Python 3.7.3 : Fix kivy python module installation.

Kivy is a multi-platform GUI development library for Python, running on Windows, Mac, Linux, Android, and iOS.
Today I tested kivy python module with python version 3.7.3 and I got some errors but I fixed.
I started with the default installation using the pip tool.

C:\Python373>cd Scripts
C:\Python373\Scripts>pip install kivy
...
Installing collected packages: docutils, pygments, Kivy-Garden, kivy
...
Successfully installed kivy-1.10.1

I used a default script to test the kivy python module.
When I tested I got these errors:

[CRITICAL] [Window      ] Unable to find any valuable Window provider.
sdl2 - ImportError: DLL load failed: The specified module could not be found.
  File "C:\Python373\lib\site-packages\kivy\core\__init__.py", line 59, in core_
select_lib
    fromlist=[modulename], level=0)
  File "C:\Python373\lib\site-packages\kivy\core\window\window_sdl2.py", line 26
, in 
    from kivy.core.window._window_sdl2 import _WindowSDL2Storage
...
[CRITICAL] [App         ] Unable to get a Window, abort.

Iinstall the kivy.deps.sdl2:

C:\Python373>cd Scripts
C:\Python373\Scripts>pip install kivy.deps.sdl2
Collecting kivy.deps.sdl2
  Downloading https://files.pythonhosted.org/packages/93/84/a0dc274d993db6f9ebdf
41eb4d55b032de005dbf47e4d54602cf83708b08/kivy.deps.sdl2-0.1.18-cp37-cp37m-win_am
d64.whl (2.5MB)
     |████████████████████████████████| 2.5MB 726kB/s
Installing collected packages: kivy.deps.sdl2
Successfully installed kivy.deps.sdl2-0.1.18

When I tested again, I got another error:

[CRITICAL] [App         ] Unable to get a Window, abort.

I try to see if the install of these python modules are right:

C:\Python373>cd Scripts
C:\Python373\Scripts>pip install pypiwin32
Requirement already satisfied: pypiwin32 in c:\python373\lib\site-packages (223)
Requirement already satisfied: pywin32>=223 in c:\python373\lib\site-packages 
(from pypiwin32) (224)
C:\Python373\Scripts>pip install kivy.deps.glew
Collecting kivy.deps.glew
...

Now the kivy works well:

[INFO   ] [Kivy        ] v1.10.1
[INFO   ] [Python      ] v3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC
v.1916 64 bit (AMD64)]
[INFO   ] [Factory     ] 194 symbols loaded
[INFO   ] [Image       ] Providers: img_tex, img_dds, img_sdl2, img_pil, img_gif
 (img_ffpyplayer ignored)
[INFO   ] [Text        ] Provider: sdl2
[INFO   ] [Window      ] Provider: sdl2
[INFO   ] [GL          ] Using the "OpenGL" graphics system
[INFO   ] [GL          ] GLEW initialization succeeded
[INFO   ] [GL          ] Backend used 
[INFO   ] [GL          ] OpenGL version 
[INFO   ] [GL          ] OpenGL vendor 
[INFO   ] [GL          ] OpenGL renderer 
[INFO   ] [GL          ] OpenGL parsed version: 4, 6
[INFO   ] [GL          ] Shading version 
[INFO   ] [GL          ] Texture max size <16384>
[INFO   ] [GL          ] Texture max units <32>
[INFO   ] [Window      ] auto add sdl2 input provider
[INFO   ] [Window      ] virtual keyboard not allowed, single mode, not docked
[INFO   ] [Base        ] Start application main loop
[INFO   ] [GL          ] NPOT texture support is available
[INFO   ] [Base        ] Leaving application in progress...

If you search on web you will se this is a common error and some users use this solution:

python -m pip install docutils pygments pypiwin32 kivy.deps.sdl2
python -m pip install kivy.deps.glew
python -m pip install kivy.deps.gstreamer

Hope this help you with python programming and kivy interface.

Python 3.7.3 : Get location of International Space Station.

Today I tested the urllib python module with python 3.7.3 and json python module.
The issue was to get the location of International Space Station - Open Notify.
The International Space Station is moving at close to 28,000 km/h so its location changes really fast! Where is it right now?
This is an open source project to provide a simple programming interface for some of NASA’s awesome data.
I do some of the work to take raw data and turn them into APIs related to space and spacecraft.

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD6
4)] on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import urllib.request
>>> with urllib.request.urlopen('http://api.open-notify.org/iss-now.json') as f:
        print(f.read(300))
...
b'{"iss_position": {"longitude": "-86.9247", "latitude": "-38.3744"}, "message":
 "success", "timestamp": 1556575039}'
>>> with urllib.request.urlopen('http://api.open-notify.org/iss-now.json') as f:
...     source = f.read()
...     data = json.loads(source)
...
>>> print(data)
{'iss_position': {'longitude': '151.1941', 'latitude': '49.4702'}, 'message': 's
uccess', 'timestamp': 1556578621}
>>> print(data['iss_position']['longitude'])
151.1941
>>> print(data['iss_position']['latitude'])
49.4702
>>> print(data['message'])
success

Python 3.7.3 and memory_profiler python module.

Today I will come up with a simpler and more effective tutorial in python programming.
First, I need to install the psutil python module for the example of this tutorial.

C:\Python373>cd Scripts
C:\Python373\Scripts>pip install psutil

Python memory monitor is very important for debugging application performance and fix bugs.
You can solve this issue is the python module named memory_profiler, see more here.
Let's install this python module with the pip python tool:

C:\Python373\Scripts>pip install memory_profiler

Let's start with a simple python script example:

import psutil

def test_psutil():
 # gives a single float value
 print(psutil.cpu_percent())
 # gives an object with many fields
 print(psutil.virtual_memory())
 # you can convert that object to a dictionary 
 print(dict(psutil.virtual_memory()._asdict()))
if __name__ == '__main__':
 test_psutil()

C:\Python373>python psutil_001.py
0.0
svmem(total=4171108352, available=1153679360, percent=72.3, used=3017428992, fre
e=1153679360)
{'total': 4171108352, 'available': 1153671168, 'percent': 72.3, 'used': 30174371
84, 'free': 1153671168}

The same result can see if you use memory_profiler

C:\Python373>python -m memory_profiler psutil_001.py
100.0
svmem(total=4171108352, available=1149018112, percent=72.5, used=3022090240, fre
e=1149018112)
{'total': 4171108352, 'available': 1149087744, 'percent': 72.5, 'used': 30220206
08, 'free': 1149087744}

Let's decorate python source code with @profile annotation to have a good output.

import psutil
@profile
def test_psutil():
 # gives a single float value
 print(psutil.cpu_percent())
 # gives an object with many fields
 print(psutil.virtual_memory())
 # you can convert that object to a dictionary 
 print(dict(psutil.virtual_memory()._asdict()))
if __name__ == '__main__':
 test_psutil()

Sure, this error tells us the decorate not working in the default way.

C:\Python373>python psutil_001.py
Traceback (most recent call last):
  File "psutil_001.py", line 2, in 
    @profile
NameError: name 'profile' is not defined

In this case, the decorate profile works great with the python module and give us all the information we need:
C:\Python373>python -m memory_profiler psutil_001.py

100.0
svmem(total=4171108352, available=1022672896, percent=75.5, used=3148435456, fre
e=1022672896)
{'total': 4171108352, 'available': 1022783488, 'percent': 75.5, 'used': 31483248
64, 'free': 1022783488}
Filename: psutil_001.py

Line #    Mem usage    Increment   Line Contents
================================================
     2   15.219 MiB   15.219 MiB   @profile
     3                             def test_psutil():
     4                                  # gives a single float value
     5   15.230 MiB    0.012 MiB        print(psutil.cpu_percent())
     6                                  # gives an object with many fields
     7   15.230 MiB    0.000 MiB        print(psutil.virtual_memory())
     8                                  # you can convert that object to a dicti
onary
     9   15.234 MiB    0.004 MiB        print(dict(psutil.virtual_memory()._asdi
ct()))

Let's test with another python script named 001.py :

from memory_profiler import profile

@profile(precision=4)
def test():
    a = 0
    a = a + 1

if __name__ == "__main__":
    test()

The result with precision=4 is this:

C:\Python373>python -m memory_profiler 001.py
Filename: 001.py

Line #    Mem usage    Increment   Line Contents
================================================
     3  15.3945 MiB  15.3945 MiB   @profile(precision=4)
     4                             def test():
     5  15.3945 MiB   0.0000 MiB       a = 0
     6  15.3945 MiB   0.0000 MiB       a = a + 1

If we change the precision=1 then this is the result:

C:\Python373>python -m memory_profiler 002.py
Filename: 002.py

Line #    Mem usage    Increment   Line Contents
================================================
     3     15.4 MiB     15.4 MiB   @profile(precision=1)
     4                             def test():
     5     15.4 MiB      0.0 MiB       a = 0
     6     15.4 MiB      0.0 MiB       a = a + 1

A good source of information for this python module can be found at GitHub.

Django REST framework - part 001.

Today I will introduce you a tutorial to fix some of the necessary elements presented in the old tutorial.
The manage tool shell can also give us some info:

C:\Python373\Scripts\example>python manage.py shell
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD6
4)] on win32
Type "help", "copyright", "credits" or "license" for more information.
(InteractiveConsole)
>>> from test001.models import test
>>> from django.db.models import Count, Min, Max, Avg
>>> out = test.objects.all
>>> out
...

One note about error method, do not use like this:

>>> out = test.objects.all
>>> out[0]
Traceback (most recent call last):
  File "", line 1, in 
TypeError: 'method' object is not subscriptable

The correct way method is:

>>> out = test.objects.all()
>>> out
]>
>>> out[0]

>>> vars(out[0])
{'_state': , 'id'
: 1, 'first_name': 'Cătălin George', 'last_name': 'Feștilă'}

We can use the annotate.
This issue can solve it into this way:

>>> minimal = test.objects.annotate(Min('last_name'))
>>> minimal
]>
>>> minimal[0]

>>> vars(minimal[0])
{'_state': , 'id'
: 1, 'first_name': 'Cătălin George', 'last_name': 'Feștilă', 'last_name__min': '
Feștilă'}

See the result of the annotate add the last_name__min value.
I created another class named city with just one field named city_name and I fill with one value:
All changes are posted at the end of this tutorial.
Let's test with the shell some of these new changes:

C:\Python373\Scripts\example>python manage.py shell
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit 
(AMD64)] on win32
Type "help", "copyright", "credits" or "license" for more information.
(InteractiveConsole)
>>> from test001.models import test,city
>>> from django.db.models import Count, Min, Max, Avg
>>> out_test = test.objects.all()
>>> out_city = city.objects.all()
>>> out_test
]>
>>> out_city
]>
>>> vars(out_city[0])
{'_state': , 'id'
: 1, 'city_name': 'Fălticeni'}

We can easy test the new example:

>>> minimal = test.objects.annotate(Min('last_name'))
>>> minimal
]>
>>> vars(minimal[0])
{'_state': , 'id'
: 1, 'first_name': 'Cătălin George', 'last_name': 'Feștilă', 'last_name__min': '
Feștilă'}
>>> minimal = city.objects.annotate(Min('city_name'))
>>> minimal
]>
>>> vars(minimal[0])
{'_state': , 'id'
: 1, 'city_name': 'Fălticeni', 'city_name__min': 'Fălticeni'}
>>> filter_test = test.objects.filter(id = 1)
>>> vars(filter_test)
{'model': , '_db': None, '_hints': {}, 'query': 
, '_result_cache': 
None, '_sticky_filter': False, '_for_write': False, '_prefetch_related_lookups':
(), '_prefetch_done': False, '_known_related_objects': {}, '_iterable_class': , '_fields': None}
>>> vars(filter_test[0])
{'_state': , 'id'
: 1, 'first_name': 'Cătălin George', 'last_name': 'Feștilă'}

Feel free to test with my old and the new example:

# models.py
from django.db import models

class test(models.Model):
    first_name = models.CharField(max_length=30)
    last_name = models.CharField(max_length=30)
    
class city(models.Model):
    city_name = models.CharField(max_length=30)
#admin.py
from django.contrib import admin
from .models import test, city
admin.site.register(test)
admin.site.register(city)
#serializers.py
from rest_framework import serializers
from .models import test, city

class test_serializer(serializers.ModelSerializer):
    class Meta:
        model = test
        fields = ('id', 'first_name', 'last_name')

class city_serializer(serializers.ModelSerializer):        
    class Meta:
        model = city
        fields = ('id', 'city_name')
#views.py
from django.shortcuts import render
from rest_framework import viewsets
from .models import test, city
from .serializers import test_serializer, city_serializer

class test_view(viewsets.ModelViewSet):
    #query to get all information from database
    queryset = test.objects.all()
    serializer_class = test_serializer

class city_view(viewsets.ModelViewSet):
    #query to get all information from database
    queryset = city.objects.all()
    serializer_class = city_serializer
#urls.py
from django.urls import path, include
from . import views
from rest_framework import routers

router = routers.DefaultRouter()
router.register('test001', views.test_view)
router.register('city', views.city_view)
#add to path 
urlpatterns = [
    path('', include(router.urls))
]

Python 3.7.3 and Django REST framework.

Today I tested something simpler for beginners: Django REST framework.
Once you understand how it works then it's simple to use.
This tutorial does not address the security issues generated by the REST, Django framework.
The official webpage comes with many information and technical specifications for this API:
Django REST framework is a powerful and flexible toolkit for building Web APIs.
The example I've submitted is built into the Scripts folder because I did not use the virtual environment.
Let's start installing the python module.

C:\Python373\> cd Scripts
C:\Python373\Scripts\>pip install djangorestframework
C:\Python373\Scripts\>django-admin startproject example
C:\Python373\Scripts\>cd example 
C:\Python373\Scripts\>python manage.py migrate 
C:\Python373\Scripts\>python manage.py createsuperuser
C:\Python373\Scripts\>python manage.py startapp test001

In the example folder we will make changes.
First is the settings.py file:

INSTALLED_APPS = [
...
    'rest_framework',
    'test001']

The next file is the urls.py:

from django.contrib import admin
from django.urls import path, include

urlpatterns = [
    path('admin/', admin.site.urls),
    path('', include('test001.urls'))
]

Also make changes in the test001 folder
You must create a python script and call it urls.py:

from django.urls import path, include

# this urlpatterns will fill later 
urlpatterns = []

You make changes to the file models.py and create a named class test.
This class will have two fields that we will update.

from django.db import models

class test(models.Model):
    first_name = models.CharField(max_length=30)
    last_name = models.CharField(max_length=30)

44/5000
The following commands will synchronize the database:

C:\Python373\Scripts\example>python manage.py makemigrations
...
  test001\migrations\0001_initial.py
    - Create model test
C:\Python373\Scripts\example>python manage.py migrate
...
Running migrations:
...

Another step is to add the test into admin.py script:

from django.contrib import admin
from .models import test
admin.site.register(test)

Serializers allow complex data such as querysets and model instances to be converted to native Python datatypes that can then be easily rendered into JSON , XML or other content types.
Let's create an serializers.py python script into test001 folder and use this code:

from rest_framework import serializers
from .models import test

class test_serializer(serializers.ModelSerializer):
    class Meta:
        model = test
        fields = ('id', 'first_name', 'last_name')

Also is need to update the views.py python script:

from django.shortcuts import render
from rest_framework import viewsets
from .models import test
from .serializers import test_serializer

class test_view(viewsets.ModelViewSet):
    #query to get all information from database
    queryset = test.objects.all()
    serializer_class = test_serializer

Now because is all create the last step is to fix the urls.py from test001 folder with the routers.
The REST framework adds support for automatic URL routing to Django.

from django.urls import path, include
from . import views
from rest_framework import routers

router = routers.DefaultRouter()
router.register('test001', views.test_view)
#add to path 
urlpatterns = [
    path('', include(router.urls))
]

Now you can test it with:

C:\Python373\Scripts\example>python manage.py runserver

If you want to make changes into models.py then you will need to use the commands to synchronize the database after these use"commands
makemigrations and migrate to fix errors.
If you encounter such run-time errors
"GET /static/assets/js/docs.min.js HTTP/1.1" 404 1667..."
These errors can be the result of settings like DEBUG, STATICFILES_DIRS or STATIC_ROOT from file settings.py.
Then you need to execute python manage.py collectstatic and Django goes through all directories where static files can be found and places them in your static root.
The result of this tutorial can be see on my youtube channel:

Google's Python Class - another step.

Here's something I like and I hope it should be known in the Python community.
Some people from Google want to attract the python community into a learning process.
Although most of the API documentation examples do not exist in the Python programming language, they have not disappeared.
Let's hope this little step will increase the chances of programming Google with the Python programming language.
This material was created by Nick Parlante working in the engEDU group at Google.
Welcome to Google's Python Class -- this is a free class for people with a little bit of programming experience who want to learn Python. The class includes written materials, lecture videos, and lots of code exercises to practice Python coding. These materials are used within Google to introduce Python to people who have just a little programming experience. The first exercises work on basic Python concepts like strings and lists, building up to the later exercises which are full programs dealing with text files, processes, and http connections. The class is geared for people who have a little bit of programming experience in some language, enough to know what a "variable" or "if statement" is. Beyond that, you do not need to be an expert programmer to use this material.
Read more about this course here.

Python 3.7.3 : Testing firebase with Python 3.7.3 .

The tutorial for today consists of using the Firebase service with python version 3.7.3 .
As you know Firebase offers multiple free and paid services.
In order to use the Python programming language, we need to use the pip utility to enter the required modules.
If your installation requires other python modules then you will need to install them in the same way.

C:\Python373>pip install firebase-admin
C:\Python373\Scripts>pip install google-cloud-firestore

The next step is to log in with a firebase account and create or use a project with a database.
You must use this link to see your project data and create your JSON configuration file for access.
Here's a screenshot of an old project in another programming language that I used for this tutorial.

At point 1, you will find Project Settings - Service accounts and you will need to use the Generate new private key button.
This will generate a JSON file that we will use in the python script.
Be careful to define the path to the python script file.
At point 2, you will find the database or you will need to create it to use it.
The script I'm going to present has commented on the lines for a better understanding of how to use it.

import firebase_admin
from firebase_admin import credentials
from firebase_admin import firestore

# the go-test.json from my project settings 
cred = credentials.Certificate("go-test.json")

# start using firebase python modules 
firebase_admin.initialize_app(cred)

# access the database
database = firestore.client()

# access the collection with limit 
my_ref = database.collection("test").limit(2)

# show the values from database
try:
    docs = my_ref.stream()
    for doc in docs:
         print(u'Doc Data:{}'.format(doc.to_dict()))
except:
    print(u'Missing data')

# result running
#Doc Data:{'nrcrt': 1, 'string_value': 'this is a text'}
#Doc Data:{'name': 'test', 'added': 'just now'}

# add data to database
my_ref_add = database.collection("test")
my_ref_add.add({u'nickname': u'catafest', u'friend': u'Last Ocelot'})

# show the new database values
try:
    docs = my_ref_add.stream()
    for doc in docs:
         print(u'Doc Data:{}'.format(doc.to_dict()))
except:
    print(u'Missing data')

# result running
#Doc Data:{'nrcrt': 1, 'string_value': 'this is a text'}
#Doc Data:{'friend': 'Last Ocelot', 'nickname': 'catafest'}
#Doc Data:{'name': 'test', 'added': 'just now'}

# get just one 
doc = database.collection('test').document('doc_id').get()

# show create time 
print(doc.create_time)

# result running
#seconds: 1556014478
#nanos: 460439000

About psychopy tool.

A good definition for this tool can be found at the Wikipedia website:
2002: PsychoPy was originally written by Peirce as a proof of concept - that a high-level scripting language could generate experimental stimuli in real time (existing solutions, such as Psychtoolbox, had to pre-generate movies or use CLUT animation techniques).
The install of this python module is very simple:

C:\Python373\Scripts>pip install psychopy

Using this command to start this tool:

C:\Python373>psychopy

The tool starts with two graphical interfaces:

• one for Coder area;
• one for the project with an untitled.psyexp;

Let's see one screenshot with this tool:

This open source tool, written in the Python programming language, help you to run a wide range of neuroscience, psychology and psychophysics experiments.
I searched the internet for the capabilities of this tool and the obvious conclusion is a utility for building experiments with a wide range of applicability.
This tool lets you use the pavlovia website, see more:
Pavlovia is a place for the wide community of researchers in the behavioural sciences to run, share, and explore experiments online.
This tool used commonly-used components for linguistic experiments:

1. Text Component (display text on the screen);
2. Sound Component (play sounds);
3. Keyboard Component (receive input from the keyboard);
4. RatingScale Component (collect a numeric rating or a choice from a few alternatives, via the mouse, the keyboard or both);
5. Code Component (insert short pieces of python code into your experiments (e.g. time stamp for the production task);

The easy way is to use the Builder tool to generate a wide range of experiments easily from the Builder using its intuitive, graphical user interface (GUI).
Today I will use the Coder with programming a simple example.
To access demos, you need to create a python script in the Coder area (use File menu - New) then use the Demos from the application menu.
Everything in a PsychoPy experiment needs a unique name.
The name must contain only letters, numbers and underscores and not contain spaces, punctuation or mathematical symbols.
This tool saves several data files: a Microsoft Excel (spreadsheet) file, a psydat file, and a log file.
The example I used today for this tutorial is how to import from a CSV file named colors_001.csv and used with psychopy python module to create stimuli:

3.3;"red"
1.1;"green"
4.4;"red"
2.2;"green"

This python script named colors.py I used to import the CSV file and use it:

from psychopy import core, visual, event
import csv
  
## Setup section, read experiment variables from file
win = visual.Window([400,300], monitor="testMonitor", units="cm", fullscr=False)
stimuli = []
datafile = open("colors_001.csv", "r",encoding="utf8")
reader = csv.reader(datafile, delimiter=";")
for row in reader:
    if len(row)==2:         # ignore empty and incomplete lines
        size = float(row[0])  # the first element in the row converted to a floating point number
        color = row[1]        # the second element in the row
        stimulus = visual.Rect(win, width=size, height=size)
        stimulus.fillColor = color
        stimuli.append(stimulus)
datafile.close()
  
## Experiment Section, use experiment variables here
for stimulus in stimuli:
    stimulus.draw()
    win.flip()
    core.wait(1.000)

## Closing Section
win.close()
core.quit()

The result of this script will show you four squares colored by the CSV file.
If you don't like to use the Builder or Coder areas, then you can simply use the python:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from psychopy import visual, core
pygame 1.9.5
Hello from the pygame community. https://www.pygame.org/contribute.html
>>> win = visual.Window()
>>> msg = visual.TextStim(win, text=u"Hello python users!")
>>> msg.draw()
>>> win.flip()
47.541564770566765

The output will be a window with a text message.

Update python modules of 3.73 version.

Today we tested an older tool with the new version of python 3.7.3.
This is a tool that will help you update your python modules.
Here's how to install:

C:\Python373\Scripts>pip install pip-review
Collecting pip-review
...
Requirement already satisfied: pyparsing>=2.0.2 in c:\python373\lib\site-package
s (from packaging->pip-review) (2.4.0)
Installing collected packages: packaging, pip-review
Successfully installed packaging-19.0 pip-review-1.0

Here is the complete overview of the options.

C:\Python373\Scripts>pip-review -h
usage: pip-review [-h] [--verbose] [--raw] [--interactive] [--auto]

Keeps your Python packages fresh.

optional arguments:
  -h, --help         show this help message and exit
  --verbose, -v      Show more output
  --raw, -r          Print raw lines (suitable for passing to pip install)
  --interactive, -i  Ask interactively to install updates
  --auto, -a         Automatically install every update found

Unrecognised arguments will be forwarded to pip list --outdated, so you can
pass things such as --user, --pre and --timeout and they will do exactly what
you expect. See pip list -h for a full overview of the options.

To update all python modules you can use:

C:\Python373\Scripts>pip-review --auto

To run interactively, you can ask to upgrade for each package:

C:\Python373\Scripts>pip-review --interactive

Using the ORB feature from OpenCV python module.

Today I will show you a simple script using the ORB (oriented BRIEF), see C++ documentation / OpenCV.
The algorithm uses FAST in pyramids to detect stable keypoints, selects the strongest features using FAST or Harris response, finds their orientation using first-order moments and computes the descriptors using BRIEF (where the coordinates of random point pairs (or k-tuples) are rotated according to the measured orientation).
One good feature of ORB is the is rotation invariant and resistant to noise.
The ORB descriptor use the Center of the mass of the patch of the Moment (sum of x,y), Centroid (the result of the matrix of all moment) and Orientation ( the atan2 of moment one and two).
One good article about ORB can be found here.
Let's see the script code of this python example:

import cv2
import numpy as np 

image_1 = cv2.imread("1.png", cv2.IMREAD_GRAYSCALE)
image_2 = cv2.imread("2.png", cv2.IMREAD_GRAYSCALE)

orb = cv2.ORB_create()
kp1, des1 = orb.detectAndCompute(image_1,None)
kp2, des2 = orb.detectAndCompute(image_2,None)

bf = cv2.BFMatcher(cv2.NORM_HAMMING, crossCheck=True)
matches = bf.match(des1, des2)
matches = sorted(matches, key = lambda x:x.distance)

matching_result = cv2.drawMatches(image_1, kp1, image_2, kp2, matches[:150], None, flags=2)

cv2.imshow("Image 1", image_1)
cv2.imshow("Image 2", image_2)
cv2.imshow("Matching result", matching_result)
cv2.waitKey(0)
cv2.destroyAllWindows()

The script use two file images 1.png and 2.png.
The result is an image composed of the two on which the areas of similitude are traced as detected by the mathematical algorithm.

Using the python module music21.

What is music21?
Music21 is a set of tools for helping scholars and other active listeners answer questions about music quickly and simply. If you’ve ever asked yourself a question like, “I wonder how often Bach does that” or “I wish I knew which band was the first to use these chords in this order,” or “I’ll bet we’d know more about Renaissance counterpoint (or Indian ragas or post-tonal pitch structures or the form of minuets) if I could write a program to automatically write more of them,” then music21 can help you with your work.
This toolkit for Computer-Aided Musical Analysis was developed at MIT by cuthbertLab. Michael Scott Cuthbert, Principal Investigator.
The development of music21 is supported by the generosity of the Seaver Institute and the NEH.
The tutorial today is about the python music21 module.
Let's start with the default pip tool to install this python module:

C:\Python364\Scripts>pip install --upgrade music21
Collecting music21
...
  Running setup.py install for music21 ... done
Successfully installed music21-5.5.0

The next step tells us to install some additional python modules:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> from music21 import * 
music21: Certain music21 functions might need these optional packages: matplotlib,
 scipy;
if you run into errors, install them by following the instructions at
http://mit.edu/music21/doc/installing/installAdditional.html

Let's install these python modules:

C:\Python373\Scripts>pip install matplotlib
C:\Python373\Scripts>pip install scipy

Let's test and play a simple example (Bach’s BWV 66.6):

>>> from music21 import *
>>> s = corpus.parse('bwv66.6')
>>> sChords = s.chordify()
>>> sChords
...
>>> sChords.show('midi')

If you want to save it, use:

>>> sChords.write("midi", "bach6.mid")
'bach6.mid'

Another example is to play a note on guitar (C#):

from music21 import stream, instrument
from music21.note import Note
cd = Note("C#", type='quarter')
test = stream.Part()
test.insert(0, instrument.AcousticGuitar())
test_measure = stream.Measure()
test_measure.append(cd)
test.append(test_measure)
test.show('midi')

You can see all the instruments here.
This python module is very complex and can be used with additional software, see here.
More details can be found in the documentation.

Using pytineye to automate searching for images.

The TinEye API is ideally suited for image and profile verification, UGC moderation, copyright compliance and fraud detection.
Read more about the TinEye API here.
You need to use authentication for this API, read here.
To use the TinEye API you must purchase a search bundle.
The documentation for Python can be found here.
Let's start with the installation.
You need to download the zip file from GitHub and install using the pip tool:

C:\Python373\Scripts>pip3.7.exe install pytineye-master.zip
...
Successfully installed pytineye-1.3

>>> import pytineye
>>> from pytineye import TinEyeAPIRequest
>>> myapi = TinEyeAPIRequest('http://api.tineye.com/rest/', 'your_public_key', 'your_private_key')
>>> myapi.remaining_searches()
{'bundles': [], 'total_remaining_searches': 0}

Because I don't have search the python code return an error:

>>> myapi.search_url(url='http://en.es-static.us/upl/2019/03/rogue-planet-CFBD-S
IR-J214947.2-040308.9-2012-800x450.jpg')
Traceback (most recent call last):
  File "", line 1, in 
  File "C:\Python373\lib\site-packages\pytineye\api.py", line 304, in search_url

    obj = self._request('search', params, **kwargs)
  File "C:\Python373\lib\site-packages\pytineye\api.py", line 276, in _request
    raise TinEyeAPIError(obj['code'], obj.get('messages'))
pytineye.exceptions.TinEyeAPIError: APIError:
                   code    = 401
                   message = ['AUTHORIZATION_ERROR', 'You have no more searches
available. Please purchase another bundle if you wish to make more searches.']

If you want to buy TinEye API searches then the prices start from:
5,000 searches $200.00 USD($0.04 per search)
10,000 searches $300.00 USD($0.03 per search)
50,000 searches $1,000.00 USD($0.02 per search)
1,000,000 searches $10,000.00 USD($0.01 per search)

First test with 3.7.3 and opencv-python module version 4.0.0 .

The Python 3.7.3 is the third maintenance release of Python 3.7 and is released at March 25, 2019.
More about this new released version can be found at official website.

C:\Python373\Scripts>pip install opencv-python
Collecting opencv-python
...
Installing collected packages: numpy, opencv-python
Successfully installed numpy-1.16.2 opencv-python-4.0.0.21

Let's test it:

C:\Python373>python.exe
Python 3.7.3 (v3.7.3:ef4ec6ed12, Mar 25 2019, 22:22:05) [MSC v.1916 64 bit (AMD64)]
 on win32
Type "help", "copyright", "credits" or "license" for more information.
>>> import cv2
>>> cv2.__version__
'4.0.0'

Let test a simple example that computes a dense optical flow using the Gunnar Farneback’s algorithm.

import cv2
import numpy as np
cap = cv2.VideoCapture(0)
ret, frame1 = cap.read()
prvs = cv2.cvtColor(frame1,cv2.COLOR_BGR2GRAY)
hsv = np.zeros_like(frame1)
hsv[...,1] = 255
while(1):
    ret, frame2 = cap.read()
    next = cv2.cvtColor(frame2,cv2.COLOR_BGR2GRAY)
    flow = cv2.calcOpticalFlowFarneback(prvs,next, None, 0.1, 1, 2, 3, 5, 11.2, 0)
    mag, ang = cv2.cartToPolar(flow[...,0], flow[...,1])
    hsv[...,0] = ang*180/np.pi/2
    hsv[...,2] = cv2.normalize(mag,None,0,255,cv2.NORM_MINMAX)
    bgr = cv2.cvtColor(hsv,cv2.COLOR_HSV2BGR)
    cv2.imshow('frame2',bgr)
    k = cv2.waitKey(30) & 0xff
    if k == 27:
        break
    prvs = next
cap.release()
cv2.destroyAllWindows()

About Ninja IDE for python programming.

This I.D.E. is a very good tool for python programming and development.

The version of this tool is 2.3.

I tested with my Django project on Windows OS and works great.

The development team comes with this info:

NINJA-IDE (from the recursive acronym: "Ninja-IDE Is Not Just Another IDE"), is a cross-platform integrated development environment (IDE). NINJA-IDE runs on Linux/X11, Mac OS X and Windows desktop operating systems, and allows developers to create applications for several purposes using all the tools and utilities of NINJA-IDE, making the task of writing software easier and more enjoyable.

The official webpage can be found here.

If you want to use it with Django the easy way is to install the plugin for this area.

You can see all about the development team about page.