ProgressPal: A Python Progress Tracker for Functions, Iterables, and Logs with Distributed and Parallel Support

ProgressPal provides an easy‑to‑use environment for tracking Python functions, iterables, and log messages, preserving the familiar tqdm syntax while extending support for threads, parallel processes, and distributed runtimes. It offers a centralized online dashboard accessible from any internet‑connected device.

Key features include real‑time progress tracking, distributed monitoring, collaborative dashboards, function call statistics, iterable and generator progress, log server integration, thread support, and searchable logs.

Installation

pip install ProgressPal

Starting the log server

ProgressPal start

If the command fails, the server can be launched from Python:

from ProgressPal.webapp.webapp import start_web_server
start_web_server()

Tracking iterables and generators

from ProgressPal import ltrack
import time
for i in ltrack(np.arange(100)):
    time.sleep(0.1)

or with a generator where the total must be supplied:

from ProgressPal import ltrack
import time
for i in ltrack(range(100), total=100):
    # providing a total is required for generators
    time.sleep(0.1)

Parallel and threaded tracking

from ProgressPal import ltrack
# example function
def testfunction(id):
    for i in ltrack(range(100), taskid=f"Loop {id}"):
        time.sleep(1)

# Threading example
from threading import Thread
threads = []
for i in ltrack(range(10), total=10, taskid="Tracking progress of Threading Threads"):
    thread = Thread(target=testfunction, args=(i,))
    threads.append(thread)
    thread.start()

# Concurrent futures example
from concurrent.futures import ThreadPoolExecutor
with ThreadPoolExecutor(max_workers=5) as executor:
    for i in ltrack(range(10), total=10, taskid="Tracking progress of concurrent threads"):
        executor.submit(testfunction, i)

# Joblib example
from joblib import Parallel, delayed
Parallel(n_jobs=5)(delayed(testfunction)(i) for i in ltrack(range(10), total=10, taskid="Tracking progress of Joblib jobs"))

Function tracking

from ProgressPal import ftrack
# Decorator usage
@ftrack()
def test_function_decorator():
    time.sleep(1)
for i in range(10):
    test_function_decorator()

# Direct function usage
def test_function_inline():
    time.sleep(1)
u = ftrack(test_function_inline, taskid="Inline function tracking u")
v = ftrack(test_function_inline, taskid="Inline function tracking v")
for i in range(10):
    u()
    v()

All tracking results are visualized on the ProgressPal web dashboard, as shown in the included screenshots. For more examples, refer to the GitHub repository https://github.com/levi2234/Progresspal .