The recoll module

connect(confdir=None, extra_dbs=None, writable = False)

The connect() function connects to one or several Recoll index(es) and returns a Db object.

This call initializes the recoll module, and it should always be performed before any other call or object creation.

  • confdir may specify a configuration directory. The usual defaults apply.

  • extra_dbs is a list of additional indexes (Xapian directories).

  • writable decides if we can index new data through this connection.

The Db class

A Db object is created by a connect() call and holds a connection to a Recoll index.

Db.close()

Closes the connection. You can't do anything with the Db object after this.

Db.query(), Db.cursor()

These aliases return a blank Query object for this index.

Db.setAbstractParams(maxchars, contextwords)

Set the parameters used to build snippets (sets of keywords in context text fragments). maxchars defines the maximum total size of the abstract. contextwords defines how many terms are shown around the keyword.

Db.termMatch(match_type, expr, field='', maxlen=-1, casesens=False, diacsens=False, lang='english')

Expand an expression against the index term list. Performs the basic function from the GUI term explorer tool. match_type can be either of wildcard, regexp or stem. Returns a list of terms expanded from the input expression.

The Query class

A Query object (equivalent to a cursor in the Python DB API) is created by a Db.query() call. It is used to execute index searches.

Query.sortby(fieldname, ascending=True)

Sort results by fieldname, in ascending or descending order. Must be called before executing the search.

Query.execute(query_string, stemming=1, stemlang="english", fetchtext=False, collapseduplicates=False)

Starts a search for query_string, a Recoll search language string. If the index stores the document texts and fetchtext is True, store the document extracted text in doc.text.

Query.executesd(SearchData, fetchtext=False, collapseduplicates=False)

Starts a search for the query defined by the SearchData object. If the index stores the document texts and fetchtext is True, store the document extracted text in doc.text.

Query.fetchmany(size=query.arraysize)

Fetches the next Doc objects in the current search results, and returns them as an array of the required size, which is by default the value of the arraysize data member.

Query.fetchone()

Fetches the next Doc object from the current search results. Generates a StopIteration exception if there are no results left.

Query.close()

Closes the query. The object is unusable after the call.

Query.scroll(value, mode='relative')

Adjusts the position in the current result set. mode can be relative or absolute.

Query.getgroups()

Retrieves the expanded query terms as a list of pairs. Meaningful only after executexx In each pair, the first entry is a list of user terms (of size one for simple terms, or more for group and phrase clauses), the second a list of query terms as derived from the user terms and used in the Xapian Query.

Query.getxquery()

Return the Xapian query description as a Unicode string. Meaningful only after executexx.

Query.highlight(text, ishtml = 0, methods = object)

Will insert <span "class=rclmatch">, </span> tags around the match areas in the input text and return the modified text. ishtml can be set to indicate that the input text is HTML and that HTML special characters should not be escaped. methods if set should be an object with methods startMatch(i) and endMatch() which will be called for each match and should return a begin and end tag

Query.makedocabstract(doc, methods = object))

Create a snippets abstract for doc (a Doc object) by selecting text around the match terms. If methods is set, will also perform highlighting. See the highlight method.

Query.getsnippets(doc, maxoccs = -1, ctxwords = -1, sortbypage=False, methods = object)

Will return a list of extracts from the result document by selecting text around the match terms. Each entry in the result list is a triple: page number, term, text. By default, the most relevants snippets appear first in the list. Set sortbypage to sort by page number instead. If methods is set, the fragments will be highlighted (see the highlight method). If maxoccs is set, it defines the maximum result list length. ctxwords allows adjusting the individual snippet context size.

Query.__iter__() and Query.next()

So that things like for doc in query: will work.

Query.arraysize

Default number of records processed by fetchmany (r/w).

Query.rowcount

Number of records returned by the last execute.

Query.rownumber

Next index to be fetched from results. Normally increments after each fetchone() call, but can be set/reset before the call to effect seeking (equivalent to using scroll()). Starts at 0.

The Doc class

A Doc object contains index data for a given document. The data is extracted from the index when searching, or set by the indexer program when updating. The Doc object has many attributes to be read or set by its user. It mostly matches the Rcl::Doc C++ object. Some of the attributes are predefined, but, especially when indexing, others can be set, the name of which will be processed as field names by the indexing configuration. Inputs can be specified as Unicode or strings. Outputs are Unicode objects. All dates are specified as Unix timestamps, printed as strings. Please refer to the rcldb/rcldoc.cpp C++ file for a full description of the predefined attributes. Here follows a short list.

  • url the document URL but see also getbinurl()

  • ipath the document ipath for embedded documents.

  • fbytes, dbytes the document file and text sizes.

  • fmtime, dmtime the document file and document times.

  • xdocid the document Xapian document ID. This is useful if you want to access the document through a direct Xapian operation.

  • mtype the document MIME type.

  • Fields stored by default: author, filename, keywords, recipient

At query time, only the fields that are defined as stored either by default or in the fields configuration file will be meaningful in the Doc object. The document processed text may be present or not, depending if the index stores the text at all, and if it does, on the fetchtext query execute option. See also the rclextract module for accessing document contents.

get(key), [] operator

Retrieve the named document attribute. You can also use getattr(doc, key) or doc.key.

doc.key = value

Set the the named document attribute. You can also use setattr(doc, key, value).

getbinurl()

Retrieve the URL in byte array format (no transcoding), for use as parameter to a system call.

setbinurl(url)

Set the URL in byte array format (no transcoding).

items()

Return a dictionary of doc object keys/values

keys()

list of doc object keys (attribute names).

The SearchData class

A SearchData object allows building a query by combining clauses, for execution by Query.executesd(). It can be used in replacement of the query language approach. The interface is going to change a little, so no detailed doc for now...

addclause(type='and'|'or'|'excl'|'phrase'|'near'|'sub', qstring=string, slack=0, field='', stemming=1, subSearch=SearchData)

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