Before it was done in the same way than it is done in UTool, by
increasing an entry in the metadata file by X each time that X tweets
are added to that CSV. However, for a script that converts from Mongo to
CSV static collections that are not growing in size, it is just better
to just count the number of lines of each CSV file once that the
conversion process has ended.

This also supresses the risk of the metadata being corrupted due to bad
parallelization

Previous version ran out of memory for big databases, because it tried
to launch all processes at once. This version has no memory issues
anymore.

Problems with not being thread safe and process collisions prevail.

Parallelized using multiprocessing library. I'm not really sure about
the code being thread safe. I think we don't care if tweets are appended
to the files in a different order, but the metadata files being
corrupted would be problematic. In the first tests the metadata were
fine, but I think this line is probably not thread safe (two threads
could load try to update the old value at the same time, resulting in
inconsistencies):

"""
metadata_file["files"][file_path]["count"] += increase
"""

Apart from that, code is much faster than before.

Simpler, more elegant and slightly faster version using the cursors instead of building a list of tweets for each page

Repository contains just one simple script for the moment to dump the
"tweets" collection of a Mongo database to a JSON file in a
"pymongodump" directory that is created at the moment and place of
execution.
Faster than mongoexport, although the format of the resulting JSONs is
somewhat different (adapted to Python's syntax).