Binus University Repository

Liawatimena, Suryadiputra

Warnars, Harco Leslie Hendric Spits

Trisetyarso, Agung

Abdurachman, Edi

Soewito, Benfano

WIBOWO, ANTONI

Gaol, Ford L.

Abbas, Bahtiar S.

 978-1-5386-9422-0/18/$31.00 ©2018 IEEE 
The 1st 2018 INAPR International Conference, 7 Sept 2018, Jakarta, Indonesia 218 
 
Django Web Framework Software Metrics 
Measurement Using Radon and Pylint 
Suryadiputra Liawatimena1,2 
1) Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
2) Computer Engineering Department  
Faculty of Engineering 
Bina Nusantara University 
Jakarta, Indonesia 11480 
suryadi@binus.edu/ 
s.liawatimena.id@ieee.org 
Edi Abdurahman 
Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
Bina Nusantara University 
Jakarta, Indonesia 11480 
edia@binus.edu 
 
Ford Lumban Gaol 
Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
Bina Nusantara University 
Jakarta, Indonesia 11480 
fgaol@binus.edu 
 
Harco Leslie Hendric Spits Warnars  
Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
Bina Nusantara University 
Jakarta, Indonesia 11480 
shendric@binus.edu 
Benfano Soewito  
Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
Bina Nusantara University 
Jakarta, Indonesia 11480 
bsoewito@binus.edu 
Bahtiar Saleh Abbas  
Industrial Engineering Department 
Faculty of Engineering 
Bina Nusantara University 
Jakarta, Indonesia 11480 
bahtiars@binus.edu 
Agung Trisetyarso  
Computer Science Department  
BINUS Graduate Program - Doctor of 
Computer Science 
Bina Nusantara University 
Jakarta, Indonesia 11480 
atrisetyarso@binus.edu 
Antoni Wibowo  
Computer Science Department 
BINUS Graduate Program – Master of 
Computer Science  
Bina Nusantara University  
Jakarta, Indonesia 11480 
anwibowo@binus.edu 
 
Abstract— Nowadays, sites are complex applications that 
carry out transactions, render real-time information and offer 
interaction. Creation of web applications that allow many 
designers, advanced tools, and many more options. Web 
frameworks deliver a brilliant way between creating an 
application from the ground and using a content management 
system. This article centers around an open source web 
development framework, to be specific to Django. The 
methodology that used in the study is measuring Django Web 
Frameworks code quality metrics using Radon and Pylint. 
Django option in the main directory has 2,200 lines of code, 
Cyclomatic Complexity score is 16.375 considered as average 
complexity, and 6.69/10 by the pylint score. 
Keywords—Cyclomatic Complexity, Maintainability Index, 
Software Metrics, Python Web Framework 
I.  INTRODUCTION 
Nowadays, in a fast-paced, very demanding and 
competitive era people tend to use a web application 
framework to build their web-enabled applications. Software 
frameworks used to establish web application, and website 
development, web services, and web resources are called 
Web application frameworks. A favorite type of web app 
framework is the Model-View-Controller (MVC) design 
separates the code for each application component into 
modules [1], [2]. 
Python gains its popularity since 2016 and become 
number 1. Together with Python, C, Java, and C++ remain in 
the top four in popularity; this paper focuses on Python web 
frameworks [3]. The Python web frameworks are full of 
options, such as Django framework is a compact Python 
framework intended for quick development in quickly paced 
environments that function well with relational databases [4]. 
Flask framework is a Python micro-framework with a 
moderate approach and powerful by itself. Flask perfect for 
stand-alone applications and rapid prototyping. Pyramid 
known as Pylons is a framework that gives reproducibility 
with NoSQL integration. Pyramid best for APIs, prototyping, 
and extensive web apps, like content management systems 
development [5], [6]. Tornado is an event-based, non-
blocking Python web server and web application framework 
serve high-traffic volume [7]. The Bottle is a light and simple 
microframework [8]. Django is chosen because of its 
popularity and widely used. 
In this article, we will find out software metrics for 
Django using Radon that provides cyclomatic complexity 
raw metrics that consists SLOC, comment lines, number 
blank lines, Maintainability Index and Halstead metrics, also 
use pylint [9], [10]. Pylint is a source code analyzer that finds 
for errors in programming, assists to use a coding standard 
strictly. 
II. RELATED WORK 
A. Django Web Framework 
In the fall of 2003, Django was created at the Lawrence 
Journal-World newspaper. Adrian Holovaty and Simon 
Willison started using Python to create web applications. In 
July 2005, Django was released under a BSD license for the 
public. Django is used by The National Aeronautics and 
Space Administration (NASA), Google, Public Broadcasting 
Service (PBS), Bit-Bucket, and other newspapers. Guitarist 
 978-1-5386-9422-0/18/$31.00 ©2018 IEEE 
The 1st 2018 INAPR International Conference, 7 Sept 2018, Jakarta, Indonesia 219 
 
Django Reinhardt is used as the framework name. Django is 
a framework for web development using python and created 
for the quick development of database driven sites [11]. 
Inside Django is MVC-style, a high-level, opensource bunch 
of libraries programmed in Python. Django is the most 
popular server-side web frameworks. Don’t repeat yourself is 
Django’s motto. As much as Python, it focuses inefficiency, 
giving developer to do almost all tasks with as little coding 
effort as possible. 
Furthermore, Django is also scalable, mature, and fast 
with a numerous community of developer and a robust set of 
built-in components. Django can access or create JSON or 
XML data instances and deal with out-of-the-box with 
relational database management systems such as Oracle, 
MySQL, SQLite, and PostgreSQL. At deployment, Django is 
fully backed up by the cloud platform AWS Elastic 
Beanstalk and Heroku. 
Three items make Django excel are its maturity, 
structure, and community. In contrast to Flask and Pyramid, 
Django stresses on getting started right out of the box using 
particular modules. In other words, Djangos bundled 
applications and modular components can reduce developer 
time when he/ she was trying to make a web application 
ready and functioning. Data science is a buzzword 
nowadays, and multitalented developers are needed more 
than ever before. A simple preparation in building apps with 
a framework as powerful, minimalistic, and easy-to-learn as 
Django will be an essential skill when launching their career 
as the web developer or an entrepreneur.  
B. Software Complexity 
Software complexity is defined as the tool to measure the 
difficulty level of any software. Software complexity is a 
branch of software metrics which is concentrated on direct 
measurement of software qualities, as disparate to additional 
software trials such as testified system failure and project 
innovative status. There are many software complexity trials, 
fluctuating from the simplest, e.g., lines of code, to the 
complex, e.g., the number of usage associations or variable 
definition [12]. It is the calculation of efforts required for the 
development, maintenance, and execution of software code. 
As the complexity of the code increases the time and effort 
also required increases [13], [14], [15]. 
There will be times as a software developer when a 
programmer works on projects that do not have unit tests, a 
daily build, a mess of legacy spaghetti code. His/ her goal is 
to control that legacy project, and the only way for any 
project to get back under control is to have metrics and to 
measure how the code base fares and then to keep weekly 
(even daily), a track of those metrics and monitor how they 
are varying. Lines of code (LOC) are the most simple 
indicators and warnings. A massive, complicated project will 
have hundreds of thousands of LOC and that normal if the 
project is well-managed. Any metrics are better than none. 
At the point when first beginning work on the legacy 
project developer require a baseline to recognize what sort of 
code he/ she has acquired. The baseline will enable the 
developer to know whether he/ she moves towards viable 
excellent code which encourages rapid advancement or 
whether he/ she fails towards slower improvement with 
messier code. If the project is in excellent condition, the 
baseline will be high enough, and at one point any changes 
or bug fixes will have reducing returns. In the other hand, if 
the project is in a dangerous condition, the baseline will be 
lower, and he/ she can make sure that every change he/ she 
make is giving essential benefits on finishing the project. 
C. Radon 
Radon is a Python tool which can measure various 
metrics from the source code. Radon can find out: raw 
metrics (Source lines of code or SLOC, blank lines, 
comment lines), all Halstead metrics, Cyclomatic 
Complexity such as McCabes Complexity, and the 
Maintainability Index for a Visual Studio metric [16], [17]. 
1. Raw Metrics.  
The accompanying is the definitions utilized by Radon: 
• LLOC: The variety of logical strains of code. Each 
logical line of code contains precisely one statement.  
• SLOC: The quantity of source lines of code. It does 
not relate to the LLOC. 
• LOC: The aggregate number of lines of code. It 
doesn't relate to the number of lines in the file. 
• Multi: The number of lines that represent multiline 
strings. 
• Comments: The number of comment lines. Multiline 
strings are not considered comment, to the Python, 
they are just strings. 
• Blanks: The number of clear lines or whitespace. 
The formula SLOC + Single comments + Multi + Blank 
= LOC ought to always hold. Moreover, comment stats are 
computed: 
• C % L: the proportion of the number of comment 
lines and LOC, stated as a percentage; 
• C % S: the proportion of the number of comment 
lines and SLOC, stated as a percentage; 
• C + M % L: the proportion between the number of 
comment and multiline strings lines and LOC, stated 
as a percentage. 
2. Maintainability Index.  
Maintainability Index is a software metric that evaluates how 
maintainable (simple to maintain and modify) the source 
code is. The maintainability index is measured as a factored 
formula comprising of Cyclomatic Complexity, Source Lines 
Of Code (SLOC), and Halstead volume. It is applied as a part 
of some automated software program metrics tools. 
General formulas are: 
• The original formula: 
 MI = 171-5.2lnV-0.23G-16.2lnL 
• the derivative utilized by Software Engineering 
Institute: 
 MI = 171-5.2log2V-0.23G-16.2log2L+50 sin(√2.4C) 
• the derivative utilized by Visual Studio: 
 978-1-5386-9422-0/18/$31.00 ©2018 IEEE 
The 1st 2018 INAPR International Conference, 7 Sept 2018, Jakarta, Indonesia 220 
 
 
• Radon uses another derivative, calculated from 
Visual Studio derivative and SEI: 
 
Where: 
• L is the quantity of Source Lines of Code (SLOC)  
• G is the total Cyclomatic Complexity 
• V is the Halstead Volume 
• C is the percent of comment lines. 
Table 1 shows the Maintainability Index, so software 
developer can measure and aware how their code complexity 
and its maintainability then he/ she can charge accordingly to 
the user. 
 
3. Mccabe’s Cyclomatic Complexity.  
McCabe's Cyclomatic Complexity metric is applied to 
discover an upper bound on the model for rating the number 
of defects. Complexity is equated with the range of 
selections a software makes so that overly elaborate sections 
can be recoded. McCabe's metric provides the upper bound 
on module complexity. The graph and formula below define 
Cyclomatic Complexity [18], [19]. The Abstract Syntax Tree 
(AST) tree of a Python program to compute Cyclomatic 
Complexity is analyzed by Radon. As shown in Table 2 
commands that have the effects on Cyclomatic Complexity. 
Cyclomatic complexity calculates the number of decision 
logic in a software module, based on the structure of the 
software control flow graph. It is measured using the control 
flow graph of the program: nodes of the graph match to 
separabwhole groups of statements of a program, and an 
engaged edge joins two nodes if the second statement is 
probably executed immediately after the first statement. 
Cyclomatic complexity may likewise be pragmatic to 
discrete components, functions, classes or methods within a 
package or a program. 
 
McCabe number is equivalent to the quantity of linearly 
independent paths throughout the code. This number can be 
utilized as a guide when testing conditional logic in blocks. 
Every block will be positioned from A as best complexity 
score to F as worst complexity score. Ranks correspond to 
complexity scores as shown in Table 3. 
 
 
D. Pylint 
Pylint is a Python instrument which verifies a module for 
coding standards. As indicated by the TurboGears project 
coding guidelines, PEP8 is the standard and pylint is a decent 
mechanical test to help the developer in accomplishing the 
goal. The scope of verifies run from Python errors, unused 
imports, missing docstrings, an unintended redefinition of 
built-ins, to awful naming and others. Following the analysis 
message, Pylint can show a group of reports, everyone 
concentrating on a specific part of the project, for example, 
number of messages by categories and modules 
dependencies. These highlights can be enabled via the –
reports=y parameter, or -rn [20]. 
For example, the measurements report shows summaries 
assembled from the current run.  
• the number of handled modules  
• for every module, the errors percentage, and 
warnings the total number of errors and warnings  
• classes percentage, functions and modules with 
docstrings, and comparison from the past run  
 978-1-5386-9422-0/18/$31.00 ©2018 IEEE 
The 1st 2018 INAPR International Conference, 7 Sept 2018, Jakarta, Indonesia 221 
 
• classes percentage, functions and modules with the 
correct name (as indicated by the coding standard), 
and comparison from the past run  
a rundown of external dependencies found in the code, 
and where they show up. 
III. METHOD AND RESULTS 
The first step is to call radon to measure Django’s raw 
information.  
E:\Github\django>radon raw 
django/contrib/admin/options.py 
Radon raw result screen shown in Fig. 1. 
 
Fig 1. Radon Raw Output 
The next measurement is to know Cyclomatic 
Complexity, by issuing a command  
E:\Github\django>radon cc Django/contrib/admin/options.py 
-a -nc 
Where: 
 
 
Figure 2 shows radon Cyclomatic Complexity (cc) result 
screen. 
 
Fig. 2. Radon Cyclomatic Complexity result 
The third measurement is to know Django 
Maintainability Index (MI), by issuing a command  
E:\Github\django>radon mi -m django/contrib/admin.  
 
This statement examines Python source code files and 
calculates the Maintainability Index score. Every positional 
argument is handled as a starting point from which to start 
looking for Python files (as in the cc command).  Its result is 
shown in Fig. 3. 
 
Fig. 3. Radon Maintainability Index result 
 
The fourth measurement using pylint.  
E:\>pylint django/contrib/admin/options.py –reports=y 
There are seven classes: 
class IncorrectLookupParameters 
class BaseModelAdmin(metaclass=forms.MediaDefiningClass) 
class ModelAdmin(BaseModelAdmin) 
class InlineModelAdmin(BaseModelAdmin) 
class DeleteProtectedModelForm(base model form) 
class StackedInline(InlineModelAdmin) 
class TabularInline(InlineModelAdmin) 
 
 
 978-1-5386-9422-0/18/$31.00 ©2018 IEEE 
The 1st 2018 INAPR International Conference, 7 Sept 2018, Jakarta, Indonesia 222 
 
 
 
Fig. 4. Pylint output 
 
CONCLUSION 
In conclusion, this paper has measure Django Web 
Framework code quality metrics. Django option in the main 
directory has 2,200 lines of code, Cyclomatic Complexity 
score is 16.375 considered as moderate complexity, and 
6.69/10 by the pylint score. With the same method, other 
web frameworks can be measured too.  
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English

Django Web Framework Software Metrics Measurement Using Radon and Pylint

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