示例#1
0
def conc_calculate(self, initial_args, user_id, corpus_name, subc_name, subchash, query, samplesize):
    """
    Perform actual concordance calculation.
    This is called automatically by the 'register()' function above.

    arguments:
    initial_args -- a dict(cachefile=..., pidfile=..., stored_pidfile=...) as obtained from register()
    user_id -- an identifier of the user who entered the query (used to specify subc. directory if needed)
    corpus_id -- a corpus identifier
    subc_name -- a sub-corpus identifier (None if not used)
    subchash -- a MD5 checksum of the sub-corpus data file
    query -- a query tuple
    samplesize -- a row number limit (if 0 then unlimited - see Manatee API)
    """
    task = concworker.ConcCalculation(task_id=self.request.id)
    subc_path = '%s/%s' % (settings.get('corpora', 'users_subcpath'), user_id)
    return task(initial_args, subc_path, corpus_name, subc_name, subchash, query, samplesize)
示例#2
0
文件: mp.py 项目: petrduda/kontext
 def run():
     with plugins.runtime.CONC_CACHE as cc:
         task = concworker.ConcCalculation(task_id=task_id, cache_factory=cc.fork())
     subc_path = '%s/%s' % (settings.get('corpora', 'users_subcpath'), user_id)
     return task(initial_args, subc_path, corpus_id, subcname, subchash, q, samplesize)
示例#3
0
 def run():
     with plugins.runtime.CONC_CACHE as cc:
         task = concworker.ConcCalculation(task_id=task_id, cache_factory=cc.fork())
     return task(initial_args, subc_path, corpus_id, subcname, subchash, q, samplesize)