kernc/backtesting.py

19.0

Adjusted Score

19.0

Raw Score

100%

Time Factor

2026-07-22

Last Push

8.7K

Stars

Python

Language

8.3K

Lines of Code

Files

Pattern Hits

2026-08-02

Scan Date

0.24

HC Hit Rate

What These Metrics Mean

Adjusted Score: Primary synthetic code indicator. Raw score normalised per 1,000 lines of code and multiplied by the temporal discount factor. This is the definitive comparative metric — use it to rank repositories by AI authorship density.
Raw Score: The unmodified sum of all severity-weighted, context-multiplied pattern match scores before temporal discounting. Reflects the absolute signal strength independent of when the repository was last active.
Time Factor: The temporal discount multiplier (0–100%) applied to the raw score. Repositories last updated before ChatGPT's launch (Nov 2022) receive a 5% factor. Full signal is only assigned to repositories active in the post-adoption era (Jan 2024+).
Pattern Hits: Total count of individual pattern matches across all files and categories. A high hit count with a low score may indicate a very large codebase with isolated AI snippets; a low count with a high score indicates dense, concentrated AI signatures.
HC Hit Rate: High+Critical pattern hits per file, averaged across the repository. This orthogonal signal catches repositories where a few files are densely packed with high-severity AI tells — a strong indicator even when the normalised score appears moderate due to codebase size.
Lines of Code / Files: Total lines and files analysed. The scanner examines 94 file extensions. These denominators are used to normalise the score, enabling fair comparison between repositories of vastly different sizes.

Score History

Longitudinal tracking requires multiple scan runs. Once this repository is re-scanned after new commits land, this chart will visualise how the synthetic code signal evolves over time — enabling you to detect whether AI authorship is growing, stabilising, or being actively corrected by human engineers.

No multi-scan history yet — run the scanner again to build trend data.

Severity Breakdown

Classifies detected patterns by their diagnostic confidence and structural impact. CRITICAL patterns (coefficient 10) represent definitive synthetic signatures — hallucinated imports, explicit LLM attribution metadata — virtually never produced by human authors. HIGH (5) indicates strong structural tells such as cross-file repetition or cross-linguistic idioms. MEDIUM (2) covers recognisable conversational padding and AI-specific vocabulary. LOW (1) captures subtle indicators like tautological comments and generic boilerplate that require density to carry independent signal.

CRITICAL 0HIGH 9MEDIUM 9LOW 80

Directory Score Breakdown

This horizontal bar chart decomposes the repository's raw synthetic code score by top-level directory, allowing you to pinpoint precisely which modules or components carry the highest AI authorship density. Directories with disproportionately high scores relative to their size warrant targeted manual review: concentrated AI signatures often trace back to mass-generated configuration layers, auto-ported test suites, LLM-scaffolded boilerplate classes, or entire subsystems authored under heavy copilot assistance. Use this view to prioritise your human code-review effort.

Pattern Findings

The scanner identified 98 distinct pattern matches across 13 syntactic categories. Each entry below represents a discrete location in the source code where the engine recorded a statistically significant AI authorship indicator. Expand any category row to inspect the individual file paths, line numbers, code snippets, and the lexical context (CODE, COMMENT, or STRING) in which each match was detected.

Reading the findings table: The Severity column indicates the diagnostic confidence level (CRITICAL / HIGH / MEDIUM / LOW). The Context column identifies whether the match occurred inside executable code, an inline comment, or a string literal — comment-context matches receive a ×1.5 weight because LLMs systematically over-annotate. The ⚡ bolt icon marks clustered matches: three or more patterns within a 10-line window, each receiving an additional ×1.5 density multiplier as dense clusters constitute far stronger evidence of synthetic authorship than isolated hits.

Cross-Language Confusion9 hits · 52 pts

Severity	File	Line	Snippet	Context
HIGH⚡	backtesting/_plotting.py	160	assert not indicators or indicators[0].df.index.equals(df.index)	CODE
HIGH⚡	backtesting/_plotting.py	163	assert equity_data.index.equals(df.index)	CODE
HIGH	backtesting/_plotting.py	221	assert df.index.equals(results['_equity_curve'].index)	CODE
HIGH	backtesting/_plotting.py	289	this.labels = this.labels \|\| formatter.doFormat(ticks	CODE
HIGH	backtesting/_plotting.py	291	.filter(t => t !== undefined));	CODE
HIGH	backtesting/_plotting.py	361	assert equity.index.equals(equity_data.index)	STRING
HIGH⚡	backtesting/test/_test.py	1124	assert close.s.equals(pd.Series(close, index=index))	CODE
HIGH⚡	backtesting/test/_test.py	1130	assert close.s.equals(pd.Series(close, index=index))	CODE
HIGH	backtesting/test/_test.py	309	self.assertTrue(df.equals(EURUSD))	CODE

Over-Commented Block24 hits · 24 pts

Severity	File	Line	Snippet	Context
LOW	backtesting/lib.py	261	# Let's convert closing prices back to pandas Series.	COMMENT
LOW	doc/examples/Strategies Library.py	1	# ---	COMMENT
LOW	doc/examples/Strategies Library.py	21	# [basic package usage](https://kernc.github.io/backtesting.py/doc/examples/Quick%20Start%20User%20Guide.html).	COMMENT
LOW	doc/examples/Strategies Library.py	101	# For other strategies of the sort, and other reusable utilities in general, see	COMMENT
LOW	doc/examples/Quick Start User Guide.py	1	# ---	COMMENT
LOW	doc/examples/Quick Start User Guide.py	21	# _Backtesting.py_ is a small and lightweight, blazing fast backtesting framework that uses state-of-the-art Python stru	COMMENT
LOW	doc/examples/Quick Start User Guide.py	41	# DataFrame should ideally be indexed with a _datetime index_ (convert it with [`pd.to_datetime()`](https://pandas.pydat	COMMENT
LOW	doc/examples/Quick Start User Guide.py	121	# [`self.data`](https://kernc.github.io/backtesting.py/doc/backtesting/backtesting.html#backtesting.backtesting.Strategy	COMMENT
LOW	doc/examples/Quick Start User Guide.py	141	# self.position.close()	COMMENT
LOW	doc/examples/Quick Start User Guide.py	161	from backtesting import Backtest	COMMENT
LOW	doc/examples/Quick Start User Guide.py	201	# %%	COMMENT
LOW	doc/examples/Quick Start User Guide.py	221	# The columns should be self-explanatory.	COMMENT
LOW	doc/examples/Parameter Heatmap & Optimization.py	1	# -- coding: utf-8 --	COMMENT
LOW	doc/examples/Parameter Heatmap & Optimization.py	21	# It is assumed you're already familiar with	COMMENT
LOW	doc/examples/Parameter Heatmap & Optimization.py	121	# It makes the function return a heatmap series along with the usual stats of the best run.	COMMENT
LOW	doc/examples/Parameter Heatmap & Optimization.py	161	)	COMMENT
LOW	doc/examples/Parameter Heatmap & Optimization.py	181	# ## Model-based optimization	COMMENT
LOW	doc/examples/Trading with Machine Learning.py	1	# ---	COMMENT
LOW	doc/examples/Trading with Machine Learning.py	21	# [basic framework usage](https://kernc.github.io/backtesting.py/doc/examples/Quick%20Start%20User%20Guide.html)	COMMENT
LOW	doc/examples/Trading with Machine Learning.py	261	bt.plot()	COMMENT
LOW	doc/examples/Trading with Machine Learning.py	281	# by increasing the conviction needed and imposing extra domain expertise and discretionary limitations before enterin	COMMENT
LOW	doc/examples/Multiple Time Frames.py	1	# ---	COMMENT
LOW	doc/examples/Multiple Time Frames.py	21	# [pandas resampling](https://pandas.pydata.org/pandas-docs/stable/user_guide/timeseries.html#resampling).	COMMENT
LOW	doc/examples/Multiple Time Frames.py	141	# In conclusion, to test strategies on multiple time frames, you need to pass in OHLC data in the lowest time frame, the	COMMENT

Hyper-Verbose Identifiers24 hits · 22 pts

Severity	File	Line	Snippet	Context
LOW	backtesting/_stats.py	14	def compute_drawdown_duration_peaks(dd: pd.Series):	CODE
LOW⚡	backtesting/test/_test.py	1136	def test_indicators_picklable(self):	CODE
LOW	backtesting/test/_test.py	100	def test_data_missing_columns(self):	CODE
LOW	backtesting/test/_test.py	238	def test_absolute_size_order_warns_on_insufficient_margin(self):	CODE
LOW	backtesting/test/_test.py	393	def test_compute_stats_bordercase(self):	CODE
LOW	backtesting/test/_test.py	426	def test_trade_enter_hit_sl_on_same_day(self):	CODE
LOW	backtesting/test/_test.py	444	def test_stop_price_between_sl_tp(self):	CODE
LOW	backtesting/test/_test.py	453	def test_position_close_portion(self):	CODE
LOW	backtesting/test/_test.py	468	def test_close_orders_from_last_strategy_iteration(self):	CODE
LOW	backtesting/test/_test.py	480	def test_check_adjusted_price_when_placing_order(self):	CODE
LOW	backtesting/test/_test.py	533	def test_broker_exclusive_orders(self):	CODE
LOW	backtesting/test/_test.py	545	def test_trade_multiple_close(self):	CODE
LOW	backtesting/test/_test.py	566	def test_stop_limit_order_price_is_stop_price(self):	CODE
LOW	backtesting/test/_test.py	575	def test_autoclose_trades_on_finish(self):	CODE
LOW	backtesting/test/_test.py	659	def test_optimize_invalid_param(self):	CODE
LOW	backtesting/test/_test.py	807	def test_resample_trades_vectorized(self):	CODE
LOW	backtesting/test/_test.py	1160	def test_backtest_run_docstring_contains_stats_keys(self):	CODE
LOW	backtesting/test/_test.py	1165	def test_readme_contains_stats_keys(self):	CODE
LOW	backtesting/test/_test.py	1204	def test_trade_on_close_closes_trades_on_close(self):	CODE
LOW	backtesting/test/_test.py	1239	def test_trades_dates_match_prices(self):	CODE
LOW	backtesting/test/_test.py	1259	def test_stop_entry_and_tp_in_same_bar(self):	CODE
LOW	backtesting/test/_test.py	1270	def test_optimize_datetime_index_with_timezone(self):	CODE
LOW	backtesting/test/_test.py	1276	def test_sl_tp_values_in_trades_df(self):	CODE
LOW	backtesting/test/_test.py	1287	def test_sl_value_in_trades_df_when_gapped_through(self):	CODE

Decorative Section Separators4 hits · 12 pts

Severity	File	Line	Snippet	Context
MEDIUM	doc/examples/Strategies Library.py	17	# ======================	COMMENT
MEDIUM	doc/examples/Quick Start User Guide.py	17	# =======================	COMMENT
MEDIUM	doc/examples/Parameter Heatmap & Optimization.py	18	# ==========	COMMENT
MEDIUM	doc/examples/Multiple Time Frames.py	17	# ============	COMMENT

AI Slop Vocabulary4 hits · 12 pts

Severity	File	Line	Snippet	Context
MEDIUM	doc/examples/Strategies Library.py	20	# It is, henceforth, assumed you're already familiar with	COMMENT
MEDIUM	doc/examples/Quick Start User Guide.py	21	# _Backtesting.py_ is a small and lightweight, blazing fast backtesting framework that uses state-of-the-art Python stru	COMMENT
MEDIUM	doc/examples/Parameter Heatmap & Optimization.py	91	# It's not a robust strategy, but we can optimize it.	COMMENT
MEDIUM	doc/examples/Trading with Machine Learning.py	151	# Let's backtest a simple strategy that buys the asset for 20% of available equity with 20:1 leverage whenever the forec	COMMENT

Unused Imports10 hits · 10 pts

Severity	File	Line	Context
LOW	backtesting/backtesting.py	9	CODE
LOW	backtesting/lib.py	14	CODE
LOW	backtesting/__init__.py	68	CODE
LOW	backtesting/__init__.py	69	CODE
LOW	backtesting/__init__.py	71	CODE
LOW	backtesting/__init__.py	71	CODE
LOW	backtesting/_plotting.py	1	CODE
LOW	backtesting/_util.py	1	CODE
LOW	backtesting/_stats.py	1	CODE
LOW	backtesting/test/__init__.py	3	CODE

Deep Nesting9 hits · 9 pts

Severity	File	Line	Context
LOW	backtesting/backtesting.py	765	CODE
LOW	backtesting/backtesting.py	875	CODE
LOW	backtesting/backtesting.py	1271	CODE
LOW	backtesting/backtesting.py	1386	CODE
LOW	backtesting/backtesting.py	1513	CODE
LOW	backtesting/lib.py	427	CODE
LOW	backtesting/_plotting.py	198	CODE
LOW	backtesting/_plotting.py	535	CODE
LOW	backtesting/_stats.py	37	CODE

AI Structural Patterns4 hits · 4 pts

Severity	File	Line	Context
LOW	backtesting/backtesting.py	1195	CODE
LOW	backtesting/backtesting.py	1658	CODE
LOW	backtesting/lib.py	330	CODE
LOW	backtesting/_plotting.py	198	CODE

Excessive Try-Catch Wrapping3 hits · 4 pts

Severity	File	Line	Snippet	Context
LOW	backtesting/backtesting.py	145	except Exception as e:	CODE
LOW⚡	backtesting/_plotting.py	152	except Exception:	CODE
LOW	backtesting/_util.py	304	except Exception:	CODE

Redundant / Tautological Comments3 hits · 4 pts

Severity	File	Line	Snippet	Context
LOW	backtesting/backtesting.py	887	# Check if stop condition was hit	COMMENT
LOW	backtesting/backtesting.py	899	# Check if limit order can be filled.	COMMENT
LOW	backtesting/_plotting.py	495	# Check if resampling was downsampling; error on upsampling	STRING

Self-Referential Comments1 hit · 3 pts

Severity	File	Line	Snippet	Context
MEDIUM	doc/examples/Quick Start User Guide.py	95	# Define the two MA lags as class variables	COMMENT

Modern Structural Boilerplate2 hits · 2 pts

Severity	File	Line	Snippet	Context
LOW	backtesting/backtesting.py	1772	__all__ = [getattr(v, '__name__', k)	CODE
LOW	backtesting/lib.py	640	__all__ = [getattr(v, '__name__', k)	CODE

Slop Phrases1 hit · 2 pts

Severity	File	Line	Snippet	Context
LOW	doc/examples/Trading with Machine Learning.py	283	# Also make sure to familiarize yourself with the full	COMMENT

Analysis Overview

What These Metrics Mean

Score History

Severity Breakdown

Directory Score Breakdown

Pattern Findings