:-)

ILexicon.py:

  - Added parseTerms() and isGlob().

  - Added get_word(), get_wid() (get_word() is old; get_wid() for symmetry).

  - Reflowed some text.

IQueryParser.py:

  - Expanded docs for parseQuery().

  - Added getIgnored() and parseQueryEx().

IPipelineElement.py:

  - Added processGlob().

Lexicon.py:

  - Added parseTerms() and isGlob().

  - Added get_wid().

  - Some pipeline elements now support processGlob().

ParseTree.py:

  - Clarified the error message for calling executeQuery() on a
    NotNode.

QueryParser.py (lots of changes):

  - Change private names __tokens etc. into protected _tokens etc.

  - Add getIgnored() and parseQueryEx() methods.

  - The atom parser now uses the lexicon's parseTerms() and isGlob()
    methods.

  - Query parts that consist only of stopwords (as determined by the
    lexicon), or of stopwords and negated terms, yield None instead of
    a parse tree node; the ignored term is added to self._ignored.
    None is ignored when combining terms for AND/OR/NOT operators, and
    when an operator has no non-None operands, the operator itself
    returns None.  When this None percolates all the way to the top,
    the parser raises a ParseError exception.

tests/testQueryParser.py:

  - Changed test expressions of the form "a AND b AND c" to "aa AND bb
    AND cc" so that the terms won't be considered stopwords.

  - The test for "and/" can only work for the base class.

tests/testZCTextIndex.py:

  - Added copyright notice.

  - Refactor testStopWords() to have two helpers, one for success, one
    for failures.

  - Change testStopWords() to require parser failure for those queries
    that have only stopwords or stopwords plus negated terms.

  - Improve compareSet() to sort the sets of keys, and use a more
    direct way of extracting the keys.  This wasn't strictly needed
    (nothing fails without this), but the old approach of copying the
    keys into a dict in a loop depends on the dict hashing to always
    return keys in the same order.

guido@.

when/if merge day comes for the installer this will make for less
confusion :-)

display the search time in milliseconds too.

for start and end of run.  Show elapsed wall-clock time in minutes.

msgs to display).  Changed the module docstring to separate the index-
generation args from the query args.

original doc text gets restored.

went wrong if they fail.

me to call it braindead <wink>).

PACK_INTERVAL.

uncomment the test cases that were failing in these contexts.

Read it and weep <wink>:  In an AND context, None is treated like the
universal set, which jibes with the convenient fiction that stop words
appear in every doc.  However, in AND NOT and OR contexts, None is
treated like the empty set, which doesn't jibe with anything except that
we want

    real_word AND NOT stop_word

and

    real_word OR stop_word

to act like

    real_word

If we treated None as if it were the universal set, these results would
be (respectively) the empty set and the universal set instead.

At a higher level, we *are* consistent with the notion that a query with
a stop word acts the same as if the clause with the stop word weren't
present.  That's what really drives this schizophrenic (context-dependent)
treatment of None.

empty.

tests that currently fail are currently commented out.

Key question:  If someone does a search on a stopword, and nothing else is
in the query, what do we want to do?  Return all docs in a random order?
Return no docs?  Raise an exception?

Second question:  What if someone does a query on

    rare_word AND NOT stop_word

?

do the same query and work as ZCTextIndex would do.

Produce a result set, pump it into NBest, and extract the 10 best.

but works with a TextIndex Lexicon.

the index knows about the doc and the wid.

_del_wordinfo and _add_wordinfo:  s/map/doc2score/g.  map is a builtin
function, and it's needlessly confusing to name a vrbl that too.

I think that the default Lexicon for TextIndex does not use a stop
word list.  For the comparison with ZCTextIndex, explicitly pass the
default stop word dict from TextIndex to the lexicon.

In unindex_doc() call _del_wordinfo() for each unique wid in the doc,
not for each wid.  Before we had WidCode and phrase searching,
_docwords stored a list of the unique wids.  The unindex code wasn't
updated when _docwords started storing all the wids, even duplicates.

Replace the try/except around __getitem__ in _add_wordinfo() with a
.get() call.

Add XXX comment about the purpose of the try/except(s) in
_del_wordinfo().  I suspect they only existed because _del_wordinfo()
was called repeatedly when a wid existed more than once.

A ZODB import is only redundant if it is not used and does not
precede an import from Persistence.

It's possible to get OOV wids here due to words the lexicon knows
about that the index has no current instances of.

in the reindexing text.

*any* words in common across the versions.  Helped Will along by adding
a pragmatic comment to his "knocking indeed" rant.  Reworked to use
the inscrutable magic of dict.setdefault.

take longer to construct now; both indexers' _get_frequencies routines
were fiddled to return the same kind of stuff again, and I had
previously fiddled the cosine indexer's _get_frequencies to do something
weirder but (probably) faster than this.

code left in it!