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. The company BioSemi introduced a version which saves all data with 24 Bit.

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 https://pyedflib.readthedocs.io.

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-0.1.35.tar.gz (2.1 MB view details)

Uploaded Source

Built Distributions

pyEDFlib-0.1.35-cp312-cp312-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.12 Windows x86-64

pyEDFlib-0.1.35-cp312-cp312-win32.whl (2.2 MB view details)

Uploaded CPython 3.12 Windows x86

pyEDFlib-0.1.35-cp312-cp312-musllinux_1_1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.12 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.12 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp312-cp312-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.12 macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp311-cp311-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.11 Windows x86-64

pyEDFlib-0.1.35-cp311-cp311-win32.whl (2.2 MB view details)

Uploaded CPython 3.11 Windows x86

pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.11 musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.11 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp311-cp311-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.11 macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp310-cp310-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.10 Windows x86-64

pyEDFlib-0.1.35-cp310-cp310-win32.whl (2.2 MB view details)

Uploaded CPython 3.10 Windows x86

pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.10 musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.10 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp310-cp310-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.10 macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp39-cp39-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.9 Windows x86-64

pyEDFlib-0.1.35-cp39-cp39-win32.whl (2.2 MB view details)

Uploaded CPython 3.9 Windows x86

pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.9 musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.9 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp39-cp39-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.9 macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp38-cp38-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.8 Windows x86-64

pyEDFlib-0.1.35-cp38-cp38-win32.whl (2.2 MB view details)

Uploaded CPython 3.8 Windows x86

pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ x86-64

pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.8 musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ x86-64

pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.8 manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp38-cp38-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.8 macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp37-cp37m-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.7m Windows x86-64

pyEDFlib-0.1.35-cp37-cp37m-win32.whl (2.2 MB view details)

Uploaded CPython 3.7m Windows x86

pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_x86_64.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.7m musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl (2.6 MB view details)

Uploaded CPython 3.7m manylinux: glibc 2.17+ ARM64

pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp37-cp37m-macosx_10_9_x86_64.whl (2.2 MB view details)

Uploaded CPython 3.7m macOS 10.9+ x86-64

pyEDFlib-0.1.35-cp36-cp36m-win_amd64.whl (2.2 MB view details)

Uploaded CPython 3.6m Windows x86-64

pyEDFlib-0.1.35-cp36-cp36m-win32.whl (2.2 MB view details)

Uploaded CPython 3.6m Windows x86

pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_x86_64.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_i686.whl (2.6 MB view details)

Uploaded CPython 3.6m musllinux: musl 1.1+ i686

pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl (2.6 MB view details)

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

pyEDFlib-0.1.35-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-0.1.35.tar.gz.

File metadata

  • Download URL: pyEDFlib-0.1.35.tar.gz
  • Upload date:
  • Size: 2.1 MB
  • Tags: Source
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35.tar.gz
Algorithm Hash digest
SHA256 831661370e032f8cc46d771f42606bfbfd8eb04499a59b1092fced77d70aba35
MD5 7061ff017ecd8ed758c99ca90380b98c
BLAKE2b-256 73795b9ed3f641fff4b6c06d2f521ab4a93ba5dce1d069db26da2bd320db8afb

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 228cd1fa412a852ecc5bd8c5edcc78b28f61d4ee2f62bced5bc9b8770b832e4e
MD5 210418cd9e3df5e2ef94727914c9938b
BLAKE2b-256 c76501211a98f0f22f0c23af1a93aedd3bf66c9d8045c126107c54bf14ec9546

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-cp312-cp312-win32.whl
  • Upload date:
  • Size: 2.2 MB
  • Tags: CPython 3.12, Windows x86
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/4.0.2 CPython/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-win32.whl
Algorithm Hash digest
SHA256 3555e7d7587a4adca3c7a5b6a7a903c5d6b475461151c2f659a7193a05224dcb
MD5 63e6217f20d1582af174cad02885fba6
BLAKE2b-256 3170f5aaf47cde4c75ec69e814936290caa83e59f93c0f273ccc13ba3046c2d1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 60246e811bda76ef1c9a7ac200265cd4da4fd0805ed2295f3c23631c2343cec2
MD5 5371eb6c2bdba7a73b5959cc18bc806d
BLAKE2b-256 569fae65deb47c91c510d32c02b5443705b034e65d59270126e9d81ab90f8cf8

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 1bb0d5ff9af59a53840b35f3f31a4d6f476f8a37cae5af799e2c5f5ef3a3c819
MD5 3070f50a875dca7f5728b1ee01b609db
BLAKE2b-256 33052da5a4c96c51a119f660f8d39fc802c49eb54e21ae1028bb2c25f08adda1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 23041de4e87c201811404204fe6c6f5b354e7c9c7fe927dc28ae3fb1d6a1fe78
MD5 1f1bdc6f05228111fd6736d5294b1a8f
BLAKE2b-256 bec0277a046abfb03c32b772b0f26558957526ec3a0aa3b630d1a0052d8e49e1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 a8bfa6995a2a70d493aaa8ad7340c8098c9c9bea9fd85b876bd280028affd521
MD5 b3353e143a20131fb277d5d2a5d7e3d4
BLAKE2b-256 e9ee07255b43f331830c20134abc631966123940327209a7da39a334480d4e77

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 204b018e9117ce3fa1b8d7d7bca97701372129570dd35b99aa8c87757ea1979e
MD5 e5da02a14a18c836c5a66652cfa33358
BLAKE2b-256 924d724fdf441ce55e281ca816e37634d1734ae099d82e41c3e08ae3c8b309d5

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-win32.whl
Algorithm Hash digest
SHA256 f635a9960444beb5af2366cc85639453b2c5236a8455523a1e67fc4e70a212db
MD5 c1883383bfc2f130d8f97de41a6cf203
BLAKE2b-256 d5e2510d1387bc03b37a3b3df12d3bad10930b99268eaf4053410d08294ebefc

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 cb370de4de8714d6e307eeeb2a09c316d1f75764512148c73556a8b45690b693
MD5 4b7fcb910a1059b71957a98b3abb39fd
BLAKE2b-256 9987485b00f8ef9829cb78214cfe12f710b267d9413d3c26c0795c5346a82239

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 3a3478006bd8a4996f8ce6ba506f0a71d01de3093144d6bd63891e9068851c42
MD5 7325a7d8a20a7cf821ccbe8a6bec21ed
BLAKE2b-256 67bc41e48bfc980a6fe637f5fe062dc888bf0356680b1a4bfb1fb3f7b596ad18

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 fee986be52a43715304743a41db4f9751ae6280c52de24191d607c9e87e58ee6
MD5 6420d44f877eb9c303e18d632041446e
BLAKE2b-256 47b573830ad85b83cf6d73df8ebd3aac3b58ab4269700a671f8be58bf59e7e60

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 423ff75fdcf67643b8164e0bef3ae25443ca8f2ada2228592d48469c409bf415
MD5 8d8f360c782dda70ca29e470a81d721c
BLAKE2b-256 1064118e51da9c79e1100934635e8bd572170c00c4c26173a91ab7d67c61aa2f

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 1e853f81baf11e11acc5873c28120e81c96711a06a6343261565c2680f8a42ac
MD5 dcd7eaa8769d4ab37420c9b64bd707df
BLAKE2b-256 69ee0253232b9bfb4e98df5d703cfc40cc3184acfead786b151865a4c6ad7325

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 30546f02cb10ed0e5585e07f7ba6aa7bf0d1fe43c56a7080dff821f1d0dd9790
MD5 f4b82d63c58cb40e5a42d2feaecbcc8e
BLAKE2b-256 0d521d6628868b2204c81ba7cc212053400e751be1c482af0da86001c4a3335f

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 00f707d1fed72f78597fd70cd06580910642dd59f3eea08e6551ed73ab10993c
MD5 6a7dadef330b067fbdb7dbf4dd83a9d6
BLAKE2b-256 05f0283a5cc81d414150644f5d6b58647d188869f24de1423d6fa895252b7fa3

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-win32.whl
Algorithm Hash digest
SHA256 5d3bc5e5ff53863999e84e08a84cda0b08383fad15223a9e68af50ee10d06a72
MD5 ceb5b90fa02b85a43a9281e7b86959e2
BLAKE2b-256 73858d1b1a2bee4ad522d736791786c0326171d5e65cf6260cfad264877d657a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 e1b201cff50cff47391c197c6f0cf3a37dea649762e7148f2c577626258943f8
MD5 13649f2941d176bddf985a9656157973
BLAKE2b-256 1a3cca64d825532dcf1cc7d2cd04981ffb3ff24ccca1d83bfa0b9bc3d542cc23

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 207916b2654d17ee4774d2abd274abcc61089a343730f83b5271592e8f6f1939
MD5 4ae577a4fe0d5dfe94b069bcc54c27e9
BLAKE2b-256 d2936fdaf7a7a80e47638180cdd86d3189d700085f802cc8af2c3863f39fe6a1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 b92a44a55d9814e417df1a11e40235be2f2c852549180c271261fed8fdf1ed7c
MD5 4e9b817041aa9c88fd2bba04a16f4c79
BLAKE2b-256 206fd7c9c73c201b0f24263f8cc863e18a815493360e301fb983d2367a107981

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 a901b8384a4e49b0420f385d7b1eaf639612c0b7cf44449616e0d8c4082712d8
MD5 8f3a2a85665a057d1b3dd338ad686444
BLAKE2b-256 6926401f627514a49da7b107d6aec06786bc27e4e145eb8fcb6f2d9e58cb9d11

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 223fa5981a97c7f23ef29990272953d2eac2204af2d937c9c110117331b69094
MD5 7aada20feb7bb4f88b75075246c9451f
BLAKE2b-256 787086d81bddbb28300f54ae0bff5a4cf09f6ea4bb5be8d1ea31905c6e834510

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 1009f95e698290f826e3dfe8d8697bf5045c7c10de5ae86c8fc08f7a63cbd1f7
MD5 9dc8d47c1da68cc71f85ffb422c272e7
BLAKE2b-256 96d6c7b41043920e57e4977ab1ff2da1eeee5b4dc9f68414faf980130019d3b7

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 5515f255469b9789ad054acdae0bdf5ecf1a9412c2b0840c4539f275fceab11d
MD5 817603dd22f2d30b692b23eed729cee2
BLAKE2b-256 5a01421fff628ea28bcbfd52385f6627fde62683fb27ee5f38ba759a2ab2a56f

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-win32.whl
Algorithm Hash digest
SHA256 a202dcc6e3f272318fa5c2b53f1424a43392f205e855efbe15ac6578d4d7027c
MD5 20db8d2ec9f6f9d54bcc2a5bfb763707
BLAKE2b-256 88aef1e0d8cff23db53fd19099bdf3f2fff8bef4df00a10ff87cead15adcff7c

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 309e5a3901f55f123ad6f61fa911ed06f6346a23005658c6b7c2c731745ddd36
MD5 e795c7082fdca0e2fc85f6eedc272128
BLAKE2b-256 597c51a9fe1b11149eb8f82628164cf008022fe80f77d27db14d8aedfaba9602

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 c8534eb43ab9df8e64b1b6af92c06d895367a7db6b1b0c88c90174c1fef13591
MD5 eb61c04e09355d256283b05906cab850
BLAKE2b-256 1f0de074d9d7e5f9e44feb7ab9b5f1a46ee80f3e915d29a8dade65d5a1efa87e

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 8ac1a0f47e92601a15e6a8a1363e2a340612670bac6432719a52940428fc0b41
MD5 5577c745e38cb4189b21d05ee7040e5c
BLAKE2b-256 38c6161168c16cee08f85744a04f329fff160b7e778649d5b2c4753864e031c8

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 4283d9aa9800163aa58fe1f404a74f84131b4971f06b1e968675ece314e14211
MD5 69d61d21e1481109d0283453dd15b7fb
BLAKE2b-256 a53d75f8c9da5eac5552833f4c15d6d60dc522b8362d1badf427a80d6e87c2cc

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 7d57220e13e5242c3debd134b85038275d9b220403a77243e24573a630c79c98
MD5 ccf5cfc5960664209554b2b97bcb1132
BLAKE2b-256 db91e5bd426d48075a715be12db12654cd893192605048da6335dbd04240f5f6

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 003203520aadfe308bebc868a69a40e1ea8e1a837171e33135c328b7bfffd9d6
MD5 3fde9f2a3bac4f0b4401a5fed37e99c7
BLAKE2b-256 36c35888841d95299d72d035ec8f3fda624009ae521f773a3e29fd6a199fb294

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 bc73f8584f993f2aa063ad525e8e1377edd6c315b7093ebcbc9f476054bf163f
MD5 362d8c3336185413a5175e55c6e7d727
BLAKE2b-256 ef4a1b4b4ded508dcca1ee889333c1a6d0303e9ba50bd97571a08d156fbb8a73

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-win32.whl
Algorithm Hash digest
SHA256 6ccd1557a7ae6a8a548e8fd3e6bacd56cb1ef8267cec30c44df7558069d2c12b
MD5 b3d35bfdc84e7557abb59921324474f9
BLAKE2b-256 5535ece064fc9ac5e96e7a486e8454508752697c88969e2a738fab5ed6a72bb8

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 4210ff4ecd141914b01b102b9951549a56fee78f900f1119df88e552e557496b
MD5 1c5381c6099c978aaec8961abfa39421
BLAKE2b-256 0dbdbba1091985d08e68978145af09827c89259ee884abaf8212170f3b2717f7

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 e14b85ea750fee16fc291b988b0ba5d0fe8f2534add6404e714180b4b982f3cc
MD5 af02ad36a02fbdb826d8959f103f616b
BLAKE2b-256 1d2adf1f91389560559b9246835fdce65feb03a465dfe448d5e6e63368895a13

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 c549b6a1e41705b2618e6a29cdf4b953b60a2634201145ca2739595858a588f6
MD5 8de0f30912ca1bedec9257e3d58a8953
BLAKE2b-256 5c9547e35760d4fdb6bde1323a21a6d76e3262613a33d23afeaf1749e69d7a44

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 90e2e3fbeaab10b2812a1ab8cdecf50324b90cd9863bfc0fbffc499f84ca57f5
MD5 7f57f5456841173c8233218f1cc72d3b
BLAKE2b-256 208e87fb57d5501812c09235da42bca00b915c95ccef4d065487c4543326d243

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 68a6015316dde44bdcfba593a9a78b1b0b95aa12e25c8c86da517b4534b7b01f
MD5 3b8de8ec0f8644068180c73d09bac771
BLAKE2b-256 5c108fdd887a9a9b9c81bee12c65607f89eaf18fe77fb0947e0eae5806e00361

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 b1e367e0f3773b1a1bde9643ecae90436a8be87cff9290ee5516e03b124754fb
MD5 b29cb7fa61c65ac10b359b19b5001c67
BLAKE2b-256 8d8b93458cd8535f970116c65e27146a761b4f0e4d006d8b4f914509dd379c8a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 2629a0a3aba0adbcbcd3c70b17070a305376b46f2255d1445b4ea1c8f50b66e2
MD5 f9f089c73b57aa45630730b5c0cbcb1e
BLAKE2b-256 a604309ec78f0e37eddaf49727d2fe597422ec13feb09e9617f3c6f75cab9221

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-win32.whl
Algorithm Hash digest
SHA256 6b01cc7f748fe3805025abf68b4e5e07c465b86c2d1eac9797ee1917f35a32a3
MD5 ead818d7d6ed8fc55899f6b7bcc8a048
BLAKE2b-256 d073269f0d76fab44dc11792f2ec082710c09de20bbccc69217da5e90607c2b6

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 a44c21f71bd2ee52107d7670dbcf8288b370df5090ca2d4acf58614770221012
MD5 7ddcc6b50fa0b3e5dfa6b945e4a9e971
BLAKE2b-256 e5360ae9426c454942532dbde80585b357b4a050efc871b1fffe52f01cdf3e58

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 5473e710c31814878512036efc216d56a44733ddc1dc813144b6b7f8114b31b0
MD5 5dbfe5fca80f76a47772fcf51090c1bf
BLAKE2b-256 b26a5b963bfa9c52d8f436fe54c8d00a60df4517cce753246deae1b6d667d84a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 97f67fe984c7fe7b24726dbba5e0066a9efbfa6f806f68dd18fadfed214cf9ff
MD5 7552f17667dde2d2529e2cd9a768b7f9
BLAKE2b-256 9dac333ee5c00698c38e974bc3b8d7f094b3cf6c2f659b6254c41a8c6f0e10df

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_17_aarch64.manylinux2014_aarch64.whl
Algorithm Hash digest
SHA256 2e22a2a03ff1535ffc5b8eab7de850a63056ab70e68dad1a931e104a2abc3392
MD5 d15dc278133b48b329e5fdc775e32c15
BLAKE2b-256 3afb75869ec278de2f9525c369eae92bb87214cc52f66a7dcecbc589205e47ec

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 dca8efcbd3b3dd4275258c1e0f081fd7f2367de898ff1a53ea74c2de7749bf74
MD5 93fe3b44179ddbc95e27ade954d33d84
BLAKE2b-256 70e365ba4a22f25c1aa33114323bcec0690bfe087e122a6784b151afa737783a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 2a4fc0e208e50cecabc139da11f0b9311c4573707fed79d7c3eee6b768552c55
MD5 e9285f3945c510284647b2eb7036bd4b
BLAKE2b-256 169f6f0f7d3ac5b2ab65757ad2c64f5120addf57b7241c3c6d10dd87f568b05d

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-win_amd64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-win_amd64.whl
Algorithm Hash digest
SHA256 90c388a3ead6b65b11c99ea58b28d78901141f3875703820c095f04e2fab7465
MD5 e29a5ce46dd1687e7e98ee003c27e2a3
BLAKE2b-256 930ee4e2b59321b91043f785f74aae3b5ee00b43aee6e56fd52458b126c36d36

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-win32.whl.

File metadata

  • Download URL: pyEDFlib-0.1.35-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/3.9.18

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-win32.whl
Algorithm Hash digest
SHA256 65e46fee896e54a7787f6adb08096c24e21c324f37ff93d3e4e4f79e3d128b53
MD5 b8fdcf7a09fe3b9dc52f752a79a13bbe
BLAKE2b-256 f5a45cc1e5fb2445b38fde334a8509391d60b3ea33b224102f88da56f12dd91f

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_x86_64.whl
Algorithm Hash digest
SHA256 5fd842cf1f9378fbc89e5a3e0ab72bc06343981911cb932772d4f7a87c30cc47
MD5 2ea09cc9fcddd4d2e127e90dc06e9acc
BLAKE2b-256 228464522d1271c447164cea3c8e5948e4275d8c172e921a8254160c6f766f63

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-musllinux_1_1_i686.whl
Algorithm Hash digest
SHA256 715ec1a7106865c0bb5e87e7275581ee6e80bd9c29d100a6291f2036d2db399f
MD5 e7c957ac20ffef9081eca538dd877496
BLAKE2b-256 270f995626da8e2c85987b757a9bedbd1c651dc50159a1f58984048aa1fb02f1

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_17_x86_64.manylinux2014_x86_64.whl
Algorithm Hash digest
SHA256 18df844783603d8ea5ac32e488ab3225f2108515afff1a7864488895fab79455
MD5 655887766945d360bcef1b6d478453c6
BLAKE2b-256 ef73e897846a290d61895111a6ffd7438b72c8a7330d421e5686a4cb1d28182a

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-manylinux_2_5_i686.manylinux1_i686.manylinux_2_17_i686.manylinux2014_i686.whl
Algorithm Hash digest
SHA256 d9f3eb8952ff8478c1fdef003073edf3a1bfec3d41d5b0805d979eb7ce6d42b0
MD5 3f9de3991a47b6b5dbb2acf0e2ac5563
BLAKE2b-256 cd30eda1fffd358a20c204f80ce36941ef3c6989476c2dcef008fe52353a5c88

See more details on using hashes here.

File details

Details for the file pyEDFlib-0.1.35-cp36-cp36m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for pyEDFlib-0.1.35-cp36-cp36m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 52653695f03aee25c0e3e754c634114f655b314f00d9d6264486b38f0bcb35db
MD5 76b676618d66408ef1cbd8ab427f80d9
BLAKE2b-256 26a425d6930d199aa4729dedf1ee85824cc5ef46222ab529c7446a742c7ec495

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