Differential Privacy in Sequential Event Logging

license language build badge PyPI version Python version supported

Project Description

Sequential event logs often contain sensitive information. This program implements differential privacy (DP) techniques to anonymize sequential event logs while preserving statistical properties for analysis. This program can run 2 different functions: the full pipeline and the pattern-oriented pipeline.

Logo

Installation

To install this program you can use the following command:

pip install dp-sequential-events

To initiate, you can use the command privseq

Usage

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Authors

_{Marta Jones}
💻

_{Anailys Hernandez}
💡

Metadata

Release files for dp-sequential-events 1.9.1

For a detailed explanation of source distributions (sdists) and built distributions (wheels), please see the package formats documentation.

Source distribution (sdist)

Source distribution for dp-sequential-events 1.9.1
File	Size	Uploaded
dp_sequential_events-1.9.1.tar.gz	161.0 kB	Jun 4, 2026	Details

Built distribution (wheel)

Table of built distributions (wheels) for dp-sequential-events 1.9.1
File	Interpreter	ABI	Platform	Reset
dp_sequential_events-1.9.1-py3-none-any.whl 169.0 kB Jun 4, 2026	Python 3	none	any	Details

Total release size: 330.0 kB

Release files / dp_sequential_events-1.9.1.tar.gz

Download URL	dp_sequential_events-1.9.1.tar.gz
Size	161.0 kB
Tags	Source
SHA-256 checksum How to use checksums	`3ee50138b3eeb371af9580d77fa7b9d063a71604aca8801b85f8a03b609a5112`
BLAKE2b-256 checksum How to use checksums	`c530c6f59eb2a6d151e72719e48bfb655141c9b8726a02a1c438049d1670cdea`
Upload date	Jun 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.10.20`

Release files / dp_sequential_events-1.9.1-py3-none-any.whl

Download URL	dp_sequential_events-1.9.1-py3-none-any.whl
Size	169.0 kB
Tags	Python 3
SHA-256 checksum How to use checksums	`272cb0399a54b1d6d4ce3abd030eb8b938152fd1a970f857bb7e4661ae98f213`
BLAKE2b-256 checksum How to use checksums	`d3ac55801d43815b5f3a62e2c4a4c6458407338daba6d79927b83376a6094c16`
Upload date	Jun 4, 2026
Uploaded using Trusted Publishing? What is trusted publishing?	No
Uploaded via	`twine/6.2.0 CPython/3.10.20`