Performance Tips

Most of the time, readability is more important than the performance of scientific software. This page contains tips for improving the performance of PlasmaPy for situations where performance becomes a bottleneck.

Python versions

Upgrade to the newest version of Python to take advantage of ongoing performance improvements from the Faster CPython project. New versions of Python also have improved error message, which can speed up the debugging process too.

A new version of Python is released in October of each year, and can be used with PlasmaPy a few months later.

Using Astropy units

PlasmaPy makes heavy use of astropy.units and Quantity operations. See Astropy’s documentation for performance tips for Quantity operations.

Because PlasmaPy uses SI units internally, performance can be improved slightly by providing Quantity objects in SI units to functions in plasmapy.formulary. Unit conversions done by the validate_quantities() decorator then do not need to be performed.


Many of the functions in plasmapy.formulary accept particle-like arguments. Arguments that are not already a Particle, CustomParticle, or ParticleList are converted into one (usually via the particle_input() decorator. When a formulary function is repeatedly called, performance can be improved by creating the particle object ahead of time.

For example, suppose we are calculating the gyrofrequency of a proton. If we represent the particle as a string, then the function will need to create a Particle each time the function is called.

from plasmapy.formulary import gyrofrequency
import astropy.units as u

for i in range(1000):
    gyrofrequency(B=0.02 * u.T, particle="p+")  # create the Particle repeatedly

If we create the Particle and Quantity ahead of time, they will need to be create only once instead of repeatedly.

from plasmapy.particles import Particle

B = 0.02 * u.T
proton = Particle("p+")  # create the Particle once

for i in range(1000):
    gyrofrequency(B=B, particle=proton)


PlasmaPy includes lite-functions for some plasmapy.formulary functions for situations when performance matters. For example, plasma_frequency_lite is the lite-function for plasma_frequency.

Lite-functions accept and return NumPy arrays (assumed to be in SI units) instead of Quantity objects. Lite-functions make use of just-in-time (JIT) compilation via Numba to achieve high performance. Because lite-functions do not include any validation of inputs, they should only be used for performance-critical applications.

If you need a lite-function version of a plasmapy.formulary function that has not already been implemented, please raise an issue.