Implemeting Data Structures and Algorithms in Python: Problems and solutions

Recently I have started using Python in a lot of places including writing algorithms for MI/data science,  so I thought to try to implement some common programming problems using data structures in Python. As I have mostly implemented in C/C++ and Perl.

Let’s get started with a very basic problem.

Anagram algorithm

An algorithm will take two strings and check to see if they are anagrams. An anagram is when the two strings can be written using the exact same letters, in other words, rearranging the letters of a word or phrase to produce a new word or phrase, using all the original letters exactly once

Some examples of anagram:
“dormitory” is an anagram of “dirty room”
“a perfectionist” is an anagram of “I often practice.”
“action man” is an anagram of “cannot aim”

Our anagram check algorithm with take two strings and will give a boolean TRUE/FALSE depends on anagram found or not?
I have used two approaches to solve the problem. First is to sorted function and compare two string after removing white spaces and changing to lower case. This is straightforward.


def anagram(str1,str2):
# First we'll remove white spaces and also convert string to lower case letters
str1 = str1.replace(' ','').lower()
str2 = str2.replace(' ','').lower()
# We'll show output in the form of boolean TRUE/FALSE for the sorted match hence return
return sorted(str1) == sorted(str2)

The second approach is to do things manually, this is because to learn more about making logic to check. In this approach, I have used a counting mechanism and Python dictionary to store the count letter. Though one can use inbuilt Python collections idea is to learn a bit about the hash table.

Check GitHub for the full working code.

I will keep adding more problems/solutions.

Stay tuned!

Ref:  The inspiration of implementing DS in Python is from this course on Udemy.

apache lucy search examples

Investigating search engines and this time apache Lucy 0.4.2. I am showing a basic indexer and a small search application. See below code for indexer (This will take documents one by one and then index them). Search module will take arugument as STDIN and then will show the search result.

This is pure command line utility just to show how basic indexing and searching works using apache lucy.


use strict;
use warnings;
use Lucy::Simple;

# Ensure the index directory is both available and empty.
my $index = "/ppant/LucyTest/index";
system( "rm", "-rf", $index );
system( "mkdir", "-p", $index );
# Create the helper...a new Lucy::Simple object
my $lucy = Lucy::Simple new( path = $index, language = 'en', );

# Add the first "document". (We are mainly adding meta data of the document)
my %one = ( title ="This is a title of first article" , body ="some text inside the body we need to test the implementaion of lucy", id =1 );
$lucy-add_doc( \%one );

# Add the second "document".
my %two = ( title ="This is another article" , body ="I am putting some basic content, using some words which are also in first document like implementation", id =2 );
$lucy add_doc( \%two );

# Both the documents are now indexed in path

One indexing of the documents is done we'll make a small search script.



use strict;
use warnings;

use Lucy::Search::IndexSearcher;

my $term = shift || die "Usage: $0 search-term";

my $searcher = Lucy::Search::IndexSearcher new( index ='/ppant/LucyTest/index');
# A basic search command line which will look for indexed items based on STDIN and will show that in which document query string is found and no of hits
my $hits = $searcher hits( query =$term );
while ( my $hit = $hits next ) {
print "Title: $hit {title} - ID: $hit {id}\n";
# End of search.cgi


If you want to explore more check Full Code on GitHub

RESTfull brief overview

Putting some thoughts mainly for newbies trying to understand REST. Sometimes I observed that the actual documentation on the web is too technical or abstract and scattered which a bit difficult for newbies..  I am writing down some broad points which in my view REST is and it’s equation with HTTP … these points based on my reading and experience working with REST. It doesn’t replace any of REST documentation. Advised to go through references given at the end for detaled study.
  • REST  REpresentational State Transfer is a design pattern/design concept (architecture) used in web applications for managing state information-> REST is not a tool/techology/specification/protocol. In other words, REST isn’t a tangible thing like a piece of software or even a specification, it’s a selection of ideals, of best practices distilled from the HTTP specs.
  •  If you are using HTTP you are being RESTful to some degree since HTTP is a REST protocol, but to take full advantage of the platform, APIs should use RESTful practices as much as possible.
  • We can make our application more RESTful by using the correct HTTP methods.
  • RESTful Web service is required to be stateless in it’s communication between server and client  so you should be able to request almost any format while non-REST mainly SOAP uses XML.
  • URL is the important part of REST. REST is more than GET/POST actually browsers pretty much just GET stuff. They don’t do a lot of other types of interaction with resources. This is a problem because it has led many people to assume that HTTP is just for GETing. But HTTP is actually ageneral purpose protocol for applying http verbs (HTTP verbs (GET, POST, PUT, DELETE, etc.) to nouns (object/web page which has a URL).

Recommended reading:

Paper by Roy Fielding

HTTP Specs

How I Explained REST to My Wife:

Happy reading!