Metadata-Version: 2.1
Name: encomp
Version: 0.6.0
Summary: General-purpose library for engineering computations
Home-page: https://github.com/wlaur/encomp
Author: William Laurén
Author-email: lauren.william.a@gmail.com
License: MIT
Platform: UNKNOWN
Requires-Python: ~=3.9
Description-Content-Type: text/markdown
License-File: LICENSE
Requires-Dist: python-dateutil
Requires-Dist: python-dotenv
Requires-Dist: pydantic
Requires-Dist: typeguard
Requires-Dist: typing-extensions
Requires-Dist: asttokens
Requires-Dist: numpy
Requires-Dist: pandas
Requires-Dist: coolprop
Requires-Dist: sympy
Requires-Dist: pint (>=0.19.2)
Requires-Dist: symbolic-equation

# encomp

> General-purpose library for *en*gineering *comp*utations, with focus on clean and consistent interfaces.

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

`encomp` is tested on Windows and Linux, with Python versions 3.9 and 3.10.

## Features

Main functionality of the `encomp` library:

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

  - Modules `encomp.units`, `encomp.utypes`
  - Extends the [pint](https://pypi.org/project/Pint) library
  - Uses Python's type system to validate dimensionalities
  - Compatible with ``mypy`` and other type checkers
  - Integrates with `np.ndarray` and `pd.Series`
  - JSON serialization and decoding

- Implements a flexible interface to [CoolProp](http://www.coolprop.org)

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

- Extends [Sympy](https://pypi.org/project/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.


## Getting started

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

```python
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_ (combination of the base dimensions), and each dimensionality will have multiple associated units.

```python
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 dimensionality cannot be inferred, the type checker will use the dimensionality `Unknown`.
At 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.

Commonly used dimensionalities are defined in the `encomp.utypes` module.
When a new dimensionality is created, the classname will be `Dimensionality[...]` (for example `Quantity[Dimensionality[[mass] ** 2 / [length] ** 3]]`).


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

# the types are inferred 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]

# 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 (Mass**2 divided by Volume) 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.
Use the ``typeguard.typechecked`` decorator to apply runtime typechecking to function inputs and outputs:

```python
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 mass flow rate), combine the `pint.UnitsContainer` objects stored in the `dimensions` class attribute.


```python
from encomp.units import Quantity as Q
from encomp.units import DimensionalityError
from encomp.utypes import Temperature, MassFlow, Volume, Dimensionality

# the class name TemperaturePerMassFlow must be globally unique
class TemperaturePerMassFlow(Dimensionality):
    dimensions = Temperature.dimensions / MassFlow.dimensions

# note the extra parentheses around (kg/s)
qty = Q[TemperaturePerMassFlow](1, 'delta_degC/(kg/s)')

# raises an exception since liter is Length**3 and the Quantity expects Mass
try:
    another_qty = Q[TemperaturePerMassFlow](1, 'delta_degC/(liter/hour)')
except DimensionalityError:
    pass

# create a new subclass of Quantity with restricted input units

CustomCoolingCapacity = Q[TemperaturePerMassFlow]

# the pint library handles a wide range of input formats and unit names
q1 = CustomCoolingCapacity(6, '°F per (lbs per week)')
q2 = Q('3 degree_Fahrenheit per (pound per fortnight)')

assert q1 == q2
assert type(q1) is type(q2)
```

### 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.

```python
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.

```python
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):

```python
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
- The `requirements.txt` file seems to include some unnecessary packages (for example `pillow`)
- What is the license of this package?
  - For example, ``pint`` uses *3-Clause BSD License*, this should be compatible with ``MIT``
  - Should this package include the ``pint`` license text somewhere?
    - Extending the ``pint`` package counts as modification



