This adds two new exprs to csv.py, useful for sequential data:
enumerate() A number incremented each result
accumulate(a) A running sum across results
To make these work required adding support for cross-row state, thus the
new state field in CsvExpr.Expr.eval.
Once you have that cross-row state, implementing enumerate/accumulate is
pretty straightforward. The only complication being that we need to hash
state by the unique Python id (`id(self)`), otherwise multiple exprs
would share state, which would be pretty weird.
Note that csv.py's pipeline is now quite complex, and stage order is
important!
input --> define --> expr --> folding --> sorting --> output
filtering eval
As a result, it's unfortunately not possible to organize enumerate/
accumulate by by fields. I poked around with the idea but decided it was
too complex (aren't I supposed be building a filesystem?). The guiding
principle behind csv.py is most problems can be solved with more process
substitution.
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This is a bit clunky since we can't use the existing fold system, but
csv.py is already a pile of hacks, so what's one more?
The reason for the clunkiness is that the original idea behind csv.py
was to treat each folded row independently and order-agnostic. Not the
greatest idea in hindsight, cross-row operations are useful!
Christopher Haster
84b2e73a30