Tuesday, June 27, 2017

XML Standards Schema Library Updates

The following new XML Standards have been added to the XML Schema Library:

Membrane Service Proxy 1.4.1

Membrane Service Proxy is an open source, reverse HTTP proxy and framework written in Java for REST and SOAP APIs, that can be used for: Service Virtualization Backend Security HTTP based Integration API Monitoring OAuth2 SSO.
http://schemas.liquid-technologies.com/MembraneSOA/1.4.1/

FpML 5.9

FpML® (Financial products Markup Language) is the industry-standard protocol for complex financial products. It is based on XML (eXtensible Markup Language), the standard meta-language for describing data shared between applications.
Confirmation : http://schemas.liquid-technologies.com/FpML/5.9/confirmation/
Legal : http://schemas.liquid-technologies.com/FpML/5.9/legal/
Pretrade : http://schemas.liquid-technologies.com/FpML/5.9/pretrade/
Record Keeping : http://schemas.liquid-technologies.com/FpML/5.9/recordkeeping/
Reporting : http://schemas.liquid-technologies.com/FpML/5.9/reporting/
Transparency : http://schemas.liquid-technologies.com/FpML/5.9/transparency/


Please contact us if you would like to suggest an XML Standard which should be added to the XML Schema Library.

Tuesday, June 20, 2017

Liquid Data Mapper - Contexts

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

We looked at Contexts in the article Aggregate Functions, but it's worth examining this transform again in a little more detail in order to better understand the concept of contexts. It is a good idea to step through the transform using F11 as you follow the description and also experiment with changing the Sum.Context input and look at the different results produced.


Liquid Data Mapper - Contexts
Liquid Data Mapper - Contexts

The output of the transform is a CSV with two columns ‘Store’ and ‘Total Assets’. When the transform runs it reads the XmlReader.Bookstore items, and creates a CsvWriter.Row from each XmlReader.Bookstore entry returned. So the CsvWriter.Row is in the context of the current XmlReader.Bookstore.

Next the mapper reads XmlReader.Bookstore.Name and creates a CsvWriter.Store item. This action is made within the context of the parent CsvWriter.Row, so the CsvWriter.Store value comes from XmlReader.Bookstore.Name using the current XmlReader.Bookstore.

Next the Sum.Result value is requested. The Sum will produce a Sum.Result for each value read from Sum.Context. The Sum.Context points to XmlReader.Bookstore, which is in context, so the Sum evaluates all the Sum.Value items within the Sum.Context. (i.e. the current XmlReader.Bookstore).

The values come from the Multipy.Result, which is calculated by evaluating Multipy.Value1 and Multipy.Value2. An implied context is created for the parent nodes XmlReader.StockItem and XmlReader.Stock so when XmlReader.price and XmlReader.quantity are read they are both taken from the same XmlReader.StockItem.

We can examine the output window for a trace describing what actions will be performed.

0001 [0000] : WriterTextFileDocument(file:02, data:03)
0002 [0000] :     Constant(..\..\Output\Agregate Functions 01.csv:String)
0003 [0000] :     WriteTextFileRow(file:01, value:04)
0004 [0000] :         ReadChildItems(source:05, nodeType:Bookstore (Node))
0005 [0000] :             XmlRootNode(xmlDocument:06, nodeType:Company (Node))
0006 [0000] :                 XmlFileReader(filename:07)
0007 [0000] :                     Constant(..\..\Data Files\CompanyData.xml:String)
0008 [0000] :             WriterTextFileColumn(file:01, type:Store (String?), value:09)
0009 [0000] :                 ReadChildItems(source:10, nodeType:Name (String))
0010 [0000] :                     ReferenceTo(04)
0011 [0000] :             WriterTextFileColumn(file:01, type:Total Assets (String?), value:12)
0012 [0000] :                 SumFunction(Ctx:13, value:14)
0013 [0013] :                     ReferenceTo(04)
0014 [0013] :                         MultiplyFunction(value 1:15, value 2:19)
0015 [0013] :                             ReadChildItems(source:16, nodeType:price (Double))
0016 [0013] :                                 ReadChildItems(source:17, nodeType:StockItem (Node))
0017 [0013] :                                     ReadChildItems(source:18, nodeType:Stock (Node))
0018 [0013] :                                         ReferenceTo(04)
0019 [0013] :                                 ReadChildItems(source:20, nodeType:quantity (Int32))
0020 [0013] :                                     ReferenceTo(16)

A breakdown of this trace is included in the help.


Tip: Execute the transform by pressing Shift-F5. Debug the transform by pressing F5 to start the debugger, then:
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Friday, June 16, 2017

Liquid Data Mapper - Sub Functions

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Custom Sub Functions are a good way to keep your transforms maintainable and easy to read by creating a library of custom components with reusable functionality.



Liquid Data Mapper - Sub Functions
Liquid Data Mapper - Sub Functions

In this example we want to tidy up our customers first name and last name, by capitalizing the first letter. The transform to do this is fairly easy to follow, it takes the first letter and makes it upper case, it takes everything after the first letter and makes it lower case and concatenates the 2 bits back together.

Although its simple there are a few parts to it and we need to use it more than once, so it ends up making our transform look quite complex.

The solution is to create a Sub Function.

Sub Function Sample - CapitalizeFirstLetter

Liquid Data Mapper - Sub Functions
Liquid Data Mapper - Sub Functions
This is a simple sub function that will capitalize the firth letter of the input string and return it as an output string.

The name and type of the sub functions inputs and outputs can be configured. You can also add more inputs and outputs as required.

It is important to name the sub function. This can be done by clicking on the canvas and setting the ‘Name’ Property in the properties window. This is the name that will then be used to find the sub function.

Sub functions can also make use of other sub functions.


Liquid Data Mapper - Sub Functions
Liquid Data Mapper - Sub Functions
We can now use the Sub Function 'CapitalizeFirstLetter' in our original transform to massively simplify the diagram but with identical functionality.


Tip: Execute the transform by pressing Shift-F5. Debug the transform by pressing F5 to start the debugger, then:
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Wednesday, June 14, 2017

Liquid Data Mapper - Dynamic Data Sources

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

It is possible to load data source documents from a URL that is calculated at runtime. These include XML documents, JSON documents, CSV files, and EDI documents.

This makes it possible to open associated files based on data in other files or to process all the files in a folder.


Liquid Data Mapper - Dynamic Data Sources
Liquid Data Mapper - Dynamic Data Sources

This simple example shows how to open two XML files 'ContactList.part1.xml'  and 'ContactList.part2.xml', and combine their contents. Although the filenames come from 'Constant' component values in this example, they could just as easily be values read from another data source.

ListFiles Component


Liquid Data Mapper - Dynamic Data Sources
Liquid Data Mapper - Dynamic Data Sources

This second example shows how to combine all the files in the folder “..\..\Data Files” that match the pattern “ContactList.part*.xml” (relative paths are resolved relative to the transform).

These settings can be edited by selecting the 'ListFiles 1' component and looking at the properties window.
Liquid Data Mapper - ListFiles Component Properties
Liquid Data Mapper - 'ListFiles' Component Properties

In both of the above examples, the first XML document 'ContactList.part1.xml' contains eight 'ContactDetails' elements and the second XML document 'ContactList.part2.xml' contains twelve 'ContactDetails' elements. When you run the transform, the resulting output contains all twenty 'ContactDetails' elements.

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>Aleshia Tomkiewicz</Name>
        <Emails>atomkiewicz@hotmail.com</Emails>
        <PhoneNumbers>01835-703597</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Evan Zigomalas</Name>
        <Emails>evan.zigomalas@gmail.com</Emails>
        <PhoneNumbers>01937-864715, 01714-737668</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>France Andrade</Name>
        <Emails>france.andrade@hotmail.com</Emails>
        <PhoneNumbers>01347-368222</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Ulysses Mcwalters</Name>
        <Emails>ulysses@hotmail.com</Emails>
        <PhoneNumbers>01912-771311, 01302-601380</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Tyisha Veness</Name>
        <Emails>tyisha.veness@hotmail.com</Emails>
        <PhoneNumbers>01547-429341, 01290-367248</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Eric Rampy</Name>
        <Emails>erampy@rampy.co.uk</Emails>
        <PhoneNumbers>01969-886290, 01545-817375</PhoneNumbers>
    </ContactDetails>
    ...etc...
</Contacts>


Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Monday, June 12, 2017

Liquid Data Mapper - Duplicating Nodes

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

By default the data mapper diagram will only allow us to connect one data source node connection point to one data target node connection point. In order to connect a second connection point you can add additional duplicate nodes by right clicking on connection point and selecting 'Duplicate'.


Liquid Data Mapper - Duplicating Nodes
Liquid Data Mapper - Duplicating Nodes
In this example, we are copying all the data from our source XML file from 'XML reader 3' to the output 'XML Writer 3', but we also need to take data from a second data source (in this case the second data set are constant values e.g. ‘Joe Bloggs’, but it could just as easily come from another data source such as XML file, Database etc.).

As you can see in the diagram, 'Xml Writer 3' has a Duplicate 'ContactDetails' node allowing us to connect a second data source.

The resulting XML would merge the data from the two data sources and look as follows:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>Aleshia Tomkiewicz</Name>
        <PhoneNumbers>01835-703597</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Evan Zigomalas</Name>
        <PhoneNumbers>01937-864715 , 01714-737668</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>France Andrade</Name>
        <PhoneNumbers>01347-368222</PhoneNumbers>
    </ContactDetails>
...etc...
    <ContactDetails>
        <Name>Joe Bloggs</Name>
        <Emails>joe@bloggs.com</Emails>
        <PhoneNumbers>0123456789</PhoneNumbers>
    </ContactDetails>
</Contacts>

Notice the last ContactDetails is constructed from our constant data source.


Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Friday, June 09, 2017

Liquid Data Mapper - Scalar Components

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Scalar Components

A Scalar component is one that takes primitive input values and return a single primitive value. However, the previous article 'Sequences', shows that the value returned from a connection point is always a sequence of values, i.e. a set of zero or more (0-n) values.

Clearly if scalar components only operate on single values but connection points always convey sequences, then we need to be able to convert between them. The problem is resolved by extracting the values from the incoming sequence and feeding them to the underlying scalar function one at a time.

Notation - For these examples, curly brackets are used to describe the contents of a sequence:
    {‘A’} is a sequence containing a single value ‘A’
    {} is an empty sequence
    {‘A’, ’B’} is sequence containing 2 values ‘A’ & ’B’

Liquid Data Mapper - Scalar Components
Liquid Data Mapper - Scalar Components
In this example, the ‘Upper 1’ component is processed as follows:

      FOREACH value1 IN inputSequenceString
             RETURN_VALUE ConvertToUpper (value1)

The sequence returned from the ‘Upper 1’ component is:
    { ConvertToUpper (‘a’), ConvertToUpper (‘b’), ConvertToUpper (‘c’) }

Which evaluates to the sequence:
    { ‘A’, ‘B’, ‘C’ }

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>A</Name>
        <Name>B</Name>
        <Name>C</Name>
    </ContactDetails>
</Contacts>


Scalar components with one input behave as you would expect, but scalar components with two or more inputs have a more noticeable effect of this transform.
Liquid Data Mapper - Scalar Components
Liquid Data Mapper - Scalar Components
In this example, the string ‘Left’ component (which takes the first n chars from the input string) has the inputs ‘String’ values and ‘Length’ values and it is evaluated as follows:

FOREACH stringValue in InputSequenceString
      FOREACH lengthValue in InputSequenceLength
             RETURN_VALUE GetStringLeft (stringValue, lengthValue)

So in this case the ‘String’ contains the sequence {‘ABCDEFGHIJ’, ‘qrstuvwxyz’}, and the ‘Length’ input contains the sequence {1, 4}, the resulting sequence is:

    { GetStringLeft (‘ABCDEFGHIJ’, 1), GetStringLeft(‘ABCDEFGHIJ’, 4), GetStringLeft(‘qrstuvwxyz’, 1), GetStringLeft(‘qrstuvwxyz’, 4)}

Which evaluates to
     {‘A’, ‘ABCD’, ‘q’, ‘qrst’}

The result is the Cartesian product of the inputs:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>A</Name>
        <Name>ABCD</Name>
        <Name>q</Name>
        <Name>qrst</Name>
    </ContactDetails>
</Contacts>


Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Thursday, June 08, 2017

Liquid Data Mapper - Sequences

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

The value returned from a connection point is always a sequence of values, i.e. a set of zero or more (0-n) values.

Even if the data source only provides a single value such as an attribute value in an XML document, this is dealt with as a sequence that contains a single value. Similarly if a source value is missing, for example an optional element in an XML document, then an empty sequence is returned.

Notation - For these examples, curly brackets are used to describe the contents of a sequence:
    {‘A’} is a sequence containing a single value ‘A’
    {} is an empty sequence
    {‘A’, ’B’} is sequence containing 2 values ‘A’ & ’B’

 
Liquid Data Mapper - Sequence
Liquid Data Mapper - Sequence
In this simple example we have a 'Constant' component value as data input. This provides the simplest possible sequence as it just returns the sequence {‘A’}. So when it is used to create the Name element in the 'XML Writer', we get a single Name element with the value ‘A’:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>A</Name>
    </ContactDetails>
</Contacts>

Liquid Data Mapper - Sequence
Liquid Data Mapper - Sequence

In this example, three 'Constant' components provide input sequences {‘A’}, {‘B’} and {‘C’} and are used as data inputs to the 'Combine' component. The 'Combine' component combines these into a single sequence {‘A’, ‘B’, ‘C’}. So now as three values are being used to create the Name element in the 'XML Writer', we get three Name elements in the XML:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>A</Name>
        <Name>B</Name>
        <Name>C</Name>
    </ContactDetails>
</Contacts>


Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)


A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Wednesday, June 07, 2017

Liquid Data Mapper - Aggregate Functions

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Aggregate Functions

You can use the Liquid Data Mapper to calculate aggregate functions such as Sum, Min, Max, Average, Count, etc.

The functions operate within a context, and all input values found within this context are included within the calculation.

Liquid Data Mapper - Aggregate Functions
Liquid Data Mapper - Aggregate Functions
In this example we are using each BookStore as a Context, so the 'Sum' aggregation function will operate on each BookStore element. The value being summed is calculated by multiplying the price by the quantity for each StockItem.

Our sample data contains three bookstores so we will get three sets of results:

Chester,1426.31
London,730.17
Leeds,423.49

Changing Context

If we now change the mapping so XmlReader.Company is connected to the Sum.Context, the 'Sum' aggregation function is now operating on all of the items in all of the Bookstores in the Company, so we only get one total value output against each Bookstore line item.
Liquid Data Mapper - Aggregate Functions
Liquid Data Mapper - Aggregate Functions
Now our sample returns a total result for every Bookstore:

Chester,2579.97
London,2579.97
Leeds,2579.97

This is probably not we want as our output, so we need to change the CSV Writer.Row context from XmlReader.Bookstore to XmlReader.Company. We will also add a Constant value to CSV Writer.Store with a value 'All Stores Total'.

Liquid Data Mapper - Aggregate Functions
Liquid Data Mapper - Aggregate Functions
Now our sample returns a total result for every Bookstore with one value:

Total for all stores,2579.97


Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)


A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Tuesday, June 06, 2017

Liquid Data Mapper - Filtering Data

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Filtering Data

Filtering data is much the same as Sorting data, except you need to provide a Boolean value that will be used to determine whether the current node will be accepted or not.

In this example, the data source is an XML file based on the same root element as the destination:
Liquid Data Mapper - Filtering Data
Liquid Data Mapper - Filtering Data

The sample shows XML data being used to create an XML document, when you run the transform you will see the resulting XML document filtered where the 'Name' field is 'Niesha Bruch':

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com)-->
<Contacts>
    <ContactDetails>
        <Name>Niesha Bruch</Name>
        <PhoneNumbers>01874-856950 , 01342-793603</PhoneNumbers>
    </ContactDetails>
</Contacts>

Tip: Execute the transform by pressing Shift-F5.Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Liquid Data Mapper - Sorting Data

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Sorting Data

This example shows how to sort the ContactDetails data elements by name.

The Set based functions have an input Node, the output of the function is determined dynamically by what is connected to this input.

You can add additional 'order by' criteria by right clicking on the Sort Key and adding another sort key above or below it.

In this example, the data source is an XML file based on the same root element as the destination:
Liquid Data Mapper - Sorting Data
Liquid Data Mapper - Sorting Data
The sample shows XML data being used to create an XML document, when you run the transform you will see the resulting XML document sorted by the 'Name' fields:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com) -->
<Contacts>
    <ContactDetails>
        <Name>Aleshia Tomkiewicz</Name>
        <PhoneNumbers>01835-703597</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Charisse Spinello</Name>
        <PhoneNumbers>01719-831436</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Charlesetta Erm</Name>
        <PhoneNumbers>01276-816806 , 01517-624517</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Corrinne</Name>
        <PhoneNumbers>01625-932209</PhoneNumbers>
    </ContactDetails>
    ... etc ...
</Contacts>


Tip: Execute the transform by pressing Shift-F5.
Debug the transform by pressing F5 to start the debugger
    F11 - Step Into
    F9  - Set break point
    F5 - Run (stops on break points)



A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Monday, June 05, 2017

Liquid Data Mapper - Debugging Transforms

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Step by Step Debugger

Running a transform is fine, but when things go wrong it’s useful to be able to step through the transform and see where and why the problem is occurring.

Stepping through transforms is also a great way to learn how the data mapper works:


Liquid Data Mapper - Debugging Transforms
Liquid Data Mapper - Debugging Transforms

Start Debugging by pressing F5 or F11 to start the debugger.

Once the debugger has started keep pressing F11 to move to the next step in the transform. A tooltip window provides a description of the current items value.

As the transforms become more complex it is useful to be able to set breakpoints. You can do this by selecting a connector or connection point and pressing F9 (pressing it a second time will remove it).

When you have a break point set pressing F5 will run until it is hit.
    F5 - Run (stops on break points)
    F9  - Set break point
    F11 - Step Into

When debugging you can explore the current state by looking at the Variables, Watch, and Call Stack windows.


A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Liquid Data Mapper - Data Manipulation

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Data Manipulation

In this this example we will show how to read data from a source file and copy it to the output target file, but we will also convert the 'Name' field values to upper case as we copy the values.

To do this we need to drag the 'Upper' component on to the canvas from the 'Component Palette' (see the View menu if it’s not visible) and connect the 'Name' field input and output nodes.

The data source will be an XML file based on the same root element as the destination:

Liquid Data Mapper - Data Manipulation
Liquid Data Mapper - Data Manipulation
The sample shows XML data being used to create an XML document, when you run the transform you will see the resulting XML document with the 'Name' fields converted to upper case:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com) -->
<Contacts>
    <ContactDetails>
        <Name>ALESHIA TOMKIEWICZ</Name>
        <PhoneNumbers>01835-703597</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>EVAN ZIGOMALAS</Name>
        <PhoneNumbers>01937-864715 , 01714-737668</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>FRANCE ANDRADE</Name>
        <PhoneNumbers>01347-368222</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>ULYSSES MCWALTERS</Name>
        <PhoneNumbers>01912-771311 , 01302-601380</PhoneNumbers>
    </ContactDetails>
     ... etc ...
</Contacts>


Tip: You can execute a transform by pressing Shift-F5.

A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Liquid Data Mapper - Copying Data

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

Copying Data

In this this example we will show how to read data from a source file and copy it to the output target file.

The data source will be an XML file based on the same root element as the destination:
Liquid Data Mapper - Copying Data
Liquid Data Mapper - Copying Data
 

Copying Data Recursively

When you are working with complex data copying every value can be a lot of work. When the source and destination types are the same you can use the 'Copy Recursively' function.

You can change a connector to 'Copy Recursively' by right clicking on it and all subsequent matching child items will be automatically connected:

Liquid Data Mapper - Copying Data Recursively
Liquid Data Mapper - Copying Data Recursively

Both samples show XML data being used to create an XML document, when you run either transform you will see the resulting XML document:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com) -->
<Contacts>
    <ContactDetails>
        <Name>Aleshia Tomkiewicz</Name>
        <PhoneNumbers>01835-703597</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Evan Zigomalas</Name>
        <PhoneNumbers>01937-864715 , 01714-737668</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>France Andrade</Name>
        <PhoneNumbers>01347-368222</PhoneNumbers>
    </ContactDetails>
    <ContactDetails>
        <Name>Ulysses Mcwalters</Name>
        <PhoneNumbers>01912-771311 , 01302-601380</PhoneNumbers>
    </ContactDetails>
    ... etc ...
</Contacts>

Tip: You can execute a transform by pressing Shift-F5.

 A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download

Liquid Data Mapper - First Transform

The Liquid Data Mapper makes building complex data transformations quick and easy, but before you start there are a few basic concepts you need to learn.

All Transforms are Target Driven, So you need a target component before anything will happen.
Data targets are shown in the ‘Component Palette’ (see the View menu if it’s not visible) and can be dragged onto the canvas to create them, upon creation a wizard to help you with the initial configuration is displayed.

The current list of data targets includes:
  • Database (SQL Server, MySQL, Oracle, etc.) Data Mapping Target
  • EDI (EDIFACT and X12) Data Mapping Target
  • JSON Data Mapping Target
  • Text files (Fixed field flat file and CSV) Data Mapping Target
  • Web Services (SOAP WSDL and RESTful WADL) Data Mapping Target
  • XML Data Mapping Target
This simple example shows an XML target based on the XML Schema 'Customers.xsd', populated with data taken from three constant values:
Liquid Data Mapper - First Transform
Liquid Data Mapper - First Transform

The sample shows some data being used to create an XML document, when you run the transform you will see the resulting XML document:

<!--Created by Liquid Data Mapper Libraries (www.liquid-technologies.com) -->
<Contacts>
    <ContactDetails>
        <Name>Joe Bloggs</Name>
        <Emails>joe@bloggs.com</Emails>
        <PhoneNumbers>0123456789</PhoneNumbers>
    </ContactDetails>
</Contacts>

Tip: You can execute a transform by pressing Shift-F5.

A free trial of the Liquid Data Mapper is available from:
https://www.liquid-technologies.com/trial-download