Introduction to Python for Engineers
Main.PythonIntroduction History
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title='Programing Language Popularity',
title='Programming Language Popularity',
Use Christoph Gohlke's whl files for Windows installations. Many of the packages depend on the Visual C++ 2015 Redistributable (x64 and x86 for CPython 3.5 and 3.6) that is available from Microsoft. After installing the Visual C++ redistributable, download and install NumPy and SciPy packages (in that order) for Python 3.6 on Windows. The downloaded wheel file names should not be changed because the wheel file name verifies compatibility with the current Python version.
This same tutorial is also show in a MATLAB introduction.
This same tutorial is also show in a MATLAB introduction.
Python is a high-level and general-purpose programming language. According to several survey results or search engine queries such as the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses the latest release of Python that is currently at version 3.9.
Python is a high-level and general-purpose programming language. According to several survey results or search engine queries such as the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy.
(:toggle hide bar_chart button show="Show Bar Chart Source":) (:div id=bar_chart:) (:source lang=python:) import pandas as pd import numpy as np import matplotlib.pyplot as plt import plotly.express as px import seaborn as sns import plotly.express as px import plotly.graph_objects as go import datetime as datetime from datetime import timedelta from plotly.subplots import make_subplots
- pip install bar_chart_race
import bar_chart_race as bcr
url = 'http://apmonitor.com/che263/uploads/Main/' data = pd.read_csv(url+'programming_languages.csv') data['Date'] = pd.to_datetime(data['Date']).dt.strftime('m')
df=data.copy() df.index=df['Date'].tolist() df=df.drop('Date',axis=1)
def make_bcr(df):
bcr.bar_chart_race(
df=df,
filename='programming_languages.mp4',
orientation='h',
sort='desc',
n_bars=20,
fixed_order=False,
fixed_max=False,
steps_per_period=6,#speed control
interpolate_period=False,
label_bars=True,
bar_size=.95,
period_label={'x': .99, 'y': .25, 'ha': 'right', 'va': 'center'},
#period_fmt='d, %Y',
period_summary_func=lambda v, r: {'x': .99, 'y': .18,'s': '',
'ha': 'right', 'size': 8,
'family': 'Courier New'},
period_length=400,
figsize=(5,3),
dpi=500,
cmap='dark24',
title='Programing Language Popularity',
title_size=10,
bar_label_size=7,
tick_label_size=5,
shared_fontdict={'color' : '.1'},
scale='linear',
writer=None,
fig=None,
bar_kwargs={'alpha': .7},
filter_column_colors=True)
make_bcr(df) (:sourceend:) (:divend:)
(:html:) <video width="550" controls autoplay muted>
<source src="/che263/uploads/Main/programming_languages.mp4" type="video/mp4"> Your browser does not support the video tag.
</video> (:htmlend:)
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<iframe width="560" height="315" src="https://www.youtube.com/embed/Z_Kxg-EYvxM" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/p2Dyx9DyQWw" frameborder="0" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/p2Dyx9DyQWw" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
Python is a high-level and general-purpose programming language. According to several survey results or search engine queries such as the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses the latest release of Python that is currently at version 3.7.
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/LfodqSAgEqg" frameborder="0" allowfullscreen></iframe> (:htmlend:)
There are several resources for learning Python online. For a good start, look at Code Academy (Python track) or view the documentation at Python.org. For users with a foundation in MATLAB, there are excellent resources that demonstrate equivalent Python (Numpy) commands.
Python is a high-level and general-purpose programming language. According to several survey results or search engine queries such as the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses the latest release of Python that is currently at version 3.9.
There are several resources for learning Python online. For a good start, look at Code Academy (Python track) or view the documentation at Python.org. For users with a foundation in MATLAB, there are excellent resources that demonstrate equivalent Python (Numpy) commands.
Option #1: Install Python from Python.org
Install Python on Windows
<iframe width="560" height="315" src="https://www.youtube.com/embed/bXWlyOMYpRE" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/_BHsM452vK0" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
The instructions are for the Windows OS but Python can be installed on most operating systems. The Python base program should be installed first and then the other packages can be installed in any order with the utility PIP or by downloading the installer package from the appropriate web-site.
Option #2: Install Anaconda
Anaconda includes the Jupyter Notebook and the Spyder IDE. Anaconda is available for download here.
Install Python on MacOS
<iframe width="560" height="315" src="https://www.youtube.com/embed/LrMOrMb8-3s" frameborder="0" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/2VECcPofhP8" frameborder="0" allow="accelerometer; autoplay; clipboard-write; encrypted-media; gyroscope; picture-in-picture" allowfullscreen></iframe>
Option #3: Online Platforms
Install Python on Linux
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Online Platforms
Anaconda includes the Jupyter Notebook and the Spyder IDE. Anaconda is available for download here.
Anaconda includes the Jupyter Notebook and the Spyder IDE. Anaconda is available for download here.
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There are several online platforms that allow Python through a web-browser including try.jupyter.org and repl.it. An example of using repl.it is here:
https://repl.it/classroom/invite/FS5LV0W
There are several online platforms that allow Python through a web-browser including Try Jupyter and Google Colab.
Python Introduction
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.7.
Python is a high-level and general-purpose programming language. According to several survey results or search engine queries such as the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses the latest release of Python that is currently at version 3.7.
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.6+.
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.7.
Below is an example on how to install APMonitor Optimization Suite from the command line (start cmd).
pip install APMonitor
The APMonitor package name can be replaced with any available package name such as NumPy.
Below is an example on how to install GEKKO Optimization Suite from the command line (start cmd).
pip install gekko
The GEKKO package name can be replaced with any available package name such as NumPy.
Load and Optionally Install APMonitor Package
Load and Optionally Install GEKKO Package
module='gekko'
from APMonitor.apm import *
from pip import main as pipmain
import pip pip.main(['install','APMonitor']) from APMonitor.apm import *
from pip._internal import main as pipmain
pipmain(['install',module])
module='numpy'
import numpy as np
from pip import main as pipmain
import pip pip.main(['install','numpy']) import numpy as np
from pip._internal import main as pipmain
pipmain(['install',module])
The APMonitor or NumPy package names can be replaced with any available package. The pip package manager connects to an online repository to retrieve the latest version of the package and install it. Sometimes a package is needed on a computer that isn't connected to the internet or the package isn't available through pip. Below is information on installing a package wheel (whl) file.
The GEKKO or NumPy package names can be replaced with any available package. The pip package manager connects to an online repository to retrieve the latest version of the package and install it. Sometimes a package is needed on a computer that isn't connected to the internet or the package isn't available through pip. Below is information on installing a package wheel (whl) file.
<iframe width="560" height="315" src="https://www.youtube.com/embed/Ju6zw83PoKo" frameborder="0" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/bXWlyOMYpRE" frameborder="0" allow="autoplay; encrypted-media" allowfullscreen></iframe>
R = 0.0821 # L-atm/K T = 500 # K V = 5 # L/mol Pc = 37.2 # atm Tc = 132.5 # K a = 0.427 * pow(R,2) * pow(Tc,2.5) / Pc b = 0.0866 * R * Tc / Pc # Compute in atm P_ig = R * T / V P_rk = R * T / (V-b) - a/(V*(V+b)*pow(T,0.5)) # Convert to Pascals P_ig = P_ig * 101325 P_rk = P_rk * 101325 print("The ideal gas pressure: " + str(P_ig) + " Pa") print("The Redlich-Kwong pressure: " + str(P_rk) + " Pa")
(:source lang=python:) R = 0.0821 # L-atm/K T = 500 # K V = 5 # L/mol Pc = 37.2 # atm Tc = 132.5 # K
a = 0.427 * pow(R,2) * pow(Tc,2.5) / Pc b = 0.0866 * R * Tc / Pc
- Compute in atm
P_ig = R * T / V P_rk = R * T / (V-b) - a/(V*(V+b)*pow(T,0.5))
- Convert to Pascals
P_ig = P_ig * 101325 P_rk = P_rk * 101325
print("The ideal gas pressure: " + str(P_ig) + " Pa") print("The Redlich-Kwong pressure: " + str(P_rk) + " Pa") (:sourceend:)
Manage Python Packages
Install Packages with pip (Command Line)
Sometimes a script uses a package that is not yet installed. Once Python is installed, a package manager such as pip or conda can be used to install, remove, or update packages.
"Hello, World!" Tutorial
The following tutorial is a "Hello, World!" (introductory) example of writing a simple Python script, running the script in debug mode, and basic programming constructs.
(:html:) <iframe width="560" height="315" src="//www.youtube.com/embed/lnNqRCXZ2cw?rel=0" frameborder="0" allowfullscreen></iframe> (:htmlend:)
Below is an example on how to install APMonitor Optimization Suite from the command line (start cmd).
pip install APMonitor
The APMonitor package name can be replaced with any available package name such as NumPy.
pip install numpy
Install Packages with pip (Python Script)
Packages can also be managed from a Python script by attempting to load the package with try. If the import fails, the except section imports pip and installs the package.
Load and Optionally Install APMonitor Package
(:source lang=python:) try:
from APMonitor.apm import *
except:
import pip pip.main(['install','APMonitor']) from APMonitor.apm import *
(:sourceend:)
Load and Optionally Install NumPy Package
(:source lang=python:) try:
import numpy as np
except:
import pip pip.main(['install','numpy']) import numpy as np
(:sourceend:)
The APMonitor or NumPy package names can be replaced with any available package. The pip package manager connects to an online repository to retrieve the latest version of the package and install it. Sometimes a package is needed on a computer that isn't connected to the internet or the package isn't available through pip. Below is information on installing a package wheel (whl) file.
Install Package Wheels (whl) Offline
The pip package manager can also be used to install local (previously downloaded) wheel (.whl) files but dependencies may not be automatically installed if not connected to the internet. Below is an example wheel file installation for NumPy version 1.13.1 and SciPy version 0.19.1 for Python 3.6 with 64-bit Python.
pip install numpy-1.13.1+mkl-cp36-cp36m-win_amd64.whl pip install scipy-0.19.1-cp36-cp36m-win_amd64.whl
Use Christoph Gohlke's whl files for Windows installations. Many of the packages depend on the Visual C++ 2015 Redistributable (x64 and x86 for CPython 3.5 and 3.6) that is available from Microsoft. After installing the Visual C++ redistributable, download and install NumPy and SciPy packages (in that order) for Python 3.6 on Windows. The downloaded wheel file names should not be changed because the wheel file name verifies compatibility with the current Python version.
Option #1: Install Python
Option #1: Install Python from Python.org
<iframe width="560" height="315" src="https://www.youtube.com/embed/7HVOP-VfU0M" frameborder="0" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/Ju6zw83PoKo" frameborder="0" allowfullscreen></iframe>
The following instructions are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order with the utility PIP or by downloading the installer package from the appropriate web-site.
The instructions are for the Windows OS but Python can be installed on most operating systems. The Python base program should be installed first and then the other packages can be installed in any order with the utility PIP or by downloading the installer package from the appropriate web-site.
Option #2: Install Anaconda
Anaconda includes the Jupyter Notebook and the Spyder IDE. Anaconda is available for download here.
<iframe width="560" height="315" src="https://www.youtube.com/embed/FKwicZF7xNE" frameborder="0" allowfullscreen></iframe>
<iframe width="560" height="315" src="https://www.youtube.com/embed/LrMOrMb8-3s" frameborder="0" allowfullscreen></iframe>
Option #2: Anaconda (includes most packages)
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy.
(:html:) <iframe width="420" height="315" src="https://www.youtube.com/embed/-llHYUMH9Dg" frameborder="0" allowfullscreen></iframe> (:htmlend:)
There are several online platforms that allow Python through a web-browser including try.jupyter.org and repl.it. Join the ChE263 course exercises at:
There are several online platforms that allow Python through a web-browser including try.jupyter.org and repl.it. An example of using repl.it is here:
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility.
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 or Python 3.6+.
Option #3: Online Platforms
There are several online platforms that allow Python through a web-browser including try.jupyter.org and repl.it. Join the ChE263 course exercises at:
https://repl.it/classroom/invite/FS5LV0W
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/LfodqSAgEqg" frameborder="0" allowfullscreen></iframe> (:htmlend:)
Option #3: Anaconda (includes most packages)
Option #2: Anaconda (includes most packages)
(:htmlend:)
Manage Python Packages
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/Z_Kxg-EYvxM" frameborder="0" allowfullscreen></iframe>
Option #2: Install Portable Python
Another option for installing Python is the Portable Python package. This can be installed on a Flash USB drive and run directly from the external drive.
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
sudo easy_install -U Numpy
The module name of Numpy can be replaced by other modules such as Scipy, Matplotlib, and others if not included by default.
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy.
(:html:) <iframe width="420" height="315" src="https://www.youtube.com/embed/-llHYUMH9Dg" frameborder="0" allowfullscreen></iframe> (:htmlend:)
The following are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order.
- Download and Install python-2.7.6.msi Δ
- Download and Install numpy-1.8.1.exe Δ
- Download and Install matplotlib-1.3.1.exe Δ
- Download and Install scipy-0.13.3.exe Δ
- Download and Install pyparsing-2.0.2.exe Δ
- Download and Install pyserial-2.7.exe Δ
- Download, Extract, and Copy dateutil folder to "C:\Python27\Lib\"
The following instructions are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order with the utility PIP or by downloading the installer package from the appropriate web-site.
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/FKwicZF7xNE" frameborder="0" allowfullscreen></iframe> (:htmlend:)
Option #3: Other Platform Options
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
Option #3: Anaconda (includes most packages)
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
Option #1: Install Individual Packages
Option #1: Install Python
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/7HVOP-VfU0M" frameborder="0" allowfullscreen></iframe> (:htmlend:)
Introduction to Python and iPython
(:html:) <iframe width="420" height="315" src="https://www.youtube.com/embed/hDmfZCVgShc" frameborder="0" allowfullscreen></iframe> (:htmlend:)
(:title Introduction to Python for Engineers and Scientists:)
(:title Introduction to Python for Engineers:)
Introduction to Python and iPython
Non-Ideal Gas Equation
Source Code
R = 0.0821 # L-atm/K T = 500 # K V = 5 # L/mol Pc = 37.2 # atm Tc = 132.5 # K a = 0.427 * pow(R,2) * pow(Tc,2.5) / Pc b = 0.0866 * R * Tc / Pc # Compute in atm P_ig = R * T / V P_rk = R * T / (V-b) - a/(V*(V+b)*pow(T,0.5)) # Convert to Pascals P_ig = P_ig * 101325 P_rk = P_rk * 101325 print("The ideal gas pressure: " + str(P_ig) + " Pa") print("The Redlich-Kwong pressure: " + str(P_rk) + " Pa")
Introduction to Python and iPython
(:html:) <iframe width="560" height="315" src="https://www.youtube.com/embed/p2Dyx9DyQWw" frameborder="0" allowfullscreen></iframe> (:htmlend:)
Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
The iPython platform installation instructions are given here. Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
Introduction to Python and iPython
(:html:) <iframe width="420" height="315" src="https://www.youtube.com/embed/hDmfZCVgShc" frameborder="0" allowfullscreen></iframe> (:htmlend:)
There are several resources for learning Python online. For a good start, look at Code Academy (Python track) or view the documentation at Python.org. For users with a foundation in MATLAB, there are excellent resources that demonstrate equivalent Python (Numpy) commands.
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility.
Python is a high-level and general-purpose programming language. According to the TIOBE index and CodeEval, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility.
- Download, Extract, and Copy to "C:\Python27\Lib\"
- Download, Extract, and Copy dateutil folder to "C:\Python27\Lib\"
Install Individual Packages
Option #1: Install Individual Packages
Install Portable Python
Option #2: Install Portable Python
Option #3: Other Platform Options
Some platforms like MacOS typically include Python pre-installed but may be missing some of the packages such as Numpy. One method to include packages such as Numpy is to use the easy_install utility such as:
sudo easy_install -U Numpy
The module name of Numpy can be replaced by other modules such as Scipy, Matplotlib, and others if not included by default.
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility. The following are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order.
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility.
Install Individual Packages
The following are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order.
Install Portable Python
Another option for installing Python is the Portable Python package. This can be installed on a Flash USB drive and run directly from the external drive.
"Hello, World!" Tutorial
- Download, Extract, and Copy to C:\Python27\Lib\
- Download, Extract, and Copy to "C:\Python27\Lib\"
- Download, Extract, and Copy to C:\Python27\Lib** Dateutil.zip
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages. The following are for the Windows OS:
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages although the newer 3.x versions are making progress with compatibility. The following are for the Windows OS. The Python base program should be installed first and then the other packages can be installed in any order.
Python is a high-level and general-purpose programming language. According to the TIOBE index, it is one of most popular programming languages. Part of the reason that it is a popular choice for scientists and engineers is the language versatility, online community of users, and powerful analysis packages such as Numpy and Scipy. This course uses Python 2.7 because of compatibility with the scientific computing packages. The following are for the Windows OS:
- Download and Install python-2.7.6.msi Δ
- Download and Install numpy-1.8.1.exe Δ
- Download and Install matplotlib-1.3.1.exe Δ
- Download and Install scipy-0.13.3.exe Δ
- Download and Install pyparsing-2.0.2.exe Δ
The following tutorial is a "Hello, World!" (introductory) example of writing a simple Python script, running the script in debug mode, and basic programming constructs.
(:title Introduction to Python for Engineers and Scientists:) (:keywords tutorial, introduction, Python, university course:) (:description Introduction to Python - Problem-Solving Techniques for Chemical Engineers at Brigham Young University:)
Python Introduction
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This same tutorial is also show in a MATLAB introduction.
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