text = ansi_escape.sub('', text)
+    visible_len = len(visible_text)
+    
+    if visible_len >= width:
+        return text
+    
+    # Add padding to the end (before the final reset code if present)
+    padding = ' ' * (width - visible_len)
+    if text.endswith('\x1B[0m'):
+        return text[:-4] + padding + '\x1B[0m'
+    else:
+        return text + padding
+
+
 def truncate_ticker(ticker, max_len=32):
    """Truncates ticker to max_len, using ellipsis if longer than 29 chars."""
    if len(ticker) > 29:
--- a/src/kalshi_csv/parser.py
+++ b/src/kalshi_csv/parser.py
@ -1,7 +1,10 @@
 import csv
 import os
+from collections import defaultdict
 from datetime import datetime

+from .categories import categorize_ticker
+

 class KalshiCSV:
    """Parses Kalshi transaction CSV data and calculates tax-relevant aggregates."""
@ -18,6 +21,11 @@ class KalshiCSV:
            "total_tax_proceeds": 0.0,
            "earliest_open_date": None,
            "latest_close_date": None,
+            "wins": 0,
+            "losses": 0,
+            "pushes": 0,
+            "best_trade": None,
+            "worst_trade": None,
        }

    def parse(self):
@ -40,8 +48,22 @@ class KalshiCSV:
                open_fees = float(row["open_fees_dollars"])
                close_fees = float(row["close_fees_dollars"])

+                open_dt = None
+                close_dt = None
+                if row.get("open_timestamp"):
+                    try:
+                        open_dt = datetime.fromisoformat(row["open_timestamp"])
+                    except ValueError:
+                        pass
+                if row.get("close_timestamp"):
+                    try:
+                        close_dt = datetime.fromisoformat(row["close_timestamp"])
+                    except ValueError:
+                        pass
+
+                ticker = row["market_ticker"]
                trade = {
-                    "ticker": row["market_ticker"],
+                    "ticker": ticker,
                    "side": row["side"].upper(),
                    "qty": qty,
                    "entry": entry,
@ -50,6 +72,9 @@ class KalshiCSV:
                    "pnl_with_fees": pnl_with_fees,
                    "open_fees": open_fees,
                    "close_fees": close_fees,
+                    "open_timestamp": open_dt,
+                    "close_timestamp": close_dt,
+                    "market_category": categorize_ticker(ticker),
                }
                self.trades.append(trade)

@ -60,27 +85,37 @@ class KalshiCSV:
                self.summary["total_pnl_with_fees"] += pnl_with_fees
                self.summary["total_fees"] += open_fees + close_fees

-                if row.get("open_timestamp"):
-                    try:
-                        open_dt = datetime.fromisoformat(row["open_timestamp"])
-                        if (
-                            self.summary["earliest_open_date"] is None
-                            or open_dt < self.summary["earliest_open_date"]
-                        ):
-                            self.summary["earliest_open_date"] = open_dt
-                    except ValueError:
-                        pass
+                if pnl_with_fees > 0:
+                    self.summary["wins"] += 1
+                elif pnl_with_fees < 0:
+                    self.summary["losses"] += 1
+                else:
+                    self.summary["pushes"] += 1

-                if row.get("close_timestamp"):
-                    try:
-                        close_dt = datetime.fromisoformat(row["close_timestamp"])
-                        if (
-                            self.summary["latest_close_date"] is None
-                            or close_dt > self.summary["latest_close_date"]
-                        ):
-                            self.summary["latest_close_date"] = close_dt
-                    except ValueError:
-                        pass
+                if (
+                    self.summary["best_trade"] is None
+                    or pnl_with_fees > self.summary["best_trade"]["pnl_with_fees"]
+                ):
+                    self.summary["best_trade"] = trade
+                if (
+                    self.summary["worst_trade"] is None
+                    or pnl_with_fees < self.summary["worst_trade"]["pnl_with_fees"]
+                ):
+                    self.summary["worst_trade"] = trade
+
+                if open_dt is not None:
+                    if (
+                        self.summary["earliest_open_date"] is None
+                        or open_dt < self.summary["earliest_open_date"]
+                    ):
+                        self.summary["earliest_open_date"] = open_dt
+
+                if close_dt is not None:
+                    if (
+                        self.summary["latest_close_date"] is None
+                        or close_dt > self.summary["latest_close_date"]
+                    ):
+                        self.summary["latest_close_date"] = close_dt

        return self

@ -101,3 +136,36 @@ class KalshiCSV:
            "cost_basis": self.summary["total_tax_basis"],
            "gain_or_loss": self.summary["total_pnl_with_fees"],
        }
+
+    def market_breakdown(self):
+        """Returns a list of dicts with market category breakdown sorted by trade count."""
+        categories = defaultdict(lambda: {"trades": 0, "wins": 0, "net_pnl": 0.0})
+
+        for trade in self.trades:
+            cat = trade["market_category"]
+            categories[cat]["trades"] += 1
+            categories[cat]["net_pnl"] += trade["pnl_with_fees"]
+            if trade["pnl_with_fees"] > 0:
+                categories[cat]["wins"] += 1
+
+        breakdown = []
+        for cat, data in categories.items():
+            win_rate = (data["wins"] / data["trades"] * 100) if data["trades"] > 0 else 0
+            breakdown.append({
+                "category": cat,
+                "trades": data["trades"],
+                "win_rate": win_rate,
+                "net_pnl": data["net_pnl"],
+            })
+
+        return sorted(breakdown, key=lambda x: x["trades"], reverse=True)
+
+    def recent_closed_positions(self, n=20):
+        """Returns the last n trades sorted by close_timestamp descending."""
+        trades_with_close = [t for t in self.trades if t["close_timestamp"] is not None]
+        sorted_trades = sorted(
+            trades_with_close,
+            key=lambda t: t["close_timestamp"],
+            reverse=True,
+        )
+        return sorted_trades[:n]
--- a/src/kalshi_csv/web.py
+++ b/src/kalshi_csv/web.py
@ -0,0 +1,294 @@
+import html
+from datetime import datetime
+from http.server import HTTPServer, BaseHTTPRequestHandler
+
+from . import __version__
+
+
+def render_portfolio_html(kalshi, csv_filename):
+    """Renders the full HTML 4.01 portfolio page from parsed Kalshi data."""
+    summary = kalshi.summary
+    market_breakdown = kalshi.market_breakdown()
+    recent_positions = kalshi.recent_closed_positions(20)
+
+    period_end = summary["latest_close_date"]
+    if period_end:
+        period_end_str = period_end.strftime("%B %d, %Y").upper()
+    else:
+        period_end_str = "N/A"
+
+    net_pnl = summary["total_pnl_with_fees"]
+    net_pnl_color = "#006600" if net_pnl >= 0 else "#990000"
+    net_pnl_str = f"${net_pnl:+.2f}"
+
+    wins = summary["wins"]
+    losses = summary["losses"]
+    pushes = summary["pushes"]
+    total = summary["trade_count"]
+    win_pct = (wins / total * 100) if total > 0 else 0
+    push_note = f" ({pushes} Push{'s' if pushes != 1 else ''})" if pushes > 0 else ""
+
+    best_trade = summary["best_trade"]
+    worst_trade = summary["worst_trade"]
+    if best_trade and worst_trade:
+        best_pnl = best_trade["pnl_with_fees"]
+        worst_pnl = worst_trade["pnl_with_fees"]
+        best_cat = best_trade["market_category"]
+        worst_cat = worst_trade["market_category"]
+        best_color = "#006600" if best_pnl >= 0 else "#990000"
+        worst_color = "#006600" if worst_pnl >= 0 else "#990000"
+        best_str = f"${best_pnl:+.2f}"
+        worst_str = f"${worst_pnl:+.2f}"
+        best_worst_subtext = f"{best_cat} / {worst_cat}"
+    else:
+        best_str = "$0.00"
+        worst_str = "$0.00"
+        best_color = "#006600"
+        worst_color = "#990000"
+        best_worst_subtext = "N/A"
+
+    rows_html = ""
+    for i, item in enumerate(market_breakdown):
+        pnl = item["net_pnl"]
+        pnl_color = "#006600" if pnl >= 0 else "#990000"
+        pnl_str = f"${pnl:+.2f}"
+        win_rate_str = f"{item['win_rate']:.1f}%"
+        rows_html += f"""
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="2">{html.escape(item['category'])}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="2">{item['trades']}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="2">{win_rate_str}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="2" color="{pnl_color}"><b>{pnl_str}</b></font></td>
+                </tr>"""
+        if i < len(market_breakdown) - 1:
+            rows_html += """
+                <tr><td colspan="4"><hr size="1" color="#E0E0E0" noshade></td></tr>"""
+
+    positions_html = ""
+    for trade in recent_positions:
+        close_dt = trade["close_timestamp"]
+        date_str = close_dt.strftime("%m/%d %H:%M") if close_dt else "N/A"
+        ticker = html.escape(trade["ticker"])
+        side = trade["side"]
+        qty = f"{trade['qty']:.2f}"
+        entry = f"${trade['entry']:.2f}"
+        exit_val = f"${trade['exit']:.2f}"
+        pnl = trade["pnl_with_fees"]
+        pnl_color = "#006600" if pnl >= 0 else "#990000"
+        pnl_str = f"${pnl:+.2f}"
+        positions_html += f"""
+                <tr>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="1">{date_str}</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="1">{ticker}</font></td>
+                    <td align="center"><font face="Courier New, Courier, monospace" size="1">{side}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="1">{qty}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="1">{entry}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="1">{exit_val}</font></td>
+                    <td align="right"><font face="Courier New, Courier, monospace" size="1" color="{pnl_color}"><b>{pnl_str}</b></font></td>
+                </tr>"""
+
+    # IRS summary section
+    irs = kalshi.irs_summary()
+    gross_proceeds_color = "#006600" if irs["gross_proceeds"] >= 0 else "#990000"
+    cost_basis_color = "#006600" if irs["cost_basis"] >= 0 else "#990000"
+    gain_loss_color = "#006600" if irs["gain_or_loss"] >= 0 else "#990000"
+    irs_html = f"""
+    <tr><td><br><hr size="1" color="#CCCCCC" noshade><br></td></tr>
+
+    <tr>
+        <td>
+            <font face="Georgia, Times New Roman, serif" size="3"><b>IRS Form 8949 / Schedule D Summary</b></font>
+            <br><br>
+
+            <table width="100%" border="0" cellspacing="0" cellpadding="4">
+                <tr>
+                    <td width="40%" align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Box to Check:</font></td>
+                    <td width="60%" align="left"><font face="Courier New, Courier, monospace" size="2"><b>{html.escape(irs['box'])}</b></font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Description:</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2">{html.escape(irs['description'])}</font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Date Acquired:</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2">VARIOUS</font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Date Sold:</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2">VARIOUS</font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Gross Proceeds:</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2" color="{gross_proceeds_color}"><b>${irs['gross_proceeds']:.2f}</b></font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Cost or Other Basis:</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2" color="{cost_basis_color}"><b>${irs['cost_basis']:.2f}</b></font></td>
+                </tr>
+                <tr><td colspan="2"><hr size="1" color="#E0E0E0" noshade></td></tr>
+                <tr>
+                    <td align="left"><font face="Geneva, Verdana, sans-serif" size="1" color="#666666">Gain or (Loss):</font></td>
+                    <td align="left"><font face="Courier New, Courier, monospace" size="2" color="{gain_loss_color}"><b>${irs['gain_or_loss']:+.2f}</b></font></td>
+                </tr>
+            </table>
+        </td>
+    </tr>
+"""
+
+    page = f"""<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN" "http://www.w3.org/TR/html4/loose.dtd">
+<html>
+<head>
+    <title>Kalshi Portfolio Statement</title>
+    <meta http-equiv="Content-Type" content="text/html; charset=iso-8859-1">
+</head>
+<body bgcolor="#FFFFFF" text="#111111" link="#111111" vlink="#444444" alink="#000000" topmargin="20" leftmargin="20" marginwidth="20" marginheight="20">
+
+<center>
+<table width="720" border="0" cellspacing="0" cellpadding="0">
+
+    <tr>
+        <td align="left">
+            <font face="Courier New, Courier, monospace" size="2"><b>KALSHI DERIVATIVES / ACCOUNT AUDIT</b></font><br>
+            <font face="Georgia, Times New Roman, serif" size="5"><b>Year-End Performance Summary</b></font><br>
+            <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">PERIOD ENDING: {html.escape(period_end_str)} &nbsp;|&nbsp; SOURCE: {html.escape(csv_filename)}</font>
+        </td>
+    </tr>
+
+    <tr>
+        <td padding="10">
+            <hr size="2" color="#111111" noshade>
+        </td>
+    </tr>
+
+    <tr>
+        <td>
+            <table width="100%" border="0" cellspacing="0" cellpadding="6">
+                <tr valign="top">
+                    <td width="25%">
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">NET REALIZED P&amp;L</font><br>
+                        <font face="Courier New, Courier, monospace" size="4" color="{net_pnl_color}"><b>{net_pnl_str}</b></font><br>
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#888888">Includes ${summary['total_fees']:.2f} fees</font>
+                    </td>
+                    <td width="25%">
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">WIN / LOSS RECORD</font><br>
+                        <font face="Courier New, Courier, monospace" size="4"><b>{wins} - {losses}</b></font><br>
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#888888">{pushes} Push{'s' if pushes != 1 else ''} ({win_pct:.1f}% Win)</font>
+                    </td>
+                    <td width="25%">
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">TOTAL VOLUME</font><br>
+                        <font face="Courier New, Courier, monospace" size="4"><b>{total}</b></font><br>
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#888888">Executed Contracts</font>
+                    </td>
+                    <td width="25%">
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">BEST/WORST SINGLE</font><br>
+                        <font face="Courier New, Courier, monospace" size="2"><font color="{best_color}"><b>{best_str}</b></font> / <font color="{worst_color}"><b>{worst_str}</b></font></font><br>
+                        <font face="Geneva, Verdana, sans-serif" size="1" color="#888888">{html.escape(best_worst_subtext)}</font>
+                    </td>
+                </tr>
+            </table>
+        </td>
+    </tr>
+
+    <tr><td><br><hr size="1" color="#CCCCCC" noshade><br></td></tr>
+
+    <tr>
+        <td>
+            <font face="Georgia, Times New Roman, serif" size="3"><b>Market Breakdown</b></font>
+            <br><br>
+
+            <table width="100%" border="0" cellspacing="0" cellpadding="4">
+                <tr bgcolor="#EEEEEE">
+                    <td width="45%" align="left"><font face="Geneva, Verdana, sans-serif" size="1"><b>ASSET CLASS / MARKET</b></font></td>
+                    <td width="15%" align="right"><font face="Geneva, Verdana, sans-serif" size="1"><b>TRADES</b></font></td>
+                    <td width="20%" align="right"><font face="Geneva, Verdana, sans-serif" size="1"><b>WIN RATE</b></font></td>
+                    <td width="20%" align="right"><font face="Geneva, Verdana, sans-serif" size="1"><b>NET P&amp;L</b></font></td>
+                </tr>
+                {rows_html}
+            </table>
+        </td>
+    </tr>
+
+    <tr><td><br><hr size="1" color="#CCCCCC" noshade><br></td></tr>
+
+    <tr>
+        <td>
+            <font face="Georgia, Times New Roman, serif" size="3"><b>Recent Closed Positions</b></font>
+            <br><br>
+
+            <table width="100%" border="0" cellspacing="0" cellpadding="3">
+                <tr bgcolor="#EEEEEE">
+                    <th align="left"><font face="Geneva, Verdana, sans-serif" size="1">DATE/TIME</font></th>
+                    <th align="left"><font face="Geneva, Verdana, sans-serif" size="1">TICKER</font></th>
+                    <th align="center"><font face="Geneva, Verdana, sans-serif" size="1">SIDE</font></th>
+                    <th align="right"><font face="Geneva, Verdana, sans-serif" size="1">QTY</font></th>
+                    <th align="right"><font face="Geneva, Verdana, sans-serif" size="1">ENTRY</font></th>
+                    <th align="right"><font face="Geneva, Verdana, sans-serif" size="1">EXIT</font></th>
+                    <th align="right"><font face="Geneva, Verdana, sans-serif" size="1">P&amp;L</font></th>
+                </tr>
+                {positions_html}
+            </table>
+        </td>
+    </tr>
+
+    {irs_html}
+
+    <tr><td><br><hr size="2" color="#111111" noshade></td></tr>
+    <tr>
+        <td align="center">
+            <font face="Geneva, Verdana, sans-serif" size="1" color="#666666">
+                {html.escape(csv_filename)} &bull; rendered with vanilla HTML 4.01 strict table markup &bull; kalshi-csv v{__version__}
+            </font>
+        </td>
+    </tr>
+
+</table>
+</center>
+
+</body>
+</html>"""
+    return page
+
+
+class LegacyWebHandler(BaseHTTPRequestHandler):
+    """HTTP request handler that serves the legacy portfolio page."""
+
+    def do_GET(self):
+        if self.path == "/" or self.path == "/index.html":
+            self.send_response(200)
+            self.send_header("Content-type", "text/html; charset=iso-8859-1")
+            self.end_headers()
+            html_content = self.server.html_content
+            self.wfile.write(html_content.encode("iso-8859-1"))
+        else:
+            self.send_error(404, "Not Found")
+
+    def log_message(self, format, *args):
+        pass
+
+
+class LegacyWebServer:
+    """HTTP server for the legacy portfolio view."""
+
+    def __init__(self, kalshi, csv_filename, host="0.0.0.0", port=8080):
+        self.kalshi = kalshi
+        self.csv_filename = csv_filename
+        self.host = host
+        self.port = port
+        self.html_content = render_portfolio_html(kalshi, csv_filename)
+
+    def serve(self):
+        """Starts the HTTP server and blocks until interrupted."""
+        server = HTTPServer((self.host, self.port), LegacyWebHandler)
+        server.html_content = self.html_content
+        print(f"Serving legacy portfolio view at http://{self.host}:{self.port}/")
+        print("Press Ctrl+C to stop.")
+        try:
+            server.serve_forever()
+        except KeyboardInterrupt:
+            print("\nShutting down server.")
+            server.server_close()
--- a/tests/test_categories.py
+++ b/tests/test_categories.py
@ -0,0 +1,48 @@
+from kalshi_csv.categories import categorize_ticker
+
+
+def test_mlb_categorization():
+    assert categorize_ticker("KXMLBGAME-26JUL081940BOSCWS-BOS") == "MLB Baseball"
+    assert categorize_ticker("KXMLBHRDERBY-26-KSCHWARBER12") == "MLB Baseball"
+
+
+def test_npb_categorization():
+    assert categorize_ticker("KXNPBGAME-26JUL150500YOMYAK-YAK") == "NPB Baseball (Japan)"
+
+
+def test_nba_summer_categorization():
+    assert categorize_ticker("KXNBASUMMERGAME-26JUL14MEMGSW-GSW") == "NBA Summer League"
+
+
+def test_wnba_categorization():
+    assert categorize_ticker("KXWNBAGAME-26JUL13PHXMIN-PHX") == "WNBA Basketball"
+
+
+def test_sp500_categorization():
+    assert categorize_ticker("KXINXU-26JUL08H1400-T7479.9999") == "S&P 500 (INXU Intraday)"
+    assert categorize_ticker("KXINX-26JUL08H1400-T7479.9999") == "S&P 500 (INXU Intraday)"
+
+
+def test_multivariate_events_categorization():
+    assert categorize_ticker("KXMVESPORTSMULTIGAMEEXTENDED-S2026769CE3FA3F9-6D4DB2E2128") == "Multivariate Events"
+    assert categorize_ticker("KXMVECROSSCATEGORY-S2026AC77F3A8C7A-6D4DB2E2128") == "Multivariate Events"
+
+
+def test_soccer_categorization():
+    assert categorize_ticker("KXWCADVANCE-26JUL07ARGEGY-ARG") == "Global Soccer / Football"
+    assert categorize_ticker("KXUCLADVANCE-26JUL14KUPSVAR-VAR") == "Global Soccer / Football"
+    assert categorize_ticker("KXBRASILEIROBGAME-26JUL13AMGLON-LON") == "Global Soccer / Football"
+    assert categorize_ticker("KXECULPGAME-26JUL14MACMUR-MUR") == "Global Soccer / Football"
+    assert categorize_ticker("KXALLSVENSKANGAME-26JUL12BROSIR-SIR") == "Global Soccer / Football"
+    assert categorize_ticker("KXCLUBFGAME-26JUL27GALVEN-VEN") == "Global Soccer / Football"
+
+
+def test_other_markets_categorization():
+    assert categorize_ticker("KXRAIN-26JUL15-ATL") == "Other Markets"
+    assert categorize_ticker("KXTRUMPMENTION-26JUL15") == "Other Markets"
+    assert categorize_ticker("KXTEMPNYCH-26JUL15") == "Other Markets"
+    assert categorize_ticker("KXHIGHCHI-26JUL15") == "Other Markets"
+
+
+def test_unknown_ticker_defaults_to_other():
+    assert categorize_ticker("UNKNOWN-TICKER-123") == "Other Markets"
--- a/tests/test_cli.py
+++ b/tests/test_cli.py
@ -103,3 +103,94 @@ def test_cli_ascii_flag(sample_csv):
    assert "|" in result.stdout
    assert "┌" not in result.stdout
    assert "│" not in result.stdout
+
+
+def test_cli_legacy_web_flag_in_help():
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", "--help"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    assert "--legacy-web" in result.stdout
+    assert "--legacy-web-port" in result.stdout
+
+
+def test_cli_legacy_web_port_default_in_help():
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", "--help"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    assert "8080" in result.stdout
+
+
+def test_cli_summary_cards_output(sample_csv):
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", sample_csv, "--no-color"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    assert "NET REALIZED P&L" in result.stdout
+    assert "WIN / LOSS RECORD" in result.stdout
+    assert "TOTAL VOLUME" in result.stdout
+    assert "BEST/WORST SINGLE" in result.stdout
+
+
+def test_cli_market_breakdown_output(sample_csv):
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", sample_csv, "--no-color"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    assert "ASSET CLASS / MARKET" in result.stdout
+    assert "TRADES" in result.stdout
+    assert "WIN RATE" in result.stdout
+    assert "NET P&L" in result.stdout
+    assert "Other Markets" in result.stdout
+
+
+def test_cli_summary_cards_box_drawing(sample_csv):
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", sample_csv, "--no-color"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    assert "┌" in result.stdout
+    assert "└" in result.stdout
+    assert "┬" in result.stdout
+    assert "┴" in result.stdout
+
+
+def test_cli_summary_cards_before_irs(sample_csv):
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", sample_csv, "--no-color"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    output = result.stdout
+    summary_pos = output.find("NET REALIZED P&L")
+    irs_pos = output.find("IRS FORM 8949")
+    assert summary_pos > 0
+    assert irs_pos > 0
+    assert summary_pos < irs_pos
+
+
+def test_cli_market_breakdown_before_irs(sample_csv):
+    result = subprocess.run(
+        [sys.executable, "-m", "kalshi_csv.cli", sample_csv, "--no-color"],
+        capture_output=True,
+        text=True,
+    )
+    assert result.returncode == 0
+    output = result.stdout
+    market_pos = output.find("ASSET CLASS / MARKET")
+    irs_pos = output.find("IRS FORM 8949")
+    assert market_pos > 0
+    assert irs_pos > 0
+    assert market_pos < irs_pos
--- a/tests/test_parser.py
+++ b/tests/test_parser.py
@ -89,3 +89,88 @@ def test_file_not_found():
    kalshi = KalshiCSV("/nonexistent/path.csv")
    with pytest.raises(FileNotFoundError):
        kalshi.parse()
+
+
+def test_market_breakdown_returns_list(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    breakdown = kalshi.market_breakdown()
+    assert isinstance(breakdown, list)
+    assert len(breakdown) > 0
+
+
+def test_market_breakdown_structure(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    breakdown = kalshi.market_breakdown()
+    for item in breakdown:
+        assert "category" in item
+        assert "trades" in item
+        assert "win_rate" in item
+        assert "net_pnl" in item
+
+
+def test_market_breakdown_sorted_by_trades(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    breakdown = kalshi.market_breakdown()
+    trade_counts = [item["trades"] for item in breakdown]
+    assert trade_counts == sorted(trade_counts, reverse=True)
+
+
+def test_recent_closed_positions_returns_list(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    positions = kalshi.recent_closed_positions()
+    assert isinstance(positions, list)
+
+
+def test_recent_closed_positions_limit(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    positions = kalshi.recent_closed_positions(n=2)
+    assert len(positions) <= 2
+
+
+def test_recent_closed_positions_sorted_by_date(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    positions = kalshi.recent_closed_positions()
+    if len(positions) > 1:
+        timestamps = [p["close_timestamp"] for p in positions]
+        assert timestamps == sorted(timestamps, reverse=True)
+
+
+def test_summary_tracks_wins_losses_pushes(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    assert kalshi.summary["wins"] >= 0
+    assert kalshi.summary["losses"] >= 0
+    assert kalshi.summary["pushes"] >= 0
+    assert kalshi.summary["wins"] + kalshi.summary["losses"] + kalshi.summary["pushes"] == kalshi.summary["trade_count"]
+
+
+def test_summary_tracks_best_worst_trade(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    assert kalshi.summary["best_trade"] is not None
+    assert kalshi.summary["worst_trade"] is not None
+    assert "pnl_with_fees" in kalshi.summary["best_trade"]
+    assert "pnl_with_fees" in kalshi.summary["worst_trade"]
+    assert kalshi.summary["best_trade"]["pnl_with_fees"] >= kalshi.summary["worst_trade"]["pnl_with_fees"]
+
+
+def test_trade_has_market_category(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    for trade in kalshi.trades:
+        assert "market_category" in trade
+        assert isinstance(trade["market_category"], str)
+
+
+def test_trade_has_timestamps(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    for trade in kalshi.trades:
+        assert "open_timestamp" in trade
+        assert "close_timestamp" in trade
--- a/tests/test_web.py
+++ b/tests/test_web.py
@ -0,0 +1,130 @@
+from kalshi_csv import KalshiCSV
+from kalshi_csv.web import render_portfolio_html
+
+
+def test_render_html_contains_header(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "KALSHI DERIVATIVES / ACCOUNT AUDIT" in html_content
+    assert "Year-End Performance Summary" in html_content
+
+
+def test_render_html_contains_summary_metrics(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "NET REALIZED P&amp;L" in html_content
+    assert "WIN / LOSS RECORD" in html_content
+    assert "TOTAL VOLUME" in html_content
+    assert "BEST/WORST SINGLE" in html_content
+
+
+def test_render_html_contains_market_breakdown(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "Market Breakdown" in html_content
+    assert "ASSET CLASS / MARKET" in html_content
+    assert "TRADES" in html_content
+    assert "WIN RATE" in html_content
+
+
+def test_render_html_contains_recent_positions(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "Recent Closed Positions" in html_content
+    assert "DATE/TIME" in html_content
+    assert "TICKER" in html_content
+    assert "SIDE" in html_content
+    assert "ENTRY" in html_content
+    assert "EXIT" in html_content
+
+
+def test_render_html_contains_trade_data(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "TESTMARKET-WIN" in html_content
+    assert "TESTMARKET-LOSS" in html_content
+    assert "TESTMARKET-SMALL" in html_content
+
+
+def test_render_html_html401_doctype(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert '<!DOCTYPE HTML PUBLIC "-//W3C//DTD HTML 4.01 Transitional//EN"' in html_content
+
+
+def test_render_html_no_css(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "<style" not in html_content
+    assert "style=" not in html_content
+
+
+def test_render_html_shows_win_loss_record(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "2 - 1" in html_content
+
+
+def test_render_html_shows_total_volume(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert ">3<" in html_content
+
+
+def test_render_html_shows_csv_filename(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "my-kalshi-data.csv")
+    assert "my-kalshi-data.csv" in html_content
+
+
+def test_render_html_escapes_html_in_tickers(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    kalshi.trades[0]["ticker"] = "<script>alert('xss')</script>"
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "<script>alert('xss')</script>" not in html_content
+    assert "&lt;script&gt;" in html_content
+
+
+def test_render_html_contains_irs_section(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert "IRS Form 8949 / Schedule D Summary" in html_content
+    assert "Box to Check:" in html_content
+    assert "Description:" in html_content
+    assert "Date Acquired:" in html_content
+    assert "Date Sold:" in html_content
+    assert "Gross Proceeds:" in html_content
+    assert "Cost or Other Basis:" in html_content
+    assert "Gain or (Loss):" in html_content
+
+
+def test_render_html_irs_values(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    assert ">C<" in html_content
+    assert "Kalshi Event Contracts (Aggregate Summary)" in html_content
+    assert "07/07/2026" in html_content
+
+
+def test_render_html_irs_after_positions(sample_csv):
+    kalshi = KalshiCSV(sample_csv)
+    kalshi.parse()
+    html_content = render_portfolio_html(kalshi, "test.csv")
+    positions_pos = html_content.find("Recent Closed Positions")
+    irs_pos = html_content.find("IRS Form 8949")
+    assert positions_pos > 0
+    assert irs_pos > 0
+    assert positions_pos < irs_pos
Author	SHA1	Message	Date
mark	8cb809bbb2	Add new handling of acquired/sold dates	2026-07-31 10:53:30 -04:00
mark	932fd06f71	Finalizing of 0.2.0 changes	2026-07-29 09:33:22 -04:00
mark	f7171c025c	Start of work on 0.2.0, add legacy compatible web view	2026-07-28 13:27:25 -04:00