Python Intro

The following is based off of "lesson3" in Professor Kevin W. Lu's iot GitHub repository

Setup

Up first, I diverged slightly from Professor Lu's implementation by installing all required packages into a virtual environment on my Pi to prevent conflicts with future labs

• I made sure that my pip3 was up to date by runing the following command
• $sudo -H pip3 install pip
• Next, I made sure that I had installed the latest version of virtualenv
• $pip3 install virtualenv
• Lastly, I created an environment for lesson3 and installed the required dependencies
• $virtualenv env_lesson3
• $source env_lesson3/bin/activate
• $pip3 install jdcal astral geopy
• $sudo apt install doxygen html2text

Running The Lab

I then ran the following commands and observed the output - I will include a section with a few of the outputs I received. Overall, everything went very well and the packages worked as expected.

• $cd git/iot
• $git pull
• $cd lesson3
• $python3 julian.py
• $python3 date_example.py
• $python3 datetime_example.py
• $python3 time_example.py
• $python3 sun.py 'New York'
• $python3 moon.py
• $python3 coordinates.py 'SC Williams Library'
• $python3 address.py '40.7448397, -74.02531776875'
• $python3 system_info.py

Output

• Julian.py
  • Calendar Date: 2020-03-23
  • Julian Date: 2458931.5
  • Modified Julian Date: 58931.0

• sun.py 'New York'
  • Information for New York/USA
  • Timezone: US/Eastern
  • Latitude: 40.72; Longitude: -74.00
  • Dawn: 2020-03-23 06:25:55.111185-04:00
  • Sunrise: 2020-03-23 06:53:46.227831-04:00
  • Noon: 2020-03-23 13:02:33-04:00
  • Sunset: 2020-03-23 19:11:35.786080-04:00
  • Dusk: 2020-03-23 19:39:31.322561-04:00

• coordinates.py '574 Bay Ridge Parkway'
  • 574, Bay Ridge Parkway, Bay Ridge, Brooklyn, Kings County, New York, 11209, United States of America
  • (40.628158850000005, -74.0209041)

• address.py '40.628158850000005, -74.0209041'
  • 574, Bay Ridge Parkway, Bay Ridge, Brooklyn, Kings County, New York, 11209, United States of America
  • (40.628158850000005, -74.0209041)

• system_info.py
  • Free RAM: 98 (926)
  • Number of processes: 115
  • Up time: 33 days, 2:13
  • Number of connections: 3
  • Temperature in C: 44.5
  • IP-address: 192.168.1.27
  • CPU speed in MHz: arm_freq=1400

• Doxygen and html2text output
  • My Project
  • Class List
  • Here are the classes, structs, unions and interfaces with brief descriptions:
  • [detail level 12]
  • ▼NpyexampDocumentation for this module
  • CPyClass Documentation for a class
  • ===============================================================================
  • Generated by [doxygen] 1.8.13

Notes + Pypy + Doxygen

The most surprising thing for me was to find that coordinates.py and address.py were able to accurately return the coordinates of and address of my fathers dental office. It was extremely satisfying to realize the power and efficiency of the packages showcased in this lab. The code for all of the scripts was minimal, and while it wasn't commented, it was written in a way that was easy to read and understand.

It is also important to note that when running pypy benchmarks for my scripts the performance difference between it and python3 was almost negligible for most of the scripts. This may be because none of them exceeded two hundred lines, more testing is required to establish that fact.

When running doxygen it was easy to see why it is such an industry standard, it was supremely easy to use and an example of its output can be found above in the output section