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from mpi4py import MPI | |
import sys | |
import argparse | |
def main(): | |
parser = argparse.ArgumentParser() | |
parser.add_argument('worker_count', type=int) | |
args = parser.parse_args() | |
mpi_info = MPI.Info.Create() |
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#! /usr/bin/env python | |
import argparse | |
import csv | |
from mpi4py import MPI | |
import logging | |
import time | |
def parseOptions(comm_world): | |
parser = argparse.ArgumentParser( |
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from bz2 import BZ2File # @UnresolvedImport | |
from datetime import datetime | |
from glob import glob | |
import itertools | |
import matplotlib | |
import matplotlib.pyplot as plt | |
MNEMOSYNE_ROOTS = ["/home/don/Dropbox/Mnemosyne_old/.mnemosyne/", | |
"/home/don/.local/share/mnemosyne/"] |
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set heading off; | |
set echo off; | |
set pages 999; | |
spool dropall.sql | |
select 'drop table ' || table_name || ';' from user_tables | |
union all | |
select 'drop sequence ' || sequence_name || ';' from user_sequences order by 1; | |
spool off | |
-- Remove header and footer from dropall.sql, then... |
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import random | |
class Markov(object): | |
def __init__(self, open_file): | |
self.cache = {} | |
self.open_file = open_file | |
self.words = self.file_to_words() | |
self.word_size = len(self.words) | |
self.database() |
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