Skip to main content

library to read/write EDF+/BDF+ files

Project description

Test Coverage Docs Build PyPI Version Conda Version Conda Downloads

What is pyEDFlib

pyEDFlib is a python library to read/write EDF+/BDF+ files based on EDFlib.

EDF means European Data Format and was firstly published Kemp1992. In 2003, an improved version of the file protocol named EDF+ has been published and can be found at Kemp2003.

The EDF/EDF+ format saves all data with 16 Bit. A version which saves all data with 24 Bit, was introduces by the company BioSemi.

The definition of the EDF/EDF+/BDF/BDF+ format can be found under edfplus.info.

This Python toolbox is a fork of the toolbox from Christopher Lee-Messer and uses the EDFlib from Teunis van Beelen. The EDFlib is able to read and write EDF/EDF+/BDF/BDF+ files.

Documentation

Documentation is available online at http://pyedflib.readthedocs.org.

Installation

pyEDFlib can be used with Python >=3.7. It depends on the Numpy package. To use the newest source code from git, you have to download the source code. You need a C compiler and a recent version of Cython. Go then to the source directory and type:

python setup.py build
python setup.py install

There are binary wheels which can be installed by (use pip3 when available):

pip install pyEDFlib

Users of the Anaconda Python distribution can directly obtain pre-built Windows, Intel Linux or macOS / OSX binaries from the conda-forge channel. This can be done via:

conda install -c conda-forge pyedflib

The most recent development version can be found on GitHub at https://github.com/holgern/pyedflib.

The latest release, including source and binary packages for Linux, macOS and Windows, is available for download from the Python Package Index. You can find source releases at the Releases Page.

Highlevel interface

pyEDFlib includes an highlevel interface for easy access to read and write edf files. Additionally functionality as anonymizing, dropping or renaming channels can be found there.

from pyedflib import highlevel

# write an edf file
signals = np.random.rand(5, 256*300)*200 # 5 minutes of random signal
channel_names = ['ch1', 'ch2', 'ch3', 'ch4', 'ch5']
signal_headers = highlevel.make_signal_headers(channel_names, sample_frequency=256)
header = highlevel.make_header(patientname='patient_x', gender='Female')
highlevel.write_edf('edf_file.edf', signals, signal_headers, header)

# read an edf file
signals, signal_headers, header = highlevel.read_edf('edf_file.edf', ch_names=['ch1', 'ch2'])
print(signal_headers[0]['sample_frequency']) # prints 256

# drop a channel from the file or anonymize edf
highlevel.drop_channels('edf_file.edf', to_drop=['ch2', 'ch4'])
highlevel.anonymize_edf('edf_file.edf', new_file='anonymized.edf'
                             to_remove=['patientname', 'birthdate'],
                             new_values=['anonymized', ''])
# check if the two files have the same content
highlevel.compare_edf('edf_file.edf', 'anonymized.edf')
# change polarity of certain channels
highlevel.change_polarity('file.edf', channels=[1,3])
# rename channels within a file
highlevel.rename_channels('file.edf', mapping={'C3-M1':'C3'})

License

pyEDFlib is a free Open Source software released under the BSD 2-clause license.

Releases can be cited via Zenodo.

https://zenodo.org/badge/DOI/10.5281/zenodo.5678481.svg

Project details


Download files

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

Source Distribution

pyEDFlib-0.1.32.tar.gz (2.1 MB view details)

Uploaded Source

Built Distributions

pyEDFlib-0.1.32-cp311-cp311-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyEDFlib-0.1.32-cp311-cp311-win32.whl (2.2 MB view details)

Uploaded CPython 3.11 Windows x86

pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_i686.whl (2.8 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.9 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp311-cp311-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyEDFlib-0.1.32-cp310-cp310-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyEDFlib-0.1.32-cp310-cp310-win32.whl (2.2 MB view details)

Uploaded CPython 3.10 Windows x86

pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_i686.whl (2.8 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.32-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp310-cp310-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyEDFlib-0.1.32-cp39-cp39-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyEDFlib-0.1.32-cp39-cp39-win32.whl (2.2 MB view details)

Uploaded CPython 3.9 Windows x86

pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_i686.whl (2.8 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.9 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.32-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp39-cp39-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyEDFlib-0.1.32-cp38-cp38-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyEDFlib-0.1.32-cp38-cp38-win32.whl (2.2 MB view details)

Uploaded CPython 3.8 Windows x86

pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_i686.whl (2.9 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.9 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.32-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp38-cp38-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

pyEDFlib-0.1.32-cp37-cp37m-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.7m Windows x86-64

pyEDFlib-0.1.32-cp37-cp37m-win32.whl (2.2 MB view details)

Uploaded CPython 3.7m Windows x86

pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_i686.whl (2.8 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp37-cp37m-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

pyEDFlib-0.1.32-cp36-cp36m-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.6m Windows x86-64

pyEDFlib-0.1.32-cp36-cp36m-win32.whl (2.2 MB view details)

Uploaded CPython 3.6m Windows x86

pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_i686.whl (2.8 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.8 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.8 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.8 MB view details)

Uploaded CPython 3.6m manylinux: glibc 2.17+ i686 manylinux: glibc 2.5+ i686

pyEDFlib-0.1.32-cp36-cp36m-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.6m macOS 10.9+ x86-64

File details

Details for the file pyEDFlib-0.1.32.tar.gz.

File metadata

  • Download URL: pyEDFlib-0.1.32.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32.tar.gz
Algorithm Hash digest
SHA256 ef2a97771034aab40ecaa6266786f0cc75223dbb384572874a6ba00cc34db3c6
MD5 48f346a6052245168ffdd14d3c032278
BLAKE2b-256 7e65f0bd874d49928f3965fd7e406974c44d5ed36811e03573e1d05b2267e3e5

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 9dcd705792f4be15d24a3753189209a67e09ee2c42d78dfd7c4574f254817fc1
MD5 af4c04b5f35064f91445923c8c1cb5b0
BLAKE2b-256 3634de63c9caf763208482f26551502b15e3a2458797d9798a900849c21cc2fa

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp311-cp311-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.11, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 b45fbaeb877458341203422be9d42181574fffd742e4525b78f8f1608f906a21
MD5 cca1bf3fa5982948b1b97791c90f2ac0
BLAKE2b-256 73645fab637e366d462bdd6bbb4fb991db266cb05a36a417d575dbb5920ff263

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 e29d47a46480f290d259f711e0e3b6766f8633bd7fcf0128311f0bfc59400904
MD5 0aa2ef7a71351b8f20dabafdb01ced42
BLAKE2b-256 edb8b04878b05dcf4867dde9dca99beb92786079e1cd2532a6d08d8834de7635

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 a951556dde6ce5508b986600a2a09422d290ff1202d5a43c9a004729573d888e
MD5 dec9a6fc79fb478065889647dae9c81e
BLAKE2b-256 129a642b78fc890a5078ec9aede9f4a57873d24d2c5928391d9cd5240b4d6a80

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 07a94148e995fa7262c1adaad2d37d36620fbc39ae9be19a0b27a6a59562af4b
MD5 aa8b3af43a4eb94692b4acfaca9129af
BLAKE2b-256 3bb71f9779ec808f121ae464d620eb27c881c47ce5c86a4add116e9c1763a5db

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 afde481736bc957fbee045199be343422a45dca0e18180539afe854e2c55b37b
MD5 1fe881c0fe7e269fd99fa625b7eaa1f6
BLAKE2b-256 595eddc525380e9f7d31bc7d694c5ee8275f38a8f0855c66ce1068629b025f71

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9229c164323aedb52e37002e2768001e00cb5e991163a9859b42393e23867d61
MD5 067c49b0480fd0b1b7e87ebb712d21c5
BLAKE2b-256 c914916b1bd38321096f2b7004a5c443a5f39f47a88ebc841e86c64fe77f4e52

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 b2ae94d8ad0d26f6bdb6254ccab9ad6902ba216c378a452d43165b5b4cb6f59d
MD5 9c828dd542a9021e6f0eb66b93de1a61
BLAKE2b-256 64c7ad908e232a08f7e89b3206b379804ec8d8a38c37058233fa721cd0b727f5

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp310-cp310-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.10, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 f9c653dc8902383e6f2af8df657376b3ae6c7bb2fd005f4edd63946870c586f6
MD5 fb411c4363d8f89adbf5aa0b83786ccd
BLAKE2b-256 16c30e7515e2f7f72cba6ea6b92d43a1b5f1e3c8df940bda07fa30cfb90051ac

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 ec9d04385023672c51b4a19e7edce0e9bcadb79148f0bba15fe35f52b337b9aa
MD5 2e40c748d45950fee943f6809c961877
BLAKE2b-256 49d1f4cd0563977b95488b9bf5d4eca7f2dae6b39fa0481ed61b50739bb8e5ed

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 d7215aa539e6df4d6e086220a681b9786dd8d4cbab0e01c8478bb6c8ad644b1c
MD5 24bdca8c023655c60f52e92db551a8c9
BLAKE2b-256 4833a6b80935f71a6b2c83d6ed60a6a20f463622997e99e5d3ab9504091ce1f8

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 50b4272031af977b2374a8fc78a2ce653272f83846fa38ca653f1065c8a4d440
MD5 ff3159e9d92952e24d8f304a22eb1c09
BLAKE2b-256 7ad26420edaab0170b914523eddbbea04583b4cffbb9dbcdc6d95b7c90bdb1f7

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 0301ae5a9ee044e39567de41d550aefc8d59ac449c2c282da90bd60e22d7ff2e
MD5 f4ec7052b9f1cdd13358260e70f760cb
BLAKE2b-256 3f2ed50052d41ca6058ad18d3c28f86a2eb310cae1efeb794571447b7ccac76b

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 11c29ef0ca961e944a368837b1d9ef692e986f8cb4d28699004ceecb6240cd5d
MD5 1b46c9f94caf7a4869ab9075a41bcab2
BLAKE2b-256 34609497136c197ee61d4f3a7768a62f29fa056137c0549c2841e89024058331

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 61d485dbed2ec151f098471dbcd92440d50bbd5c87d13b20bc43d49e1495679f
MD5 ab89d2eb956b008d8bdf524f3c42e5bd
BLAKE2b-256 659ba2e252223d8ba1fd2f59cb750766b93083e54fe612349538c3b22f2b3348

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 1d65d8ef03a38dcdaa3580d95a988f0450b411af578cc232f577df245e88a56e
MD5 ee1ab3dbde1479ffb38515c07947c352
BLAKE2b-256 d69a9377922f3ad16fa0480634f329981674d0667c62bec179811c64ca7f5298

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp39-cp39-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.9, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 75dee5a995f29a4ea25e10e9f522e3c0c59b3229e143af73dc8a38d53f3e37ac
MD5 7998c504bf97272c9301c845672b27cb
BLAKE2b-256 07110ea832bc9e5b7d7e003928247fda6fd7684b6c014da04436ca908928a7e9

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5831ccb4086a6d5fa5aad3a2c2bb9768d034a493ebccb0adc8c720c6c4c69509
MD5 222fb9e0e7a821b71c6e9d3061de9d67
BLAKE2b-256 d235e4b4d4278e49160e7dc1bf32f3de1e71519f7197aaff9debbce97a5f44af

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 4124330b47ab3eb128708aca5d551ed5dce83737aabcfe2aeb08b5f127d2a1f1
MD5 517e7762d3f79438dcde203ae2c11481
BLAKE2b-256 bd5f824dbc07c15938f27371a4f52c9b663d32e4520fab2a898af2936dfd483a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 7554e099d35b07a98ed25696e672cf65a72f1ae63f2ee6df27e1cde53b9e6ed2
MD5 4e5d9c9a71b4082d44f4faa4514235ba
BLAKE2b-256 391c044d05220f9cecc72e7799b7a92b4431856b1b974c7764f511cda32a9cbd

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 c0e84b160b9f0a3d3f8252bceace3d79ac937418e878c390b23a339fbb87d694
MD5 da6b14b77300b0ae598c4a3ae2d55ceb
BLAKE2b-256 36ea0a7c3e2038e1de7010c55c42ed9e9a05cd4688262fecf76f6e10f29e4e60

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 8c2998f92f9915bf0ddc469457ab7e696e94dfe50ecda0590d460670f298a383
MD5 66337674cb8fe8b02e2fbddf4e3ff09a
BLAKE2b-256 274872c309751c7d1d187702ca1c94ab69280ae97f70a4586283760db3e500f9

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 065a3588a25126345b5452778a08b8c042662804acc2dc619b15701c37beb37e
MD5 46105d7a9ada8d815e279252cd4a8b19
BLAKE2b-256 37af72a79c33f7d07409c3f0e591c84b8ff63070cc409e8e21af76d0e99e009a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 dbde7141891126ce5250fc3d1548e6b2671f0610cc19e92d39cd520a92d30fab
MD5 5b97ef6f521aa53448408fd4ec404139
BLAKE2b-256 eeeaba626f856762c41a109530c997f19fccf1dc446f97c246202462e8d4c626

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp38-cp38-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.8, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 3af017cf8f81f5848f17ba417958d24da1a39fabca4a10489beadc26c47afd5c
MD5 7c77d7be6486a9804a9c41fc2e61df7f
BLAKE2b-256 36a0769d7b33d374a4a60f969fb0acae55ff4f9bf70d952e8870b76c30297655

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 07ccdc341adcae7412839195e6a53549f5b362c11656e0334d010270905f492f
MD5 c523d5c30ec3cebff24faa9343383f6c
BLAKE2b-256 4e3f83c824d5d4eae0f57c31e98405666eec0d63920e78dbd18ac8c2e8731833

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 820726ae18053434795eaad6a3f3b72e557a789364b2135d1e229f57fae4302b
MD5 76eb5f75ed8edd1aa7dd8cdaaa7ddaeb
BLAKE2b-256 b1874c1523724a923869e5998e9973f79ff234b093569b1a7b2f4a55ed80df80

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 540a15adeade7b986f0322d6aeb9e2cf9967d65a52133f6642f6f6ed519ac971
MD5 50990a0d11903058a5c15a52bfe8d98d
BLAKE2b-256 22987fa89c01efa19936a6f7cb3f91499925872456a7c1ddd389d09dbd0a2671

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 46e2808232a60514be6c416bfc6de6f5f88c74ae603a48b85cf81734ad6efb12
MD5 2a67940df2c3b0f52293909f107276e4
BLAKE2b-256 b31e6809bd0ecbca0a5f1a0c15762927be356b94a82200c0e32fb50fe2c4cfa0

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 39ea6d1f3aabb9b955c81c672a6e0970e88172f7fae42b500df3e47e2287b6c5
MD5 a8d5c3208c621ed544228db00c0b3602
BLAKE2b-256 59551e842dfdcbd11e3968870f0e32a8244362ef07bcfb5d6c7fadd5fe600ecc

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 29373c2a576c568a4969d3da661296d1b47c99831b19371e71d0173bb14d2a05
MD5 5c9ff9ce9abae646fa2dcc630cac5113
BLAKE2b-256 b40adcc91a7790f5f6ab940213c0ed61e396ad1f0c07c7bf2d69bb7db01b90ad

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 920bdb003034e4991f9f43a6743d885cabc76b8813d9060a8ce9b4bc07536bdc
MD5 84130de6807be95cacffe0124033b2de
BLAKE2b-256 74b5ba5c30a51e41bdd06610e0442286dea6e76d435969a1665a3bbf1a7adab3

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp37-cp37m-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.7m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 8498bd17c58edfec52c16fc922e853ff8b6ea15e093dd6d79caf251264d71778
MD5 802a7b6be70f12ff257876daa7b9ff05
BLAKE2b-256 7ba9cf33d09e3fa51bb3f622dee53a87da8b219fad788e9e5be52b59b8921f48

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 852a36ecce66cbcb95ea0113ec19f0dc6b3799b7236aad1fd3d8e13280e592c1
MD5 8b8c6237ba247c61e358bec40c4d0c65
BLAKE2b-256 9ae1b274a5f2b4f08280c574cbc6057f32227bfb15ca6aed96439d4a6aa1ba78

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 ff162d9755903e06d3c42f08f2d1ab03cfda744ee86c12694cabc8ad9b45b2fe
MD5 b9f78a83239b02ab1a3ef2cde0651977
BLAKE2b-256 a0bf768e122ce8a8be0affa5c876a6873e03656d94ce819a3e5b04c3dbe4a07b

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 6803b86ae5183ff48756bc9cb24383ade1096871605c1f4362c2b36ef18a16f7
MD5 12305caf5f7cb39c1b224ea71be0cb60
BLAKE2b-256 f904e656ddf02075526d36eb8e0abfb44f9d105b2b9d6ba7a2a933b7036de06a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 30ee3f049f3cada3acbf5cb139b34d646923ca21fede9e42ddeca956af135c96
MD5 23782bbd433d9967d622b1ce9a9f3e81
BLAKE2b-256 d67b68e57c24ffd7e3c75e236d24523505ca8a62932d332c17f4ecd694a72b71

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 da7f9e711674ffc50853e6f5de3dceb1284d6ff6e88a3e589cc234561018b2cb
MD5 23a4171fd9cd50a23e63075b98ef7002
BLAKE2b-256 514716089c7e5d0fa0784c1fa0fa9ae2d4ed89365e052692f874bef699ef653a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 98d3f4bc9a990a9540a54944397e8a789eead3d58815861534cb0111aa9551c1
MD5 d40b6d506f49867d451dd68e2c53e31d
BLAKE2b-256 73a44df4319742bbab43ca34a275e527fdc4c15832ad90531bf4959479e8b249

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 85e668eca49b892451dc7fe81db6cc7880b8446926a5c8ad9dd3217645437f83
MD5 b0db231715749f394e05eb269a8d14c5
BLAKE2b-256 ef3e333af8212bb0fe041446e809cfa62ce95f0cf9cdbdf58bf36a6acd1bdd04

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.32-cp36-cp36m-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.6m, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.16

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 31682be9cd224fe7d2176bda642d7baf73cf39229cb3214379ce74dbaf90fe22
MD5 1d69bd9d73911e0a0526baca531034ae
BLAKE2b-256 309c25cddc96e4769a50f10cccc7c87825be330e1438167dfce0d7167b6d4413

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 bbacbb405017fc4697108fdefa5c1466ceb5f1d2f6e910574b7e5e9e077d70b5
MD5 414137a6ca03a87a61e29638566210d5
BLAKE2b-256 9e4594b510ffacea9268c35773e86cf2179f4cb69af0c085edb3028c7d6ca467

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 2ee90a29963e196f8dcc7f24445b41a46b599acd49eea512d9a1266a051ea9a1
MD5 ffee217d8424a285820d02da5df92e75
BLAKE2b-256 782c3e599df48f4f2cd7b81c35b6b15537bd724963235e043cc3026b42e8d7d0

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8cbab35eacec987e3cf390a46a9d002bffa3f82b9da1c85f016949e4493cde94
MD5 f56d0f1e660b1e7f3a3f872ae34a27f6
BLAKE2b-256 e557882d61ac7410c0000c338486e56aa1f91e79be5a8aa82ee4529830ab7e92

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 fcfbd4fba7ca6a91b2c199cbef9b44bdf58eb9389ade92a5113bec1ee61d2347
MD5 78cbfd4833474d18b77f9dbe204df0cc
BLAKE2b-256 54331e9a58db31bb7a659bc27e9b67ecca17a981183381c7b089423ca9e6f9c1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 516402c494f0f2774a9d574981f190a9b09ec0765fa2f4cf7fc289570585f59e
MD5 de234b3da01731b6ba2a90a599ae9609
BLAKE2b-256 f367ea4b91853bfd4f9133f6badf66cd0aeadd146525048b82a99af7fa734054

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.32-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.32-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 9f2dd5ac0853a02598aaba464d44cb91ed345747f48c1d9a9d70fded92ac22cf
MD5 607111ac8da33f2d9a97e8e508599ab3
BLAKE2b-256 02f6280a8aa01466ccb2455594b4f39198ea4316d2dd02617299894e65b51636

See more details on using hashes here.

Supported by

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