Developing a RESTful API for Data Integration using Python: ICT 705

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ICT 705

Table of Contents
Introduction.................................................................................................................................................3
Component of the data...............................................................................................................................4
Data Reading:..........................................................................................................................................4
Data Cleaning:.........................................................................................................................................4
Data Merger:...........................................................................................................................................5
REST Web services:......................................................................................................................................5
Screenshots:................................................................................................................................................6
Conclusion...................................................................................................................................................8
References...................................................................................................................................................8
Figure 1: Data reading.................................................................................................................................4
Figure 2: Data cleaning................................................................................................................................5
Figure 3: Data Merger.................................................................................................................................5
Figure 4: HTTP.............................................................................................................................................6
Figure 5: Service ID HTTP.............................................................................................................................6
Figure 6: Screenshots..................................................................................................................................6
Figure 7: JSON..............................................................................................................................................7
Figure 8: Search office.................................................................................................................................7
Figure 9: Search location.............................................................................................................................7
Figure 10: Map integration..........................................................................................................................8

Introduction
Data and the system integration is the most important section in the process of reading and
developing a data source file. This task is based on the implementation of the python
development programming language and there are multiple thing that need to be remember
and should be updated. This python program is based on the web application development
process and for the web development services there are REST web services has been
successfully implemented.

Component of the data
In the implementation of the data and system integration there are multiple process that need
to be follow and each and every process are having the most important uniqueness and
functionality. In this python based web application there are some aspects are available such
as: firstly the program should be able to read the data source file and after that there will be
another process of data cleaning and this is the most important section of the data and system
integration.
Data Reading:
This is the first and the initial step of the process of data and system integration. The python
program should be able to read the data source file. In this python based program there are
several data source file are available such as office_locator.csv, office_location.csv and other. In
the implementation of the python programming each and every thing and the data need to be
read to use first.
Figure 1: Data reading
Data Cleaning:
Data cleaning is the next step and this is the most important process of the operation of the
data and system integrity. The step of data cleaning takes place because if any duplicate data
found in the data source file at that time that particular data could be remove easily and each
and every data would be unique.

Figure 2: Data cleaning
Data Merger:
This is the final step of the process of data and system integration. In this section the data
source file after updating need to be read and accessible. In this python programming the data
integration file is the most important section and successfully created and build. In the data
integration file there are each and every data source file has been successfully implemented
and completed.
Figure 3: Data Merger
REST Web services:
In the implementation of the web service the REST API has been successfully implemented. In
the implementation of the web application development the RESTFUL API’s is the most

important functionality. In this python based project the API is used and the framework which is
used in this project to create the website is bottle.
Figure 4: HTTP
Screenshots:
Figure 5: Service ID HTTP
Figure 6: Screenshots

Figure 7: JSON
Figure 8: Search office
Figure 9: Search location

Figure 10: Map integration
Conclusion
The python program has been successfully created and implemented and there are several
section that has been successfully developed. This program was based on the implementation
of the python based web application. There were some data source files was given and each
and every data source file was having the different data. The task of this program is to read the
data source file and show the output.
References
 Bohannon, P., Fan, W., Geerts, F., Jia, X. and Kementsietsidis, A., 2007, April.
Conditional functional dependencies for data cleaning. In 2007 IEEE 23rd international
conference on data engineering (pp. 746-755). IEEE.
 Van den Broeck, J., Cunningham, S.A., Eeckels, R. and Herbst, K., 2005. Data cleaning:
detecting, diagnosing, and editing data abnormalities. PLoS medicine, 2(10), p.e267.
 Chaudhuri, S., Ganjam, K., Ganti, V. and Motwani, R., 2003, June. Robust and efficient
fuzzy match for online data cleaning. In Proceedings of the 2003 ACM SIGMOD
international conference on Management of data (pp. 313-324). ACM.