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After the basic elements of Tefigel have been introduced, it is
now possible to shortly describe some more advanced and useful
features and applications of Tefigel.
The main driver to the definition and implementation of Tefigel
has been its role as the back-end language within the SoProTech[tm],
fully described in
"Somusar/Software Production Technique[tm]: An Introduction
".
Thus, Tefigel -
although fully applicable as a powerful stand-alone tool - should
be viewed as a part of a larger picture, as illustrated below.
Figure 1 - Tefigel and Sisendel
This concept is also illustrated and described in
"Somusar/Software Production Technique[tm]: A Sample Project
".
Multilevel contents association is a simple
mechanism that can be used
to build reference-to-contents relationships stored into
associative variables, as the
next example shows. "Multilevel" means that nested contents
of an aggregated group of data
can be directly referenced to at any level of its nesting.
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Code Example 37 - Contents association via DASH
|
Usage of DASH to accomplish contents association. Note that
dynamically changing DASH does not impact contents association.
Multilevel association is
shown on source lines 7, 8, 16, 17, 28 and 30.
Built-in VALUE, used on lines 25, 27, 30 and 33,
repeatedly expands its parameter - usually an associative
variable - until all placeholders therein
contained have been substituted with their current value.
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Source code - File "associate"
|
1 #
2 # Set type definitions for Java
3 #
4 @ dash :
5 @ set Java:Float=double
6 @ set Java:Boolean=boolean
7 @ set Java:String:Short=String
8 @ set Java:String:Long=String
9 Type definition for "Float" in Java:: JavaFloat
10 #
11 # Set type definitions for SQL
12 #
13 @ dash /
14 @ set SQL/Float=decimal(10,2)
15 @ set SQL/Boolean=char(1)
16 @ set SQL/String/Short=varchar(20)
17 @ set SQL/String/Long=varchar(200)
18 Type definition for "StringLong" in SQL: SQLStringLong
19 #
20 # Access values by means of associative operator dash and built-in value
21 #
22 @ dash .
23 @ set Type=Boolean
24 @ set Language=Java
25 Definition of "Type" in Language: ~value(Language.Type)
26 @ set Language=SQL
27 Definition of "Type" in Language: ~value(Language.Type)
28 @ set Type=String.Long
29 Mapping of Type between Java and SQL:
30 SQL ~value(SQL.Type) maps to Java ~value(Java.Type)
31 @ set Type=Float
32 Mapping of Type between Java and SQL:
33 SQL ~value(SQL.Type) maps to Java ~value(Java.Type)
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Output of
"/opt/somusar/bin/tefigel associate"
|
1 Type definition for "Float" in Java: double
2 Type definition for "StringLong" in SQL: varchar(200)
3 Definition of "Boolean" in Java: boolean
4 Definition of "Boolean" in SQL: char(1)
5 Mapping of StringLong between Java and SQL:
6 SQL varchar(200) maps to Java String
7 Mapping of Float between Java and SQL:
8 SQL decimal(10,2) maps to Java double
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Data translation filters are a means to process input textual data
that are structured in various regular forms like lists or tables,
for instance comma-separated records, or name-value pairs.
With Tefigel filters it is rather simple to
convert data from tabular form, such as the following
file of bar-separated records to - for example - XML.
|
Input table - File "data_tab"
|
1 Name|Position|Age|Salary
2
3 John Smith|Product manager|34|120,000
4 Mark Twain|Technical writer|67|250,000
5 # This is a comment and should be ignored by tefigel filters
6 Bill Young|Java programmer|4|85,000
7 # This is a comment and should be ignored by tefigel filters
8 Tom Rich|Millionaire|49|0
|
|
It should be noted that the first line
in the input file above contains the description of the
records, thus making the file self-described. Additional
information in the file header would easily allow to associate
a complete metadata description of the table contents, specifying
for example the type of the data fields.
|
Code Example 38 - Table filters
|
Tefigel FILTERs to translate data from raw tabular form into
simple XML: the first filter "t_data"
processes lines containing separator "|", the second one "t_skip"
skips all other lines (empty and comments). Note use of
the special character instruction ARGDELIM, that sets the
parameter separator to "/" instead of
",".
|
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Source code - File "t_filter"
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1 @ argdelim /
2 @ filter t_data |
3 @ filter t_skip ^.*$
|
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Output of
"/opt/somusar/bin/tefigel t_filter data_tab"
|
1 <!-- next record >
2 <Name> John Smith </Name>
3 <Position> Product manager </Position>
4 <Age> 34 </Age>
5 <Salary> 120,000 </Salary>
6 <!-- next record >
7 <Name> Mark Twain </Name>
8 <Position> Technical writer </Position>
9 <Age> 67 </Age>
10 <Salary> 250,000 </Salary>
11 <!-- next record >
12 <Name> Bill Young </Name>
13 <Position> Java programmer </Position>
14 <Age> 4 </Age>
15 <Salary> 85,000 </Salary>
16 <!-- next record >
17 <Name> Tom Rich </Name>
18 <Position> Millionaire </Position>
19 <Age> 49 </Age>
20 <Salary> 0 </Salary>
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Code Example 39 - Table filter 1
|
This filter splits matching input record into separate fields,
and writes them out as XML fragments. Note use of GLOBSET
to store field descriptor tags recognized on first input row
into global name space variables called COL_0, COL_1, etc.
Also note use of built-in FIELD to extract n-th field
from the bar-separated record: note that separator "|" is also
a parameter to built-in FIELD.
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Source code - File "t_data"
|
1 @ interface(LINE)
2 @ eval ignore LINE~^#
3 @ if ignore=0
4 @ set VAL_0=~field(LINE/0/|)
5 @ set VAL_1=~field(LINE/1/|)
6 @ set VAL_2=~field(LINE/2/|)
7 @ set VAL_3=~field(LINE/3/|)
8 @ if COL_0=
9 @ globset COL_0=VAL_0
10 @ globset COL_1=VAL_1
11 @ globset COL_2=VAL_2
12 @ globset COL_3=VAL_3
13 @ else
14 <!-- next record >
15 <COL_0> VAL_0 </COL_0>
16 <COL_1> VAL_1 </COL_1>
17 <COL_2> VAL_2 </COL_2>
18 <COL_3> VAL_3 </COL_3>
19 @ endif
20 @ endif
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Source code - File "t_skip"
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