Python Progress Bar

Exploring tqdm and its 'cousins'

Need something more than the basics? Let's check out some powerful progress bar tools and their standout features.

Zooming with concurrency

Want to fly through tasks like a superstar? Use tqdm with concurrent.futures for real-time updates that'll make even Usain Bolt jealous:

from tqdm import tqdm
from concurrent.futures import ThreadPoolExecutor

with ThreadPoolExecutor() as executor:
    list(tqdm(executor.map(your_function_faster_than_light, your_iterable), total=len(your_iterable)))
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Taking it 'live' with alive-progress

Desire to put on a show with your terminal updates? Get alive-progress on stage via pip install alive-progress:

from alive_progress import alive_bar

with alive_bar(total) as bar:
    for item in your_iterable:
        # Processing

        bar()  # Call me maybe... to indicate completion
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Jupyter Notebooks integration

Ever wondered if notebooks could be more colorful? Boldly go with tqdm.notebook or alive-progress and bedazzle your code journey.

Levels of customization

Does the one-size-fits-all approach bother you? Let's examine some advanced progress bar customization methods.

Tailoring with progressbar2

progressbar2 is a gizmo for the control freaks—happy customization and install via pip install progressbar2:

from progressbar import ProgressBar, Bar, Percentage

progressbar = ProgressBar(widgets=[Bar('=', '[', ']'), ' ', Percentage()])
for i in progressbar(your_iterable):
    # Codename: operation progress bar
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Control the reins with stdout

Ready to take the wheel? Channel your inner artisan and craft progress bars using sys.stdout:

import sys
import time

total = 100
for i in range(total):
    sys.stdout.write(f'\rProgress: {(i+1)/total*100:.2f}%')
    sys.stdout.flush()
    time.sleep(0.1)  # Shhh! Coding in progress
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Connecting with Telegram and Discord

Ever imagined your code updating you on the move? tqdm.contrib.telegram and tqdm.contrib.discord are your tickets for progress bars on your mobile. Install, authenticate and get going!

Choosing between library and manual approach

An essential debate: library vs custom code. Libraries provide convenience and flair, while manual coding allows total control but at the expense of time commitment. Your choice, Skywalker!

Customizing the toolbox

Ponder between using a pre-constructed toolbox versus handpicking your tools. Leveraging a library, like tqdm or progressbar2, consolidates numerous components for efficiency. Conversely, creating custom progress bars bestows the power of personalization.

Use cases of Python progress bars

• Tracking the process of long computational tasks.
• Providing visual feedback for downloading or uploading files.
• Progress visualization for batch jobs on servers or scripts.

The ‘gotchas!’ aka potential issues

• Blocking I/O operations: Make sure that asynchronous tasks do not impede the progress bar updates.
• Vague time estimates: Uneven workload distribution can lead to inaccurate time estimates.
• Thread safety: In multithreading scenarios, ensure that you use thread-safe progress bar solutions.