encomp 0.5.4

General-purpose library for engineering computations

encomp

General-purpose library for engineering computations, with focus on clean and consistent interfaces.

Documentation at https://encomp.readthedocs.io/en/latest/

Features

Main functionality of the encomp library:

• Handles physical quantities with magnitude(s), dimensionality and units

  • Modules encomp.units, encomp.utypes
  • Extends the pint library
  • Uses Python's type system to validate dimensionalities
  • Integrates with np.ndarray and pd.Series
  • Automatic JSON serialization and decoding

• Implements a flexible interface to CoolProp

  • Module encomp.fluids
  • Uses quantities for all inputs and outputs
  • Fluids are represented as class instances, the properties are class attributes

• Extends Sympy

  • Module encomp.sympy
  • Adds convenience methods for creating symbols with sub- and superscripts
  • Additional functions to convert (algebraic) expressions and systems to Python code that supports Numpy arrays

• Jupyter Notebook integration

  • Module encomp.notebook
  • Imports commonly used functions and classes
  • Defines custom Jupyter magics

The other modules implement calculations related to process engineering and thermodynamics. The module encomp.serialize implements custom JSON serialization and decoding for classes used elsewhere in the library.

Installation

Install with pip:

pip install encomp

This will install encomp along with its dependencies into the currently active Python environment.

CoolProp is not installable with pip for Python 3.9. Install manually with conda for now:

conda install conda-forge::coolprop

Getting started

To use encomp from a Jupyter Notebook (or REPL), import the encomp.notebook module:

# imports commonly used functions and registers Notebook magics
from encomp.notebook import *

This will import commonly used functions and classes. It also registers the %read and %%write Jupyter magics for reading and writing custom objects from and to JSON.

The Quantity class

The fundamental building block of encomp is the encomp.units.Quantity class (shorthand alias Q), which is an extension of pint.Quantity. This class is used to construct objects with a magnitude and unit. Each unit also has a dimensionality, and each dimensionality will have multiple associated units.

from encomp.units import Quantity as Q

# converts 1 bar to kPa, displays it in case it's the cell output
Q(1, 'bar').to('kPa')

# a single string with one numerical value can also be given as input
Q('0.1 MPa').to('bar')

# list and tuple inputs are converted to np.ndarray
Q([1, 2, 3], 'bar') * 2 # [2, 4, 6] bar

# in case no unit is specified, the quantity is dimensionless
Q(0.1) == Q(10, '%')

Quantity type system

The Quantity object has an associated Dimensionality type parameter that is dynamically determined based on the unit. Each dimensionality (for example pressure, length, time, dimensionless) is represented by a subclass of Quantity.

Common dimensionalities can be statically determined based on overload variants of the Quantity.__new__ method (see encomp.utypes.get_registered_units for a list of units that support this). Additionally, operations using *, ** and / are also defined using overload variants for combinations of the default dimensionalities.

In case the unit is not registered by default, the type checker will use the dimensionality Unknown. During runtime, the dimensionality will be evaluated based on the unit that was specified.

The Unknown dimensionality is also used for operations using *, ** and / that are not explicitly defined as overload variants. If necessary, the dimensionality of a quantity can be explicitly specified by providing a subclass of encomp.utypes.Dimensionality as type parameter.

Most dimensionalities are defined in the encomp.utypes module. In case a new dimensionality is created, the classname will be Dimensionality[...], for example Quantity[Dimensionality[[mass] ** 2 / [length] ** 3]].

from encomp.units import Quantity as Q
from encomp.utypes import Volume, MassFlow

# the types are determined by a static type checker like mypy

# the unit "m" is registered as a Mass unit
m = Q(12, 'kg')  # Quantity[Mass]

V = Q(25, 'liter')  # Quantity[Volume]

# some common / and * operations are encoded as overloads
rho = m / V  # Quantity[Density]

# the unit "kg/week" is not registered by default
# the individual units "kg" and "week" are registered, however
# the type checker does not know how to combine these units
m_ = Q(25, 'kg/week')  # Quantity[Unknown]

# at runtime, the dimensionality of m_ will be evaluated to MassFlow
isinstance(m, Q[MassFlow])  # True

# these operations (** and /) are not explicitly defined as overloads
# at runtime, the type will be evaluated to
# Quantity[Dimensionality[[mass] ** 2 / [length] ** 3]]
x = m**2 / V  # Quantity[Unknown]

# the unit name "meter cubed" is not defined using an overload,
# the type parameter Volume is instead used to infer the type
y = Q[Volume](15, 'meter cubed')  # Quantity[Volume]

# in case the explicitly defined dimensionality does
# not match the unit, an error will be raised at runtime

y = Q[MassFlow](15, 'meter cubed')
# ExpectedDimensionalityError: Quantity with unit "m³" has incorrect dimensionality
# [length] ** 3, expected [mass] / [time]

Runtime type checking

The Quantity subtypes can be used to restrict function and class attribute types at runtime. If the ENCOMP_TYPE_CHECKING environment variable is set to True, the typeguard.typechecked decorator is automatically applied to all functions and methods inside the main encomp library. To use it on your own functions, apply the decorator explicitly:

from typeguard import typechecked
from typing import TypedDict

from encomp.units import Quantity as Q
from encomp.utypes import Temperature, Length, Pressure

@typechecked
def some_func(T: Q[Temperature]) -> tuple[Q[Length], Q[Pressure]]:
    return T * Q(12.4, 'm/K'), Q(1, 'bar')

some_func(Q(12, 'delta_degC'))  # the dimensionalities check out
some_func(Q(26, 'kW'))  # raises an exception:
# TypeError: type of argument "T" must be Quantity[Temperature];
# got Quantity[Power] instead

class OutputDict(TypedDict):

    P: Q[Pressure]
    T: Q[Temperature]

@typechecked
def another_func(s: Q[Length]) -> OutputDict:
    return {
        'T': Q(25, 'm'),
        'P': Q(25, 'kPa')
    }

another_func(Q(25, 'm'))
# TypeError: type of dict item "T" for the return value must be
# encomp.units.Quantity[Temperature]; got encomp.units.Quantity[Length] instead

To create a new dimensionality (for example temperature difference per length), combine the pint.UnitsContainer objects stored in the dimensions class attribute.

from encomp.units import Quantity as Q
from encomp.utypes import Temperature, Length, Volume, Dimensionality

class TemperaturePerLength(Dimensionality):
    dimensions = Temperature.dimensions / Length.dimensions

qty = Q[TemperaturePerLength](1, 'delta_degC / km')

# raises an exception since liter is Length**3 and the Quantity expects Length**1
another_qty = Q[TemperaturePerLength](1, 'delta_degC / liter')

# create a new subclass of Quantity with restricted input units

class CustomDimensionality(Dimensionality):
    dimensions = Temperature.dimensions / Volume.dimensions

CustomCoolingCapacity = Q[CustomDimensionality]

# the underlying pint library handles a wide range of input formats and unit names
assert CustomCoolingCapacity(3, '°F per yard³') == Q('3 degree_Fahrenheit per yard cubed')

The Fluid class

The class encomp.fluids.Fluid is a wrapper around the CoolProp library. The class uses two input points (three for humid air) that fix the state of the fluid. Other fluid parameters can be evaluated using attribute access. The outputs and inputs are Quantity objects. CoolProp property names and codes are used throughout. Use the .search() method to find the correct name.

from encomp.units import Quantity as Q
from encomp.fluids import Fluid

air = Fluid('air', T=Q(25, 'degC'), P=Q(2, 'bar'))

# common fluid properties have type hints, and show up using autocomplete
air.D # 2.338399526231983 kilogram/meter3

air.search('density')
# ['DELTA, Delta: Reduced density (rho/rhoc) [dimensionless]',
#  'DMOLAR, Dmolar: Molar density [mol/m³]',
#  'D, DMASS, Dmass: Mass density [kg/m³]', ...

# any of the names are valid attributes (case-sensitive)
air.Dmolar # 80.73061937328056 mole/meter3

The fluid name 'water' (or the subclass Water) uses IAPWS to evaluate steam and water properties.

from encomp.units import Quantity as Q
from encomp.fluids import Fluid, Water

Fluid('water', P=Q(25, 'bar'), T=Q(550, 'C'))
# <Fluid "water", P=2500 kPa, T=550.0 °C, D=6.7 kg/m³, V=0.031 cP>

# note that the CoolProp property "Q" (vapor quality) has the same name as the class
# the Water class has a slightly different string representation
Water(Q=Q(0.5), T=Q(170, 'degC'))
# <Water (Two-phase), P=792 kPa, T=170.0 °C, D=8.2 kg/m³, V=0.0 cP>

Water(H=Q(2800, 'kJ/kg'), S=Q(7300, 'J/kg/K'))
# <Water (Gas), P=225 kPa, T=165.8 °C, D=1.1 kg/m³, V=0.0 cP>

The HumidAir class requires three input points (R means relative humidity):

from encomp.units import Quantity as Q
from encomp.fluids import HumidAir

HumidAir(P=Q(1, 'bar'), T=Q(100, 'degC'), R=Q(0.5))
# <HumidAir, P=100 kPa, T=100.0 °C, R=0.50, Vda=2.2 m³/kg, Vha=1.3 m³/kg, M=0.017 cP>

Settings

The attributes in the encomp.settings.Settings class can be modified with an .env-file. Place a file named .env in the current working directory to override the default settings. The attribute names are prefixed with ENCOMP_. See the file .env.example in the base of this repository for examples.

TODO

• Possible to use a secondary type variable / generic to figure out the magnitude type?
  • This could use TypeVarTuple (import from typing_extensions until Python 3.11)
  • Not supported by mypy yet, need to wait with this
• Document the Quantity[Dimensionality] type system