support standalone library

.github/workflows/deploy.yml

@@ -26,7 +26,7 @@ jobs:
             set -e
             cd /opt/tono
             git pull --ff-only
-            .venv/bin/pip install -e . --quiet
+            .venv/bin/pip install -e ".[server]" --quiet
             cd frontend && npm ci --ignore-scripts && npm run build && cd ..
             sudo systemctl restart tono
           REMOTE

.github/workflows/tests.yml

@@ -22,7 +22,7 @@ jobs:
           cache: npm
 
       - name: Install Python dependencies
-        run: pip install -e ".[dev]"
+        run: pip install -e ".[server,dev]"
 
       - name: Install Node dependencies
         run: npm install --ignore-scripts

README.md

@@ -16,7 +16,7 @@ Install a local binary from the Releases section, or run locally:
 ```bash
 # Installation
 python -m venv .venv && source .venv/bin/activate   # Windows: .venv\Scripts\activate
-pip install -e ".[dev]"
+pip install -e ".[server,dev]"
 npm install
 
 # Running the servers
@@ -29,29 +29,46 @@ npm run dev       # terminal 2 — Vite dev server, open the URL it prints
 ```bash
 git clone https://github.com/VIPQualityPost/tono.git && cd tono
 python -m venv .venv && source .venv/bin/activate
-pip install -e .
+pip install -e ".[server]"
 cd frontend && npm ci && npm run build && cd ..
 TONO_HOST=0.0.0.0 python -m backend.main
 ```
 
 See [Self-Hosting](docs/self-hosting.md) for reverse proxy setup, environment variables, and configuration.
 
+## Python library
+
+tono's processing nodes can also be used as a standalone Python library — no server needed:
+
+```bash
+pip install -e .
+```
+
+```python
+import tono
+
+fields = tono.load("scan.gwy")
+leveled = tono.apply("PlaneLevelField", fields[0])
+filtered = tono.apply("GaussianFilter", leveled, sigma=2.0)
+```
+
+See [Library Usage](docs/library.md) for the full API and more examples.
+
 ## Docs
 
 - [Building](docs/building.md) — setup, dev mode, web deployment, and native desktop builds for macOS, Linux, and Windows
 - [Self-Hosting](docs/self-hosting.md) — deploying tono on a server
+- [Library Usage](docs/library.md) — using tono as a Python signal processing library
 - [Plugins](docs/plugins.md) — writing and uploading custom node plugins
 - [Testing](docs/testing.md) — running tests and writing new ones
 
-## Project layout
+## Project plans
 
-```text
+- Please help with providing demo files for validating importers!
-tono/
+- Please try making weird workflows to see what breaks or does not flow nicely
-  backend/         Python server, execution engine, nodes
+
-  frontend/        React/Vite app
+- Adding support for force curves
-  plugins/         User plugin files (.py)
+- Adding general support for spectroscopic data
-  tests/           Python tests
+- Adding general support for spectroscopic volumes
-  docs/            Documentation
+
-  desktop.py       Desktop launcher
+- Adding more generic numerical operations and visualisations
-  scripts/         Build scripts (macOS, Linux, Windows)
-```

backend/api.py

@@ -0,0 +1,233 @@
+"""
+Standalone library API for tono signal processing nodes.
+
+Usage::
+
+    import tono
+
+    # Load an SPM file
+    fields = tono.load("scan.gwy")
+    field = fields[0]
+
+    # Apply a processing node
+    result = tono.apply("GaussianFilter", field, sigma=3.0)
+
+    # Chain operations
+    result = tono.apply("PlaneLevelField", field, mode="subtract_mean")
+    result = tono.apply("GaussianFilter", result, sigma=2.0)
+
+    # Get available nodes
+    print(tono.nodes())
+
+    # Direct node access
+    node = tono.get_node("GaussianFilter")
+    (filtered,) = node.process(field=field, sigma=3.0)
+"""
+
+from __future__ import annotations
+
+from pathlib import Path
+from typing import Any
+
+from backend.data_types import DataField, LineData, RecordTable, DataTable, MeshModel
+
+
+def _ensure_registry() -> None:
+    """Import all node modules so @register_node decorators fire."""
+    from backend.node_registry import NODE_CLASS_MAPPINGS
+    if NODE_CLASS_MAPPINGS:
+        return
+    import backend.nodes  # noqa: F401 — triggers auto-discovery
+
+
+def load(path: str | Path) -> list[DataField]:
+    """Load an SPM data file and return a list of DataField channels.
+
+    Supported formats: .gwy, .sxm, .ibw, .hdf5, .png, .tif, .jpg, and more.
+
+    Parameters
+    ----------
+    path : str or Path
+        Path to the data file.
+
+    Returns
+    -------
+    list[DataField]
+        One DataField per channel in the file.
+
+    Raises
+    ------
+    ValueError
+        If the file extension is not supported.
+    """
+    from backend.importers import get_importer
+
+    p = Path(path)
+    ext = p.suffix.lower()
+    importer = get_importer(ext)
+    if importer is None:
+        from backend.importers import all_extensions
+        supported = ", ".join(sorted(all_extensions()))
+        raise ValueError(
+            f"Unsupported file extension {ext!r}. Supported: {supported}"
+        )
+    return importer.load(str(p))
+
+
+def channel_names(path: str | Path) -> list[str]:
+    """Return the channel names in a data file without loading the full data."""
+    from backend.importers import get_importer
+
+    p = Path(path)
+    importer = get_importer(p.suffix.lower())
+    if importer is None:
+        raise ValueError(f"Unsupported file extension: {p.suffix!r}")
+    return importer.channel_names(str(p))
+
+
+def supported_formats() -> frozenset[str]:
+    """Return all supported file extensions (e.g. {'.gwy', '.sxm', ...})."""
+    from backend.importers import all_extensions
+    return all_extensions()
+
+
+def nodes() -> list[str]:
+    """Return a sorted list of all registered node class names."""
+    from backend.node_registry import NODE_CLASS_MAPPINGS
+    _ensure_registry()
+    return sorted(NODE_CLASS_MAPPINGS.keys())
+
+
+def get_node(class_name: str) -> Any:
+    """Return a fresh instance of the named node class.
+
+    Parameters
+    ----------
+    class_name : str
+        The node class name, e.g. ``"GaussianFilter"``.
+
+    Returns
+    -------
+    object
+        A node instance. Call its ``process(**kwargs)`` method to run it.
+
+    Raises
+    ------
+    KeyError
+        If no node with that name is registered.
+    """
+    from backend.node_registry import NODE_CLASS_MAPPINGS
+    _ensure_registry()
+    if class_name not in NODE_CLASS_MAPPINGS:
+        raise KeyError(
+            f"Unknown node {class_name!r}. "
+            f"Use tono.nodes() to list available nodes."
+        )
+    return NODE_CLASS_MAPPINGS[class_name]()
+
+
+def apply(class_name: str, *args: Any, **kwargs: Any) -> Any:
+    """Run a node's process function and return the result.
+
+    Positional arguments are mapped to the node's required inputs in order.
+    Keyword arguments are passed directly.
+
+    If the node returns a single output, it is unwrapped from the tuple.
+    If the node returns multiple outputs, the full tuple is returned.
+
+    Parameters
+    ----------
+    class_name : str
+        The node class name, e.g. ``"GaussianFilter"``.
+    *args
+        Positional arguments mapped to required inputs in declaration order.
+    **kwargs
+        Keyword arguments passed directly to the node's process function.
+
+    Returns
+    -------
+    DataField or tuple
+        Single output unwrapped, or tuple of outputs if multiple.
+
+    Examples
+    --------
+    >>> result = tono.apply("GaussianFilter", field, sigma=3.0)
+    >>> leveled, mask = tono.apply("PlaneLevelField", field, mode="subtract_mean")
+    """
+    from backend.node_registry import NODE_CLASS_MAPPINGS
+    from backend.execution_context import execution_callbacks, active_node
+
+    _ensure_registry()
+    if class_name not in NODE_CLASS_MAPPINGS:
+        raise KeyError(
+            f"Unknown node {class_name!r}. "
+            f"Use tono.nodes() to list available nodes."
+        )
+
+    cls = NODE_CLASS_MAPPINGS[class_name]
+    instance = cls()
+
+    # Map positional args to required input names in declaration order
+    if args:
+        input_types = cls.INPUT_TYPES()
+        required_names = list(input_types.get("required", {}).keys())
+        for i, arg in enumerate(args):
+            if i >= len(required_names):
+                raise TypeError(
+                    f"{class_name} has {len(required_names)} required inputs, "
+                    f"but {len(args)} positional arguments were given"
+                )
+            name = required_names[i]
+            if name in kwargs:
+                raise TypeError(
+                    f"{class_name}: input {name!r} specified both as positional "
+                    f"argument and keyword argument"
+                )
+            kwargs[name] = arg
+
+    func = getattr(instance, cls.FUNCTION)
+
+    # Run inside an execution context so emit_* calls are no-ops
+    with execution_callbacks(), active_node("api"):
+        result = func(**kwargs)
+
+    if not isinstance(result, tuple):
+        result = (result,)
+
+    return result[0] if len(result) == 1 else result
+
+
+def field(data: Any, xreal: float = 1e-6, yreal: float = 1e-6,
+          si_unit_xy: str = "m", si_unit_z: str = "m", **kwargs: Any) -> DataField:
+    """Create a DataField from a 2D array.
+
+    A convenience wrapper around ``DataField(...)`` with sensible defaults.
+
+    Parameters
+    ----------
+    data : array_like
+        2D numpy array or anything convertible to one.
+    xreal : float
+        Physical width in metres (default 1 um).
+    yreal : float
+        Physical height in metres (default 1 um).
+    si_unit_xy : str
+        Lateral unit string (default "m").
+    si_unit_z : str
+        Height/value unit string (default "m").
+    **kwargs
+        Additional DataField keyword arguments.
+
+    Returns
+    -------
+    DataField
+    """
+    import numpy as np
+    return DataField(
+        data=np.asarray(data, dtype=np.float64),
+        xreal=xreal,
+        yreal=yreal,
+        si_unit_xy=si_unit_xy,
+        si_unit_z=si_unit_z,
+        **kwargs,
+    )

docs/building.md

@@ -8,17 +8,17 @@
 ### First-time setup
 
 ```bash
-# Install Python dependencies
+# Install Python dependencies (server extra required for the web app)
-pip install -e .
+pip install -e ".[server]"
 
 # Install frontend dependencies
 npm install
 
 # For running tests
-pip install -e ".[dev]"
+pip install -e ".[server,dev]"
 
 # For building desktop executables
-pip install -e ".[desktop]"
+pip install -e ".[server,desktop]"
 ```
 
 Using a virtual environment is recommended:
@@ -26,7 +26,7 @@ Using a virtual environment is recommended:
 ```bash
 python -m venv .venv
 source .venv/bin/activate   # Windows: .venv\Scripts\activate
-pip install -e ".[dev,desktop]"
+pip install -e ".[server,dev,desktop]"
 ```
 
 ---

docs/library.md

@@ -0,0 +1,212 @@
+# Using tono as a Python library
+
+tono's processing nodes can be used as a standalone Python library for scripting, batch processing, and integration into other tools — no web server required.
+
+## Installation
+
+```bash
+pip install -e .
+```
+
+This installs the core library with all signal processing dependencies (numpy, scipy, scikit-image, etc.) but **not** the web server (aiohttp). To install the full app with the server, use `pip install -e ".[server]"`.
+
+## Quick start
+
+```python
+import tono
+
+# Load an SPM data file
+fields = tono.load("scan.gwy")
+height = fields[0]
+
+# Apply a processing node
+leveled = tono.apply("PlaneLevelField", height)
+filtered = tono.apply("GaussianFilter", leveled, sigma=2.0)
+
+# Access the raw numpy array
+print(filtered.data.shape)   # (256, 256)
+print(filtered.data.mean())  # height in metres
+```
+
+## API reference
+
+### Loading data
+
+#### `tono.load(path) -> list[DataField]`
+
+Load an SPM data file. Returns one `DataField` per channel.
+
+```python
+fields = tono.load("scan.gwy")       # Gwyddion
+fields = tono.load("image.sxm")      # Nanonis
+fields = tono.load("data.ibw")       # Igor Binary Wave
+fields = tono.load("scan.hdf5")      # HDF5
+fields = tono.load("photo.png")      # Standard images
+```
+
+#### `tono.channel_names(path) -> list[str]`
+
+Get channel names without loading the full data.
+
+```python
+names = tono.channel_names("scan.gwy")
+# ['Height', 'Phase', 'Amplitude']
+```
+
+#### `tono.supported_formats() -> frozenset[str]`
+
+List all supported file extensions.
+
+### Processing
+
+#### `tono.apply(node_name, *args, **kwargs)`
+
+Run a processing node. Positional arguments are mapped to required inputs in declaration order. Returns a single output if the node has one output, or a tuple if it has multiple.
+
+```python
+# Positional: first required input is `field`
+result = tono.apply("GaussianFilter", my_field, sigma=3.0)
+
+# All keyword arguments
+result = tono.apply("GaussianFilter", field=my_field, sigma=3.0)
+
+# Nodes with multiple outputs return a tuple
+field_out, mask_out = tono.apply("ThresholdMask", my_field, method="otsu")
+```
+
+#### `tono.get_node(name) -> node_instance`
+
+Get a node instance for direct use. This gives full control over the node's `process()` method.
+
+```python
+gauss = tono.get_node("GaussianFilter")
+(result,) = gauss.process(field=my_field, sigma=3.0)
+```
+
+#### `tono.nodes() -> list[str]`
+
+List all available node class names.
+
+```python
+for name in tono.nodes():
+    print(name)
+```
+
+### Creating data
+
+#### `tono.field(data, xreal=1e-6, yreal=1e-6, ...) -> DataField`
+
+Create a `DataField` from a numpy array.
+
+```python
+import numpy as np
+
+# From a numpy array
+f = tono.field(np.random.randn(256, 256))
+
+# With physical dimensions (10 um x 10 um scan)
+f = tono.field(data, xreal=10e-6, yreal=10e-6, si_unit_z="V")
+```
+
+### Data types
+
+#### `DataField`
+
+The core 2D data container, analogous to Gwyddion's `GwyDataField`.
+
+| Attribute | Type | Description |
+|---|---|---|
+| `data` | `np.ndarray` | 2D float64 array (yres x xres) |
+| `xres`, `yres` | `int` | Pixel dimensions |
+| `xreal`, `yreal` | `float` | Physical dimensions in metres |
+| `dx`, `dy` | `float` | Pixel size in metres (property) |
+| `si_unit_xy` | `str` | Lateral unit (e.g. `"m"`) |
+| `si_unit_z` | `str` | Value unit (e.g. `"m"`, `"V"`, `"A"`) |
+| `domain` | `str` | `"spatial"` or `"frequency"` |
+
+Key methods:
+- `field.copy()` — deep copy
+- `field.replace(data=..., si_unit_z=...)` — copy with selected fields replaced
+
+#### Other types
+
+- `LineData` — 1D data with optional x-axis and units
+- `RecordTable` — list of `{quantity, value, unit}` dicts (scalar measurements)
+- `DataTable` — list of row dicts (tabular data like grain statistics)
+
+## Batch processing example
+
+```python
+import tono
+from pathlib import Path
+
+input_dir = Path("scans/")
+results = {}
+
+for path in input_dir.glob("*.gwy"):
+    fields = tono.load(path)
+    height = fields[0]
+
+    # Standard processing pipeline
+    leveled = tono.apply("PlaneLevelField", height)
+    filtered = tono.apply("GaussianFilter", leveled, sigma=1.5)
+
+    # Extract statistics
+    stats_node = tono.get_node("Statistics")
+    (table,) = stats_node.process(field=filtered)
+    results[path.name] = table
+
+    print(f"{path.name}: processed {height.xres}x{height.yres} "
+          f"({height.xreal*1e6:.1f} x {height.yreal*1e6:.1f} um)")
+```
+
+## Integration with matplotlib
+
+```python
+import tono
+import matplotlib.pyplot as plt
+import numpy as np
+
+fields = tono.load("scan.gwy")
+field = fields[0]
+
+# Convert physical coordinates for axis labels
+extent = [0, field.xreal * 1e6, 0, field.yreal * 1e6]  # in micrometres
+
+fig, axes = plt.subplots(1, 3, figsize=(15, 4))
+
+axes[0].imshow(field.data * 1e9, extent=extent, cmap="afmhot")
+axes[0].set_title("Raw")
+axes[0].set_xlabel("x (um)")
+axes[0].set_ylabel("y (um)")
+
+leveled = tono.apply("PlaneLevelField", field)
+axes[1].imshow(leveled.data * 1e9, extent=extent, cmap="afmhot")
+axes[1].set_title("Leveled")
+
+filtered = tono.apply("GaussianFilter", leveled, sigma=2.0)
+axes[2].imshow(filtered.data * 1e9, extent=extent, cmap="afmhot")
+axes[2].set_title("Filtered")
+
+for ax in axes:
+    ax.set_xlabel("x (um)")
+
+plt.tight_layout()
+plt.savefig("pipeline.png", dpi=150)
+```
+
+## Available nodes
+
+Use `tono.nodes()` to list all nodes. Major categories include:
+
+| Category | Example nodes |
+|---|---|
+| **Level & Correct** | PlaneLevelField, PolyLevelField, FacetLevelField, LineCorrection, DriftCorrection |
+| **Filter** | GaussianFilter, MedianFilter, KuwaharaFilter, WaveletDenoise, EdgeDetect |
+| **Spectral** | FFT2D, FFT2DInverse, FFTFilter, PSDF, ACF2D, CrossCorrelate |
+| **Measure** | Statistics, Histogram, CrossSection, Curvature, FractalDimension |
+| **Detect** | FeatureDetection, HoughTransform, TemplateMatch, PixelClassification |
+| **Mask** | ThresholdMask, GrainMark, DrawMask, MaskMorphology |
+| **Grains** | GrainAnalysis, WatershedSegmentation, GrainDistributions |
+| **Geometry** | CropResizeField, RotateField, Resample, AffineCorrection |
+| **Tip** | TipModel, TipDeconvolution, BlindTipEstimate |

docs/self-hosting.md

@@ -7,7 +7,7 @@ tono can be self-hosted on any server with Python 3.10+ and Node.js 18+.
 ```bash
 git clone https://github.com/VIPQualityPost/tono.git && cd tono
 python -m venv .venv && source .venv/bin/activate
-pip install -e .
+pip install -e ".[server]"
 cd frontend && npm ci && npm run build && cd ..
 TONO_HOST=0.0.0.0 python -m backend.main
 ```
@@ -31,7 +31,7 @@ sudo chown tono:tono /var/lib/tono
 ```bash
 sudo git clone https://github.com/VIPQualityPost/tono.git /opt/tono
 sudo chown -R tono:tono /opt/tono
-sudo -u tono bash -c 'cd /opt/tono && python3 -m venv .venv && source .venv/bin/activate && pip install -e .'
+sudo -u tono bash -c 'cd /opt/tono && python3 -m venv .venv && source .venv/bin/activate && pip install -e ".[server]"'
 sudo -u tono bash -c 'cd /opt/tono/frontend && npm ci && npm run build'
 ```
 

examples/library_usage.py

@@ -0,0 +1,77 @@
+#!/usr/bin/env python3
+"""
+Example: using tono as a standalone signal processing library.
+
+Run from the repo root:
+    python examples/library_usage.py
+"""
+
+import numpy as np
+import tono
+
+# ── 1. Generate a synthetic surface ──────────────────────────────────
+
+print("Generating synthetic surface...")
+surface = tono.apply(
+    "SyntheticSurface",
+    pattern="fbm",
+    xres=256,
+    yres=256,
+    xreal=10e-6,   # 10 um
+    yreal=10e-6,
+    amplitude=50e-9,  # 50 nm height range
+    seed=42,
+)
+print(f"  Shape: {surface.data.shape}")
+print(f"  Physical size: {surface.xreal*1e6:.1f} x {surface.yreal*1e6:.1f} um")
+print(f"  Height range: {np.ptp(surface.data)*1e9:.1f} nm")
+
+# ── 2. Level the surface ─────────────────────────────────────────────
+
+print("\nLeveling...")
+leveled = tono.apply("PlaneLevelField", surface)
+print(f"  Mean after leveling: {leveled.data.mean()*1e9:.4f} nm")
+
+# ── 3. Apply a Gaussian filter ───────────────────────────────────────
+
+print("\nFiltering...")
+filtered = tono.apply("GaussianFilter", leveled, sigma=2.0)
+print(f"  Height range after filtering: {np.ptp(filtered.data)*1e9:.1f} nm")
+
+# ── 4. Compute statistics ────────────────────────────────────────────
+
+print("\nStatistics:")
+stats_node = tono.get_node("Statistics")
+(table,) = stats_node.process(field=filtered)
+for row in table:
+    print(f"  {row['quantity']}: {row['value']:.6g} {row.get('unit', '')}")
+
+# ── 5. Edge detection ────────────────────────────────────────────────
+
+print("\nEdge detection...")
+edges = tono.apply("EdgeDetect", filtered, method="sobel", sigma=1.0)
+print(f"  Edge map range: [{edges.data.min():.2f}, {edges.data.max():.2f}]")
+
+# ── 6. Create a DataField from a numpy array ─────────────────────────
+
+print("\nCreating field from numpy array...")
+data = np.sin(np.linspace(0, 4 * np.pi, 128).reshape(1, -1)) * \
+       np.cos(np.linspace(0, 6 * np.pi, 128).reshape(-1, 1))
+custom_field = tono.field(data, xreal=5e-6, yreal=5e-6, si_unit_z="V")
+print(f"  Shape: {custom_field.data.shape}")
+print(f"  Unit: {custom_field.si_unit_z}")
+
+# ── 7. FFT analysis ──────────────────────────────────────────────────
+
+print("\nFFT of the filtered surface...")
+fft_log_mag, fft_mag, fft_phase, fft_psdf = tono.apply("FFT2D", filtered, windowing="hann", level="mean")
+print(f"  FFT shape: {fft_mag.data.shape}")
+print(f"  Domain: {fft_mag.domain}")
+
+# ── 8. List available nodes ──────────────────────────────────────────
+
+all_nodes = tono.nodes()
+print(f"\nTotal available nodes: {len(all_nodes)}")
+print("First 10:", ", ".join(all_nodes[:10]))
+
+print("\nDone!")

pyproject.toml

@@ -9,7 +9,6 @@ description = "topographical node-based image analysis."
 readme = "README.md"
 requires-python = ">=3.10"
 dependencies = [
-    "aiohttp>=3.9,<4",
     "gwyfile>=0.2",
     "h5py>=3.10,<4",
     "igor>=0.3",
@@ -22,6 +21,9 @@ dependencies = [
 ]
 
 [project.optional-dependencies]
+server = [
+    "aiohttp>=3.9,<4",
+]
 dev = [
     "pytest>=8,<9",
     "pytest-cov>=7,<8",
@@ -38,6 +40,9 @@ icons = [
 [project.scripts]
 tono = "backend.main:main"
 
+[tool.setuptools]
+py-modules = ["tono"]
+
 [tool.setuptools.packages.find]
 include = ["backend*"]
 

scripts/build-linux.sh

@@ -28,7 +28,7 @@ echo "Building frontend bundle..."
 npm run build
 
 echo "Installing desktop build dependencies..."
-uv pip install -e ".[desktop]"
+uv pip install -e ".[server,desktop]"
 
 echo "Packaging desktop app with PyInstaller..."
 $PYTHON -m PyInstaller \

scripts/build-mac.sh

@@ -28,7 +28,7 @@ echo "Building frontend bundle..."
 npm run build
 
 echo "Installing desktop build dependencies..."
-uv pip install -e ".[desktop]"
+uv pip install -e ".[server,desktop]"
 
 echo "Packaging desktop app with PyInstaller..."
 $PYTHON -m PyInstaller \

scripts/build-windows.ps1

@@ -46,7 +46,7 @@ npm run build
 Assert-LastExitCode "Frontend build"
 
 Write-Host "Installing desktop build dependencies..."
-& uv pip install -e ".[desktop]"
+& uv pip install -e ".[server,desktop]"
 Assert-LastExitCode "Desktop dependency installation"
 
 $pyInstallerArgs = @(

tono.py

@@ -0,0 +1,40 @@
+"""
+tono — topographical signal processing library.
+
+This module provides a convenient ``import tono`` entry point for using
+tono's processing nodes as a standalone Python library, without running
+the web server.
+
+Quick start::
+
+    import tono
+
+    # Load SPM data
+    fields = tono.load("scan.gwy")
+
+    # Process
+    result = tono.apply("GaussianFilter", fields[0], sigma=3.0)
+
+    # Create a field from a numpy array
+    import numpy as np
+    f = tono.field(np.random.randn(256, 256))
+
+See ``backend.api`` for the full API documentation.
+"""
+
+from backend.api import (  # noqa: F401
+    apply,
+    channel_names,
+    field,
+    get_node,
+    load,
+    nodes,
+    supported_formats,
+)
+from backend.data_types import (  # noqa: F401
+    DataField,
+    DataTable,
+    LineData,
+    MeshModel,
+    RecordTable,
+)