Functional Python Programming by Lott Steven;

Author:Lott, Steven;
Language: eng
Format: epub
Publisher: Packt Publishing

Finally, we chained all of the readers into a single iterator with chain(*readers). This was used to yield the sequence of rows from all of the files.

It's important to note that we can't return the chain(*readers) object. If we do, this would exit the with statement context, closing all the source files. Instead, we must yield individual rows so that the with statement context is kept active.

Partitioning an iterator with groupby()

We can use the groupby() function to partition an iterator into smaller iterators. This works by evaluating the given key() function for each item in the given iterable. If the key value matches the previous item's key, the two items are part of the same partition. If the key does not match the previous item's key, the previous partition is ended and a new partition is started.

The output from the groupby() function is a sequence of two tuples. Each tuple has the group's key value and an iterable over the items in the group. Each group's iterator can be preserved as a tuple or processed to reduce it to some summary value. Because of the way the group iterators are created, they can't be preserved.

In the Running totals with accumulate() section, earlier in the chapter, we showed how to compute quartile values for an input sequence.

Given the trip variable with the raw data and the quartile variable with the quartile assignments, we can group the data using the following commands:

group_iter= groupby(zip(quartile, trip), key=lambda q_raw: q_raw[0]) for group_key, group_iter in group_iter: print(group_key, tuple(group_iter))

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