Skip to main content

Localization in GWT UiBinder howto

In GWT the localization process is more complex using the UiBinder declarative layout than the Java layout and the official documentation is lacking. In this post I will shortly describe the steps to follow to localize your UiBinder views.
First of all you have to add the local properties to your GWT XML module file:


<inherits name="com.google.gwt.i18n.I18N"/>
<extend-property name="locale" values="en"/>
<extend-property name="locale" values="it"/>


In this example I am considering English and Italian as possible languages. Then you have to add the locale namespaces to any of the *.ui.xml file of your project:


<ui:UiBinder xmlns:ui="urn:ui:com.google.gwt.uibinder"
xmlns:g="urn:import:com.google.gwt.user.client.ui" 
ui:generateFormat="com.google.gwt.i18n.rebind.format.PropertiesFormat"
       ui:generateKeys="com.google.gwt.i18n.rebind.keygen.MD5KeyGenerator"
       ui:generateLocales="default">


Start to add to the XML layout the messages to be localized. Example:


<g:Label horizontalAlignment="ALIGN_CENTER" styleName="titleH2Style">
<ui:msg description="registrationTitle">Registration</ui:msg>  
</g:Label>


Now you need to set Eclipse to generate the resource bundle files. Select the project and click on the GWT Compile Project... button:



The GWT compiler wizard will appear. Click on the Advanced button and then add the following additional compiler argument:
-extra <message_folder>
Example:



Compile the project clicking on the Compile button. At the end of the compilation refresh the project and you will find a generated resource bundle file for each ui.xml layout containing messages to be localized. The generated files have the following naming convention:

<view_full_package_name><view_name><view_name>UiBinderImplGenMessages.properties

Example:

com.myproject.views.RegistrationRegistrationUiBinderImplGenMessages.properties

Inside them you will find the messages in the following format:


# Description: registrationTitle
0F98B7F230F3C91292F0DE4C99E263F2=Registration


Copy these files in the packages containing the corresponding *.ui.xml files and then remove the full package name prefix. Finally duplicate them for each language you need and add the languages suffix to the file names. In our example we will have:

RegistrationRegistrationUiBinderImplGenMessages_en.properties
RegistrationRegistrationUiBinderImplGenMessages_it.properties

Translate the messages and then compile again and start your application to check that everything was fine.
That's all.

Comments

  1. Hi! This was very helpful! This is the first resource that i find that states explicitly that we can "Copy these files in the packages containing the corresponding *.ui.xml files and then remove the full package name prefix"! This is a very important detail! Thanks!

    ReplyDelete
    Replies
    1. Hi Christian,
      I am happy this post helped you to solve this problem. I remember I was going crazy last year before I found this solution in order to keep the internazionalization after moving the application from the Java to the UI binder layout. Thanks for reading my blog.
      Merry Christmas!

      Delete
  2. Localization In Gwt Uibinder Howto >>>>> Download Now

    >>>>> Download Full

    Localization In Gwt Uibinder Howto >>>>> Download LINK

    >>>>> Download Now

    Localization In Gwt Uibinder Howto >>>>> Download Full

    >>>>> Download LINK BC

    ReplyDelete

Post a Comment

Popular posts from this blog

Streamsets Data Collector log shipping and analysis using ElasticSearch, Kibana and... the Streamsets Data Collector

One common use case scenario for the Streamsets Data Collector (SDC) is the log shipping to some system, like ElasticSearch, for real-time analysis. To build a pipeline for this particular purpose in SDC is really simple and fast and doesn't require coding at all. For this quick tutorial I will use the SDC logs as example. The log data will be shipped to Elasticsearch and then visualized through a Kibana dashboard. Basic knowledge of SDC, Elasticsearch and Kibana is required for a better understanding of this post. These are the releases I am referring to for each system involved in this tutorial: JDK 8 Streamsets Data Collector 1.4.0 ElasticSearch 2.3.3 Kibana 4.5.1 Elasticsearch and Kibana installation You should have your Elasticsearch cluster installed and configured and a Kibana instance pointing to that cluster in order to go on with this tutorial. Please refer to the official documentation for these two products in order to complete their installation (if you do

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

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