Delta Lake helper methods. No Spark dependency.

Install the latest version with pip install levi.

The delta_file_stats function provides information on the number of bytes in files of a Delta table. Example usage:

import levi
from deltalake import DeltaTable

dt = DeltaTable("some_folder/some_table")
levi.delta_file_sizes(dt)

# return value
{
    'num_files_<1mb': 345, 
    'num_files_1mb-500mb': 588,
    'num_files_500mb-1gb': 960,
    'num_files_1gb-2gb': 0, 
    'num_files_>2gb': 5
}

This output shows that there are 345 small files with less than 1mb of data and 5 huge files with more than 2gb of data. It'd be a good idea to compact the small files and split up the large files to make queries on this Delta table run faster.

You can also specify the boundaries when you invoke the function to get a custom result:

levi.delta_file_sizes(dt, ["<1mb", "1mb-200mb", "200mb-800mb", "800mb-2gb", ">2gb"])

Provides information on the number of files and number of bytes that are skipped for a given set of predicates.

import levi

dt = DeltaTable("some_folder/some_table")
levi.skipped_stats(dt, filters=[('a_float', '=', 4.5)])

# return value
{
    'num_files': 2,
    'num_files_skipped': 1,
    'num_bytes_skipped': 996
}

This predicate will skip one file and 996 bytes of data.

You can use skipped_stats to figure out the percentage of files that get skipped. You can also use this information to see if you should Z ORDER your data or otherwise rearrange it to allow for better file skipping.

The latest_version function gets the most current Delta Table version number and returns it.

import levi
from deltalake import DeltaTable

dt = DeltaTable("some_folder/some_table")
levi.latest_version(dt)

# return value
2