Skip to main content

Model View Presenter pattern

Model View Presenter (MVP) is a software design pattern that brings a lot of benefits developing web applications having GWT as frontend framework. I am going to do a brief description of this pattern. I am currently applying it on a project I am working on and I have noticed that for people coming from MVC (Model View Controller) sometimes it's hard to understand the benefits of MVP (and how to implement it): so I decided to share my experience explaining this pattern from scratch.
MVP is a derivative of the MVC pattern and it's used mainly for building user interfaces. As well as the MVC pattern, MVP decouples the model from the views and the views from the logic that controls them. This way you really have the separation of concerns for the presentation logic. The three actors of this pattern are:


  • Model: an interface defining the data to be displayed.
  • View: a passive interface that displays the data of a model and routes user commands (typically events) to the presenter to act upon the data.
  • Presenter: it retrieves data from the model and then formats it to be displayed in the views.


The MVP pattern that best fits with GWT is more similar to the Model View Presenter Controller pattern (an extension of MVP). The Presenter is split into two components, the presenter (view control logic) and the controller (abstract purpose control logic). So the View, the Presenter and the Controller are really separated and then they can vary independently. MVPC improves MVP because:


  • controllers applying different control logics can be interchanged without impacting the presenter or the view;
  • completely different views can be applied to the same controller without impacting the underlying control logic;
  • multiple related views can be coordinated by a single controller. 


The following image shows an high level architectural diagram of the MVP implementation in GWT:



In the next post we will explore more in detail this diagram and then we will see how to code everything.
 
Labels:

Comments

Post a Comment

Popular posts from this blog

Exporting InfluxDB data to a CVS file

Sometimes you would need to export a sample of the data from an InfluxDB table to a CSV file (for example to allow a data scientist to do some offline analysis using a tool like Jupyter, Zeppelin or Spark Notebook). It is possible to perform this operation through the influx command line client. This is the general syntax: sudo /usr/bin/influx -database '<database_name>' -host '<hostname>' -username '<username>'  -password '<password>' -execute 'select_statement' -format '<format>' > <file_path>/<file_name>.csv where the format could be csv , json or column . Example: sudo /usr/bin/influx -database 'telegraf' -host 'localhost' -username 'admin'  -password '123456789' -execute 'select * from mem' -format 'csv' > /home/googlielmo/influxdb-export/mem-export.csv
6 comments
Read more

jOOQ: code generation in Eclipse

jOOQ allows code generation from a database schema through ANT tasks, Maven and shell command tools. But if you're working with Eclipse it's easier to create a new Run Configuration to perform this operation. First of all you have to write the usual XML configuration file for the code generation starting from the database: <?xml version="1.0" encoding="UTF-8" standalone="yes"?> <configuration xmlns="http://www.jooq.org/xsd/jooq-codegen-2.0.4.xsd">   <jdbc>     <driver>oracle.jdbc.driver.OracleDriver</driver>     <url>jdbc:oracle:thin:@dbhost:1700:DBSID</url>     <user>DB_FTRS</user>     <password>password</password>   </jdbc>   <generator>     <name>org.jooq.util.DefaultGenerator</name>     <database>       <name>org.jooq.util.oracle.OracleDatabase</name>     ...
Post a Comment
Read more

Using Rapids cuDF in a Colab notebook

During last Spark+AI Summit Europe 2019 I had a chance to attend a talk from Miguel Martinez  who was presenting Rapids , the new Open Source framework from NVIDIA for GPU accelerated end-to-end Data Science and Analytics. Fig. 1 - Overview of the Rapids eco-system Rapids is a suite of Open Source libraries: cuDF cuML cuGraph cuXFilter I enjoied the presentation and liked the idea of this initiative, so I wanted to start playing with the Rapids libraries in Python on Colab , starting from cuDF, but the first attempt came with an issue that I eventually solved. So in this post I am going to share how I fixed it, with the hope it would be useful to someone else running into the same blocker. I am assuming here you are already familiar with Google Colab. I am using Python 3.x as Python 2 isn't supported by Rapids. Once you have created a new notebook in Colab, you need to check if the runtime for it is set to use Python 3 and uses a GPU as hardware accelerator. You...
5 comments
Read more