FICO Xpress Optimization Examples Repository: Reading and writing records and lists

FICO Xpress Optimization Examples Repository

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Reading and writing records and lists

Description

This set of examples shows how to work with advanced data structures when accessing data in spreadsheets and databases:

reading in records (recordin*.mos)
writing out records (recordout*.mos)
reading and writing lists (listinout*.mos)

The basic model version uses an ODBC connection to spreadsheets or databases through the odbc driver, model version (2) uses ODBC through SQL statements, and model version (3) uses the software-specific driver excel to access Excel spreadsheets. Model version (1) shows how to work with Mosel's text data file format.

Further explanation of this example: Xpress Whitepaper 'Using ODBC and other database interfaces with Mosel', Section Examples - Working with lists - Working with records.

listrecord.zip

[download all files]

Source Files

By clicking on a file name, a preview is opened at the bottom of this page.

recordin.mos	[download]
recordin1.mos	[download]
recordin2.mos	[download]
recordin3.mos	[download]
recordin4.mos	[download]
recordin5.mos	[download]
recordin6.mos	[download]
recordout.mos	[download]
recordout1.mos	[download]
recordout2.mos	[download]
recordout3.mos	[download]
recordout4.mos	[download]
recordout5.mos	[download]
recordout6.mos	[download]
listinout.mos	[download]
listinout1.mos	[download]
listinout2.mos	[download]
listinout3.mos	[download]
listinout4.mos	[download]
listinout5.mos	[download]
listinout6.mos	[download]

Data Files

recorddata.dat	[download]
recorddata.csv	[download]
recorddata2.csv	[download]
recorddata.mdb	[download]
recorddata.xls	[download]
recorddata2.xls	[download]
recordout_templ.xls	[download]
recorddata.xlsx	[download]
recorddata2.xlsx	[download]
recorddata.sqlite	[download]
listdata.dat	[download]
listdata.csv	[download]
listdata.mdb	[download]
listdata.xls	[download]
listdata.xlsx	[download]
listdata.sqlite	[download]

recordin6.mos

(!******************************************************
   Mosel Example Problems
   ====================== 

   file recordin6.mos
   ``````````````````
   Reading records from spreadsheets.
   - Using 'initializations from' with the csv driver -
   
   (c) 2012 Fair Isaac Corporation
       author: S. Heipcke, Dec. 2012, rev. Feb. 2019
*******************************************************!)

model "Record input (CSV)"
 uses "mmsheet"

 parameters
  CSTR= 'mmsheet.csv:recorddata.csv'
  CSTR2= 'mmsheet.csv:skiph;recorddata2.csv'
 end-parameters
 
 public declarations
  PRODUCTS: set of string
  MACH: range
  ProdRec = public record
   Cost: real
   Duration: integer
  end-record 
  PDATA,PDATA2,PDATA3,PDATA4: dynamic array(PRODUCTS,MACH) of ProdRec

  R = 1..9
  AllDataRec = public record
   Product: string
   Mach: integer
   Cost: real
   Duration: integer
  end-record 
  ALLDATA,ALLDATA2,ALLDATA3,ALLDATA4: array(R) of AllDataRec
 end-declarations

! **** Reading from a datafile that contains various data sets in the expected formats ****

! Reading complete records

 initializations from CSTR
  PDATA as "[B4:E12]"
  ALLDATA as "noindex;[B4:E12]"
 end-initializations

! Reading record fields

 initializations from CSTR
  PDATA2(Cost) as "[B4:D12]"
  ALLDATA2(Product,Mach,Duration) as "noindex;[B17:D25]"
 end-initializations

! Now let us see what we have
 writeln('PDATA is: ', PDATA)
 writeln('ALLDATA is: ', ALLDATA)
 writeln('PDATA2 is: ', PDATA2)
 writeln('ALLDATA2 is: ', ALLDATA2)


! **** Reading from a datafile that contains a single table, selecting columns from a specified range ****

 initializations from CSTR2
! Reading complete records
  PDATA3 as "[A:D]"
  ALLDATA3 as "noindex;[A:D]"

! Reading selected record fields
! With option 'skiph' the column headers can be used to select columns
  PDATA4(Cost) as "[A:D](Product,Mach,Cost)"
!  PDATA4(Cost) as "[A:D](#1,#2,#3)"    ! Alternative form of column selection in spreadsheet
  ALLDATA4(Product,Mach,Duration) as "noindex;[A:D](Product,Mach,Duration)"
 end-initializations

! Now let us see what we have
 writeln('PDATA3 is: ', PDATA3)
 writeln('ALLDATA3 is: ', ALLDATA3)
 writeln('PDATA4 is: ', PDATA4)
 writeln('ALLDATA4 is: ', ALLDATA4)

end-model