Free mafia data extractor 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

XML Extractor is a set of tools for transforming XML-like markup into entities or well-formed XML files.

The sourcecode XML metadata extraction tools are intended to be used for extracting and transforming XML-like markup embedded in source code comments into syntactically correct external entities or well-formed XML files.

This can be used for JavaDoc-like code annotation, providing structured comments, or even embedding metadata used by the build process or configuration management tools.

INSTALLATION

For info and options about installing this tool, type:
# python setup.py --help

USAGE

To see usage info for this tool, type:
# python xlf_to_wfx_cli.py --help

ccextractor project is a fast closed captions extractor for MPEG files.
ccextractor is mostly a mildly optimized C port of McPoodles excellent but painfully slow Perl script SCC_RIP. It lets you rip the raw closed captions (read: subtitles) data from a number of sources, such as DVD or replay TV.
As an added bonus compared to the original SCC_RIP, ccextractor can extract subtitles from the HDTV transport streams that are becoming more common.
At this point ccextractor extracts the line 21 captions (which must legally be present for a number of years until the transition to digital is complete). Note that in most .ts you can find, there will be subtitle data for both analog (EIA-608) decoders and digital (EIA-708). AFAIK there are not
freely available EIA-708 rippers.
Anyway, since line 21 captions will be available for some time, we have time to build a decent 708 ripper.
Basic Usage
For details on CC, please go to McPoodles page:
http://www.geocities.com/mcpoodle43/SCC_TOOLS/DOCS/SCC_TOOLS.HTML
You will need his tools to use ccextrators output.
The basic idea is that you get the raw closed caption dump from ccextractor.
Then you need other tools (which vary depending on what you want to do) to continue processing.
To get a transcript from a .ts file in .srt (I assume this will be the most common use) do this:
ccextractor -12 input_file
-12 means "extract both subtitle tracks" (actually technical names are fields but tracks is easier to understand). 1 is almost always English. 2 is Spanish in HBO (at least in the few samples Ive seen) but could be anything. Just extract both of them and check.
Example: cctractor -12 house315.ts
ccextractor will create two files, called house315_1.bin and _2.
Then use McPoodles RAW2SCC to create a temporary SCC file (means Scenerist, which is originally the native format for some program, its not important here).
raw2scc house315_1.bin
This creates house315_1.scc
From this .scc file, you can get the final .srt by using McPoodles CCASDI:
ccasdi -s house315_1.srt
Which looks like this (just 3 random lines shown).
514
00:24:07,400 --> 00:24:09,300
Theyve got another trial
going on at Duke.
515
00:24:09,367 --> 00:24:12,567
15% extend their lives
beyond five years.
516
00:24:12,634 --> 00:24:13,701
If youre positive
for protein PHF--
Enhancements:
- This release adds support for DVR-MS files.
- It improves the CC decoder.
- There are several bugfixes, a major speed boost (20%-40%), improved timing for non-TS files, improved format autodetection, and other minor improvements.

Erwin Data Structures is a library that is meant to be the ultimate data structure library for mixed usage of C and C++.

Arbitrary key and value types are implemented by template files that dont use C++ templates, but are instantiated by a Perl script.

This way, mixed usage in C and C++ is possible. However, a C++ interface is generated to support the advantages of the C++ language. No templates, no void*.
Erwin contains a number of tools, too, all of them written in Perl. The following list shows the data structures and tools, together with some typical examples.

Sunrise Data Dictionary is a library for hashtable storage of arbitrary data objects with built-in reference counting and guaranteed order iteration for the C programming language.
Sunrise Data Dictionary library can participate in external reference counting systems or use its own built-in reference counting. It comes with a variety of hash functions and allows the use of runtime supplied hash functions via callback mechanism. The source code is well documented.
The Sunrise Data Dictionary was specifically designed for use within the Afelio and Callweaver telephony servers, the implementation focuses on performance and scalability.
Enhancements:
- This is the initial release of the full API (all header files) and a developer snapshot of the implementation.

Common Data Format is a self-describing data abstraction for the storage and manipulation of multidimensional data in a platform- and discipline-independent fashion.
It consists of a scientific data management package (known as the "CDF Library") that allows programmers and application developers to manage and manipulate scalar, vector, and multi-dimensional data arrays.
Enhancements:
- Adds new sets of APIs to allow Standard Interface to interact with zVariables and other CDF-related information.
- Adds MingW and FreeBSD ports.
- Adds support for Intel C++ and Fortran for Linux.
- Adds the ability to create legacy CDF 2.7 files.
- Fixes a bug that prevented directories from having .cdf or .skt extensions.

WWW::Yahoo::KeywordExtractor is a Perl module to get keywords from summary text via the Yahoo API.

SYNOPSIS

This module will submit content to the Yahoo keyword extractor API to return a list of relevant keywords.

use WWW::Yahoo::KeywordExtractor;
my $yke = WWW::Yahoo::KeywordExtractor->new();
my $keywords = $yke->extract(content => My wife and I love to cook together.

Carolyn surprises me with new things to love about her everyday.);

print join q{}. Keyword 1: , $keywords->[0], "n";

SUBROUTINES/METHOD

new

The new subroutine creates and returns a WWW:Yahoo::KeywordExtractor object.

extract

This method will return a list of keywords based on sample data. It will die if there is no content arg given.

Data::Generate allows you to create various types of synthetic data by parsing "regex-like" data creation rules.

This module generates data by parsing given text statements (data creation rules). These statements are flexible and powerful regex-like way to control the production of synthetic data. Think about a program that instead of selecting data which matches a regex filter expression, produces it. For example, from the rule [a-c], the generator would produce the array a,b,c. The module works as following:

Specify data creation rules.
my $generator= Data::Generate::parse(VC(24) [0-9][2-3]);
At this step first you define one kind of output datatype (for ex. VC(24)= "output is a string with max length 24") and then with the rest of the expression define what it should look like. If parsing is successful a Data Generator object is instantiated.

Get data
my $Data= $generator->get_unique_data(10);
To really get the data, users must call the get_unique_data method by indicating the desired number of output values. The generator returns the values contained in an array reference. Please remark that output format is fixed according to the data type.