PyneCore - Pine Script to Python Transpiler

Installation (New Computer)

# 1. Navigate to the pynecore directory
cd pynecore

# 2. Create virtual environment
python3 -m venv .venv

# 3. Install pynecore runtime (editable mode)
.venv/bin/pip install -e ~/workspace/github/pynecore

# 4. Install required dependencies
.venv/bin/pip install typer typing_extensions

# 5. Activate the virtual environment
source .venv/bin/activate  # On Linux/mac
# OR
.venv\Scripts\activate     # On Windows

Note: All commands below assume you are in the pynecore directory with the venv activated.

How to Convert Pine Script to Python

Single File Conversion

python -m pine2pyne path/to/script.pine -o path/to/output.py

Batch Conversion

python -m pine2pyne "sample/pinescript/*.pine" -o workdir/scripts/

Running Tests

Run All Test Samples

python test_all_samples.py

Run Specific Pattern

python test_all_samples.py "ex_001*"          # Filter by pattern
python test_all_samples.py "ex_347_*"        # Single file pattern

Additional Options

python test_all_samples.py --timeout 30       # Custom timeout (default: 15s)
python test_all_samples.py --verbose           # Show stderr on failure

Test Framework Details

• Source directory: sample/pinescript/
• Output directory: workdir/scripts/
• Test data: workdir/data/
• Results: test_results.json and test_results.txt

For Claude Code / LLM Development

See CLAUDE.md in this directory for transpiler architecture, output format specs, optimizer documentation, and CSV rounding rules. See pine2pyne/README.md for transpiler internals and transformation rules.

Optimizing Strategies

Quick start: pyne optimize script.py data.ohlcv params.json -n 20

See Optimizer.md for full documentation (parameter JSON format, parallel execution, output files).

Distributed Optimization (multi-machine)

Two tools distribute pyne optimize across SSH clusters:

# Dynamic (recommended): flat-queue, pre-syncs once, auto-adapts to machine speed
# Run from workdir/ directory:
../tools/pyne-dynamic.sh scripts/strategy.py data/data.ohlcv optimize_variants/ \
  -H ../tools/machines.txt -C 24 --name my_run --output-dir runs/output/

# Static: pre-assigns chunks by core count
./tools/pyne-parallel.sh scripts/strategy.py data/data.ohlcv optimize.json \
  -H tools/machines.txt --sync

# Check progress / collect results
../tools/pyne-dynamic.sh --status
../tools/pyne-dynamic.sh --collect

Both use the same machines.txt format. See CLAUDE.md for cluster setup, machine file format, and troubleshooting.