Just see the next source code:
>>> text='0123456789'
>>> reverse_text=text[::-1]
>>> print reverse_text
9876543210
>>>
Is a blog about python programming language. You can see my work with python programming language, tutorials and news.
Just see the next source code:
>>> text='0123456789'
>>> reverse_text=text[::-1]
>>> print reverse_text
9876543210
>>>
A fractal is a mathematical set that has a fractal dimension that usually exceeds its topological dimension , see Fractal wikipedia.
Today I used my mind and also my python skills to make one fractal image.
I use Newton's method to make all points and PIL python module to save the result.
Let's see the source code and comments.
from PIL import Image
#size of image
imgx = 600
imgy = 400
#make image buffer
image = Image.new("RGB", (imgx, imgy))
# area of fractal
xa = -2.0
xb = 2.0
ya = -2.0
yb = 2.0
#define constants
max_iterations = 10 # max iterations allowed
step_derivat = 0.002e-1 # step size for numerical derivative
error = 5e-19 # max error allowed
# function will generate the newton fractal
def f(z): return z * z + complex(-0.31,0.031)
# draw derivate fractal for each y and x
for y in range(imgy):
zy = y * (yb - ya)/(imgy - 1) + ya
for x in range(imgx):
zx = x * (xb - xa)/(imgx - 1) + xa
z = complex(zx, zy)
for i in range(max_iterations):
# make complex numerical derivative
dz = (f(z + complex(step_derivat, step_derivat)) - f(z))/complex(step_derivat,step_derivat)
# Newton iteration see wikipedia
z0 = z - f(z)/dz
# stop to the error
if abs(z0 - z) < error:
break
z = z0
#I use modulo operation expression to do RGB colors of the pixels
image.putpixel((x, y), (i % 8 * 16, i % 4 * 32,i % 2 * 64))
#save the result
image.save("fractal.png", "PNG")
This is the final result of Newton fractal image:
The new version : PP 1.6.4 is released and working well.
What is PP python module?
PP is a python module which provides mechanism for parallel execution of python code on SMP and clusters.
SMP - systems with multiple processors or cores;
clusters - computers connected via network;
Read more Parallel Python.
The python module Flask is a small web framework.
Install the module using pip.
(my_new_env)[free-tutorials@free-tutorials ~]$ pip install Flask
Downloading/unpacking Flask
Downloading Flask-0.9.tar.gz (481kB): 481kB downloaded
Running setup.py egg_info for package Flask
warning: no files found matching '*' under directory 'tests'
...
...
Successfully installed Flask Werkzeug Jinja2
Cleaning up...
Create the next python script and save as : flask-web.py .
from flask import Flask
app = Flask(__name__)
@app.route('/')
def hello_world():
return 'Hello World!'
if __name__ == '__main__':
app.run()
Run the python script:
(my_new_env)[free-tutorials@free-tutorials ~]$ python flask-web.py
* Running on http://127.0.0.1:5000/
127.0.0.1 - - [25/Jan/2013 00:10:35] "GET / HTTP/1.1" 200 -
127.0.0.1 - - [25/Jan/2013 00:10:36] "GET /favicon.ico HTTP/1.1" 404 -
127.0.0.1 - - [25/Jan/2013 00:10:36] "GET /robots.txt HTTP/1.1" 404 -
127.0.0.1 - - [25/Jan/2013 00:10:36] "GET /favicon.ico HTTP/1.1" 404 -
127.0.0.1 - - [25/Jan/2013 00:10:36] "GET /robots.txt HTTP/1.1" 404 -
You will see something like this:
Also you can try the quickstart tutorial here.
Use pip and virtualenv and you can make sandboxed Python development environments.
With this tools such as pip and virtualenv you have total control over the development environment.
Why? Because if your project is developed by a team with mutiple developers then they prefer having exactly replicated environments.
Let's try some simple example commands:
1. Start your environment ( in my case is: my_new_env ).
[free-tutorials@free-tutorials ~]$ python virtualenv.py my_new_env
New python executable in my_new_env/bin/python
Installing setuptools..................done.
Installing pip.............done.
Activate your environment ( in my case is: my_new_env ).
[free-tutorials@free-tutorials ~]$ . my_new_env/bin/activate
Let's see the pip --help command :
(my_new_env)[free-tutorials@free-tutorials ~]$ pip --help
Usage: pip COMMAND [OPTIONS]
--version show program's version number and exit
-h, --help Show help
-v, --verbose Give more output
-q, --quiet Give less output
--log Log file where a complete (maximum verbosity)
record will be kept
--proxy Specify a proxy in the form
user:passwd@proxy.server:port. Note that the
user:password@ is optional and required only if
you are behind an authenticated proxy. If you
provide user@proxy.server:port then you will be
prompted for a password.
--timeout Set the socket timeout (default 15 seconds)
--exists-action
Default action when a path already exists. Use
this option more than one time to specify
another action if a certain option is not
available. Choices: (s)witch, (i)gnore, (w)ipe,
(b)ackup
Commands available:
bundle: Create pybundles (archives containing multiple packages)
freeze: Output all currently installed packages (exact versions) to stdout
help: Show available commands
install: Install packages
search: Search PyPI
uninstall: Uninstall packages
unzip: Unzip individual packages
zip: Zip individual packages
Now we will use freeze and install.
I will list all the pip packages used in my virtual environment.
(my_new_env)[free-tutorials@free-tutorials ~]$ pip freeze -l
PyOpenGL==3.0.2
PyOpenGL-accelerate==3.0.2
Put all the output in my_packages.txt file.
(my_new_env)[free-tutorials@free-tutorials ~]$ pip freeze -l > my_packages.txt
Install my packages from my_packages.txt .
(my_new_env)[free-tutorials@free-tutorials ~]$ pip install -r my_packages.txt
Requirement already satisfied (use --upgrade to upgrade): PyOpenGL==3.0.2 in
./my_new_env/lib/python2.7/site-packages (from -r my_packages.txt (line 1))
Requirement already satisfied (use --upgrade to upgrade): PyOpenGL-accelerate==3.0.2 in
./my_new_env/lib/python2.7/site-packages (from -r my_packages.txt (line 2))
Cleaning up...
Let's try now to find one python module : opencv .
(my_new_env)[free-tutorials@free-tutorials ~]$ pip search opencv
remotecv - remotecv is an OpenCV server for facial and
feature recognition
ctypes-opencv - ctypes-opencv - A Python wrapper for OpenCV using
ctypes
pyopencv - PyOpenCV - A Python wrapper for OpenCV 2.x using
Boost.Python and NumPy
opencv-cython - An alternative OpenCV wrapper
CVtypes - Python OpenCV wrapper using ctypes
Tippy - another Toolbox for Image Processing in PYthon,
based on OpenCV
You can see where the version of python you are using installs to by running it the next python code.
>>> import sys
>>> sys.prefix
'/home/free-tutorials/my_new_env'
>>> sys.exec_prefix
'/home/free-tutorials/my_new_env'
To leave your environment just type next command: $ deactivate.
I will come with new tutorials about pip and virtualenv .
See you later.