class_docstr: TREC's 2007 Spam Track dataset.
  
  The data contains 75,419 chronologically ordered items, i.e. 3 months of emails delivered
  to a particular server in 2007. Spam messages represent 66.6% of the dataset.
  The goal is to predict whether an email is a spam or not.
  
  The available raw features are: sender, recipients, date, subject, body.
  
  References
  ----------
  [^1]: [TREC 2007 Spam Track Overview](https://trec.nist.gov/pubs/trec16/papers/SPAM.OVERVIEW16.pdf)
  [^2]: [Code ran to parse the dataset](https://gist.github.com/gbolmier/b6a942699aaaedec54041a32e4f34d40)
code: def _iter(self):
      return stream.iter_csv(
          self.path,
          target="y",
          delimiter=",",
          quotechar='"',
          field_size_limit=1_000_000,
      )
  
imports: from __future__ import annotations
  from river import stream
  from .None import base
label_desc: Use image node_id 2 for calling the TREC07 obj's underlying member method code with example usage: obj._iter() and returns: stream