Skip to main content

A memory profiler for data batch processing applications.

Project description

The Fil memory profiler for Python

Your Python code reads some data, processes it, and uses too much memory; maybe it even dies due to an out-of-memory error. In order to reduce memory usage, you first need to figure out:

  1. Where peak memory usage is, also known as the high-water mark.
  2. What code was responsible for allocating the memory that was present at that peak moment.

That's exactly what Fil will help you find. Fil an open source memory profiler designed for data processing applications written in Python, and includes native support for Jupyter. Fil runs on Linux and macOS, and supports Python 3.6 and later.

Getting help

What users are saying

"Within minutes of using your tool, I was able to identify a major memory bottleneck that I never would have thought existed. The ability to track memory allocated via the Python interface and also C allocation is awesome, especially for my NumPy / Pandas programs."

—Derrick Kondo

"Fil has just pointed straight at the cause of a memory issue that's been costing my team tons of time and compute power. Thanks again for such an excellent tool!"

—Peter Sobot

License

Copyright 2021 Hyphenated Enterprises LLC

Licensed under the Apache License, Version 2.0 (the "License"); you may not use this file except in compliance with the License. You may obtain a copy of the License at

 http://www.apache.org/licenses/LICENSE-2.0

Unless required by applicable law or agreed to in writing, software distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distributions

No source distribution files available for this release.See tutorial on generating distribution archives.

Built Distributions

filprofiler-2021.11.2-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (10.7 MB view details)

Uploaded CPython 3.9manylinux: glibc 2.12+ x86-64

filprofiler-2021.11.2-cp39-cp39-macosx_10_15_x86_64.whl (488.9 kB view details)

Uploaded CPython 3.9macOS 10.15+ x86-64

filprofiler-2021.11.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (8.0 MB view details)

Uploaded CPython 3.8manylinux: glibc 2.12+ x86-64

filprofiler-2021.11.2-cp38-cp38-macosx_10_15_x86_64.whl (488.7 kB view details)

Uploaded CPython 3.8macOS 10.15+ x86-64

filprofiler-2021.11.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (5.4 MB view details)

Uploaded CPython 3.7mmanylinux: glibc 2.12+ x86-64

filprofiler-2021.11.2-cp37-cp37m-macosx_10_15_x86_64.whl (488.7 kB view details)

Uploaded CPython 3.7mmacOS 10.15+ x86-64

filprofiler-2021.11.2-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl (2.7 MB view details)

Uploaded CPython 3.6mmanylinux: glibc 2.12+ x86-64

filprofiler-2021.11.2-cp36-cp36m-macosx_10_15_x86_64.whl (488.7 kB view details)

Uploaded CPython 3.6mmacOS 10.15+ x86-64

File details

Details for the file filprofiler-2021.11.2-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for filprofiler-2021.11.2-cp39-cp39-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 569173764877cd44d31c1755a33875a94ae9f908c800def295918fbac0644906
MD5 ebbcd23a4d64b22dded3dac064ad56ed
BLAKE2b-256 a65758169ce4fcbe80d886d4dce6bb2d21011c9991c41f6d4b070bb30a1d9fce

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp39-cp39-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: filprofiler-2021.11.2-cp39-cp39-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 488.9 kB
  • Tags: CPython 3.9, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.8

File hashes

Hashes for filprofiler-2021.11.2-cp39-cp39-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 3aeff2d3842a4aff73f754dcc18dbcf219fb9653634232997be32ff32dc8215a
MD5 1871f4bcad2ec9ccd184cbf7bfec49b1
BLAKE2b-256 cb01b7b40307ff49e36863791ffd400b8363a2fca2a5d7d5595bd1ba53c17869

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for filprofiler-2021.11.2-cp38-cp38-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 e0d843e461966e3cacd60144a7cb4ecf97b156f80ca8110c59c97dbcc7f962de
MD5 8c01bc779cbf578034d75b505261c6c8
BLAKE2b-256 dadd22d55c89c767d8ca96379b406754fae5f865d956d4917f63799d96b38e88

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp38-cp38-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: filprofiler-2021.11.2-cp38-cp38-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 488.7 kB
  • Tags: CPython 3.8, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.8

File hashes

Hashes for filprofiler-2021.11.2-cp38-cp38-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 a6482fc2436e167c167b59fb68428c5dae0914c46e77f1a85403e05dd535aefd
MD5 50d847e8f3ba6b4445e0951e57478e62
BLAKE2b-256 761196f1cb2bd53afd1798181a5e252e308195608b70e8c96f996f256bbad270

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for filprofiler-2021.11.2-cp37-cp37m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 d4450e0ff75621f2c471121dcbc23cbc4324f6aa6c0e311f3254ccac989c3ba8
MD5 c8ce87e64b9abbdba1e1f05179fde2bd
BLAKE2b-256 d133aa966d62de77e404c1978e171e4f3a54aa38d1aef456b66ea6930711df7e

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp37-cp37m-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: filprofiler-2021.11.2-cp37-cp37m-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 488.7 kB
  • Tags: CPython 3.7m, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.8

File hashes

Hashes for filprofiler-2021.11.2-cp37-cp37m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 d2346be63590ccd134c9f44553d3908e143916bb8c20a1b9222efa8d609d436d
MD5 3bd775a67a3237ad525e3c39f3ef010e
BLAKE2b-256 887a244ef143f1ae153faba2740a7187ba5006d05d06a934fa19d02295a6cb73

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl.

File metadata

File hashes

Hashes for filprofiler-2021.11.2-cp36-cp36m-manylinux_2_12_x86_64.manylinux2010_x86_64.whl
Algorithm Hash digest
SHA256 85872394004d3eb9fd73bc7dfe946a5c08225385bb69f954fa625700e4f53bb8
MD5 3fe2cd76a79c95620fa9a98762c93594
BLAKE2b-256 e41eaf661e32c535f908fd423b0c6a577ca16c802f0b40f2d5efdde94133db3f

See more details on using hashes here.

File details

Details for the file filprofiler-2021.11.2-cp36-cp36m-macosx_10_15_x86_64.whl.

File metadata

  • Download URL: filprofiler-2021.11.2-cp36-cp36m-macosx_10_15_x86_64.whl
  • Upload date:
  • Size: 488.7 kB
  • Tags: CPython 3.6m, macOS 10.15+ x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/3.6.0 importlib_metadata/4.8.2 pkginfo/1.8.1 requests/2.26.0 requests-toolbelt/0.9.1 tqdm/4.62.3 CPython/3.9.8

File hashes

Hashes for filprofiler-2021.11.2-cp36-cp36m-macosx_10_15_x86_64.whl
Algorithm Hash digest
SHA256 8ed4ce7a6bcaefd0295b45fca115c7db6ca7e3f98b4261654361e7c79f595985
MD5 0a813df55117335fd60a0aecdd4888f6
BLAKE2b-256 9ab7cbe10ad7cd8efb9b7dd8b4e636bb497b341c24e400932a328ab338f9b48f

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page