Free web data extractor 4.3 software for linux

Flat File Extractor can be used for reading different flat file structures and printing them in different formats. ffe is a command line tool developed in GNU/Linux environment and it is distributed under GNU General Public License 2 or later.
Main areas of use are:
- Extracting particular fields or records from a flat file
- Converting data from one format to an other, e.g. from CSV to fixed length
- Verifying a flat file structure
- Testing tool for flat file development
- Displaying flat file content in human readable form
Main features:
- Command-line tool
- Reads standard input and writes to standard output as default
- One input file can contain several types of records (lines)
- Fields in a flat file can be fixed length or separated
- Input file structure and output definitions are independent, meaning one output format can be used with several input files
- Input file structure and output format are freely configurable, they are not predefined
- Output can be formatted e.g. as: fixed length, separated, tokenized, XML, SQL,...
- ffe tries to guess the input format, user needs not to give it as a parameter
Enhancements:
- Configuration keyword const has been added

Obscure-Extractor-GTK can extract data from simple and unusual archives as used by games, e.g. Neverwinter Nights, Homeworld 2, BloodRayne.

Mostly a framework where I can easily add new modules when I want to have a look at the inner workings of games, though the Delphi version has some more advanced stuff like support for old InstallShield archives that would need to be ported.

GPS Tracker project allows someone to track a GPS enabled cell phone using Google maps. For this project I used a Motorola i355 cell phone on the Sprint/Nextel network.
You need to have a data plan so that you can make updates to your website from the cellphone. Please read the ReadMe.txt file in the download for installation instructions. I hope you enjoy the project. If you have any questions, feel free ask them in the forum.
There are two projects available. The first project is built with .NET and Microsoft SQL Server. The second project is built with PHP and MySQL. If you have any suggestions, please feel free to let me know. Both projects use java (J2ME) on the phone.
How It Works:
None of the code for this project is very difficult, but it does span a number of tiers and languages which may be unfamiliar to some. Figure 1 shows the data flow from phone to Google map.
Phone
Lets start with the code on the phone. This app is written in java using Java 2 Micro Edition (J2ME). Java is very similar to C#. As you look through the code, the only thing that might confuse a C# coder is the vector. A java vector is pretty much a C# ArrayList, a dynamic array. There are 2 classes in the app, LBSMidlet7 and Qworker. A midlet is an app that runs on cell phones. Take a look at the class definition. It extends the MIDlet class and implements a LocationListener interface. That means that we need to put all the method definitions of that interface into our class. Well get to that in a bit, right now lets look at the constructor.
We do 2 things in the constructor. We create a QWorker object and pass it "this" and the website that we will be uploading to. The getAppProperty method gets attributes out of the JAD file. Open the JAD file in your favorite text editor and there youll see the webpage that youll be sending GPS data to. Notice how were passing "this" to the GWorker object? Thats the LBSMidlet7 object. Take a quick look at the QWorker class, it extends the Thread class. Thats why we call worker.start() in the LBSMidlet7 constructor. We want to start our worker thread.
When you start a thread, what you are doing is creating an object and then running that objects run() method. Take a look at the run method. It has an endless loop and in the loop the first thing it does is call queue.wait(). Look at the definition of the queue. The queue is an abstract data type (ADT), it just like a queue at a bank, enter the queue at the back of the line and leave the queue when you get to the front of the line. Look at the definition of the queue, its our vector (dynamic array). When you call wait() on an object within a class that extends the Thread class, it puts that object to sleep. Think about that a little. When we hit that line, our QWorker object is now waiting... Whats it waiting for? Well get to that in a minute. Before we do that, take a look at the synchronized keyword. Notice that its wrapping the queue. What that does is it puts a lock on the queue and tells all other processes not to touch the queue until that little block of code is done with it.
Ok, so now weve started a worker thread and put it to sleep. Lets now go back to the LBSMidlet7 class and take a look at the startApp() method. In the lifecycle of a midlet, the constructor is called once and then the startApp() method is called next. In fact it can be called several times, like for instance when you close a flip phone and then open it again. What happens is that the app is suspended and when you flip the phone open again, startApp() is called again. In startApp(), we get our display and then we create a LocationProvider if one hasnt already been created and we create another thread... Why are we creating all these threads? Good question. When a midlet (app) is suspended, the backgroud threads that are created keep running. That allows us to get our GPS data and send it to our webserver while we do other important stuff, like make phone calls.
The LocationProvider is what gets our GPS data. First we create a criteria, were using the default, but you can set stuff like accuracy, response time etc. Next we create our Location Listener. Its pretty much just what it sounds like. Here you can set the interval for how often you want to get GPS data. Its currently set to 60 which is in seconds. When data comes in, the locationUpdated() method is called. This is another one of the required methods in the LocationListener interface. Here we create yet another thread and call getLocation(). The getLocation() method gets the GPS coordinates, creates a queryString which we will send to the web server a little later and then calls worker.addToQueue in the QWorker class.
Lets go back over to the QWorker class and see what happens in that method. It add the queryString to the queue and then calls queue.notify(). Guess what queue.notify() does? It wakes up our sleeping QWorker thread and tells it to get to work! Notice that our calls to the queue are once again wrapped in a synchronized block. Please practice safe threading... When notify() is called on a thread, what it does is go back to the run() method and execute the next line of code right after where we told the queue to wait(). So now we are just about ready to send the GPS data to the web server. We have a couple of interesting lines of code there. First we call peekInQueue() which gets the queryString out of the queue but leaves it there for now. Then it sends the queryString to the getUrl method which attempts to send the queryString to our web server. If its successful, we can remove the queryString from the queue. If not, we leave the queryString in the queue and try to send it to the webserver again later.
Why in the world do we have this complicated queue here? Im glad you asked. There may be times when you are receiving GPS data but are not actually in an area that has a cell phone connection. If we dont have a cell phone connection, we cant send our GPS data to our web server. So we stick our queryString in our queue and wait until we get back into an area with cell phone connectability. Can you hear me now?
Well, weve spent a pretty fair bit of time explaining the phone code. Its a little complicated but its important to know whats going on if you want to take the code and make modifications to it to suit your needs. Heres a good article on the Sun website to let you know about more capabilities of the Location Based Services API. Right about now, our queryString should be arriving at our website, lets catch up to it and see what happens.
Enhancements:
- Added comments to code

The Virtual Data Center (VDC) is a digital library system "in a box" for numeric data.

The VDC is a web application which provides everything necessary to maintain and disseminate collections of research studies: including facilities for the storage, archiving, cataloging, translation, and dissemination of each collection.

It includes on-line analysis, powered by the R Statistical environment. It also provides extensive support for distributed and federated collections including: location-independent naming of objects, distributed authentication and access control, federated metadata harvesting, remote repository caching, and distributed virtual

MySpace Data Mining Tools are a set of Java classes designed to mine information from MySpace profile and blog pages using a multi-threaded Web page access method.
Enhancements:
- Direct database connectivity via JDBC was implemented for data storage.
- A basic user profile class was created to handle both user data compression and database access.
- Minor bugs were fixed for some of the raw data accessing routines.

How do you build a web application without data? Suppose it has many pages, including forms and pages for display. Until theyre developed, users cant enter information. Mock data has to be provided to the application, to test the interaction between screens, business logic, and database.
It may take a good amount of effort to create a mock dataset large and complex enough to mimic real world situations. For example, it is not unusual for an application to be supported by a database schema with hundreds of tables, each with many columns and many foreign key relationships. The database may have millions of rows of data. Datatypes include integer, floating precision, datetime, and string. There are a wide range of values, and they are dependent on each other in ways that must satisfy the business requirements.
Mock data is useful at various points in development. It can be used with an HTTP test client, to simulate the responses a user makes at the front end. It can be inserted directly into the database, to test the database access layer. It can replace the database layer, and be provided directly to the business logic implementation.
It might be nice if the datasets at these different stages come from the same pool, so that their values represent the same underlying model. It would be nice if this model could be constructed once, and then the presentation of the data tailored for the stage at which its used.
Often a great deal of effort is spent reducing the worlds objects into a compact object model. Datamixer goes the other way: it takes a conceptual object model, and explodes it back into a diversity of objects. It tries to make this diversity easy to manage, through configuration and customization. It interacts with data repositories, and is able to mix and merge mock values with real ones. The aim is to make it easy to create the data, so that time can be spent on the data model.
Datamixer does not attempt to analyze a problem domain, in order to generate data that does a better job at testing the domain. It could be driven by a tool that does that kind of analysis.
Installation:
To install, simply unzip or unjar the distribution package to a directory of your choice. A distribution has these directories:
- The data directory has files with samples of commonly used data, such as names. It is intended to grow.
- The doc directory has documentation.
- The examples directory has example Java source and XML configuration scripts. Apache Ant is used to run these examples: type ant build
- The lib directory has all jars required by the application.
Enhancements:
- license changed to BSD.