This document provides an introduction and overview of using Python on the Raspberry Pi. It discusses that Python is a general purpose language created in the late 1980s that is supported on many operating systems and hardware, including the Raspberry Pi. It then provides tips and recommendations for learning Python, using popular Python libraries, virtual environments, best coding practices, and web development frameworks. Specific libraries and tools mentioned include IPython, Requests, Pandas, Matplotlib, Scikit-Learn, Bottle, Flask, and Django. Source code examples are also included.

1. Python on Pi

2. Who am I?

3. What is python

4. Created in the late 80’s

5. General purpose language

6. Supported many OS/Hardware

7. It is supported by the pi foundation

8. ● http://learnpythonthehardway.org/
● https://docs.python.org/
Where to learn python

9. few tip for good python

10. explore standard library
● python is battery included
● Have extensive library
○ unittest
○ json
○ csv
○ sqlite3
○ etc
● On the side is how you start a simple web
server to serve file on the directory the
command run
$ python -m SimpleHTTPServer 8000
$ echo '{"foo": "lorem", "bar": "ipsum"}' | python -
m json.tool

11. use ipython
● Advanced python shell
● feature
○ autocomplete
○ notebook capability, for sharing
○ syntax highlighting
● installation
○ sudo apt-get install ipython
○ pip install ipython
● There is also a notebook. but lets not go
there
$ ipython
Python 2.7.10 (default, Oct 14 2015, 16:09:02)
Type "copyright", "credits" or "license" for more information.
IPython 3.1.0 -- An enhanced Interactive Python.
? -> Introduction and overview of IPython's features.
%quickref -> Quick reference.
help -> Python's own help system.
object? -> Details about 'object', use 'object??' for extra details.
In [1]: import random
In [2]: print(random.randint())
---------------------------------------------------------------------------
TypeError Traceback (most recent call last)
<ipython-input-2-5c3017620459> in <module>()
----> 1 print(random.randint())
TypeError: randint() takes exactly 3 arguments (1 given)
In [3]: print(random.randint(1,10))
9

12. Use virtualenv(when possible)
● environment isolation
● Why?
○ python is used extensively as a tool on
linux
○ thus library might conflict
● Why not?
○ sometime it will compile c module
○ The pi OS might not have the necessary
header
● but there --system-site-package for a
reason
$ virtualenv --system-site-package pijam2015
New python executable in pijam2015/bin/python
Installing setuptools, pip, wheel...done.
$ source pijam2015/bin/activate
(pijam2015)$

13. Create a main function
● STOP writing code outside a function and
if __name__ == “__main__”
● Why?
○ Make testing easy
○ sometime you don’t want code to run when
you import a module
import random
def main():
print(random.randint(1,10))
if __name__ == “__main__”:
main()

14. use a *.local hostname
● Not exactly a python thing
● it is a domain for zeroconf networking
● avahi is installed on your pi anyway
● Just make sure the domain name is
unique
$ sudo echo “your_awesome_name.local” >
/etc/hostname

15. use pip
● Don’t download zip file
● standard python tools
● When you have internet connection use
pip
● When binary is available pip (wheel). It will
download it
$ sudo pip install something
$ sudo pip remove something

16. Use new style
● People begin to use python 3 in production
● A number of chances to syntax
print(“spam”)
instead of
print “spam”

17. Best tools

18. use request
● http library
● easy to use
● not on standard lib
● install
○ pip install requests
○ sudo apt-get install python-requests
import requests
def main():
r = requests.get(“google.com”)
print(r.status_code)
if __name__ == “__main__”:
main()

19. Panda the data cruncher
● make data processing easy
● introduce data frame
● can import/export to csv
● Install
○ sudo apt-get install python-pandas
● Use system package version. It is faster
get the source code at
https://github.com/sweemeng/klpijam2015_dem
o/blob/master/sense_plotter.py

20. Matplotlib
● standard plotting library
● save image locally
● if headless set matplotlib.use('Agg')
● can be complicated. but powerful
● install
○ pip install python-matplotlib
○ sudo apt-get install python-matplotlib
● fyi if you installed pandas matplotlib is
installed as a dependency
n [1]: import matplotlib
In [2]: matplotlib.use('Agg')
In [3]: import matplotlib.pyplot as plt
In [4]: fig = plt.figure()
In [5]: plt.plot([1,2,3,4])
Out[5]: [<matplotlib.lines.Line2D at 0x73fe9fd0>]
In [6]: fig.savefig('tmp.png')

21. Scikit-learn
● Add machine learning to code
● have many algorithm
● use system package version
● install
○ sudo apt-get install python-scikitlearn
from sklearn import svm
from sklearn import datasets
digits = datasets.load_digits()
clf = svm.SVC(gamma=0.001, C=100.)
clf.fit(digits.data[:-1], digits.target[:-1])
clf.predict(digits.data[-1:])

22. Web development
● plenty of choice.
● For powerful feature full framework, I like
django
● For no frill, no dependency, i like bottle
● For if I need serious flexibility I use flask.
from bottle import static_file, route, run, view, template
import os
@route("/static/<filename>")
def serve_file(filename):
return static_file(filename, root="./")
@route("/")
def directory():
content = os.listdir("./")
directory = []
for item in content:
if ".jpg" in item:
directory.append(item)
template_str = """
%for item in directory:
<img src="/static/{{item}}/><br/>
%end
"""
return template(template_str, directory=directory)
if __name__ == "__main__":
run(host="0.0.0.0", port="8080", debug=True)

23. Final tips
● sometime you might want to use system package, because it is precompiled
● system package is older
● lack new feature
● usually good enough
● standard library is extensive, explore it.

24. There’s more!
● But i’m can’t fit everything to slide
● so Ask me!

25. Source code
● A lot of this rely on the sense_hat that I got for hacking.
● But the code is https://github.com/sweemeng/klpijam2015_demo/

26. Hope that’s helpful