Huntlib

Latest version: v0.5.1

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0.5.1

* `huntlib.data.chunk()`: Given a sequence-like object (list, pandas Series, etc), divide it into chunks of a given size and return a chunks as a generator.
* `huntlib.util.punctuation_pattern()`: Return only the non-alphanumeric characters in the input string.

0.5.0

It also has moved the following functions from the main library into the `huntlib.util` package:
* promptCreds
* entropy
* entropy_per_byte

Attempting to use these functions in their old location still works, but generates a warning to update the code to the proper location. This backwards compatibility will go away in a future release.

There is also a new function `huntlib.util.benfords` to test whether a group of numbers conforms to Benford's Law. See the documentation for more details.

0.5.0.a4

* `huntlib.domaintools.DomainTools` objects now have working `iris_enrich()` and `enrich()` functions.
* All the functions previously offered by importing the main huntlib module (`entropy()`, `entropy_per_byte()`, `promptCreds()` and `edit_distance()` have been moved to the new `huntlib.util` module. Attempting to use the old imports will still work, but result in a FutureWarning to the user.
* `huntlib.data` now provides a new `flatten()` function for transforming nested dicts and/or lists into a single namespace useful for creating pandas DataFrames

0.5.0.a3

Alpha 3 contains the new `domaintools` module for hunting-relevant API calls and data enrichment of pandas DataFrames.

0.4.5

Because the Splunk API is so incredibly slow, this release ditches it's oneshot() function in favor of the lower-level Splunk Jobs API. Since we had to write our own results retrieval code, we used Python's built-in multiprocessing module to retrieve results in parallel. The default is now to retrieve results with a single worker, which decreased total search time by about 45% while retrieving 1mil rows in testing.

0.4.0

The major changes since 0.3.0 are:
* Now have at least basic unit tests for SplunkDF and ElasticDF classes
* ElasticDF and SplunkDF now both support the fields arg to specify which columns you want in your DataFrame
* A new huntlib.data module has drop-in replacements for pandas read_csv() and read_json() which can accept filenames with wildcards for easily reading multiple files into a single DataFrame
* Some updates to avoid calling deprecated functions in the underlying libraries

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