Reporting Pool

A simple wrapper around Python multiprocessing Pool that allows tracking of progress and storage of exceptions.

While starmap runs, a report is printed that shows % of jobs completed, time elapsed, estimated remaining time and a list of jobs statuses. Status can be: Q -- queued, R -- running, S -- success, F -- failed (in case track_failures is enabled).

The wrapper runs multiprocessing.pool.starmap on the func and p_args (see Examples).

Enabling track_failures allows native tracking of failed function runs. For other arguments, see help(ReportingPool).

For many people, a tqdm tracking of parallel processes would be a simpler solution. The Reporting Pool is useful when each process prints a lot of information that cannot be suppressed, so a high-frequency reporting is useful, and can raise exceptions for unpredictable reasons breaking program flow.

Suggestions and contributions are welcome.

Getting Started

This project's code is available on GitHub.

Prerequisites

Software:

• Python 3+ (tested on 3.7, 3.8, 3.11, 3.12)

Installation

Reporting pool can now be installed from pypi:

py -m pip install reporting_pool

Install from source

1. Download the repository or clone it using git: git clone https://github.com/nishbo/reporting_pool.git.
2. Open Terminal, Command Line, or the desired Anaconda environment in the project folder.
3. Run python setup.py install.

Examples

Example of a normal use:

from reporting_pool import ReportingPool

def _reporting_pool_test_func_wof(v):
    time.sleep(0.25)
    return v**2

p_args = [[v] for v in range(40)]

pool = ReportingPool(_reporting_pool_test_func_wof, p_args, processes=8,
                     report_on_change=True)
res = pool.start()

print(res)

Output:

Completed 0.00% of jobs. Time elapsed: 0.00 s, remaining: NaN s. List: QQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 20.00% of jobs. Time elapsed: 0.28 s, remaining: 1.13 s. List: SRSRSRSRSRSRSRSRQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 25.00% of jobs. Time elapsed: 0.53 s, remaining: 1.59 s. List: SSSSSRSRSRSRSRSRRQRQQQQQQQQQQQQQQQQQQQQQ.
Completed 40.00% of jobs. Time elapsed: 0.56 s, remaining: 0.84 s. List: SSSSSSSSSSSSSSSSRQRQRQRQRQRQRQRQQQQQQQQQ.
Completed 42.50% of jobs. Time elapsed: 0.78 s, remaining: 1.06 s. List: SSSSSSSSSSSSSSSSSRRQRQRQRQRQRQRQQQQQQQQQ.
Completed 60.00% of jobs. Time elapsed: 0.81 s, remaining: 0.54 s. List: SSSSSSSSSSSSSSSSSRSRSRSRSRSRSRSRQQQQQQQQ.
Completed 65.00% of jobs. Time elapsed: 1.06 s, remaining: 0.57 s. List: SSSSSSSSSSSSSSSSSSSSSRSRSRSRSRSRRQRQQQQQ.
Completed 80.00% of jobs. Time elapsed: 1.09 s, remaining: 0.27 s. List: SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSRQRQRQRQ.
Completed 82.50% of jobs. Time elapsed: 1.31 s, remaining: 0.28 s. List: SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSRRQRQRQ.
Completed 90.00% of jobs. Time elapsed: 1.34 s, remaining: 0.15 s. List: SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSRSRSRSR.
Completed 95.00% of jobs. Time elapsed: 1.59 s, remaining: 0.08 s. List: SSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSSRSR.
Reporting pool finished after 1.6205 s.
[0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521]

Example where the function can throw exceptions:

from reporting_pool import ReportingPool

# a function that throws an error
def _reporting_pool_test_func_wf(v):
    time.sleep(0.25)
    if v % 6 == 0:
        raise ValueError()
    return v**2

p_args = [[v] for v in range(40)]

pool = ReportingPool(_reporting_pool_test_func_wf, p_args,
                     report_rate=20, track_failures=True)
res = pool.start()

print(res)

Output:

[0, 1, 4, 9, 16, 25, 36, 49, 64, 81, 100, 121, 144, 169, 196, 225, 256, 289, 324, 361, 400, 441, 484, 529, 576, 625, 676, 729, 784, 841, 900, 961, 1024, 1089, 1156, 1225, 1296, 1369, 1444, 1521]
Completed 0.00% of jobs. Time elapsed: 0.00 s, remaining: NaN s. List: QQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 0.00% of jobs. Time elapsed: 0.07 s, remaining: NaN s. List: RRRRRRRRRRRRQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 0.00% of jobs. Time elapsed: 0.13 s, remaining: NaN s. List: RRRRRRRRRRRRQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 0.00% of jobs. Time elapsed: 0.19 s, remaining: NaN s. List: RRRRRRRRRRRRQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 0.00% of jobs. Time elapsed: 0.26 s, remaining: NaN s. List: RRRRRRRRRRRRQQQQQQQQQQQQQQQQQQQQQQQQQQQQ.
Completed 30.00% of jobs. Time elapsed: 0.32 s, remaining: 0.75 s. List: FSSSSSFSSSSSRRRRRRRRRRRRQQQQQQQQQQQQQQQQ.
Completed 30.00% of jobs. Time elapsed: 0.38 s, remaining: 0.89 s. List: FSSSSSFSSSSSRRRRRRRRRRRRQQQQQQQQQQQQQQQQ.
Completed 30.00% of jobs. Time elapsed: 0.44 s, remaining: 1.04 s. List: FSSSSSFSSSSSRRRRRRRRRRRRQQQQQQQQQQQQQQQQ.
Completed 30.00% of jobs. Time elapsed: 0.51 s, remaining: 1.19 s. List: FSSSSSFSSSSSRRRRRRRRRRRRQQQQQQQQQQQQQQQQ.
Completed 60.00% of jobs. Time elapsed: 0.57 s, remaining: 0.38 s. List: FSSSSSFSSSSSFSSSSSFSSSSSRRRRRRRRRRRRQQQQ.
Completed 60.00% of jobs. Time elapsed: 0.63 s, remaining: 0.42 s. List: FSSSSSFSSSSSFSSSSSFSSSSSRRRRRRRRRRRRQQQQ.
Completed 60.00% of jobs. Time elapsed: 0.70 s, remaining: 0.47 s. List: FSSSSSFSSSSSFSSSSSFSSSSSRRRRRRRRRRRRQQQQ.
Completed 60.00% of jobs. Time elapsed: 0.76 s, remaining: 0.51 s. List: FSSSSSFSSSSSFSSSSSFSSSSSRRRRRRRRRRRRQQQQ.
Completed 77.50% of jobs. Time elapsed: 0.83 s, remaining: 0.24 s. List: FSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFRRRRRRRRR.
Completed 90.00% of jobs. Time elapsed: 0.89 s, remaining: 0.10 s. List: FSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFSSSSSRRRR.
Completed 90.00% of jobs. Time elapsed: 0.95 s, remaining: 0.11 s. List: FSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFSSSSSRRRR.
Completed 90.00% of jobs. Time elapsed: 1.01 s, remaining: 0.11 s. List: FSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFSSSSSRRRR.
Completed 95.00% of jobs. Time elapsed: 1.08 s, remaining: 0.06 s. List: FSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFSSSSSFSRR.
Reporting pool finished after 1.1385 s.
Jobs 0, 6, 12, 18, 24, 30, 36 were not finished correctly.
[None, 1, 4, 9, 16, 25, None, 49, 64, 81, 100, 121, None, 169, 196, 225, 256, 289, None, 361, 400, 441, 484, 529, None, 625, 676, 729, 784, 841, None, 961, 1024, 1089, 1156, 1225, None, 1369, 1444, 1521]

Authors

• Anton Sobinov

Keywords

python, multiprocessing, pool, starmap