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Airfoil analysis in Python — XFOIL-faithful solver with a local web UI

Project description

flexfoil

Airfoil analysis in Python -- XFOIL-faithful viscous solver with a local web UI.

import flexfoil

foil = flexfoil.naca("2412")
result = foil.solve(alpha=5.0, Re=1e6)
print(result)
# SolveResult(α=5.00°, Re=1e+06, CL=0.8094, CD=0.00775, CM=-0.0540, converged)

Install

pip install flexfoil

Pre-built wheels are available for:

  • macOS (Apple Silicon and Intel)
  • Linux x86_64
  • Windows x86_64

Plotly is included by default for interactive plots. Optional extras:

pip install "flexfoil[all]"        # server + matplotlib + pandas
pip install "flexfoil[matplotlib]" # matplotlib for polar.plot(backend="matplotlib")
pip install "flexfoil[dataframe]"  # pandas for polar.to_dataframe()
pip install "flexfoil[server]"     # starlette + uvicorn for flexfoil.serve()

What is this?

flexfoil wraps the RustFoil solver (an XFOIL-faithful Rust reimplementation) in native Python bindings via PyO3. Every solve is cached in a local SQLite database (~/.flexfoil/runs.db). The same web UI from foil.flexcompute.com can be launched locally with flexfoil.serve(), reading from the same database. No data leaves your machine unless you explicitly export it.

Quick start

Single-point solve

import flexfoil

foil = flexfoil.naca("2412")
result = foil.solve(alpha=5.0, Re=1e6)

print(result.cl)          # 0.8094
print(result.cd)          # 0.00775
print(result.cm)          # -0.0540
print(result.converged)   # True
print(result.ld)          # 104.5
print(result.x_tr_upper)  # 0.315  (transition location, upper surface)

Polar sweep

polar = foil.polar(alpha=(-5, 15, 0.5), Re=1e6)
print(polar)
# PolarResult('NACA 2412', Re=1e+06, 40/41 converged)

# Interactive plotly figure (default): CL-α, CD-α, CL-CD, CM-α
polar.plot()

# Or use matplotlib
polar.plot(backend="matplotlib")

# Export to pandas
df = polar.to_dataframe()
df.to_csv("polar.csv", index=False)

Compare multiple airfoils

import matplotlib.pyplot as plt
import flexfoil

for naca in ["0012", "2412", "4412"]:
    foil = flexfoil.naca(naca)
    polar = foil.polar(alpha=(-4, 14, 1.0), Re=1e6)
    plt.plot(polar.alpha, polar.cl, ".-", label=foil.name)

plt.xlabel("α (°)")
plt.ylabel("CL")
plt.legend()
plt.grid(True, alpha=0.3)
plt.show()

Load a .dat file

foil = flexfoil.load("e387.dat")   # Selig or Lednicer format
result = foil.solve(alpha=4.0, Re=2e5)

Custom coordinates

foil = flexfoil.from_coordinates(x_list, y_list, name="my shape")
result = foil.solve(alpha=3.0, Re=1e6)

Inviscid analysis

result = foil.solve(alpha=5.0, viscous=False)
# result.cd == 0.0 (no drag in potential flow)

Launch the web UI

flexfoil.serve()
# Opens the full flexfoil web app in your browser.
# Defaults to port 8420; automatically picks the next free port if busy.

Or from the command line:

flexfoil serve
flexfoil serve --port 9000 --no-browser

The web UI reads from the same local SQLite database as the Python API. Runs you solve from the browser (via the built-in WASM solver) are also written to the shared database, so flexfoil.runs() in Python sees them and vice versa.

Query the run database

Every solve (from Python or the web UI) is cached in ~/.flexfoil/runs.db.

# All runs as a pandas DataFrame (or list[dict] if pandas not installed)
df = flexfoil.runs()
print(f"{len(df)} runs cached")

# Filter by airfoil
naca_runs = df[df.airfoil_name == "NACA 2412"]

CLI

flexfoil solve 2412 -a 5 -r 1e6    # quick solve from the terminal
flexfoil serve                       # launch the web UI
flexfoil info                        # show config and DB location

API reference

Top-level functions

Function Description
flexfoil.naca(designation, n_panels=160) Create airfoil from NACA 4-digit string
flexfoil.load(path, n_panels=160) Load from .dat file
flexfoil.from_coordinates(x, y, name, n_panels) Create from raw x/y arrays
flexfoil.runs() All cached runs (DataFrame or list)
flexfoil.serve(port, host, open_browser) Launch local web UI + API server

Airfoil

Property / Method Description
.name Airfoil name
.n_panels Number of panel nodes
.raw_coords Original coordinates list[(x, y)]
.panel_coords Repaneled coordinates list[(x, y)]
.hash SHA-256 hash of panel coords (cache key)
.solve(alpha, Re, mach, ncrit, max_iter, viscous, store) Single-point analysis
.polar(alpha, Re, mach, ncrit, max_iter, viscous, store) Sweep over alpha range

SolveResult

Field Type Description
.cl float Lift coefficient
.cd float Drag coefficient
.cm float Moment coefficient (quarter-chord)
.converged bool Whether the Newton solve converged
.iterations int Newton iterations used
.residual float Final Newton residual
.x_tr_upper float Transition x/c, upper surface
.x_tr_lower float Transition x/c, lower surface
.alpha float Angle of attack (degrees)
.reynolds float Reynolds number
.mach float Mach number
.ncrit float e^N transition criterion
.ld float | None Lift-to-drag ratio
.success bool Overall success flag
.error str | None Error message if failed

PolarResult

Property / Method Description
.alpha list[float] — angles (converged only)
.cl list[float] — lift coefficients
.cd list[float] — drag coefficients
.cm list[float] — moment coefficients
.ld list[float] — lift-to-drag ratios
.converged list[SolveResult] — converged results only
.results list[SolveResult] — all results
.to_dict() Export as dict
.to_dataframe() Export as pandas.DataFrame
.plot(show=True, backend="plotly") 4-panel figure (plotly default, or "matplotlib")

RunDatabase

Method Description
.insert_run(...) Insert a solver run
.lookup_cache(...) Cache lookup by (hash, alpha, Re, ...)
.query_all_runs() All runs as list[dict]
.query_runs(airfoil_name, limit, offset) Filtered query
.row_count() Number of cached runs
.delete_all_runs() Clear all runs
.save_airfoil(name, coords_json) Save a named airfoil
.list_airfoils() List saved airfoils
.export_bytes() Export SQLite as bytes
.import_bytes(data) Import SQLite from bytes

Configuration

Environment variable Default Description
FLEXFOIL_DATA_DIR ~/.flexfoil Directory for runs.db

How it works

┌──────────────────────────────────┐     ┌──────────────────────────┐
│  Python                          │     │  Browser                 │
│                                  │     │                          │
│  import flexfoil                 │     │  localhost:8420           │
│  foil.solve() ──► Rust solver    │     │  React SPA               │
│        │         (PyO3)          │     │  WASM solver ──┐         │
│        ▼                         │     │                │         │
│  ~/.flexfoil/runs.db ◄──────────────── REST API ◄──────┘         │
│  (SQLite, WAL mode)              │     │                          │
│                                  │     │  SSE live updates ◄──┐  │
│  flexfoil.serve() ───► Starlette ──────►                     │  │
│                        uvicorn   │     │  (runs appear as     │  │
│                                  │     │   Python solves them) │  │
│  foil.polar() ──► insert rows ───────────────────────────────┘  │
└──────────────────────────────────┘     └──────────────────────────┘

The Rust solver called from Python is the exact same code as the WASM solver in the browser — both are compiled from the rustfoil-xfoil crate. Results are byte-identical.

Examples

See the examples/ directory:

Script What it does
01_quickstart.py Single-point solve
02_polar_sweep.py Full polar with table + plot
03_compare_airfoils.py Overlay multiple NACA foils
04_reynolds_sweep.py Re effect on drag polar
05_dat_file.py Load from .dat file
06_pandas_export.py Export to CSV via pandas
07_inviscid_vs_viscous.py Inviscid vs viscous comparison
08_batch_matrix.py Batch sweep: airfoils x Re x alpha
09_custom_coordinates.py Build airfoil from x, y arrays

Supported platforms

Platform Status
macOS Apple Silicon (arm64) Pre-built wheel
macOS Intel (x86_64) Pre-built wheel
Linux x86_64 Pre-built wheel
Windows x86_64 Pre-built wheel
Linux aarch64 (ARM) Build from source (requires Rust toolchain)

Development

cd packages/flexfoil-python

# Create a venv
python -m venv .venv
source .venv/bin/activate  # or .venv\Scripts\activate on Windows

# Install Rust toolchain and maturin
curl --proto '=https' --tlsv1.2 -sSf https://sh.rustup.rs | sh
pip install maturin

# Install dependencies
pip install starlette 'uvicorn[standard]' matplotlib pandas pytest

# Build and install in development mode
maturin develop

# Run tests (28 tests)
pytest tests/ -v

# Bundle the web UI (optional, for `flexfoil serve`)
./build_frontend.sh

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