Hey r/algotrading,

pandas-ta-classic is the community-maintained fork of pandas-ta — a comprehensive technical analysis library for pandas DataFrames. This release is the largest update since the fork, spanning 66 commits and 338 changed files.

GitHub: github.com/xgboosted/pandas-ta-classic
PyPI: pip install pandas-ta-classic

🎯 TL;DR

• TA-Lib exact parity — Wilder smoothing, chained EMA lookbacks, and PSAR reversal checks now match the C library within float64 precision. All 60 oracle tests pass at tol=1e-7.
• Fluent API chaining — df.ta.chain().sma(50).rsi().macd(). Chain indicators in one expression, call df.ta.unchain() to go back to normal mode.
• Property-based testing — 55 Hypothesis tests verify mathematical invariants (SMA(constant) == constant, RSI ∈ [0,100]) across random inputs.
• Test coverage 78% → 89% — 1427 tests, zero failures. Every indicator has offset, fill, and None-guard coverage.
• Code modernized — Python 3.9–3.14, 370 dead-code instances removed, tal alias replaced with talib everywhere.

⚡ Fluent API Chaining (PR #113)

import pandas_ta_classic as ta

df = df.ta.chain().sma(50).rsi().macd().bbands(20)
# df now has SMA_50, RSI_14, MACD_12_26_9, MACDh_12_26_9, MACDs_12_26_9,
# BBL_20_2.0, BBM_20_2.0, BBU_20_2.0, BBB_20_2.0, BBP_20_2.0

df.ta.unchain()  # back to normal append mode

No more repetitive append=True on every call. The chain mode accumulates columns in one fluent expression, then unchain() returns you to standard usage.

🔬 TA-Lib Parity Fixes

Wilder's Smoothing

The PR #112 remediation extracted wilder_smooth() into a shared utility (utils/_wilder.py). It implements Wilder's cumulative-sum smoothing with the correct sum(raw[1:length]) seeding, matching TA-Lib's internal PLUS_DM / MINUS_DM calculation exactly. Used by dm.py — no more hand-rolled NumPy loop inlined.

Chained EMA Lookbacks

DEMA, TEMA, and T3 now correctly strip leading NaN before feeding EMA output back into EMA. This matches TA-Lib's lookback of depth*(length-1). Extracted into _ema_chain() in overlap/ema.py, reducing ~70 lines of repetitive boilerplate to ~10.

PSAR Reversal Check

The SAR guard (max/min clamp at row-1/row-2) now applies before the reversal test, matching TA-Lib's behaviour. Previously, the raw projected SAR was checked, causing off-by-one splits at reversal bars.

Bug Fixes

• cdl_doji — fixed < → <= threshold and added shift(1) to match TA-Lib's look-ahead behavior
• ichimoku — apply_fill now covers all 5 output series (was 3)
• pvr — added None-guard, offset, and fill support
• 13 indicators — added missing apply_fill for fillna/fill_method kwargs

🧪 Test Infrastructure

assertions.py + IndicatorSpec

assert_indicator_standard(self, IndicatorSpec(
    func=ta.rsi,
    args=[self.close],
    expected_name="RSI_14",
    expected_type=Series,
    none_arg_idx=0,
))

One call tests: return type, name, columns (DataFrame), offset, fill (fillna, ffill, bfill), None-guard, and length-in-name. Applied uniformly across all indicator test modules.

Property-Based Testing

55 Hypothesis tests using @given(price_series(), ...). Examples:

• SMA(constant) == constant for all window sizes
• BBANDS: lower ≤ mid ≤ upper for every row
• RSI output always ∈ [0, 100]
• STDEV always non-negative
• Offset preserves length, fillna removes NaN
• verify_series(None) returns None

Fixture Auto-Regeneration

tests/__init__.py now regenerates expected_values.json and regression_snapshots.json on import when TA-Lib is installed. No more stale fixtures — test data is always in sync with the code.

make test-all   # regenerate fixtures + run 1427 tests
make fixtures   # regenerate fixture JSONs only (requires TA-Lib)

Oracle Parity

• 60/60 TA-Lib oracle tests now pass at tol=1e-7 — exact float64 match achieved by the Wilder smoothing and chained EMA fixes

📦 Package & Quality

Code Modernization

• Removed 279 unnecessary # -*- coding: utf-8 -*- declarations (UP009)
• 65 useless f"..." prefixes (no placeholders) removed
• 87 unused imports removed across candle/overlap/momentum modules
• Optional[X] → X | None, List[Y] → list[Y] (pyupgrade)
• tal → talib rename — all test files now import talib directly
• ruff CI-critical checks (E9, F63, F7, F82) — all passed

Python Support

Tested and passing on Python 3.10, 3.11, 3.12, 3.13, 3.14.

🔗 Links

• GitHub: github.com/xgboosted/pandas-ta-classic
• PyPI: pip install pandas-ta-classic
• Changelog: CHANGELOG.md
• Contributing: CONTRIBUTING.md