Convert Pine Script into reviewed Python strategy packages.
Paste your Pine logic, let Stockey extract rules and assumptions, review the generated StrategySchema, run historical backtests with your own broker data access, and export a self-hosted Python package.
> strategy(...)> emaFast = ta.ema(close, 20)> emaSlow = ta.ema(close, 50)> longCondition = ta.crossover(emaFast, emaSlow)> exitCondition = ta.crossunder(emaFast, emaSlow)strategy_category: "trend_following"source_type: "pine_import"entry_rules: "review_required"exit_rules: "review_required"risk_controls: "missing"backtest_source: "broker_historical_or_csv"live_mode: "self_hosted_disabled_by_default"Pine conversion is not copy-paste automation. It is a review workflow.
Pine scripts often contain assumptions about timeframe, repainting, request.security calls, entry timing, order behavior, and missing risk controls. Stockey turns those assumptions into reviewable fields before generating code.
Rule extraction
Detect indicators, inputs, entry conditions, exit conditions, and strategy calls.
Assumption detection
Flag missing timeframe, segment, broker, risk, sizing, and data-source details.
Repainting review
Highlight logic that may behave differently in historical and self-hosted evaluation.
StrategySchema conversion
Normalize extracted rules into a structured, versioned strategy contract.
Python package generation
Generate strategy-specific code, configs, docs, and backtest entrypoints.
Human approval
Require user review before backtesting, package baking, or self-hosted deployment.
From Pine logic to self-hosted Python package.
Every stage keeps extracted rules, assumptions, data source, and package readiness visible before export.
paste strategy or indicator logic
detect indicators, entries, exits, and inputs
confirm missing risk, broker, timeframe, and segment details
create a structured Stockey strategy contract
use broker historical data or CSV selected by the user
review drawdowns, data gaps, rule behavior, and improvement ideas
export Python scripts, configs, and deployment docs
What Stockey can extract from Pine logic.
The converter creates a structured review draft; it does not claim perfect compatibility or skip human checks.
Inputs and parameters
Extract configurable variables and default values.
Indicators
Identify common moving averages, RSI, MACD, ATR, volume, and condition logic.
Entry and exit conditions
Detect crossover, crossunder, threshold, time, and condition rules.
Strategy calls
Map strategy-style calls into structured order-intent logic for review.
Alerts and webhooks
Convert alert-style logic into package configuration notes.
Visual plots
Use plots as explanation context, not as execution rules unless confirmed.
Some Pine logic must be confirmed before code generation.
Review-required items stay visible until the user confirms what should become part of the StrategySchema.
Review required
- request.security / multi-timeframe logic
- repainting-sensitive logic
- intrabar assumptions
- bar close vs real-time behavior
- broker segment and lot size
- stop loss and sizing rules
- partial exits and re-entry logic
- strategy pyramiding behavior
Not automatically assumed
- runtime execution behavior
- broker-specific order type
- F&O expiry selection
- options strike selection
- MCX contract rollover
- missing risk controls
- missing capital allocation
- missing transaction cost assumptions
Review assumptions before testing.
| Detected item | Current value | Confidence | Required action |
|---|---|---|---|
| Timeframe | Not specified | Low | Select timeframe |
| Segment | Not specified | Low | Choose Equity, Futures, Options, or MCX |
| Risk rule | Missing | High | Add SL / target / kill switch |
| Entry rule | EMA crossover | Medium | Confirm bar-close behavior |
| Exit rule | EMA crossunder | Medium | Confirm exit priority |
| Data source | Not selected | High | Choose broker historical data or CSV |
| Runtime behavior | Disabled | High | Self-hosted only after export |
Conversion readiness
Test converted logic with your own historical data access.
After review, Stockey can run historical backtests using broker-provided historical data or user-uploaded CSVs. The available range depends on the broker, instrument, segment, and timeframe.
Backtests are historical simulations. They do not predict future performance and are not investment advice.
AI analyzes the conversion and the backtest. It does not tell you what to trade.
AI analysis stays focused on strategy review, education, and user-selected experiments.
Conversion analysis
Explains extracted rules, missing assumptions, and translation risks.
Backtest analysis
Reviews drawdown, trade distribution, stop-loss behavior, exposure, and data limitations.
Improvement experiments
Suggests additional tests the user may choose to run, such as alternate exits, risk limits, or time filters.
Every approved conversion leaves as an auditable package.
Safeguards
Convert the script. Review the assumptions. Test before export.
Stockey turns Pine logic into a structured, reviewable Python strategy package — with historical backtesting and AI analysis before self-hosted deployment.