Progress bar

Progress bar support is added through the tqdm package (installed by default when installing MPIRE). The most easy way to include a progress bar is by enabling the progress_bar flag in any of the map functions:

with WorkerPool(n_jobs=4) as pool:, range(100), progress_bar=True)

This will display a basic tqdm progress bar displaying the time elapsed and remaining, number of tasks completed (including a percentage value) and the speed (i.e., number of tasks completed per time unit).

Progress bar style

You can switch to a different progress bar style by changing the progress_bar_style parameter. For example, when you require a notebook widget use 'notebook' as the style:

with WorkerPool(n_jobs=4) as pool:, range(100), progress_bar=True, progress_bar_style='notebook')

The available styles are:

  • None: use the default style (= 'std' , see below)

  • 'std': use the standard tqdm progress bar

  • 'rich': use the rich progress bar (requires the rich package to be installed, see Rich progress bars)

  • 'notebook': use the Jupyter notebook widget

  • 'dashboard': use only the progress bar on the dashboard

When in a terminal and using the 'notebook' style, the progress bar will behave weirdly. This is not recommended.


If you run into problems with getting the progress bar to work in a Jupyter notebook (with 'notebook' style), have a look at Progress bar issues with Jupyter notebooks.

Changing the default style

You can change the default style by setting the mpire.tqdm_utils.PROGRESS_BAR_DEFAULT_STYLE variable:

import mpire.tqdm_utils

mpire.tqdm_utils.PROGRESS_BAR_DEFAULT_STYLE = 'notebook'

Progress bar options

The tqdm progress bar can be configured using the progress_bar_options parameter. This parameter accepts a dictionary with keyword arguments that will be passed to the tqdm constructor.

Some options in tqdm will be overwritten by MPIRE. These include the iterable, total and leave parameters. The iterable is set to the iterable passed on to the map function. The total parameter is set to the number of tasks to be completed. The leave parameter is always set to True. Some other parameters have a default value assigned to them, but can be overwritten by the user.

Here’s an example where we change the description, the units, and the colour of the progress bar:

with WorkerPool(n_jobs=4) as pool:, some_data, progress_bar=True,
             progress_bar_options={'desc': 'Processing', 'unit': 'items', 'colour': 'green'})

For a complete list of available options, check out the tqdm docs.

Progress bar position

You can easily print a progress bar on a different position on the terminal using the position parameter of tqdm, which facilitates the use of multiple progress bars. Here’s an example of using multiple progress bars using nested WorkerPools:

def dispatcher(worker_id, X):
    with WorkerPool(n_jobs=4) as nested_pool:
        return, X, progress_bar=True,
                               progress_bar_options={'position': worker_id + 1})

def main():
    with WorkerPool(n_jobs=4, daemon=False, pass_worker_id=True) as pool:, ((range(x, x + 100),) for x in range(100)), iterable_len=100,
                 n_splits=4, progress_bar=True)


We use worker_id + 1 here because the worker IDs start at zero and we reserve position 0 for the progress bar of the main WorkerPool (which is the default).

It goes without saying that you shouldn’t specify the same progress bar position multiple times.


When using the rich progress bar style, the position parameter cannot be used. An exception will be raised when trying to do so.


Most progress bar options are completely ignored when in a Jupyter/IPython notebook session or in the MPIRE dashboard.