flexfoil 1.1.4

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

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 sweeps are parallelized by default using all available CPU cores (via Rust's rayon thread pool). A 41-point polar runs ~3x faster than sequential.

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")

# Sequential mode (for debugging or progress output)
polar = foil.polar(alpha=(-5, 15, 0.5), Re=1e6, parallel=False)

# 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)

Flap deflection

flapped = foil.with_flap(hinge_x=0.75, deflection=10)
print(flapped)
# Airfoil('NACA 2412 +flap(75%, +10.0°)', n_panels=160)

result = flapped.solve(alpha=5.0, Re=1e6)
print(result.cl)  # ~1.27 (vs 0.81 clean)

# Sweep flap deflections
for defl in [0, 5, 10, 15]:
    f = foil.with_flap(hinge_x=0.75, deflection=defl)
    polar = f.polar(alpha=(-4, 14, 1.0), 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)
.with_flap(hinge_x, deflection, hinge_y_frac, n_panels)	Return new Airfoil with flap deflected
.solve(alpha, Re, mach, ncrit, max_iter, viscous, store)	Single-point analysis
.polar(alpha, Re, mach, ncrit, max_iter, viscous, store, parallel)	Sweep over alpha range (parallel by default)

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
10_flap_study.py	Sweep flap deflections (0-20 deg)
11_flap_hinge_sweep.py	Find optimal hinge position for L/D
12_matrix_sweep.py	Alpha x Re matrix for a flapped airfoil

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 (112 tests)
pytest tests/ -v

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