Python pool.map方法代碼示例

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_imap_unordered_handle_iterable_exception(self):
        if self.TYPE == 'manager':
            self.skipTest('test not appropriate for {}'.format(self.TYPE))

        it = self.pool.imap_unordered(sqr,
                                      exception_throwing_generator(10, 3),
                                      1)
        expected_values = map(sqr, range(10))
        with self.assertRaises(SayWhenError):
            # imap_unordered makes it difficult to anticipate the SayWhenError
            for i in range(10):
                value = next(it)
                self.assertIn(value, expected_values)
                expected_values.remove(value)

        it = self.pool.imap_unordered(sqr,
                                      exception_throwing_generator(20, 7),
                                      2)
        expected_values = map(sqr, range(20))
        with self.assertRaises(SayWhenError):
            for i in range(20):
                value = next(it)
                self.assertIn(value, expected_values)
                expected_values.remove(value) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def main(n_workers=args.n_workers):
    if args.input_dir:
        files = [os.path.join(args.input_dir, fi) for fi in os.listdir(args.input_dir)]
    elif args.input_file_list:
        files = np.squeeze(np.asarray(pd.read_csv(args.input_file_list, header=None, sep="\n"))).tolist()
    elif args.input_file:
        files = [args.input_file]
    else:
        pass
    for file in files:
        save_dir = os.path.join(args.output_dir, os.path.splitext(os.path.basename(file))[0])
        df = pd.read_csv(file, header=None, sep=" ")
        name_url_zip = zip(np.squeeze(np.asarray(df.ix[:, 0])).tolist(), np.squeeze(np.asarray(df.ix[:, 1])).tolist())
        dn = partial(download, tarDir=save_dir)
        pool = Pool(processes=n_workers)
        try:
            pool.map(dn, name_url_zip)
        except Exception as e:
            logger.error("Error occurred during multiprocessing thread: %s @ time %s" %(str(e), time.strftime("%Y%m%d-%H%M%S"))) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def map(self, func, iterable, chunksize=None):
        """
        Equivalent of `map()` built-in, without swallowing
        `KeyboardInterrupt`.

        :param func:
            The function to apply to the items.

        :param iterable:
            An iterable of items that will have `func` applied to them.

        """
        # The key magic is that we must call r.get() with a timeout, because
        # a Condition.wait() without a timeout swallows KeyboardInterrupts.
        r = self.map_async(func, iterable, chunksize)

        while True:
            try:
                return r.get(self.wait_timeout)
            except multiprocessing.TimeoutError:
                pass
            except KeyboardInterrupt:
                self.terminate()
                self.join()
                raise 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_map_handle_iterable_exception(self):
        if self.TYPE == 'manager':
            self.skipTest('test not appropriate for {}'.format(self.TYPE))

        # SayWhenError seen at the very first of the iterable
        with self.assertRaises(SayWhenError):
            self.pool.map(sqr, exception_throwing_generator(1, -1), 1)
        # again, make sure it's reentrant
        with self.assertRaises(SayWhenError):
            self.pool.map(sqr, exception_throwing_generator(1, -1), 1)

        with self.assertRaises(SayWhenError):
            self.pool.map(sqr, exception_throwing_generator(10, 3), 1)

        class SpecialIterable:
            def __iter__(self):
                return self
            def __next__(self):
                raise SayWhenError
            def __len__(self):
                return 1
        with self.assertRaises(SayWhenError):
            self.pool.map(sqr, SpecialIterable(), 1)
        with self.assertRaises(SayWhenError):
            self.pool.map(sqr, SpecialIterable(), 1) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def scrape_pages(pages):
    for page in pages:
        make_transient(page)

    # free up the connection while doing net IO
    db.session.close()
    db.engine.dispose()

    pool = get_worker_pool()
    map_results = pool.map(scrape_with_timeout, pages, chunksize=1)
    scraped_pages = [p for p in map_results if p]
    logger.info(u'finished scraping all pages')
    pool.close()
    pool.join()

    logger.info(u'preparing update records')
    row_dicts = [x.__dict__ for x in scraped_pages]
    for row_dict in row_dicts:
        row_dict.pop('_sa_instance_state')

    logger.info(u'saving update records')
    db.session.bulk_update_mappings(PageNew, row_dicts)

    scraped_page_ids = [p.id for p in scraped_pages]
    return scraped_page_ids


# need to spawn processes from workers but can't do that if worker is daemonized 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def get_worker_pool():
    num_request_workers = int(os.getenv('GREEN_SCRAPE_PROCS_PER_WORKER', 10))
    return NDPool(processes=num_request_workers, maxtasksperchild=10)


# Pool.map hangs if a worker process dies, so wrap the scrape in a new process and watch that 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_map(self):
        pmap = self.pool.map
        self.assertEqual(pmap(sqr, range(10)), map(sqr, range(10)))
        self.assertEqual(pmap(sqr, range(100), chunksize=20),
                         map(sqr, range(100))) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_map_unplicklable(self):
        # Issue #19425 -- failure to pickle should not cause a hang
        if self.TYPE == 'threads':
            self.skipTest('test not appropriate for {}'.format(self.TYPE))
        class A(object):
            def __reduce__(self):
                raise RuntimeError('cannot pickle')
        with self.assertRaises(RuntimeError):
            self.pool.map(sqr, [A()]*10) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_imap(self):
        it = self.pool.imap(sqr, range(10))
        self.assertEqual(list(it), map(sqr, range(10)))

        it = self.pool.imap(sqr, range(10))
        for i in range(10):
            self.assertEqual(it.next(), i*i)
        self.assertRaises(StopIteration, it.next)

        it = self.pool.imap(sqr, range(1000), chunksize=100)
        for i in range(1000):
            self.assertEqual(it.next(), i*i)
        self.assertRaises(StopIteration, it.next) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_imap_unordered(self):
        it = self.pool.imap_unordered(sqr, range(100))
        self.assertEqual(sorted(it), map(sqr, range(100)))

        it = self.pool.imap_unordered(sqr, range(1000), chunksize=100)
        self.assertEqual(sorted(it), map(sqr, range(1000))) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_release_task_refs(self):
        # Issue #29861: task arguments and results should not be kept
        # alive after we are done with them.
        objs = list(CountedObject() for i in range(10))
        refs = list(weakref.ref(o) for o in objs)
        self.pool.map(identity, objs)

        del objs
        time.sleep(DELTA)  # let threaded cleanup code run
        self.assertEqual(set(wr() for wr in refs), {None})
        # With a process pool, copies of the objects are returned, check
        # they were released too.
        self.assertEqual(CountedObject.n_instances, 0) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def pool_in_process():
    pool = multiprocessing.Pool(processes=4)
    x = pool.map(_afunc, [1, 2, 3, 4, 5, 6, 7]) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_imap_unordered(self):
        it = self.pool.imap_unordered(sqr, range(1000))
        self.assertEqual(sorted(it), map(sqr, range(1000)))

        it = self.pool.imap_unordered(sqr, range(1000), chunksize=53)
        self.assertEqual(sorted(it), map(sqr, range(1000))) 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def test_empty_iterable(self):
        # See Issue 12157
        p = self.Pool(1)

        self.assertEqual(p.map(sqr, []), [])
        self.assertEqual(list(p.imap(sqr, [])), [])
        self.assertEqual(list(p.imap_unordered(sqr, [])), [])
        self.assertEqual(p.map_async(sqr, []).get(), [])

        p.close()
        p.join() 

# 需要導入模塊: from multiprocessing import pool [as 別名]
# 或者: from multiprocessing.pool import map [as 別名]
def _fetch_stock_data(self, stock_list):
        """獲取股票信息"""
        pool = multiprocessing.pool.ThreadPool(len(stock_list))
        try:
            res = pool.map(self.get_stocks_by_range, stock_list)
        finally:
            pool.close()
        return [d for d in res if d is not None]