Style Guide

This style guide summarizes code conventions used in ProbNum. This is intended as a reference for developers. ProbNum follows the *Black* code style, which can be viewed as a strict subset of PEP 8, and we recommend *Black* for automated code formatting.



Use absolute imports over relative imports.

  • import x for importing packages and modules.
  • from x import y where x is the package prefix and y is the module name with no prefix.
  • from x import y as z if two modules named y are to be imported or if y is an inconveniently long name.
  • import y as z only when z is a standard abbreviation (e.g. np for numpy).

Use __all__ = [...] in files to fix the order in which the methods are visible in the documentation. This also avoids importing unnecessary functions via import statements from ... import *. Almost all methods are “pulled up” to a higher-level namespace via files. Import from there wherever there is no chance for confusion and/or circular imports. This makes imports more readable. When changing the namespace of classes make sure to to correct module paths in the documentation by adding SuperClass.__module__ = "probnum.module" to the corresponding __init.py__.


The package itself is written “ProbNum” except when referred to as a package import, then probnum should be used.

Classes, Functions, Methods and Variables

  • joined_lower for functions, methods, attributes, variables
  • joined_lower or ALL_CAPS for constants
  • StudlyCaps for classes
  • camelCase only to conform to pre-existing conventions, e.g. in unittest

Probabilistic Numerical Methods

Function names and signatures of PN methods attempt to replicate numpy or scipy naming conventions. For example

  • probsolve_ivp(...) (scipy: solve_ivp(...))
  • problinsolve(...) (scipy: linalg.solve(...))

Methods with “Bayesian” in the name come with the prefix bayes, e.g. bayesquad; Bayesian quadrature, BayesFilter; Bayesian filter, BayesSmoother; Bayesian smoother.

Printable Representations

The way an object is represented in the console or printed is defined by the following functions:

  • repr(obj) is defined by obj.__repr__() and should return a developer-friendly representation of obj. If possible, this should be code that can recreate obj.
  • str(obj) is defined by obj.__str__() and should return a user-friendly representation of obj. If no .__str__() method is implemented, Python will fall back to the .__repr__() method.

As an example consider numpy’s array representation

array([[1, 0],
      [0, 1]])

versus its output of str.

[[1 0]
 [0 1]]

Notational Conventions

Stick to the first few letters for abbreviations if they are sufficiently descriptive:

  • cov: covariance
  • fun: function
  • mat: matrix
  • vec: vector
  • arr: array; wherever applicable, specify vec or mat

Further conventions are

  • unit2unit: convert between types or units, e.g. mat2arr: convert matrix to array or s2ms: convert seconds to milliseconds. Can also be used for simple adapter methods, along the lines of filt2odefilt.

  • proj: projection (if required: projmat, projvec, projlinop, …)

  • precond: preconditioner

  • inv*: for inverse of a matrix; e.g. invprecond, invcovmat, …

  • optional arguments via **kwargs, e.g.: fun(t, x, **kwargs)

  • msg: message, e.g. for issuing raising and warnings (errmsg, warnmsg)

  • randvar: random variable; if concatenated with e.g. init, abbreviate to initrv (initial random variable)

  • dist: distribution. The only exception is in instantiation of a RandomVariable object, where specifies a distribution key.

  • data: data (don’t abbreviate that one)

  • functions/methods that do something from time t0 to time t1 with step size h use the signature (start, stop, step, **kwargs) or any corresponding subset of that. This is in line with np.arange for instance. Use it like (start=t0, stop=t1, step=h, **kwargs).

  • jacob: Jacobian, if necessary use jacobfun. Hessians are hess, respectively hessfun.

  • param(s): parameter(s). If abbreviations are necessary (e.g. in inline-function definition, use par(s)).

  • Indices via idx (either idx1, idx2, … or idx, jdx, kdx) and not via i, j, k. The former is more readable (and follows PEP8); the latter may collide with the built-in imaginary constant j=sqrt(-1).

  • A function maps from its domain to its range. The range of a random variable is the domain of its distribution.

    The range of a random process is the range of the associated random variables. The domain of a random process is either given by supportpts {t_1, t_2, …} (discrete-time processes) or bounds (a, b) (continuous-time processes).

Errors and Warnings

Package Structure

Modules and Folders

  • low (shortened lower caps) for modules/folders in the namespace, e.g. probnum.linalg.linops
  • lower for modules/folders not in the namespace, e.g. probnum/prob/distributions. Rule of thumb: the more low-level the module is, the longer (more descriptive) the file name can be, because the chances that access is provided through higher-level namespaces are rather high.

PN methods should be in a file with the same name as the containing folder (e.g. probnum/linalg/linearsolvers/, while their implementation (in classes) is in the same folder in other files.


All documentation is written in American English. Every publicly visible class or function must have a docstring. Do not use extensive documentation as a clutch for spaghetti code – divide and conquer instead!