231 lines
7 KiB
Python
231 lines
7 KiB
Python
import pytest
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from kalshi_csv import KalshiCSV
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def test_parse_returns_self(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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result = kalshi.parse()
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assert result is kalshi
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def test_trade_count(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert kalshi.summary["trade_count"] == 3
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def test_total_fees(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert abs(kalshi.summary["total_fees"] - 0.07) < 1e-6
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def test_total_pnl_without_fees(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert abs(kalshi.summary["total_pnl_without_fees"] - (-0.20)) < 1e-6
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def test_total_pnl_with_fees(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert abs(kalshi.summary["total_pnl_with_fees"] - (-0.27)) < 1e-6
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def test_total_tax_basis(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert abs(kalshi.summary["total_tax_basis"] - 1.64) < 1e-6
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def test_total_tax_proceeds(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert abs(kalshi.summary["total_tax_proceeds"] - 1.37) < 1e-6
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def test_trades_list_length(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert len(kalshi.trades) == 3
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def test_first_trade_data(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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trade = kalshi.trades[0]
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assert trade["ticker"] == "TESTMARKET-WIN"
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assert trade["side"] == "YES"
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assert trade["qty"] == 1.0
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assert trade["entry"] == 0.50
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assert trade["exit"] == 1.00
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assert abs(trade["pnl_no_fees"] - 0.50) < 1e-6
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assert abs(trade["pnl_with_fees"] - 0.47) < 1e-6
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def test_irs_summary(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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irs = kalshi.irs_summary()
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assert irs["box"] == "C"
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assert irs["description"] == "Kalshi Event Contracts (Aggregate Summary)"
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assert irs["date_acquired"] == "07/07/2026"
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assert irs["date_sold"] == "07/07/2026"
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assert abs(irs["gross_proceeds"] - 1.37) < 1e-6
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assert abs(irs["cost_basis"] - 1.64) < 1e-6
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assert abs(irs["gain_or_loss"] - (-0.27)) < 1e-6
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def test_date_tracking(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert kalshi.summary["earliest_open_date"] is not None
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assert kalshi.summary["latest_close_date"] is not None
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assert kalshi.summary["earliest_open_date"].strftime("%m/%d/%Y") == "07/07/2026"
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assert kalshi.summary["latest_close_date"].strftime("%m/%d/%Y") == "07/07/2026"
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def test_file_not_found():
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kalshi = KalshiCSV("/nonexistent/path.csv")
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with pytest.raises(FileNotFoundError):
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kalshi.parse()
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def test_market_breakdown_returns_list(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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breakdown = kalshi.market_breakdown()
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assert isinstance(breakdown, list)
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assert len(breakdown) > 0
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def test_market_breakdown_structure(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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breakdown = kalshi.market_breakdown()
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for item in breakdown:
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assert "category" in item
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assert "trades" in item
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assert "win_rate" in item
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assert "net_pnl" in item
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def test_market_breakdown_sorted_by_trades(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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breakdown = kalshi.market_breakdown()
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trade_counts = [item["trades"] for item in breakdown]
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assert trade_counts == sorted(trade_counts, reverse=True)
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def test_sp500_price_tier_breakdown_groups_entry_prices_and_excludes_other_markets():
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kalshi = KalshiCSV("unused.csv")
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entries_and_pnls = [
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(0.399, 1.0),
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(0.40, -0.5),
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(0.4001, -0.25),
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(0.69, 0.0),
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(0.70, 2.0),
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(0.7001, -1.0),
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(0.85, 3.0),
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(0.8501, -2.0),
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(1.00, 4.0),
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(-0.01, 100.0),
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(1.01, 100.0),
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]
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kalshi.trades = [
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{
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"entry": entry,
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"pnl_with_fees": pnl,
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"market_category": "S&P 500 (INXU Intraday)",
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}
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for entry, pnl in entries_and_pnls
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]
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kalshi.trades.append({
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"entry": 0.50,
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"pnl_with_fees": 100.0,
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"market_category": "Other Markets",
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})
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breakdown = kalshi.sp500_price_tier_breakdown()
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assert [item["price_tier"] for item in breakdown] == [
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"<=$0.40 (Out-of-the-Money Speculative)",
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">$0.40-$0.70 (At-the-Money / Coincident)",
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">$0.70-$0.85 (Likely / Moderate ITM)",
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">$0.85 (Deep ITM / High Probability)",
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]
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assert [item["trades"] for item in breakdown] == [2, 3, 2, 2]
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assert [item["win_rate"] for item in breakdown] == pytest.approx([50.0, 100 / 3, 50.0, 50.0])
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assert [item["average_win"] for item in breakdown] == [1.0, 2.0, 3.0, 4.0]
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assert [item["average_loss"] for item in breakdown] == [-0.5, -0.25, -1.0, -2.0]
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assert [item["net_pnl"] for item in breakdown] == [0.5, 1.75, 2.0, 2.0]
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def test_sp500_price_tier_breakdown_is_empty_without_sp500_trades():
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kalshi = KalshiCSV("unused.csv")
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kalshi.trades = [{
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"entry": 0.50,
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"pnl_with_fees": 1.0,
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"market_category": "Other Markets",
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}]
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assert kalshi.sp500_price_tier_breakdown() == []
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def test_recent_closed_positions_returns_list(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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positions = kalshi.recent_closed_positions()
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assert isinstance(positions, list)
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def test_recent_closed_positions_limit(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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positions = kalshi.recent_closed_positions(n=2)
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assert len(positions) <= 2
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def test_recent_closed_positions_sorted_by_date(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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positions = kalshi.recent_closed_positions()
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if len(positions) > 1:
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timestamps = [p["close_timestamp"] for p in positions]
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assert timestamps == sorted(timestamps, reverse=True)
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def test_summary_tracks_wins_losses_pushes(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert kalshi.summary["wins"] >= 0
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assert kalshi.summary["losses"] >= 0
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assert kalshi.summary["pushes"] >= 0
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assert kalshi.summary["wins"] + kalshi.summary["losses"] + kalshi.summary["pushes"] == kalshi.summary["trade_count"]
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def test_summary_tracks_best_worst_trade(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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assert kalshi.summary["best_trade"] is not None
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assert kalshi.summary["worst_trade"] is not None
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assert "pnl_with_fees" in kalshi.summary["best_trade"]
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assert "pnl_with_fees" in kalshi.summary["worst_trade"]
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assert kalshi.summary["best_trade"]["pnl_with_fees"] >= kalshi.summary["worst_trade"]["pnl_with_fees"]
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def test_trade_has_market_category(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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for trade in kalshi.trades:
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assert "market_category" in trade
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assert isinstance(trade["market_category"], str)
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def test_trade_has_timestamps(sample_csv):
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kalshi = KalshiCSV(sample_csv)
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kalshi.parse()
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for trade in kalshi.trades:
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assert "open_timestamp" in trade
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assert "close_timestamp" in trade
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