13. History

Latest release is 4.4.8.

13.1. Version 4

Version 4 dates from March, 2014. It switches to Python3.

Change Details:

  • Added a “replacing” option to the COBOL Schema Loader.

    with open("xyzzy.cob", "r") as cobol:
        schema= stingray.cobol.loader.COBOLSchemaLoader( cobol, replacing=("'WORD'", "BAR") )

    The idea is to permit a copybook that expects “REPLACING” to be parsed.

  • Handle multiple 01-level declarations.

    When we look at the context for cobol.loader.RecordFactory.makeRecord(), this becomes an iterator which yields each 01 level DDE.

    When the stack is popped down to empty, yield the structure and then start parsing again.

    The cobol.loader.COBOLSchemaLoader.load() method builds the schema, iterates through all the 01 objects returned by cobol.loader.RecordFactory.makeRecord(), and returns v.schema as the resulting schema.

    Any unit test that uses cobol.loader.RecordFactory.makeRecord() must change to reflect it’s revised interface as an iterator.

  • Add some COBOL demos.

  • Handle more complex VALUES clauses for more complex 88-level items.

  • Restructure cobol, cobol.loader to add a cobol.defs module.

  • Handle Occurs Depending On. Parse the syntax for ODO. Update LazyRow to tweak size and offset information for each row fetched.

  • Add Z/OS RECFM handling in the cobol.EBCDIC_File class. This will allow processing “Raw” EBCDIC files with RECFM of V and RECFM of VB – these files include BDW and RDW headers on blocks and records.

  • Fix the cobol.dump() to properly iterate through all fields.

  • Fix the cobol.defs.Usage hierarchy to properly handle data which can’t be converted. An ErrorCell is created in the (all too common) case where the COBOL data is invalid.

  • Support iWork ‘09 and iWork ‘13 Numbers Workbook files. This lead to a profound refactoring of the stingray.workbook module into a package.

  • Remove % string formatting and from __future__. Correct class references. Replace u'' Unicode string literals with simple string literals. https://sourceforge.net/p/stingrayreader/tickets/6/

  • Updated documentation. https://sourceforge.net/p/stingrayreader/tickets/7/

  • Handled precision of comp3 correctly. https://sourceforge.net/p/stingrayreader/tickets/9/

  • Added cobol.loader.Lexer_Long_Lines to parse copybooks with junk in positions 72:80 of each line. https://sourceforge.net/p/stingrayreader/tickets/11/

  • Added RECFM=N to handle variable-length files with NO BDW/RDW words. This is the default. https://sourceforge.net/p/stingrayreader/tickets/12/

  • Fixed Occurs Depending On Calculation initialization error. https://sourceforge.net/p/stingrayreader/tickets/15/

  • Tweaked performance slightly based on profile results.

  • Make embedded schema loader tolerate blank sheets by producing a warning and returning None instead of raising an StopIteration exception. Tweak the Data validation demo to handle the None-instead-of-schema feature.

  • Changed cobol.COBOL_file.row_get() to leave trailing spaces intact. This may disrupt applications that expected stripping of usage DISPLAY fields.

    This created a problem of trashing COMP items that had values of 0x40 exactly – an EBCDIC space.

  • Handle Compiler Control Statements EJECT, SKIP1, SKIP2, and SKIP3 by silently dropping them in the lexical scanner.

  • Changed RENAMES handling to be a warning instead of an exception. This allows compiling – but not fully processing – DDE’s with RENAMES clauses.

  • Handle “subrecord” processing. See stingray.test.cobol_2.Test_Copybook_13( DDE_Test ). The idea is that we can do subrow= data.subrow( self.segment_abc, row.cell(schema_header_dict['GENERIC-FIELD'])  ) to map a field, GENERIC-FIELD, to an 01-level schema, self.segment_abc. We can then pick fields out of subrow using fields defined in self.segment_abc.

  • Add cobol.loader.COBOL_schema() and cobol.loader.COBOL_schemata() functions to provide a higher-level API for building a record schema or a (less common) multiple schemata.

  • Fix a bug in cobol.RECFM_VB.bdw_iter() function.

  • Fix a bug in handling signed usage display EBCDIC numbers.

  • Fix a bug in handling complex picture clauses with 9(x)v9(y) syntax.

  • Added some unit tests to confirm some previous fixes. Cleanup testing and build to make it easier to test a single class as part of debugging.

13.2. Version 3

Version 3 dates from August of 2011. It unifies COBOL DDE processing with Workbook processing. They’re both essentially the same thing.

The idea is to provide a schema that structures access to a file.

And release a much better version of the data profiling for COBOL files.

13.3. Version 2

An almost – but not quite – unrelated development was a library to unify various kinds of workbooks.

This was started in ‘06 or so. The context was econometric data analysis. The sources were rarely formatted consistently. While spreadsheets were common, fixed-format files (clearly produced by COBOL) had to be handled gracefully.

The misdirection of following the csv design patterns for eager loading of rows created small complications that were worked around badly because lazy row loading was missing from the design.

The idea of the separation of physical format from logical layout was the obvious consequence of the endless format and layout variations for a single conceptual schema.

Also, this reinforced the uselessness of trying to create a data-mapping DSL when Python expresses the data mapping perfectly.

The data mapping triple is

target = source.conversion()

Since this is – effectively – Python code, a DSL to do this is a waste of time.

13.4. Version 1

Version 1 started in ‘02 or so. Again, the context is data warehouse processing.

COBOL-based files were being examined as part of a data profiling exercise.

The data profiling use case was very simple. In effect, it was something like the following.

summary = defaultdict( lambda: defaultdict(int) )
def process_sheet( sheet ):
    for row in schema.rows_as_dict_iter(sheet.rows()):
        for k in row:
            summary[k][row[k]] += 1
    for attribute in summary:
        print( attribute )
        for k in summary[attribute]:
            print( k, summary[attribute][k] )

This version was a rewrite of the original C into Python.

It was posted into SourceForge as https://sourceforge.net/projects/cobol-dde/.

13.5. Version 0

Version 0 started in the late 90’s. In the context of data warehouse processing, COBOL-based files were being moved from mainframe to a VAX (later a Dec Alpha).

The original processing included the following.

  1. Convert the EBCDIC files from mixed display and COMP-3 to all display.
  2. Copy the files from Z/OS to the VAX (or Alpha) via a magnetic tape transfer. This handled EBCDIC to ASCII conversion. (It was the 90’s.)
  3. Convert the resulting ASCII files from all display back to the original mixture of display and COMP-3 to resurrect the original data.
  4. Process the files for warehouse loading.

The first version of this schema-based file reader did away with the painful, not-system-utility copying steps. It reduced the processing to this.

  1. Copy the files from Z/OS to the VAX (or Alpha) via a magnetic tape transfer. Do no conversion. The resulting file was mixed display and COMP-3 in EBCDIC encoding.
  2. Use the COBOL source DDE to determine field encoding rules. Copy the source file from mixed display and COMP-3 in EBCDIC encoding to mixed display and COMP-3 in ASCII encoding.
  3. Process the files for warehouse loading.

This was written in C.