Tqdm#

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import time

import numpy as np
import pandas as pd
import panel as pn

from panel.widgets import Tqdm

pn.extension()

The Tqdm indicator wraps the well known tqdm progress indicator and displays the progress towards some target. You can use it in the notebook or in your Panel web app.


Tqdm




Parameters:#


    

  • layout (Column or Row): The layout of the progress indicator and the text_pane.
    • 

  • max (int): The maximum progress value.
    • 

  • progress (Progress): The Progress indicator to display the progress on.
    • 

  • text (int): The current text being output by tqdm.
    • 

  • text_pane (Str): The Pane displaying the progress text.
    • 

  • value (int or None): The current value towards the progress.
    • 

  • write_to_console (bool): Whether or not to also write to the console, only works on server.
    • 



For details on other options for customizing the component see the layout and styling how-to guides. For a general introduction to tqdm and lots of examples checkout the tqdm github page.




To use the Tqdm indicator instantiate the object and then use the resulting variable just like you would use tqdm.tqdm, i.e. you can iterate over any iterable:


tqdm = Tqdm()

def run_loop(*events, timeout=0.2):
    for i in tqdm(range(0,10), desc="My loop bar", leave=True, colour='#666666'):
        if pn.state._is_pyodide:
            # time.sleep does not work in pyodide
            np.random.random((10**6, 30))  
        else:
            time.sleep(timeout)
        
tqdm








Most of the parameters supported by tqdm can be passed to the call method of the Tqdm indicator.


Click the button below to see the progress bar update (if you viewing this on a live kernel):


button = pn.widgets.Button(name="Run Loop", button_type="success")
button.on_click(run_loop)
button












Nesting#


When nesting Tqdm indicators using the margin parameter allows visually indicating the level of nesting.


tqdm_outer = Tqdm()
tqdm_inner = Tqdm(margin=(0, 0, 0, 20))

def run_nested_loop(*events, timeout=0.05):
    for i in tqdm_outer(range(10)):
        for j in tqdm_inner(range(10)):
            if pn.state._is_pyodide:
                # time.sleep does not work in pyodide
                np.random.random((10**6, 30))  
            else:
                time.sleep(timeout)
            
run_nested_loop(timeout=0.01)

pn.Column(tqdm_outer, tqdm_inner)








button = pn.widgets.Button(name="Run Nested Loop", button_type="success")
button.on_click(run_nested_loop)
button












Pandas#


To use the tqdm pandas integration you can activate it by calling tqdm.pandas with all the configuration options. Once activated the progress_apply method is available on a pandas.DataFrame:


tqdm_pandas = Tqdm(width=500)

# Register Pandas. This gives DataFrame.progress_apply method
tqdm_pandas.pandas(desc="Pandas Progress")

df = pd.DataFrame(np.random.randint(0, 100, (100000, 600)))

def run_df(*events):
    df.progress_apply(lambda x: x**2)
    
run_df()

tqdm_pandas








pandas_button = pn.widgets.Button(name="Run Pandas Apply", button_type="success")
pandas_button.on_click(run_df)
pandas_button










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