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This project is a library for any POJO class to implement a toString method. Given a class name and instance, the project will use reflection from Java API to get the getter methods for the given instance and execute it to print the methodName = methodValue in an appended string with comma separated values. This is very generic implementation so anybody can use this code to write their toString implementation. The idea is to avoid implementing toString by writing your own implementation every time. Please put your thoughts on the implementation so we can evolve as a project which will help every Java Developer.

This module provides a convenient way to convert string case. <h3>Usage</h3> In the editor panel: <ol> <li>Select the text you want to change the case of</li> <li>Right-click to open the contextual menu</li> <li>Open the <code>Convert To...</code> submenu</li> <li>Click on the converter of your choice</li> </ol> Please note that if no text is selected, the menu is disabled. <h3>Available converters</h3> <ul> <li><b>camelCase</b>: first capitalized letter of each word, except for the first letter of the resulting word, no space</li> <li><b>hyphen-case</b>: lower case words separated with an hyphen</li> <li><b>lower case</b>: lower case words</li> <li><b>PascalCase</b>: first capitalized letter of each word, no space</li> <li><b>Sentence case.</b>: first capitalized letter of the first word, ends with a dot (capital letters within the sentence are preserved)</li> <li><b>snake_case</b>: lower case words separated with an underline character</li> <li><b>Title Case</b>: first capitalized letter of each word, one space between words</li> <li><b>UPPER CASE</b>: upper case words</li> </ul>

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

In some data processing tasks we need to use huge maps or sets that are bigger than available JVM heap space or they are loading too slow to standard Java or Scala Maps. We use TSV format (text file with tab separated columns) for persist this kind of Maps or Sets. Some columns are used as a key and rest of columns as a value. Idea of this library is simple. We can prepare these maps once (sort by key), store it to file and then use it as memory mapped file. Searching key in sorted file has log(n) complexity. If more processes uses the same memory mapped file, it exists in memory just once (on Linux). This file can be loaded lazy by OS.

The idea and motivation of the lindbergframework is to provide resources and simple solutions to problems based on the concept 'Plug and Use'. In the current version, the framework provides easy and simple solutions to the population of beans from SQL queries, abstraction of the complexities to access to stored procedures and stored functions , population of database cursors, transaction management, dependency injection, integration with Spring, JSF and Adobe Flex. The lindberg-persistence (LINP) solution, implements a important concept: separated repository of SQL commands. Among other resources.