ICT705 Project: Clinic Locator Application with Mashups and Python

This project focuses on developing a clinic locator application using mashup software, RESTful web services, and the Python programming language. The process involves data cleaning and merging to create a consolidated dataset from XML and CSV files. The Bottle framework is utilized to fetch JSON data from the RESTful web server, which is then used by the mashup software to create location blips on a geographical map. The report details the implementation of data merging, RESTful web services, and mashups, including instructions on how to run the application and interpret the results, demonstrating how the application successfully locates clinics on a map by identifying the longitude and latitude of the area.

ICT705

EXECUTIVE SUMMARY
This project for Clinic Locations locates on the map by generating a blip which helps to relocate
the area. This document uses different models of programming paradigm and the code is
developed in Python language to achieve integration of data accomplices in a single bundle. In
this module, first clean the not required data from a bunch of data and this cleaned data will be
utilised by bottleneck framework to fetch the information in CSV format from the RESTful web
server. This report also utilizes Mashup which helps into search area by generating a blip on the
geographical map by taking JSON data from servers on request.

Table of Contents
EXECUTIVE SUMMARY....................................................................................................2
1.0Introduction....................................................................................................................4
2.0Key System Concepts...................................................................................................5
2.1 Data merging and cleaning.......................................................................................5
2.2 RESTful Web Services...........................................................................................10
2.3 Mashups.................................................................................................................13
3.0Demo Running Instructions.........................................................................................14
Step 1: run the data_merger.py file..............................................................................14
Step 2: Run the clinic_locator.py file............................................................................15
Implementation of Mashup web service.......................................................................15
4.0Conclusion...................................................................................................................18
Bibliography......................................................................................................................19
List of Figures
Figure 1: Before Data cleaning Clinics.csv........................................................................6
Figure 2: file After Data cleaning........................................................................................7
Figure 3 Email Cleaning code............................................................................................8
Figure 4 After merging the clinicservicelocations...............................................................9
Figure 5 clinicLocator.py (For restful eservices implementation).....................................11
Figure 6 Run data_merger.py file.....................................................................................14
Figure 7 web page............................................................................................................16
Figure 8 flag to represent the location for the entered postcode.....................................16
Figure 9 location details on a particular flag....................................................................17

1.0Introduction
The motivation of this document is to provide the location of Clinic through creating a blip on
the map by using software which helps to accomplish this. The Mashup software utilized for
removing data which is not required and pass to the server for merging and this process known
as data integration. This document consists of different files with data utilized for remove and
merges from RESTful web servers which provide service for fetching the data from CSV files
which is cob=verted from an XML file. This file data will merge for getting the required
information to locate the clinic on a map using python language. The bottle framework provides
JSON data fetched from RESTful web servers and this data is used by Mashup software to create
a blip on the map. The basic knowledge of this report is XML file change in CSV file and
unwanted data will clean and store at the server which will fetch by Mashup software and the
bottle framework use this data in JSON format to locate the area or location on the map by
creating blip through Mashup software.

2.0Key System Concepts
The whole report is based on Mashup software to help in providing or extending previous tasks
or activities for fetching the details form data files.
2.1 Data merging and cleaning
Data Cleansing
Each time we are preparing any information, the information that arises could be of
various organizations like Tab-delimited content (.TXT) and comma-delimited qualities
(.CSV) design. The preparing is ready to consolidate or coordinate the comparable sort
of information into one.
Cleaning of data: From this table, first, remove the unwanted data by using some approach
or algorithm which is identical or look like nit useful. It can achieve by data cleaning by analyzing
the data and exclude the characteristics and noteworthy part and remove the rest information
from this clinic.csv file.

Figure 1: Before Data cleaning Clinics.csv
After Data Clinic the output is shown below:

Figure 2: file After Data cleaning
Coding to clean the file:

Figure 3 Email Cleaning code
Data Merge
In this area, we will centre around the scrubbing part and after that consolidate
everything. This is finished by utilizing Python. So, two documents are there:
 Clinics.csv: It consist of every information about the facilities like; Suburb, state, Email
as metadata, Name, Postcode. This record contains entire information that should be
prepared keeping in mind the end goal to accomplish the coveted outcome that is combining
the information of Clinics.csv as with the information from the locations.xml.
 cliniclocations.xml: This file consists the details about the location of the clinic. Data
merging code:
Output of above code:

Figure 4 After merging the clinicservicelocations

2.2 RESTful Web Services
Restful web server recognizes the variables or data by utilizing the structure of Virtual
Hierarchical organizer and display the output in some way like customer provides.
The RESTful web server starts to keep web program which is implemented in python language
help to find the required data and execute from the command prompt
Code for the restful web services implementation is:

Figure 5 clinicLocator.py (For restful eservices implementation)
The URL to fetch the JSON data is given below1:
http://localhost:8080/ getclinics?serviced=x
Suppose user put http://localhost:8080/ getclinics?serviced=2
The output is shown below in the screenshots:
Here /getclinics = this is the capacity in python code which is called each time the
customer composes this in the URL. /serviced=2 = this is the parameter inside the
capacity which is put away the postcode entered by the client and after that gets
contrasted and the postcode segment of the clinicservicelocation.csv document. 2 is the
service id of Psychiatry and it is properties or qualities are shown in the JSON reaction.

For this web server, I made a python document named clinic_locator.py which will
conjure the RESTful web server when the client enters the connection composed
previously.
Composed web administration will keep running on any coveted web program. For
beginning the RESTful web benefit which will be begun when the python content record
named "clinic_locator.py" is keep running on Command Prompt contingent on the
necessities.

2.3 Mashups
Mashup software is defined as a cross breed application produced from at least two
sources like network application or site pages. Mashups takes use of those applications
for making the single GUI or the solitary application. So, in this task of project:
 The RESTful Web Service is created which takes contribution from the yield of the
python source code composed on the framework of handling information.
 The output from RESTful Web server is sustained as a contribution to the application of
Mashup as JSON information and further handling is finished.
 In this, the HTML document is develop using JScript and CSS and didn’t utilise any
preparation. The record made in this procedure is clinic_map.html. Therefore, the
objective of the Mashup is: Already created HTML site pages will take include from client
as postcode.
 Also, the page in HTML form extract the information from the network of RESTful web
profits made in the past advance in a part of JSON and will show the area on Map
boundary. The HTML webpage will display the location of clinic on the Google Map.

3.0Demo Running Instructions
Bottle framework and Petl module has been used to develop this application.
This project is implemented by subdividing the whole project into four subtasks: first do
Data Cleaning process, Data merging to create a new file named
clinicservicelocation.csv. Both task are completed by creating a python program named
data_merger.py. third and fourth task are RESTful Web Service implementation and
Making a Mashup.
Step 1: run the data_merger.py file
Figure 6 Run data_merger.py file

Step 2: Run the clinic_locator.py file
Then the python command prompt will show the output as shown below:
Implementation of Mashup web service
To run the Mashup web service double click on the clinic_map.html file then webpage of
the application will be opened as shown below in the screenshots:

Figure 7 web page
When user enters the post code and select the medical services from the drop down list
then the map will the location of the clinic.
Figure 8 flag to represent the location for the entered postcode

Figure 9 location details on a particular flag

4.0Conclusion
This project for finding the location of the clinic on the map by creating a blip using Mashup
software concludes that the developed application or webpage work successfully and found the
location in the geographical region.
This document uses the various software as Bottle framework, Mashup software and RESTful
web server which help to convert XML file to CSV and then generate JSON data to create a blip
on the map by creating the data from files which consist of unwanted data information. And this
cleaned data from different files merge into a single file named as clinclication.csv which provide
support to recognize the location by finding longitude and latitude of that area. Thess
parameter of location found the exact region where the clinic is located.

Bibliography
 Patel, A., Seyfi, A., Taghavi, M., Wills, C., Na, L., Latih, R. and Misra, S., 2012. A
comparative study of agile, component-based, aspect-oriented and mashup
software development methods. Tehnicki Vjesnik, 19(1), pp.175-189.
 Taneja, S. and Gupta, P.R., 2014. Python as a tool for web server application
development. JIMS8I-International Journal of Information Communication and
Computing Technology, 2(1), pp.77-83.
 Richardson, L. and Ruby, S., 2008. RESTful web services. " O'Reilly Media, Inc.".

Appendix: