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Nicolas Kruse
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README.md
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README.md
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# Gaspype
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The python package provides an performant library for thermodynamic calculations
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like equilibrium reactions for several hundred gas species and their mixtures -
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written in Python/Numpy.
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Species are treated as ideal gases. Therefore the application is limited to moderate
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pressures or high temperature applications.
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Its designed with goal to be portable to Numpy-style GPU frameworks like JAX and PyTorch.
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## Key features
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- Tensor operations to prevent bottlenecks by the python interpreter
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- Immutable types
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- Elegant pythonic interface
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- Great readable and compact syntax when using this package
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- Good usability in Jupyter Notebook
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- High performance for multidimensional fluid arrays
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# Copapy
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## Installation
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Installation with pip:
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``` bash
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pip install gaspype
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```
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Installation with conda:
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``` bash
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conda install conda-forge::gaspype
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pip install copapy
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```
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## Getting started
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Gaspype provides two main classes: ```fluid``` and ```elements```.
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### Fluid
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A fluid class describes a mixture of molecular species and their individual molar amounts.
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``` python
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import gaspype as gp
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fl = gp.fluid({'H2O': 1, 'H2': 2})
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fl
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```
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```
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Total 3.000e+00 mol
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H2O 33.33 %
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H2 66.67 %
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```
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Its' functions provides thermodynamic, mass balance and ideal gas properties of the mixture.
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``` python
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cp = fl.get_cp(t=800+273.15)
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mass = fl.get_mass()
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gas_volume = fl.get_v(t=800+273.15, p=1e5)
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```
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The arguments can be provided as numpy-arrays:
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``` python
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import numpy as np
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t_range = np.linspace(600, 800, 5) + 273.15
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fl.get_density(t=t_range, p=1e5)
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```
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```
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array([0.10122906, 0.09574625, 0.09082685, 0.08638827, 0.08236328])
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```
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A ```fluid``` object can have multiple compositions. A multidimensional ```fluid``` object can be created for example by multiplication with a numpy array:
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``` python
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fl2 = gp.fluid({'H2O': 1, 'N2': 2}) + \
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np.linspace(0, 10, 4) * gp.fluid({'H2': 1})
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fl2
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```
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```
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Total mol:
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array([ 3. , 6.33333333, 9.66666667, 13. ])
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Species:
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H2 H2O N2
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Molar fractions:
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array([[0. , 0.33333333, 0.66666667],
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[0.52631579, 0.15789474, 0.31578947],
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[0.68965517, 0.10344828, 0.20689655],
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[0.76923077, 0.07692308, 0.15384615]])
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```
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A fluid object can be converted to a pandas dataframe:
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``` python
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import pandas as pd
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pd.DataFrame(list(fl2))
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```
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| | H2O | N2 | H2
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|----|-----|-----|-------
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|0 | 1.0 | 2.0 | 0.000000
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|1 | 1.0 | 2.0 | 3.333333
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|2 | 1.0 | 2.0 | 6.666667
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|3 | 1.0 | 2.0 | 10.000000
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The broadcasting behavior is not limited to 1D-arrays:
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``` python
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fl3 = gp.fluid({'H2O': 1}) + \
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np.linspace(0, 10, 4) * gp.fluid({'H2': 1}) + \
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np.expand_dims(np.linspace(1, 3, 3), axis=1) * gp.fluid({'N2': 1})
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fl3
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```
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```
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Total mol:
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array([[ 2. , 5.33333333, 8.66666667, 12. ],
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[ 3. , 6.33333333, 9.66666667, 13. ],
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[ 4. , 7.33333333, 10.66666667, 14. ]])
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Species:
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H2 H2O N2
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Molar fractions:
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array([[[0. , 0.5 , 0.5 ],
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[0.625 , 0.1875 , 0.1875 ],
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[0.76923077, 0.11538462, 0.11538462],
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[0.83333333, 0.08333333, 0.08333333]],
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[[0. , 0.33333333, 0.66666667],
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[0.52631579, 0.15789474, 0.31578947],
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[0.68965517, 0.10344828, 0.20689655],
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[0.76923077, 0.07692308, 0.15384615]],
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[[0. , 0.25 , 0.75 ],
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[0.45454545, 0.13636364, 0.40909091],
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[0.625 , 0.09375 , 0.28125 ],
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[0.71428571, 0.07142857, 0.21428571]]])
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```
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### Elements
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In some cases not the molecular but the atomic composition is of interest. The ```elements``` class can be used for atom based balances and works similar:
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``` python
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el = gp.elements({'N': 1, 'Cl': 2})
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el.get_mass()
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```
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```
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np.float64(0.08490700000000001)
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```
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A ```elements``` object can be as well instantiated from a ```fluid``` object. Arithmetic operations between ```elements``` and ```fluid``` result in an ```elements``` object:
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``` python
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el2 = gp.elements(fl) + el - 0.3 * fl
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el2
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```
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```
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Cl 2.000e+00 mol
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H 4.200e+00 mol
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N 1.000e+00 mol
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O 7.000e-01 mol
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```
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Going from an atomic composition to an molecular composition is a little bit less straight forward, since there is no universal approach. One way is to calculate the thermodynamic equilibrium for a mixture:
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``` python
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fs = gp.fluid_system('CH4, H2, CO, CO2, O2')
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el3 = gp.elements({'C': 1, 'H': 2, 'O':1}, fs)
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fl3 = gp.equilibrium(el3, t=800)
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fl3
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```
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```
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Total 1.204e+00 mol
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CH4 33.07 %
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H2 16.93 %
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CO 16.93 %
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CO2 33.07 %
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O2 0.00 %
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```
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The ```equilibrium``` function can be called with a ```fluid``` or ```elements``` object as first argument. ```fluid``` and ```elements``` referencing a ```fluid_system``` object witch can be be set as shown above during the object instantiation. If not provided, a new one will be created automatically. Providing a ```fluid_system``` gives more control over which molecular species are included in derived ```fluid``` objects. Furthermore arithmetic operations between objects with the same ```fluid_system``` are potentially faster:
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``` python
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fl3 + gp.fluid({'CH4': 1}, fs)
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```
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```
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Total 2.204e+00 mol
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CH4 63.44 %
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H2 9.24 %
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CO 9.24 %
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CO2 18.07 %
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O2 0.00 %
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```
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Especially if the ```fluid_system``` of one of the operants has not a subset of molecular species of the other ```fluid_system``` a new ```fluid_system``` will be created for the operation which might degrade performance:
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``` python
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fl3 + gp.fluid({'NH3': 1})
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```
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```
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Total 2.204e+00 mol
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CH4 18.07 %
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CO 9.24 %
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CO2 18.07 %
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H2 9.24 %
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NH3 45.38 %
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O2 0.00 %
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```
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## Developer Guide
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Contributions are welcome, please open an issue or submit a pull request on GitHub.
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To get started with developing the `gaspype` package, follow these steps.
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To get started with developing the `copapy` package, follow these steps.
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First, clone the repository to your local machine using Git:
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```bash
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git clone https://github.com/DLR-Institute-of-Future-Fuels/gaspype.git
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cd gaspype
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git clone https://github.com/nonannet/copapy.git
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cd copapy
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```
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It's recommended to setup an venv:
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```bash
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python -m venv venv
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source venv/bin/activate # On Windows use `venv\Scripts\activate`
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python -m venv .venv
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source .venv/bin/activate # On Windows use `.venv\Scripts\activate`
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```
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Install the package and dev-dependencies while keeping the package files
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