|
| 1 | +import subprocess |
| 2 | +import time |
| 3 | +import os |
| 4 | +import shutil |
| 5 | +import sys |
| 6 | + |
| 7 | + |
| 8 | +def get_cell(seconds): |
| 9 | + cell = ', { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], ' \ |
| 10 | + '"source": [ "time.sleep(' + str(seconds) + ')\\n", "t1 = time.time()\\n", "log += ' \ |
| 11 | + 'str(t1 - t0) + \'\\\\n\'\\n", "t0 = t1" ] }' |
| 12 | + return cell |
| 13 | + |
| 14 | + |
| 15 | +def get_ipynb(cell_nb, sleep_per_cell, result_dir): |
| 16 | + ipynb = '{ "cells": [ { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs"' \ |
| 17 | + ': [], "source": [ "import uuid\\n", "import time\\n", "fname = str(uuid.uuid4()) + \'' \ |
| 18 | + '.log\'\\n", "log = \'\'\\n", "t0 = time.time()" ] }' |
| 19 | + for i in range(cell_nb): |
| 20 | + cell = get_cell(sleep_per_cell) |
| 21 | + ipynb += cell |
| 22 | + ipynb += ', { "cell_type": "code", "execution_count": null, "metadata": {}, "outputs": [], ' \ |
| 23 | + '"source": [ "with open(\'' + result_dir + '/\' + fname, \'w\') as f:\\n", " ' \ |
| 24 | + 'f.write(log)" ] }' |
| 25 | + ipynb += ' ], "metadata": { "kernelspec": { "display_name": "Python 3", "language": "python", ' \ |
| 26 | + '"name": "python3" }, "language_info": { "codemirror_mode": { "name": "ipython", ' \ |
| 27 | + '"version": 3 }, "file_extension": ".py", "mimetype": "text/x-python", "name": "python"' \ |
| 28 | + ', "nbconvert_exporter": "python", "pygments_lexer": "ipython3", "version": "3.8.1" } }' \ |
| 29 | + ', "nbformat": 4, "nbformat_minor": 4 }' |
| 30 | + return ipynb |
| 31 | + |
| 32 | + |
| 33 | +def test_performance(): |
| 34 | + sleep_per_cell = 0.1 # each cell sleeps for that amount of seconds |
| 35 | + cell_nb = 100 # each notebook consists of so many cells |
| 36 | + client_nb = 10 # number of clients (kernels) launched in parallel |
| 37 | + ipynb_path = 'tests/notebooks/sleep.ipynb' # generated notebook, results are stored in the directory without ".ipynb" |
| 38 | + |
| 39 | + ipynb_dname, ipynb_fname = os.path.split(ipynb_path) |
| 40 | + os.chdir(ipynb_dname) |
| 41 | + result_dir = ipynb_fname[:-6] |
| 42 | + |
| 43 | + if os.path.exists(result_dir): |
| 44 | + shutil.rmtree(result_dir) |
| 45 | + os.makedirs(result_dir) |
| 46 | + |
| 47 | + ipynb = get_ipynb(cell_nb, sleep_per_cell, result_dir) |
| 48 | + |
| 49 | + # generate notebook |
| 50 | + with open(ipynb_fname, 'w') as f: |
| 51 | + f.write(ipynb) |
| 52 | + |
| 53 | + # launch voila |
| 54 | + voila = subprocess.Popen(('voila --no-browser ' + ipynb_fname).split()) |
| 55 | + time.sleep(1) |
| 56 | + |
| 57 | + # launch clients |
| 58 | + clients = [subprocess.Popen('wget -O/dev/null -q http://localhost:8866'.split()) for i in range(client_nb)] |
| 59 | + |
| 60 | + # wait for all notebooks to execute |
| 61 | + t0 = time.time() |
| 62 | + done = False |
| 63 | + timeout = False |
| 64 | + i = 0 |
| 65 | + exec_time = cell_nb * sleep_per_cell # notebook execution time |
| 66 | + launch_time = client_nb * 0.5 # kernel takes about 0.5s to launch |
| 67 | + # min_time = launch_time + exec_time # theoretical time for all notebooks to execute |
| 68 | + timeout_time = launch_time + 2 * exec_time # timeout allows slow machines to finish |
| 69 | + while not done: |
| 70 | + time.sleep(1) |
| 71 | + done = True |
| 72 | + i += 1 |
| 73 | + # print(i, '/', min_time) |
| 74 | + for client in clients: |
| 75 | + if client.poll() is None: |
| 76 | + done = False |
| 77 | + if not done: |
| 78 | + if time.time() - t0 > timeout_time: |
| 79 | + done = True |
| 80 | + timeout = True |
| 81 | + |
| 82 | + # stop voila and all clients |
| 83 | + voila.kill() |
| 84 | + [client.kill() for client in clients] |
| 85 | + |
| 86 | + if timeout: |
| 87 | + raise TimeoutError |
| 88 | + |
| 89 | + # analyze data |
| 90 | + fnames = os.listdir(result_dir) |
| 91 | + data = [] |
| 92 | + for fname in fnames: |
| 93 | + with open(result_dir + '/' + fname) as f: |
| 94 | + data += [float(d) for d in f.read().split()] |
| 95 | + |
| 96 | + meantime_per_cell = sum(data) / len(data) |
| 97 | + exceed_pct = 50 # allowing for time budget exceedance (%) |
| 98 | + maxtime_per_cell = sleep_per_cell * (exceed_pct / 100 + 1) |
| 99 | + if meantime_per_cell > maxtime_per_cell: |
| 100 | + print('Mean time per cell', meantime_per_cell, '>', sleep_per_cell, '(with', exceed_pct, '% margin)') |
| 101 | + sys.exit(1) |
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