Skip to main content

SAS Scripting Wrapper for Analytics Transfer (SWAT)

Project description

SAS Scripting Wrapper for Analytics Transfer (SWAT)

Overview

The SAS SWAT package is a Python interface to the SAS Cloud Analytic Services (CAS) engine (the centerpiece of the SAS Viya framework). With this package, you can load and analyze data sets of any size on your desktop or in the cloud. Since CAS can be used on a local desktop or in a hosted cloud environment, you can analyze extremely large data sets using as much processing power as you need, while still retaining the ease-of-use of Python on the client side.

Using SWAT, you can execute workflows of CAS analytic actions, then pull down the summarized data to further process on the client side in Python, or to merge with data from other sources using familiar Pandas data structures. In fact, the SWAT package mimics much of the API of the Pandas package so that using CAS should feel familiar to current Pandas users.

With the best-of-breed SAS analytics in the cloud and the use of Python and its large collection of open source packages, the SWAT package gives you access to the best of both worlds.

To view updates to this project see the Change Log.

Prerequisites

To access the CAS binary protocol (recommended), you need the following:

  • 64-bit Python 3.7 to 3.13 on Windows or Linux (see shared library notes below)

The binary protocol requires pre-compiled components found in the pip installer only. These pieces are not available as source code and are under a separate license (see documentation on SAS TK). The binary protocol offers better performance than REST, especially when transferring larger amounts of data. It also offers more advanced data loading from the client and data formatting features.

To access the CAS REST interface only, you can use the pure Python code which runs in Python 3.7 to 3.13 on all platforms. While not as fast as the binary protocol, the pure Python interface is more portable.

Linux Library Dependencies

Some Linux distributions may not install all of the needed shared libraries by default. Most notably, the shared library libnuma.so.1 is required to make binary protocol connections to CAS. If you do not have this library on your machine you can install the numactl package for your distribution to make it available to SWAT.

Python Dependencies

The SWAT package uses many features of the Pandas Python package and other dependencies of Pandas. If you do not already have version 0.16.0 or greater of Pandas installed, pip will install or update it for you when you install SWAT.

If you are using pip version 23.1 or later to install from a tar.gz file, the python wheel package is required. If you do not have this package installed, you can install it using pip.

Installation

SWAT can be installed using pip:

pip install swat

You can also install from the files on the SWAT project releases page. Simply locate the file for your platform and install it using pip as follows:

pip install https://github.com/sassoftware/python-swat/releases/download/vX.X.X/python-swat-X.X.X-platform.tar.gz

Where X.X.X is the release you want to install, and platform is the platform you are installing on. You can also use the source code distribution if you only want to use the CAS REST interface. It does not contain support for the binary protocol.

Getting Started

For the full documentation go to sassoftware.github.io/python-swat. A simple example is shown below.

Once you have SWAT installed and you have a CAS server to connect to, you can import swat and create a connection::

>>> import swat
>>> conn = swat.CAS(host, port, username, password)

Note the default port for the Python SWAT connection is 5570.

If you are using python-swat version 1.8.0 or later to connect to a SAS Viya 3.5 CAS server using Kerberos, prior to connecting you must set the Service Principal Name (SPN) using the CASSPN environment variable. For SAS Viya 3.5, the SPN string must start with 'sascas@', followed by the hostname.

export CASSPN=sascas@host

If you get an error message about the TCP/IP negClientSSL support routine, you likely have an issue with your SSL certificate configuration. See the Encryption documentation for more information.

If that is successful, you should be able to run an action on the CAS server::

>>> out = conn.serverstatus()
NOTE: Grid node action status report: 1 nodes, 6 total actions executed.
>>> print(out)
[About]

 {'CAS': 'Cloud Analytic Services',
  'Copyright': 'Copyright © 2014-2016 SAS Institute Inc. All Rights Reserved.',
  'System': {'Hostname': 'cas01',
   'Model Number': 'x86_64',
   'OS Family': 'LIN X64',
   'OS Name': 'Linux',
   'OS Release': '2.6.32-504.12.2.el6.x86_64',
   'OS Version': '#1 SMP Sun Feb 1 12:14:02 EST 2015'},
  'Version': '3.01',
  'VersionLong': 'V.03.01M0D08232016',
  'license': {'expires': '20Oct2016:00:00:00',
   'gracePeriod': 62,
   'site': 'SAS Institute Inc.',
   'siteNum': 1,
   'warningPeriod': 31}}

[server]

 Server Status

    nodes  actions
 0      1        6

[nodestatus]

 Node Status

     name        role  uptime  running  stalled
 0  cas01  controller   4.836        0        0

+ Elapsed: 0.0168s, user: 0.016s, sys: 0.001s, mem: 0.287mb

>>> conn.close()

Contributing

The Contributor Agreement details on how contributions can be made to the project. The Contributing includes instructions and rules as it relates to making contributions on the project.

Licensing

The LICENSE.md states how this package is released and licensed.

Additional Resources

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

If you're not sure about the file name format, learn more about wheel file names.

swat-1.17.0-0-cp313-cp313-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.13Windows x86-64

swat-1.17.0-0-cp313-cp313-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.13

swat-1.17.0-0-cp313-cp313-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.13macOS 11.0+ ARM64

swat-1.17.0-0-cp313-cp313-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.13macOS 10.9+ x86-64

swat-1.17.0-0-cp312-cp312-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.12Windows x86-64

swat-1.17.0-0-cp312-cp312-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.12

swat-1.17.0-0-cp312-cp312-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.12macOS 11.0+ ARM64

swat-1.17.0-0-cp312-cp312-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.12macOS 10.9+ x86-64

swat-1.17.0-0-cp311-cp311-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.11Windows x86-64

swat-1.17.0-0-cp311-cp311-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.11

swat-1.17.0-0-cp311-cp311-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.11macOS 11.0+ ARM64

swat-1.17.0-0-cp311-cp311-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.11macOS 10.9+ x86-64

swat-1.17.0-0-cp310-cp310-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.10Windows x86-64

swat-1.17.0-0-cp310-cp310-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.10

swat-1.17.0-0-cp310-cp310-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.10macOS 11.0+ ARM64

swat-1.17.0-0-cp310-cp310-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.10macOS 10.9+ x86-64

swat-1.17.0-0-cp39-cp39-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.9Windows x86-64

swat-1.17.0-0-cp39-cp39-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.9

swat-1.17.0-0-cp39-cp39-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.9macOS 11.0+ ARM64

swat-1.17.0-0-cp39-cp39-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.9macOS 10.9+ x86-64

swat-1.17.0-0-cp38-cp38-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.8Windows x86-64

swat-1.17.0-0-cp38-cp38-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.8

swat-1.17.0-0-cp38-cp38-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.8macOS 11.0+ ARM64

swat-1.17.0-0-cp38-cp38-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.8macOS 10.9+ x86-64

swat-1.17.0-0-cp37-cp37m-win_amd64.whl (61.2 MB view details)

Uploaded CPython 3.7mWindows x86-64

swat-1.17.0-0-cp37-cp37m-manylinux1_x86_64.whl (46.9 MB view details)

Uploaded CPython 3.7m

swat-1.17.0-0-cp37-cp37m-macosx_11_0_arm64.whl (466.2 kB view details)

Uploaded CPython 3.7mmacOS 11.0+ ARM64

swat-1.17.0-0-cp37-cp37m-macosx_10_9_x86_64.whl (466.2 kB view details)

Uploaded CPython 3.7mmacOS 10.9+ x86-64

File details

Details for the file swat-1.17.0-0-cp313-cp313-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp313-cp313-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.13, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp313-cp313-win_amd64.whl
Algorithm Hash digest
SHA256 d4c1a95f9761863719f25498dec5b6391f42b8e5ec833b982d994d77514957ad
MD5 c7e0383f296c48ce7a7fdd0bc6929773
BLAKE2b-256 fe69eacf068465b265ed51fed84658b51a76a82b79e72622227bd12c998db934

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp313-cp313-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp313-cp313-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 6e4d263275df1916fa39769acdf7767382130fdba9dd831acb8983cd2a73177d
MD5 b26e4347ce25a57b3af520b3ff746ad8
BLAKE2b-256 e619c64dd9f690427ff36a3192f28bbd631609826be464dd1672d19df9822420

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp313-cp313-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp313-cp313-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a29bd756b1c7729c2f26d392d05f8a0872169504337b9c6329244066993cbb9f
MD5 9a8dc3c253defc966a459fd8ef3e00c9
BLAKE2b-256 ae1b4a55b8ec50ed1e426a789b6106b838975c698f6ab80b443ac2e9d0f2c544

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp313-cp313-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp313-cp313-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 886cb45fda460ff489a578f2c5a234a8a19aafc7e7f5f52cc4a9e1c99b8f7a3e
MD5 b28b0a37c6bc68109aa17b5a0c17057c
BLAKE2b-256 808239d8f68f67789a5168e394c25403d05814bc8aa5812ddaad4466a6b0f009

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp312-cp312-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp312-cp312-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.12, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp312-cp312-win_amd64.whl
Algorithm Hash digest
SHA256 2afb988c88dd395d7abc54dd5c440cd905b31d335e99e81b7d799bf4c0eb5e54
MD5 1323c1a250e9f6336fb6c316001e96b0
BLAKE2b-256 c28e52d8756808755a2df9e443aaf8b8e53cd8a393bc43dd0343504d7e0e6042

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp312-cp312-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp312-cp312-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 881692decff34652f02be166d3e74d2227f9e86759fc4a87159a189beece9c76
MD5 4c5bc09d79f1ede93cbb714be7aab50b
BLAKE2b-256 d00efba288d59bb5d868b40a55665106c16349623d8e3779bc9e3bb51fdebe30

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp312-cp312-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp312-cp312-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 a576e3379b9045620a5a64ee8b27f92d2dac3575d3abc3b25fe5c4c3f4355f28
MD5 b1df085a66166fd8a2c69576ad336a8a
BLAKE2b-256 4095cf96cbe9faa04154d39f29b3a46a01aa852233766dff1464ab9c3fdcc873

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp312-cp312-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp312-cp312-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 e788bb32d523e76b1f98482d7852eb3acaa50ed2f765d5d718e9d540ba159d6a
MD5 e705d0e4e6cf367ed8b97269af0ab245
BLAKE2b-256 a0697515a0a382c1a27c4565bab40ae918e1bd2f1d988763c335cd7e2f406d7d

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp311-cp311-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp311-cp311-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.11, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp311-cp311-win_amd64.whl
Algorithm Hash digest
SHA256 912660b4df2ffb7e000eb5ac2352c049cfeac4f63516d92ff002197f3dfb0231
MD5 5c1cf382276625e899ffff10bc60f65a
BLAKE2b-256 435eb95c4f25c399b44151ac3b5b869321e4d68d62829afb3df0804ec5197a61

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp311-cp311-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp311-cp311-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 4709206b40ed87adaa3fd8edb697fdb41a2972c78285097148648ad72f56d2bd
MD5 abec4db0370da82d667884d8396412b9
BLAKE2b-256 c1671fc99f420aa41b811673e62721f7c5f3b6e6187660d9335cd2930a5074c2

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp311-cp311-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp311-cp311-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 5591761a72a009cf016a1ecb6d8535577379146f75d8363c5c4f39ffd1f62b73
MD5 555adf8a37d6dee0890b41ab64acb3dc
BLAKE2b-256 efa3ef46596b2f6bcececf4e03cda467a5588efbbf81b376333d0c1e876c7612

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp311-cp311-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp311-cp311-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 8550eebe28d47ce47ef090855b0a46e4cb76e51ecf850bd4fe1274438d3da474
MD5 224063fa660024c975a7e204e46ff9a5
BLAKE2b-256 187982043884b20e6504c659d242a71928989efc4d58a10141d90686b14e0629

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp310-cp310-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp310-cp310-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.10, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp310-cp310-win_amd64.whl
Algorithm Hash digest
SHA256 eb6d149a08f0f8477f2e673aba63d0db0682e9a7827dd5451d50afe13a8dd8eb
MD5 f88e07aa8c776d726606aeb79818b36b
BLAKE2b-256 903d8a644a0523167a572c9bf890bcd2b5889d12dfd462d1c4677f131be327ba

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp310-cp310-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp310-cp310-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 d0ae19b7a333f12b8e86f087038ade02d63f101844ad67976386b8c1820166fd
MD5 4efd06f354c4c3bfd5067e20488f6c18
BLAKE2b-256 7bd51aa2336caa02c0d1187aa92450965a8eaa0f1e5283138ae4b6c7e63a9333

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp310-cp310-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp310-cp310-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 f1132ff5c60845952ecf09218f55133b8bc2c09547ee18fe08ef34a5adcd4b3a
MD5 2739cf23cd8da6aa2e5a5c7483535531
BLAKE2b-256 c5f712dba45a51459fb1d174f1a1f638690e26fc127e7cce61e38d887e06e568

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp310-cp310-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp310-cp310-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 905c6a000ef5b81ee692b5010661ca2078a4e14a9e2b9dcf4748df9baba5e876
MD5 89de886e806f012e4647fd4b337229f2
BLAKE2b-256 4cf16774b199f470a175c6d18e6841289bd5dcec20d1c9fb20b8872b8bd19f45

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp39-cp39-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp39-cp39-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.9, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp39-cp39-win_amd64.whl
Algorithm Hash digest
SHA256 437cbc0be5f677b0e258fe7e53f69be09fdaa57c31719094f1e3ba704f1e18ac
MD5 3010aa162bc814421ad66763d01d2a9d
BLAKE2b-256 72aaf26097f6c1db3058aa7d0c2a0347ac2c3100febb4f09b0c41f4d2a45dfea

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp39-cp39-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp39-cp39-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 c91dbbc3ad03feb97399e3498bd3c42a77e7ecbebd1239c13251d7e6c8565771
MD5 4b47737a21a1084f9a39e0a457ebc798
BLAKE2b-256 fd83e81c1ec72118dee774865f8b986727c3e60b9169aea051572a9e412f904b

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp39-cp39-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp39-cp39-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 03c4b18abfbb1fe69fb6db49a71711d32d9283dda29b315b7824a386059e20c1
MD5 9adea5c5a7a1ab53a45af804fde195e9
BLAKE2b-256 96a0186ea3f92a635928e8b59b8ff8452a9e9404d107068b63712948af877a1f

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp39-cp39-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp39-cp39-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 60f3e1e8ffbc081b4bfec056dfb9053df3efaf51ce9f0d8e9c01b9f3c2101f4d
MD5 9c0b0a1e7c7618d0b8507e79287589ce
BLAKE2b-256 626776dec0e3bb351367676d0625e3dac84993be53428a46b4e32ef0211db400

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp38-cp38-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp38-cp38-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.8, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp38-cp38-win_amd64.whl
Algorithm Hash digest
SHA256 04df8f6228f7b33a5fabeb86b7ed29f51db9e13056db6d02f3ae9c04d34583a4
MD5 eb9b36c8d019b2da25cb121625a3304e
BLAKE2b-256 3d2a10813c6f2bb2468ec995d575d805bed278997f020b66ec8f3ba81448e77d

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp38-cp38-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp38-cp38-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 f77c7def740003e8f0cc37e73f7587fd804eff220cc4dcd4dd3fefbb2cb06b9f
MD5 44b55f9b75f0e263cafc1f189b9aba75
BLAKE2b-256 03316af31ab5d93b97cc533040a75cdfdb47242374783fa2b18e02e2a1d426e6

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp38-cp38-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp38-cp38-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 bdeb09e26093fff79b4e88b674485132245be1533e16a657b5f70735fd57ba74
MD5 33d9fd6637bd1b527483bad02a0c4c2e
BLAKE2b-256 9a364d5a1dd31433677b8398858fec1e9c96dc70da22d90e683c737220e82337

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp38-cp38-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp38-cp38-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 446ce6ce68cbcf725e38dfa1abe1ada368bf38c4b8f13837fcf68e764a308b0f
MD5 fc784902fe948638902554fb6d5490c2
BLAKE2b-256 011ac926354ea39d64ce47298b3cf3c4cab1f034019a07bf1cb97cffaeb040ea

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp37-cp37m-win_amd64.whl.

File metadata

  • Download URL: swat-1.17.0-0-cp37-cp37m-win_amd64.whl
  • Upload date:
  • Size: 61.2 MB
  • Tags: CPython 3.7m, Windows x86-64
  • Uploaded using Trusted Publishing? No
  • Uploaded via: twine/6.1.0 CPython/3.11.13

File hashes

Hashes for swat-1.17.0-0-cp37-cp37m-win_amd64.whl
Algorithm Hash digest
SHA256 c3aacfb6bfe260bc8e226c8f7cc65a593af92fd885c410fc0c0dc9a58ee16d6c
MD5 bbc26c5c5369f95da16d77fd131963e4
BLAKE2b-256 4338c34b75f94ce2c4a48622ae34f5a38db022341bbc382a46c106d436e51ae7

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp37-cp37m-manylinux1_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp37-cp37m-manylinux1_x86_64.whl
Algorithm Hash digest
SHA256 adaebf7b2135c8e9a611feac114c9d7df353b30d77c59825cd10b5c89e52de5d
MD5 3a1b99b7961e38c2c998ec0cfe60b263
BLAKE2b-256 4ab3040e6c795cd2dc97abfdbbdfba67453dd2b58ba1f2f4afd9ea9d428b6f2f

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp37-cp37m-macosx_11_0_arm64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp37-cp37m-macosx_11_0_arm64.whl
Algorithm Hash digest
SHA256 11718af5f5130bbdfb75636a90fa013fff62a8c8a6b7e89219ec2e97760d563f
MD5 40065d191fabee652efd36960382586d
BLAKE2b-256 c1abed33d8a4c9b1ee5ffc8089317493d53c2937e6ae40f76f80af79e46a58a7

See more details on using hashes here.

File details

Details for the file swat-1.17.0-0-cp37-cp37m-macosx_10_9_x86_64.whl.

File metadata

File hashes

Hashes for swat-1.17.0-0-cp37-cp37m-macosx_10_9_x86_64.whl
Algorithm Hash digest
SHA256 05d9af02fcfddc7c88fec58ed0c0c48c30915606d9c0b8ef49dfde65d50cc04a
MD5 8086bd9cbb9e2a90701a2708cfab007e
BLAKE2b-256 eb9c5136641e8f50aea7107ea0842f2d091b4611553c8fdf8044cbf5913d1ef4

See more details on using hashes here.

Supported by

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