PyPScript Best Practices

Good PyPScript is not just valid.

It is:

• easy to read
• easy to review
• easy to explain
• conservative about when it trades

1. Start With One Clear Idea

A script should have one main reason for existing.

Examples:

• trend continuation
• pullback entry
• momentum breakout
• mean reversion

Bad scripts often try to be all of them at once.

2. Name For Meaning

Prefer:

trend_up
momentum_up
entry_trigger
volatility_ok

Avoid:

x1
cond2
my_signal
temp_a

If the variable name cannot be understood without reading the formula, the name is weak.

3. Separate Measurements From Decisions

Good structure:

fast_ma = sma.evaluate(close, 20)
slow_ma = sma.evaluate(close, 50)
rsi_value = rsi.evaluate(close, 14)

trend_up = above(fast_ma, slow_ma)
momentum_up = above(rsi_value, 55)
entry_trigger = cross(close, fast_ma)

This is easier to maintain than mixing every calculation directly inside the patterns block.

4. Keep Patterns Short

Good:

patterns {
    trend_up and momentum_up and entry_trigger -> UP(confidence: 0.85)
    default -> HOLD(confidence: 0.95)
}

Weak:

patterns {
    above(sma.evaluate(close, 20), sma.evaluate(close, 50)) and above(rsi.evaluate(close, 14), 55) and cross(close, sma.evaluate(close, 20)) -> UP(confidence: 0.85)
    default -> HOLD(confidence: 0.95)
}

5. Treat HOLD As A Feature

A serious strategy should be comfortable not trading.

Use HOLD for:

• neutral momentum
• contradictory conditions
• weak structure
• low-conviction zones

Do not force signals where there is no real edge.

6. Put Stronger Rules First

Patterns are order-dependent.

Write them from:

• strongest
• to weaker
• to default hold

Example:

patterns {
    trend_up and momentum_up and breakout -> UP(confidence: 0.90)
    trend_up and breakout -> UP(confidence: 0.75)
    default -> HOLD(confidence: 0.96)
}

7. Use Confidence Honestly

Do not inflate confidence because the pattern looks sophisticated.

A good rule of thumb:

• more filters and cleaner context = higher confidence
• broader fallback conditions = lower confidence
• explicit neutral-state hold = very high confidence hold is often fine

8. Keep The Script Internally Consistent

If the script name, meta description, and config say one thing, the logic should match.

Example:

If the script is named:

eurusd_1m_scalper

then the config and logic should not read like a slow swing system.

9. Avoid Redundant Calculations

Weak:

patterns {
    above(close, sma.evaluate(close, 50)) -> UP(confidence: 0.70)
    below(close, sma.evaluate(close, 50)) -> DOWN(confidence: 0.70)
    default -> HOLD(confidence: 0.95)
}

Better:

trend_ma = sma.evaluate(close, 50)

patterns {
    above(close, trend_ma) -> UP(confidence: 0.70)
    below(close, trend_ma) -> DOWN(confidence: 0.70)
    default -> HOLD(confidence: 0.95)
}

10. Be Conservative With Multi-Timeframe Scope

If a script only truly makes sense on one timeframe, say so in config.

Do not make a strategy “multi-timeframe” just because the UI allows it.

11. Comment The Why, Not The Obvious

Useful comment:

// Only allow longs when price structure and momentum agree

Weak comment:

// Calculate RSI
momentum = rsi.evaluate(close, 14)

12. Write Reviewable Strategies

Ask these questions:

• Can another trader explain the long setup in one sentence?
• Can they explain the short setup in one sentence?
• Can they tell when the script is intentionally doing nothing?

If not, simplify.

Example Of A Clean Script

#!pyp/1.0
engine: pyp-1.0

import indicators.sma
import indicators.rsi
import indicators.atr
import functions.above
import functions.below
import functions.cross

strategy "clean_trend_pullback" {
    fast_ma = sma.evaluate(close, 20)
    slow_ma = sma.evaluate(close, 50)
    rsi_value = rsi.evaluate(close, 14)
    atr_value = atr.evaluate(high, low, close, 14)

    trend_up = above(fast_ma, slow_ma)
    trend_down = below(fast_ma, slow_ma)
    long_momentum = above(rsi_value, 55)
    short_momentum = below(rsi_value, 45)
    volatility_ok = above(atr_value, 0.0)
    long_trigger = cross(close, fast_ma)
    short_trigger = cross(fast_ma, close)

    patterns {
        trend_up and long_momentum and long_trigger and volatility_ok -> UP(confidence: 0.85)
        trend_down and short_momentum and short_trigger and volatility_ok -> DOWN(confidence: 0.85)
        default -> HOLD(confidence: 0.96)
    }
}

meta {
    author: "PyP"
    version: "1.0.0"
    description: "Trend pullback logic for intraday directional moves"
}

config {
    pairs: ["EURUSD"]
    timeframes: ["5m"]
}

Final Standard

A strong PyPScript file should feel like:

• a trading thesis
• translated into a precise decision table

not like:

• a pile of indicator calls

Related Pages

• Basics
• Pattern Matching
• Troubleshooting