tensor-network-editor 0.2.2

Interactive local editor for building tensor networks and generating Python code.

Tensor Network Editor

tensor-network-editor is a local Python package for drawing tensor networks, saving them as versioned JSON, and generating readable Python code for several backends.

It is useful when you want a visual editor without losing the things that make scientific Python workflows practical: plain data objects, files you can version, offline use, and generated code you can inspect.

Why This Project

• Draw tensor-network diagrams in a local browser session.
• Save and reload backend-independent JSON designs.
• Generate code for tensornetwork, quimb, tensorkrowch, einsum_numpy, and einsum_torch.
• Use built-in templates for MPS, MPO, PEPS, MERA, and binary-tree layouts.
• Build repeated chains with For mode and export them with any bundled backend.
• Inspect manual contraction paths and optional planner suggestions.
• Get structural analysis with FLOP and MAC cost summaries.
• Use the package from the CLI or directly from Python.

The editor opens in your browser, but the server runs locally on your own machine. No Node runtime or cloud service is needed for normal use.

Minimal Installation

The PyPI package name is tensor-network-editor. The Python import package is tensor_network_editor.

PowerShell:

python -m venv .venv
.\.venv\Scripts\Activate.ps1
python -m pip install -U pip
python -m pip install tensor-network-editor

Bash:

python3 -m venv .venv
source .venv/bin/activate
python -m pip install -U pip
python -m pip install tensor-network-editor

For backend extras, planner support, source installs, and development setup, read docs/installation.md.

Basic Use

Launch the visual editor:

tensor-network-editor edit

This command starts a local server and waits until you press Done or Cancel in the browser session.

Open an existing design and save generated code when the session is confirmed:

tensor-network-editor edit --load my_network.json --engine quimb --save-code generated_network.py

Use the editor from Python:

from tensor_network_editor import launch_tensor_network_editor


def main() -> None:
    result = launch_tensor_network_editor()
    if result is None:
        print("Editor cancelled.")
        return

    print(f"Design name: {result.spec.name}")
    if result.codegen is not None:
        print(result.codegen.code)


if __name__ == "__main__":
    main()

Generate code without opening the editor:

from tensor_network_editor import EngineName, generate_code, load_spec


spec = load_spec("my_network.json")
result = generate_code(spec, engine=EngineName.EINSUM_NUMPY)
print(result.code)

Documentation

• Documentation index: where to go for each topic.
• Installation: full setup instructions.
• Getting started: first useful workflow.
• User guide: editor workflow, templates, planner, tips, and limits.
• Python API: public functions and practical examples.
• Data models: NetworkSpec, tensors, edges, groups, notes, and contraction plans.
• CLI: terminal commands, JSON output, and template workflows.
• Troubleshooting: common problems and fixes.

Current Limits

• Hyperedges are not supported yet.
• Real tensor values are not edited in the visual editor; generated tensors are initialized by the generated backend code.
• TenPy code generation is not included.
• For mode works with all bundled backends. Manual outer-product steps still cannot be exported safely to tensorkrowch.

Project Links

• Source code: github.com/DOKOS-TAYOS/Tensor-Network-Editor
• Changelog: CHANGELOG.md
• Example script: examples/basic_usage.py
• Issue tracker: github.com/DOKOS-TAYOS/Tensor-Network-Editor/issues
• License: LICENSE