progress-table 1.1.0

Display progress as a pretty table in the command line.

Note: versions 1.X introduced new features and changes of default behaviour.

The old version is still available as progress_table.ProgressTableV0.

New features include:

• Nested progress bar support
• Custom table styles support
• Color customization on row level support
• Adding columns automatically, without calling add_column
• Continuous progress bar when iterator length is unknown
• Pandas and numpy being only optional dependencies
• Other minor changes

Progress Table

Lightweight utility to display the progress of your process as a pretty table in the command line. Alternative to TQDM whenever you want to track metrics produced by your process.

Designed to monitor machine learning experiments, but can be used for any metrics-producing process. Allows you to quickly see what's going on with your process. Increases readability and simplifies your command line logging.

Purpose

Change this:

Into this:

Example

Click here for examples of integration with deep learning libraries: integrations.md.

import random
import sys
import time

from progress_table import ProgressTable

# Create table object:
table = ProgressTable()

# Or customize its settings:
table = ProgressTable(
    columns=["step"],
    refresh_rate=10,
    num_decimal_places=4,
    default_column_width=None,
    default_column_color=None,
    default_column_alignment=None,
    default_column_aggregate=None,
    default_row_color=None,
    embedded_progress_bar=True,
    pbar_show_throughput=True,
    pbar_show_progress=False,
    print_row_on_update=True,
    reprint_header_every_n_rows=30,
    custom_format=None,
    table_style="round",
    file=sys.stdout,
)

# You can define the columns at the beginning
table.add_column("x", width=3)
table.add_column("x root", color="red")
table.add_column("random average", color=["bright", "red"], aggregate="mean")

for step in range(10):
    x = random.randint(0, 200)

    # There are two ways to add new values:
    table["x"] = x
    table["step"] = step
    # Second:
    table.update("x root", x ** 0.5)
    table.update("x squared", x ** 2)

    # Display the progress bar by wrapping the iterator
    for _ in table(10):  # -> Equivalent to `table(range(10))`
        # You can use weights for aggregated values
        table.update("random average", random.random(), weight=1)
        time.sleep(0.1)

    # Go to the next row when you're ready
    table.next_row()

# Close the table when it's ready
table.close()

# Export your data
data = table.to_list()
pandas_df = table.to_df()  # Requires pandas to be installed
np_array = table.to_numpy()  # Requires numpy to be installed

Installation

Install Progress Table easily with pip:

pip install progress-table

Links

• See on GitHub
• See on PyPI

Alternatives

• Progress bars: great for tracking progress, but they don't provide ways to display data in clear and compact way

  • tqdm
  • rich.progress
  • keras.utils.Progbar

• Libraries displaying data: great for presenting tabular data, but they lack the progress tracking aspect

  • rich.table
  • tabulate
  • texttable