Python : List of Python Tutorials

If you are looking for a single list of python tutorial, then you landed on a very good blog post.

Learn Python online – A curated list of courses on Python

Here is the link :

This will allow you to try our different python courses available online.

Python : How to covert python dictionary into json and why we need that


You want to read or write data encoded as JSON (JavaScript Object Notation).


The json module provides an easy way to encode and decode data in JSON. The two main functions are json.dumps() and json.loads(), mirroring the interface used in other serialization libraries, such as pickle. Here is how you turn a Python data structure into JSON:

import json

data = {
   'name' : 'ACME',
   'shares' : 100,
   'price' : 542.23

json_str = json.dumps(data)

Here is how you turn a JSON-encoded string back into a Python data structure:

data = json.loads(json_str)

If you are working with files instead of strings, you can alternatively usejson.dump() and json.load() to encode and decode JSON data. For example:

# Writing JSON data
with open('data.json', 'w') as f:
     json.dump(data, f)

# Reading data back
with open('data.json', 'r') as f:
     data = json.load(f)

Dictionary and json are not same, so when dealing with web application in python we need to convert the python dictonay into json and visa vera. json.dumps and json.loads are used for the same.

# json dumps takes dict as input and return the json object as string.

# json loads takes a json object / string and returns the dict.


The sample console output , while trying to get value out on dumped dict :

>> import json
>>> a = {‘foo’: 3}
>>> json.dumps(a)
‘{“foo”: 3}’
>>> obj = json.dumps(a)
>>> print obj
{“foo”: 3}

>>> isinstance(obj,str)
>>> a[‘foo’]
>>> obj[‘foo’]
Traceback (most recent call last):
File “<stdin>”, line 1, in <module>
TypeError: string indices must be integers, not str
>>> dict = json.loads(obj)
>>> dict[‘foo’]

Python : What is None in python ;-)

Python’s None is Null of of Java, php, javascript of other programing language.

The concept of a null keyword is that it gives a variable a neutral, or “null” behaviour.

Python’s null Equivalent: None

The equivalent of the null keyword in Python is None. It was designed this way for two reasons:

  • Many would argue that the word “null” is somewhat esoteric. It’s not exactly the most friendliest word to programming novices. Also, “None” refers exactly to the intended functionality – it is nothing, and has no behaviour.
  • In most object-oriented languages, the naming of objects tend to use camel-case syntax. eg. ThisIsMyObject. As you’ll see soon, Python’s None type is an object, and behaves as one.

Checking if a Variable is None

There are two ways to check if a variable is None. One way can be performed by using the is keyword. Another is using the == syntax. Both comparison methods are different, and you’ll see why later:

null_variable is None
not_null_variable is not None
null_variable is None
not_null_variable is not None

Python : How to set a global variable in a function

x = 1 # make a global module variable

def f():
      print x # try to print the global
      for j in range(100):
           if q > 3:

Any variable assigned in a function is local to that function, unless it is specifically declared global. Since a value is bound to x as the last statement of the function body, the compiler assumes that x is local. Consequently the “print x” statement attempts to print an uninitialized local variable and will trigger aUnboundLocalError (or in earlier Python versions, a NameError).

The solution is to insert an explicit global declaration at the start of the function:

def f():
      global x
      print x # try to print the global
      for j in range(100):
           if q > 3:

In this case, all references to x are interpreted as references to the x from the module namespace.

Note that the global declarations must be placed at the beginning of the function, and that it affects all uses of the variable inside the function.

Python : SQLAlchemy ORM Library for python

SQLAlchemy  is a Python Library created by Mike Bayer to provide a high-level, Pythonic (idiomatically Python) interface to relational databases such as Oracle, DB2, MySQL, PostgreSQL, and SQLite. SQLAlchemy attempts to be unobtrusive to your Python code, allowing you to map plain old Python objects (POPOs) to database tables without substantially changing your existing Python code. SQLAlchemy includes a database server-independent SQL expression language and an object-relational mapper (ORM) that lets you use SQL to persist your application objects automatically.

Doc link :

NOTE : It is similar to what hibernate framework does in java.

SQLAlchemy  provides the following functionality:

  1. It maps relational databases into objects
  2. It manages an applications database connections
  3. It can create/alter a database layout if it is allowed to

The most powerful feature of SQLAlchemy is the first point: given a table description, it maps the data in tables into classes of objects, where each instance of an object is a row in the table, and can be worked with like a class or structure in code.

Example: Given a table called “Users”, with a FirstName and LastName column. Once the columns are described in the Python code, to add a row to the users table might look like this:

joebruin = User()
joebruin.FirstName = “Joe”
joebruin.LastName = “Bruin”

What is ISO date format

As world is becoming a big family with globalization, we need the standard to followed to avoid confusion especially related to date and time. If every country or person would write dates in different format, it would be confusing to figure out exact date while doing communication across countries, hence ISO has come up with ISO date format to be followed by every one. 

International Standard ISO 8601 specifies numeric representations of date and time. This standard notation helps to avoid confusion in international communication caused by the many different national notations and increases the portability of computer user interfaces.



     YYYY = four-digit year

     MM   = two-digit month (01=January, etc.)

     DD   = two-digit day of month (01 through 31)

     hh   = two digits of hour (00 through 23) (am/pm NOT allowed)

     mm   = two digits of minute (00 through 59)

     ss   = two digits of second (00 through 59)

     s    = one or more digits representing a decimal fraction of a second

     TZD  = time zone designator (Z or +hh:mm or -hh:mm)


 1997-07-16T19:20:30.45Z (Z at end indicates time is taken with Zero correction i.e. UTC time)

 1997-07-16T19:20:30.45+01:00 (+1:00 at end indicates time is taken at time zone which is 1:00 ahead of UTC time)

Advantages of the ISO 8601 standard date notation compared to other commonly used variants:

  • easily readable and writeable by software (no ‘JAN’, ‘FEB’, … table necessary)
  • easily comparable and sortable with a trivial string comparison
  • language independent
  • can not be confused with other popular date notations
  • consistency with the common 24h time notation system, where the larger units (hours) are also written in front of the smaller ones (minutes and seconds)
  • strings containing a date followed by a time are also easily comparable and sortable (e.g. write “1995-02-04 22:45:00”)
  • the notation is short and has constant length, which makes both keyboard data entry and table layout easier
  • identical to the Chinese date notation, so the largest cultural group (>25%) on this planet is already familiar with it 🙂
  • date notations with the order “year, month, day” are in addition already widely used e.g. in Japan, Korea, Hungary, Sweden, Finland, Denmark, and a few other countries and people in the U.S. are already used to at least the “month, day” order
  • a 4-digit year representation avoids overflow problems after 2099-12-31

The Zen of Python

The Zen of Python

    Beautiful is better than ugly.
    Explicit is better than implicit.
    Simple is better than complex.
    Complex is better than complicated.
    Flat is better than nested.
    Sparse is better than dense.
    Readability counts.
    Special cases aren't special enough to break the rules.
    Although practicality beats purity.
    Errors should never pass silently.
    Unless explicitly silenced.
    In the face of ambiguity, refuse the temptation to guess.
    There should be one-- and preferably only one --obvious way to do it.
    Although that way may not be obvious at first unless you're Dutch.
    Now is better than never.
    Although never is often better than *right* now.
    If the implementation is hard to explain, it's a bad idea.
    If the implementation is easy to explain, it may be a good idea.
    Namespaces are one honking great idea -- let's do more of those!