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Robbie Dee
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I used a utility program many years ago which did a similar thing. Given a flat file, it could parse each record and check each column met certain requirements.

The basic blocks were typestypes, rangesranges and valuesvalues.

TypesTypes were very basic ones such as:

  • String
  • Int
  • Float
  • Date

For some of these columns, rangesranges could be defined. For example, you could say that for a certain column, values 101-999 were valid values.

For more complex columns, you could define the valid valuesvalues. E.g. for gender you might have:

  • M
  • F
  • U

Simple but effective. We used it for all kinds of data files.

I used a utility program many years ago which did a similar thing. Given a flat file, it could parse each record and check each column met certain requirements.

The basic blocks were types, ranges and values.

Types were very basic ones such as:

  • String
  • Int
  • Float
  • Date

For some of these columns, ranges could be defined. For example, you could say that for a certain column, values 101-999 were valid values.

For more complex columns, you could define the valid values. E.g. for gender you might have:

  • M
  • F
  • U

I used a utility program many years ago which did a similar thing. Given a flat file, it could parse each record and check each column met certain requirements.

The basic blocks were types, ranges and values.

Types were very basic ones such as:

  • String
  • Int
  • Float
  • Date

For some of these columns, ranges could be defined. For example, you could say that for a certain column, values 101-999 were valid values.

For more complex columns, you could define the valid values. E.g. for gender you might have:

  • M
  • F
  • U

Simple but effective. We used it for all kinds of data files.

Source Link
Robbie Dee
  • 9.8k
  • 2
  • 26
  • 54

I used a utility program many years ago which did a similar thing. Given a flat file, it could parse each record and check each column met certain requirements.

The basic blocks were types, ranges and values.

Types were very basic ones such as:

  • String
  • Int
  • Float
  • Date

For some of these columns, ranges could be defined. For example, you could say that for a certain column, values 101-999 were valid values.

For more complex columns, you could define the valid values. E.g. for gender you might have:

  • M
  • F
  • U