Free statements software for linux

makepp_statements Perl package contains various statements in a makefile.

and, build_cache, "build_check", define, else, enddef, endef, endif, "export", global, ifdef, "ifeq", "ifmakeperl", ifndef, ifneq, ifnsys, "ifperl", "ifsys", "include", "_include", load_makefile, make, perl, "makesub", no_implicit_load, or, perl, "perl_begin", perl_end, "prebuild", register_scanner, "register_command_parser", "register_input_suffix", repository, "runtime", signature, "sub"

A statement is any line beginning with a word which does not have a : in it. (A colon implies that the line is a rule.) For example, these are statements:

include extra_rules.mk
load_makefile subdir

Makepp has a number of builtin statements which you may occasionally need to use.

Note that wherever you see an underscore, you may also use a dash, because makepp converts dashes to underscores in statement names.

Conditionals

Conditionals are special statements, which control what lines of the Makeppfile are actually seen. The simplest form (where ifxxx stands for any of the conditional statements documented below) is:

ifxxx ...
lines seen if the statement evaluates as true
endif

or:

ifxxx ...
lines seen if the statement evaluates as true
else
lines seen if the statement evaluates as false
endif

There is also the possibility to do complex combinations like this:

ifxxx ...
and ifxxx ...
and ifxxx ...
or ifxxx ...
and ifxxx ...
lines seen if the combined statements evaluate as true
else ifxxx ...
or ifxxx ...
and ifxxx ...
lines seen if the first combination evaluates as false
and these combined statements evaluate as true
else
lines seen if the statements above evaluate as false
endif

As is suggested by the indentation, and has higher precedence than or. In other words an or elects between two groups of and`s. There may be any number of and ifxxx`s, or ifxxx`s and else ifxxx`s.

SQL::Statement::Embed can embed a SQL engine in a DBD or module.

SQL::Statement is designed to be easy to embed in other modules and to be especially easy to embed in DBI drivers. It provides a SQL Engine and the other module needs to then provide a data source and a storage mechanism. For example, the DBD::CSV module uses SQL::Statement as an embedded SQL engine by implementing a file-based data source and by using DBI as the user interface. Similarly DBD::Amazon uses SQL::Statement as its SQL engine, provides its own extensions to the supported SQL syntax, and uses on-the-fly searches of Amazon.com as its data source.

SQL::Statement is the basis for eight existing DBDs (DBI database drivers). If you have a new data source, you too can create a DBD without having to reinvent the SQL wheel. Its fun, its easy, become a DBD author today!

SQL::Statement can be also be embedded without DBI. Well explore that first since developing a DBD uses most of the same methods and techniques.

The role of SQL::Statement subclasses

SQL::Statement provides a SQL parsing and execution engine. It does not provide a data source or storage mechanism other than in-memory tables. The DBD::File module is a subclass of SQL::Statement that provides access to file-based storage mechanisms. Its quite possible to use things other than files as data souces, in which case we wouldnt use DBD::File, instead wed replace DBD::Files methods with our own. In the examples below, well use DBD::File, replacing only a few methods.

SQL::Statement provides SQL parsing and evaluation and DBD::File provides file-based storage. The only thing missing is a data source - what we actually want to store and query. As an example suppose we are going to create a subclass called Foo that will provide as a data source a simple file similar to a passwd file - one record per line, fields separated by colons, with only three fields "username, uid, gid".

Consider what needs to happen to perform a SELECT query on our Foo data:

* recieve a SQL string
* parse the SQL string into a request structure
* open the table(s) specified in the request
* define column names and postions for the table
* read rows from the table
* convert the rows from colon-separated format into perl arrays
* match the columns and rows against the requested selection criteria
* return requested rows and columns to the user

To perform operations like INSERT and DELETE, we also need to:

* convert rows from perl arrays into colon-separated format
* write rows
* delete rows

SQL::Statement takes care of all of the SQL parsing and evaluation. DBD::File takes care of file opening, reading, writing, and deleting. So the only things Foo is really responsible for are:

* define column names and postions for the table
* convert rows from colon-separated format into perl arrays
* convert rows from perl arrays into colon-separated format

In SQL::Statement subclasses these responsibilities are assigned to two objects, a ::Statement object is responsible for opening the table, defining the column names and positions, and for creating new ::Table objects. A ::Table object is responsible for reading, converting, writing, and deleting data.

StelsDBF is a DBF JDBC type 4 driver that allows to perform SQL queries and other JDBC operations on DBF files (dBase III/ IV/ V, xBase, FoxPro, FoxBase, Clipper).
StelsDBF driver is completely platform-independent and does not require installing additional client or server software to provide access to DBF files. It can be effectively used to create, process and export DBF databases in your Java applications.
Main features:
- It supports most keywords of ANSI SQL92
- It supports inner and outer table joins
- It supports CREATE, INSERT, UPDATE and DELETE statements
- It supports transactions
- It supports aggregate, converting, string and user-defined SQL functions
- It is a platform independent

SQL::Abstract::Limit is a portable LIMIT emulation.

SYNOPSIS

use SQL::Abstract::Limit;

my $sql = SQL::Abstract::Limit->new( limit_dialect => LimitOffset );;

# or autodetect from a DBI $dbh:
my $sql = SQL::Abstract::Limit->new( limit_dialect => $dbh );

# or from a Class::DBI class:
my $sql = SQL::Abstract::Limit->new( limit_dialect => My::CDBI::App );

# or object:
my $obj = My::CDBI::App->retrieve( $id );
my $sql = SQL::Abstract::Limit->new( limit_dialect => $obj );

# generate SQL:
my ( $stmt, @bind ) = $sql->select( $table, @fields, %where, @order, $limit, $offset );

# Then, use these in your DBI statements
my $sth = $dbh->prepare( $stmt );
$sth->execute( @bind );

# Just generate the WHERE clause (only available for some syntaxes)
my ( $stmt, @bind ) = $sql->where( %where, @order, $limit, $offset );

xmms-status-plugin is a general plugin for the xmms mp3 player. It provides a docklet for the GNOME Status applet and the KDE panel.
Under GNOME 2.0 XMMS Status Plugin uses the freedesktop.org Notification Area specification. To use this you must add the Notification Area applet to your panel.
Under GNOME 1.2 XMMS Status Plugin uses the GNOME status dock. To use XMMS Status Plugin you need to add the status dock from the panel right click menu.
The KDE equivalent of the docklet panel applet is apparently on the KDE panel by default and the xmms-status-plugin has been reported to work under KDE.
Enhancements:
- src/eggtrayicon.c: Add some debugging stuff.
- src/gtkplugxembed.c: Remove loads of old g_print statements. Use gdk_window_(un)ref not gtk_object_(un)ref in several places.
- src/xmms-status-plugin.c: Be more careful with the timeout function to ensure it doesnt continue runnign when we exit, and the callback takes care of error conditions more gracefully.

Schema-compare is a script that will compares two database schema and show the differences side-by-side.
Schema-compare can also generate SQL statements that will alter the old database to match the schema of the new database.
The comparisons are correct, but the SQL statements at the bottom are not quite right, they are close to what is necessary, but probably not exactly right.
To install simply ungzip/untar the file wherever you want to put it in your web folder and then edit the include/config.inc.php file with the information needed to connect to the two databases you want to compare. Both databases need to be on the same database server and use the same username and password to connect to them.
Enhancements:
- This is the first release of schema-compare. It compares the database schema just fine, but the sql alter statements it creates could use some work.

NamespaceSim project can be used to emulate class namespaces under PHP 5.
It parses PHP code to extract namespace definition statements. The code is rewritten to emulate the namespace support in a way similar to the Java language namespace support.
This package implements new commands named package and import. The package command defines the package that a class belongs. The package name is prepended to the class names using PEAR class naming and directory conventions.
The import command indicates that the package should be imported for use in the PHP script on which the import command is used. Classes that are not found in the current script are looked in the imported namespaces.
Error mapping has been added since 0.4.0, which requires that caching is enabled. This features makes php errors in rewritten files point to the right place in the original file.
As of version 0.5.0 nsim supports namespaces in:
- class definition (w/inheritance & interfaces implementation)
- interface definition (w/inheritance)
- static class vars & functions
- class constants
- instanceof operator
- type hinting

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.