Ubuntu
pprofile package

pprofile 1.11.0-1 source package in Ubuntu

Changelog

pprofile (1.11.0-1) unstable; urgency=medium

  * New upstream release 1.11.0
  * debian/control: Bumps Standards-Version to 4.0.1, no changes needed.
  * debian/control: Adds Suggests field with python{3}-ipython to
    pprofile{3} package

 -- Josue Ortega <email address hidden>  Sat, 12 Aug 2017 11:55:11 -0400

Upload details

Uploaded by:
Josue Ortega
Uploaded to:
Sid
Original maintainer:
Josue Ortega
Architectures:
all
Section:
misc
Urgency:
Medium Urgency

See full publishing history Publishing

Series Pocket Published Component Section
Bionic release universe misc

Builds

Artful: [FULLYBUILT] amd64

Downloads

File Size SHA-256 Checksum
pprofile_1.11.0-1.dsc 2.0 KiB 1332ad6c53300d90dacb99fe554881afa41d62a74b40e19fc156068e8dab66bb
pprofile_1.11.0.orig.tar.gz 26.3 KiB 41cbe4ca6722c0d2b189c4c7561af70139121ccf4017ad0f8f57ab2f970bc78c
pprofile_1.11.0-1.debian.tar.xz 3.2 KiB 9960a57b05451072e35532da3a72db3827ea6a95b65faa7ee9eebae86541e0c5

Available diffs

No changes file available.

Binary packages built by this source

python-pprofile: Line-granularity, deterministic and statistic Python profiler

 Line granularity allows locating precisely where time is spent in code.
 Thread awareness automatically propagates profiling to all threads (all
 threads in statistic mode, or threads spawned by profiled code in
 deterministic mode).
 .
 Deterministic profiling gives precise measures, but at a large speed
 cost (best used on minimal test scenario).
 .
 Statistic profiling gives rough measure, but has an extremely low
 overhead (suitable for live code profiling).
 .
 Does not require marking methods to profile, allowing non-method
 profiling (module imports, class & function declarations and other
 module-level code).
 .
 This package installs the library for Python 2.

python3-pprofile: Line-granularity, deterministic and statistic Python 3 profiler

 Line granularity allows locating precisely where time is spent in code.
 Thread awareness automatically propagates profiling to all threads (all
 threads in statistic mode, or threads spawned by profiled code in
 deterministic mode).
 .
 Deterministic profiling gives precise measures, but at a large speed
 cost (best used on minimal test scenario).
 .
 Statistic profiling gives rough measure, but has an extremely low
 overhead (suitable for live code profiling).
 .
 Does not require marking methods to profile, allowing non-method
 profiling (module imports, class & function declarations and other
 module-level code).
 .
 This package installs the library for Python 3.