Saravanan666/pypi-org huggingface dataset:
Package: benchsuite.scheduler
Benchmarking Suite SchedulerThis component is a simple scheduler to execute and repeat Benchmarking Suite tests after a given time interval. The scheduling is read from a MongoDB collection.DocumentationUser and technical documentation is available athttp://benchmarking-suite.readthedocs.io/.SupportFor bugs, enhancements or support go tohttps://github.com/benchmarking-suite/benchsuite-issues/issues/.LegalThe Benchmarking Suite is released under theApache 2.0license.Copyright © 2014-2018 Engineering Ingegneria Informatica S.p.A. All rights reserved.This work has received partial funding from the European Commission under grant agreements No. FP7-317859 and No. H2020-732258
Package: benchsuite.stdlib
Benchmarking Suite Standard LibraryThe standard library for Benchmarking SuiteDocumentationUser and technical documentation is available athttp://benchmarking-suite.readthedocs.io/.SupportFor bugs, enhancements or support go tohttps://github.com/benchmarking-suite/benchsuite-issues/issues/.LegalThe Benchmarking Suite is released under theApache 2.0license.Copyright © 2014-2018 Engineering Ingegneria Informatica S.p.A. All rights reserved.This work has received partial funding from the European Commission under grant agreements No. FP7-317859 and No. H2020-732258
Package: bench-utils
Benchmark UtilitiesAboutA collection of benchmarking
tools.PYPI PackageTable of ContentsUsing the libraryInstalling and using the libraryManually install the libraryPrerequisitesInstall the requirementsUpdate PyPI packageLicenseUsing the libraryInstalling and using the libraryFirst, you need to install the library either using pip:$pipinstallbench_utilsThen, import it and use it like so:frombench_utilsimporttimeit,profileit# --- Timeit --- ## Context Managerwithtimeit():# A code blockpass@timeit()defmy_func():# Function codepass# --- Profileit --- ## Context Managerwithprofileit():# A code blockpass@profileit()defmy_func():# Function codepassFor more advanced examples
checkexample_timeit.pyandexample_profileit.py.Manually install the libraryThese instructions will get you a copy of the project up and running on your local machine for
development and testing purposes.PrerequisitesYou need to have a machine withanacondainstalled and
any Bash based shell (e.g. zsh) installed.$ conda -V
conda 4.10.1

$ echo $SHELL
/usr/bin/zshInstall the requirementsAll the installation steps are being handled by
theMakefile.First, modify the python version (min_python) and everything else you need in
thesettings.ini.Then, execute the following commands:$ make create_env
$ conda activate yaml_config_wrapper
$ make distNow you are ready to use and modify the library.Update PyPI packageThis is mainly for future reference for the developers of this project. First,
create a file called~/.pypircwith your pypi login details, as follows:[pypi]
username = your_pypi_username
password = your_pypi_passwordThen, modify the python version (min_python), project status (status), release version (version)
and everything else you need in
thesettings.ini.Finally, execute the following commands:$ make create_env
$ conda activate yaml_config_wrapper
$ make releaseFor a dev release, change thetesting_versionand instead ofmake release, runmake release_test.LicenseThis project is licensed under the MIT License - see
theLICENSEfile for details.
Package: benchwork
benchworkA framework for benchmarking in pythonInstallationpipinstall-UbenchworkUsagefrombenchworkimport(BenchAPI,BenchCaseSpeed,BenchSuite,BenchSetSpeed,BenchSetVersion,run_suite,)classBenchAPIPackage1(BenchAPI):name="package1"version="0.0.1"classBenchAPIPackage2(BenchAPI):name="package2"version="0.0.2"classBenchCaseSpeed(BenchCaseSpeed):timeit_number=10defrun_core(self):importtimetime.sleep(.1)classBenchSetSpeed(BenchSetSpeed):case=BenchCaseSpeedclassBenchSuite(BenchSuite):"""Benchmarking suite"""set_classes=[BenchSetVersion,BenchSetSpeed]if__name__=="__main__":run_suite(BenchSuite,None,"Benchmarking")Output:# BenchmarkingBenchmarking suite## VersionsShow versions of testing packages

| |Version|
|-|-----------------------|
|package1|0.0.1|
|package2|0.0.2|## Running speed| |Speed|
|-|-----------------------|
|package1|1.003228693996789|
|package2|1.0028911930057802|
Package: bencode-open
bencodebencode-openis an open-source MIT-licensed library for parsing and converting
objects to and fromBencode format.Rationalebencode-openis MIT-licensed and can thus be included to almost all software,
compared tobencodeandbencode.py.Installationbencode-openis available onGitHuband onPyPI.Installingbencode-openfrom PyPI is recommended and can be done as follows:pip install bencode-openUsageimportbencode_openprint(bencode_open.dumps(b"Hello?"))# Outputs b"6:Hello?"print(bencode_open.dumps(17))# Outputs b"i17e"print(bencode_open.loads(b"6:Hello?"))# Outputs b"Hello?"print(bencode_open.loads(b"i17e"))# Outputs 17Running testspython test.py
Package: bencode-parser
bencode-parserBencode parser for python.For more information about bencode format please refer towiki_pageINSTALLATION$ pip install bencode-parserUSAGE>>> import bencode
>>> bencode.decode('3:abc')
'abc'
>>> bencode.decode('i123e')
123
>>> bencode.decode('li1ei2ei3ee')
[1, 2, 3]
>>> bencode.decode('d1:1i1e1:2i2e1:3i3ee')
{'1': 1, '3': 3, '2': 2}
>>> bencode.encode('abc')
'3:abc'
>>> bencode.encode(123)
'i123e'
>>> bencode.encode([1,2,3])
'li1ei2ei3ee'
>>> bencode.encode({'1': 1, '3': 3, '2': 2})
'd1:1i1e1:3i3e1:2i2ee'
Package: bencode.py
Simple bencode parser (for Python 2, Python 3 and PyPy), forked from thebencodepackage by Thomas Rampelberg.UsageEncode:>>>importbencodepy>>>bencodepy.encode({'title':'Example'})b'd5:title7:Examplee'>>>bencodepy.encode(12)b'i12e'Decode:>>>importbencodepy>>>bencodepy.decode('d5:title7:Examplee'){b'title':b'Example'}>>>bencodepy.decode('i12e')12Decode to UTF-8:>>>importbencodepy>>>bc=bencodepy.Bencode(encoding='utf-8')>>>bc.decode('d5:title7:Examplee'){'title':'Example'}bencode(legacy, backwards-compatible package)This package will continue to be provided for backwards-compatibility, but upgrading tobencodepyis recommended for more reliable decoding results.Under-the-hood this just provides proxies to aBencodeinstance created with:Bencode(encoding='utf-8',encoding_fallback='value',dict_ordered=True,dict_ordered_sort=True)Encode:>>>importbencode>>>bencode.encode({'title':'Example'})'d5:title7:Examplee'>>>bencode.encode(12)'i12e'Decode:>>>importbencode>>>bencode.decode('d5:title7:Examplee')OrderedDict([(u'title',u'Example')])>>>bencode.decode('i12e')12APIbencodepy.Bencode(encoding=None, encoding_fallback=None, dict_ordered=False, dict_ordered_sort=False)Create instanceencodingEncoding to decode strings with (orNonefor binary)encoding_fallbackFallback to binary when decoding fails on the specified string types.key- dictionary keysvalue- valuesall- always fallback to binaryNone- always raise decoding errorsdict_orderedUseOrderedDictdict_ordered_sortEnsureOrderedDictis sortedMethods:decode(value)Decode bencode stringvalue.encode(value)Encodevalueinto a bencode string.read(fd)Decode bencode from file or pathfd.write(data, fd)Encodedatato file or pathfd.bencodepy.BencodeDecoder(encoding=None, encoding_fallback=None, dict_ordered=False, dict_ordered_sort=False)Create decoderencodingEncoding to decode strings with (orNonefor binary)encoding_fallbackFallback to binary when decoding fails on the specified string types.key- dictionary keysvalue- valuesall- always fallback to binaryNone- always raise decoding errorsdict_orderedUseOrderedDictdict_ordered_sortEnsureOrderedDictis sortedMethods:decode(value)Decode bencode stringvalue.bencodepy.BencodeEncoder()Create encoderMethods:encode(value)Encodevalueinto a bencode string.bencodepy.bencode(value)bencodepy.encode(value)Encodevalueinto a bencode string with the default encoder.bencodepy.bdecode(value)bencodepy.decode(value)Decode bencode stringvaluewith the default decoder.bencodepy.bread(fd)Decode bencode from file or pathfdwith the default decoder.bencodepy.bwrite(data, fd)Encodedatato file or pathfdwith the default encoder.bencodebencode.bencode(value)bencode.encode(value)Encodevalueinto the bencode format.bencode.bdecode(value)bencode.decode(value)Decode bencode formatted stringvalue.bencode.bread(fd)Read bencode formatted string from file or pathfd.bencode.bwrite(data, fd)Writedataas a bencode formatted string to file or pathfd.
Package: bencode-python
BencodeBencode encoder and decoder written in python.Installationpipinstallbencode-pythonUsageDecoderDecoding bencode data.frombencode.decoderimportDecoderdecoder=Decoder()decoded=decoder.decode(b"i42e")print(decoded)# 42EncoderEncoding Python data types into bencode format.frombencode.encoderimportEncoderencoder=Encoder()encoded=encoder.encode(42)print(encoded)# b'i42e'LicenseLicensed under the MIT License.
Package: bencoder.pyx
A fast bencode implementation in Cython supports both Python2 & Python3 .Installpipinstallbencoder.pyxUsagefrombencoderimportbencode,bdecode,bdecode2assertbencode("WWWWWW")==b'6:WWWWWW'assertbencode(233)==b'i233e'withopen("debian-8.3.0-amd64-netinst.iso.torrent","rb")asf:torrent=bdecode(f.read())print(torrent['announce'])decoded,length=bdecode2(b'6:WWWWWWi233e')assertdecoded==b'WWWWWW'assertlength==8ChangeLogVersion 3.0.1Add support for Python 3.11Versoin 3.0.0Add support for Python 3.9 & 3.10Drop support for Python 2Build wheels for musl & aarch64Version 2.0.1Add support for Python 3.8Drop support for Python 3.4Version 2.0.0Use built-in dict instead of OrderedDict on Python >= 3.7Drop support for Python 3.3Fix bytes parsing when used with python-future#41Version 1.2.1Drop support for Python 2.6Performance boost forbencodemethod.#7Version 1.2.0Addbdecode2method.#6Version 1.1.3Performance ImprovementFix package metainfo#3Version 1.1.2Support encode large intVersion 1.1.0Use OrderedDict instaed of dictSupport encoding subclasses of dict
Package: bencode-vug
BencodeA module that mimics thejsonstandard lib module interface for
BencodeInstallationSimply clone the repository and then run the following on the root dir of the repo.python3-mbuild&&python3-mpipinstalldist/bencode-0.0.1-py3-none-any.whlUsageReading bencoded dataBothloadandloadsfunctions will decode bencoded data.importbencodedecoded_dic=bencode.loads(encoded_data)# deserializing bencoded data from a filewithopen("bencoded_file.torrent","rb")asfp:decoded_dic=bencode.load(fp)Encoding dataPragmatically, only dictionaries are encoded in real life applications of this encoding format, but any other supported types can be singularly encoded.importbencodepeers_dic={b'peers':[{b'127.0.0.1':b'29123'},{b'127.0.0.1':b'6432'}]}# b'd5:peersld9:127.0.0.15:29123ed9:127.0.0.14:6432eee'bencoded_peers=bencode.dumps(peers_dic)# serialize an object as a bencoded stream to a file:withopen("my_bencoded_file.torrent","rb")asfp:bencode.dump(peers_dic,fp)
Package: bencodex
This package implementsBencodexserialization format which extendsBencoding.UsageThis package’s API follows the tradition of Python’spickleandjsonmodules:bencodex.dump(obj: bencodex.BValue, fileobj: typing.BinaryIO)->Nonebencodex.dumps(obj: bencodex.BValue)->bytesbencodex.load(fileobj: typing.BinaryIO)->bencodex.BValuebencodex.loads(encoded: bytes)->bencodex.BValueExamples>>> from bencodex import dumps, loads
>>> dumps({'name': 'Jane Doe', 'age': 30, 'nationality': ['BR', 'US']})
b'du3:agei30eu4:nameu8:Jane Doeu11:nationalitylu2:BRu2:USee'
>>> loads(_)
{'age': 30, 'name': 'Jane Doe', 'nationality': ['BR', 'US']}LicenseDistributed underGPLv3or later.
Package: bendcode
A python module for decoding bencoded dataBencodingBencoding is a meta data representation format fot the BitTorrent
Protocol (BTP). The Augmented BNF syntax for Bencoding is given belowdictionary = "d" 1*(string anytype) "e"
  list       = "l" 1*anytype "e"
  integer    = "i" signumber "e"
  string     = number ":" <number long sequence of any CHAR>
  anytype    = dictionary / list / integer / string
  signumber  = "-" number / number
  number     = 1*DIGIT
  CHAR       = %x00-FF
  DIGIT      = "0" / "1" / "2" / "3" / "4" /
               "5" / "6" / "7" / "8" / "9"Source:BTP
RFCUsageDecoding bencoded data is simple.>>> import bendcode
>>> bendcode.decode('i123e')
123
>>> bendcode.decode('4:John')
'John'
>>> bendcode.decode('li234ei123ee')
[234, 123]
>>> bendcode.decode('d1:ai123e1:bi234ee')
{'a': 123, 'b': 234}You can decode invidual types too !>>> import bendcode
>>> bendcode.match_string('3:abc')
('abc', '')
>>> bendcode.match_int('i-123e')
(-123, '')
>>> bendcode.match_list('li123ee')
([123], '')
>>> bendcode.match_dict('d1:a1:bei123e')
({'a': 'b'}, 'i123e')Note:The match_* series of functions return a tuple(first_possbile_match, remaining_unmatched_string)Bendcodecan encode too>>> import bendcode
>>> bendcode.encode(123)
'i123e'
>>> bendcode.encode('John')
'4:John'
>>> bendcode.encode([123, 'bro'])
'li123e3:broe'
>>> bendcode.encode({'hello': 123})
'd5:helloi123ee'
>>> bendcode.encode(None)
''You decide whether to raise an exception or not for any functions
mentioned above by setting thefail_silentlyparameter toTrueorFalse>>> import bendcode
>>> bendcode.match_string('abc')
(None, 'abc')
>>> bendcode.match_string('abc', fail_silently=False)
Traceback (most recent call last):
  File "<stdin>", line 1, in <module>
  File "bendcode\bendcode.py", line 39, in match_string
    raise MalformedBencodeError('Failed to match string in ' + str(raw))
bendcode.exceptions.MalformedBencodeError: Failed to match string in abcTestsRun tests using the following code>>> from bendcode import tests
>>> tests.run_tests()
..................................
----------------------------------------
Ran 34 tests in 0.015s

OKIssuesIf you find any bug, feel free to create an issuehere.LicenseBenDcode uses GNU v2 License. Read the terms of the licensehere.
Package: bendeep
BENDeepBENDeepis a pytorch based deep learning solution for Bengali NLP Task likebengali translation,bengali sentiment analysisand so on.Installationpip install bendeepDependencypytorch 1.5.0+Pretrained ModelSentiment AnalysisTranslation ModelAPISentiment AnalysisAnalyzing SentimentThis sentiment analysis model is a RNN basedGRUmodel trained withsocian sentiment datasetwith loss 0.073 in 150 epochs.
Dataset size: 4000 sentencesfrombendeepimportsentimentmodel_path="senti_trained.pt"vocab_path="vocab.txt"text="রোহিঙ্গা মুসলমানদের দুর্ভোগের অন্ত নেই।জলে কুমির ডাংগায় বাঘ।আজকে দুটি ঘটনা আমাকে ভীষণ ব্যতিত করেছে।নিরবে কিছুক্ষন অশ্রু বিসর্জন দিয়ে মনটাকে হাল্কা করার ব্যর্থ প্রয়াস চালিয়েছি।"sentiment.analyze(model_path,vocab_path,text)Training Sentiment ModelTo train this model you need a csv file with one columnreviewmeans text and another columnsentimentwith 0 or 1, where 1 for positive and 0 for negative sentiment.Example:,review,sentiment
0,তোমাকে খুব সুন্দর লাগছে।,1
1,আজকের আবহাওয়া খুব খারাপ।,0reviewsentiment0তোমাকে খুব সুন্দর লাগছে।11আজকের আবহাওয়া খুব খারাপ।0frombendeepimportsentimentdata_path="sentiment_data.csv"sentiment.train(data_path)# you can also pass these parameter# sentiment.train(data_path, batch_size = 64, epochs=100, model_name="trained.pt")after successfully training it will complete training and save model astrained.ptalso save vocab file asvocab.txtMachine TranslationTranslate Bengali to EnglishThis model is a seq2seq attentional model trained withthisdataset with loss 0.0.frombendeepimporttranslationfrombendeep.translationimportEncoderRNNfrombendeep.translationimportAttnDecoderRNNdata_path="data/translation/eng-ben.txt"encoder="models/translation/encoder.pt"decoder="models/translation/decoder.pt"input_sentence="আমার শীত করছে।"translation.bn2en(data_path,encoder,decoder,input_sentence)# outupt# > আমার শীত করছে ।# = i feel cold .Training Translation ModelTo train translation model you need a dataset in.txtformat with tab separateinputandtargetsentences.Example:I eat rice. আমি ভাত খাই।
He goes to school.  সে বিদ্যালয়ে যায়।frombendeepimporttranslationfrombendeep.translationimportEncoderRNNfrombendeep.translationimportAttnDecoderRNNdata_path="data/translation/eng-ben.txt"translation.training(data_path,iteration=10000)after successfully training it will complete training and save encoder and decoder model asencoder.pt,decoder.pt. Also display some random evaluation results.Referencespytorchpytorch tutorialen-bn datasetsocian sentiment dataset
Package: bendercito
# bendercitoChange your Slack status from command line.## InstallTo install **bendercito**, just run:```sh$ sudo pip install bendercito```## ConfigureFirst create a config file with your favorite status.Example config.json:```javascript{"clean":{"emoji": "","message": ""},"pomodoro":{"emoji": ":tomato:","message": "Pomodoro don't disturb"},"pairing":{"emoji": ":beers:","message": "Pairing"},"open":{"emoji": ":two_hearts:","message": "Open for Pairing"},"dinning":{"emoji": ":fork_and_knife:","message": "Dinning"},"doctor":{"emoji": ":syringe:","message": "Doctor visit"}}```Then you need to create two environment variables.```shBENDERCITO_FILE="path_to_your_config_file"BENDERCITO_SLACK_TOKEN="your_slack_token"```## Usage```sh$ bendercito pairing``````sh$ bendercito --list```
Package: bendercoder
BendercoderLibrary for encoding and decoding bencode data.Table of contentIntroductionInstallingUsageUseful LinksIntroductionBencode (pronounced like B-encode) is the encoding used by the peer-to-peer file sharing system BitTorrent for storing and transmitting loosely structured data.
It supports four different types of values:byte strings,integers,lists,dictionaries (associative arrays).Bencoding is most commonly used in torrent files. These metadata files are simply bencoded dictionaries.Description fromwikipedia.Installingpip install bendercoderUsageFor decoding and encoding the integer number 10.# coding=utf-8fromdecoderimportDecoderfromencoderimportEncoderdecoder=Decoder(payload=b'i10e')decoded_value=decoder.decode()print(decoded_value)encoder=Encoder(payload=decoded_value)encoded_value=encoder.encode()print(encoded_value)For decoding and encoding the string foo.# coding=utf-8fromdecoderimportDecoderfromencoderimportEncoderdecoder=Decoder(payload=b'3:foo')decoded_value=decoder.decode()print(decoded_value)encoder=Encoder(payload=decoded_value)encoded_value=encoder.encode()print(encoded_value)For decoding and encoding the list [1, 2, 3, 'bar']# coding=utf-8fromdecoderimportDecoderfromencoderimportEncoderdecoder=Decoder(payload=b'li1ei2ei3e3:bare')decoded_value=decoder.decode()print(decoded_value)encoder=Encoder(payload=decoded_value)encoded_value=encoder.encode()print(encoded_value)For decoding and encoding the dictionary {'test': 'foo', 'bar': 2}# coding=utf-8fromdecoderimportDecoderfromencoderimportEncoderdecoder=Decoder(payload=b'd4:test3:foo3:bari2ee')decoded_value=decoder.decode()print(decoded_value)encoder=Encoder(payload=decoded_value)encoded_value=encoder.encode()print(encoded_value)LinksWikipediaTheory.orgbittorrent.org
Package: bender-hooks
bender-hooksis a library which provides ways to easily create, search and invoke hooks anywhere in your
code.Hooks will be created as decorators so all you have to do is decorating functions you want to be
invoked through that hook.It can be used to define interfaces or callbacks for your application.InstallTo installbender-hooksall it takes is one command line:pip install bender-hooksDocumentationGetting startedAPISupportNeed help? Clickhereand open a new issue. You’ll get your answer ASAP.Contributebender-hooksis under development, so if you want to join the team, you are welcome.Feel free toopen issuesrelated to bugs or ideas.If you are a developer:Forkbender-hooksbefore making any changes.Write tests.Create aPull Requestso changes can be merged.Licensebender-hooksis licensed underLGPL v3.0 license.
Package: benderthon
Set of utilities to work easier withBender.Currently there’s support for TensorFlow and Caffe, but we are working
on more stuff!Works on Python 2.7.+ and 3.+, with Tensorflow 1.2+.To install:pipinstallbenderthonTensorFlow is required too. The simplest way to install it is:pipinstalltensorflowThere are other ways, seeInstalling
Tensorflow. Benderthon does not
install it by default to let the usage of a custom installation.tf-freezeUtility to convertTensorFlowcheckpoints into minimal frozengraphs.UsageTo take the checkpoint incheckpoint_path.ckpt, whose output is
yielded by the node namedTanh, and save it tograph_with_weights.pb:benderthontf-freezecheckpoint_path.ckptgraph_with_weights.pbTanhSampleThe filesample.pycontains a network example for MNIST dataset with
2 convolutional layers and 2 dens layers. If you run it, it will
generate checkpoints files with prefixcheckpoints/mnist.ckpt:./sample.pyThen you can get a minimal protobuf version with the weights frozen:benderthontf-freezecheckpoints/mnist.ckptoutput/mnist.pbPredictionThe generated file occupieshalfthe original checkpoints (26MB to
13MB).You can also get only the graph, which occupies just13kB:benderthontf-freeze--no-weightscheckpoints/mnist.ckptoutput/mnist_only_graph.pbPredictionTo save the weights in a separate path for later processing:benderthontf-freeze--only-weightscheckpoints/mnist.ckptweights/Predictioncaffe-freezeThis module cannot be accessed from the command line utility, it should
be used from Python code, importingbenderthon.caffe_freeze.You needcaffeflowpackage installed first:pipinstall-egit://github.com/xmartlabs/caffeflow.git@4618f89#egg=caffeflowDevelopmentThis utility is under development and the APIis not stable. So, do
not heavily rely on it.To install locally you should do./setup.py install, but first havepandocandpypandocinstalled.LicenseCopyright 2017 Xmartlabs SRL.

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

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

Unless required by applicable law or agreed to in writing, software
distributed under the License is distributed on an "AS IS" BASIS,
WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied.
See the License for the specific language governing permissions and
limitations under the License.
Package: bendev
bendevA crossplatform Python package for communicating with the USB/SCPI-enabled Bentham Instruments hardware devices such as the TLS120Xe. The package uses hidapi to send and receive text based commands and replies using the USB HID protocol.CompatibilityThis software has been tested on Mac OS X, Ubuntu, and Windows, with python 3.8 onwards. It is compatible Bentham Instruments devices with an SCPI over USB HID packet interface.Installationpip install bendevUsagebendev devices can be instantiated in context managers:>>>importbendev>>>withbendev.Device()asdev:...print(dev.query("*IDN?"))"Bentham Instruments Ltd.","MSH150_RD_Direct","99999/9","1.2.53"or normally:>>>importbendev>>>my_tls=bendev.Device()>>>my_tls.write("SYSTEM:REMOTE")>>>my_tls.query("MONO:GOTO? 555")"1"Devices can be opened by serial number, product string or manufacturer string:>>>importbendev>>>device_a=bendev.Device(serial_number="99999/9")>>>device_b=bendev.Device(product_string="TLS120Xe")>>>device_c=bendev.Device(manufacturer_string="Bentham")Forproduct_stringandmanufacturer_string, it is sufficient if the given substring is present in the device descriptor. Theserial_numberhas to be exact.manufacturer_stringdefaults to"Bentham".The package can also tell you what devices are connected:>>>importbendev>>>devs=bendev.list_connected_devices(verbose=True)ConnectedDevices:Device18:BenthamInstruments,TLS120Xe,...Known issuesOn ubuntu the python hidapi module has been noted to fail to read device strings for an unknown reason; until this is resolved the devices may be opened as raw hid devices, bypassing the hidapi module:>>>importbendev>>>my_device=bendev.Device(hidraw="/dev/hidraw2")>>>my_device.query("*IDN?")'"Bentham Instruments Ltd.","TLS120Xe","12345/6","0.5.3"'Version historyv0.0.1 - v0.0.3: test releasesv0.0.4: first releasev0.1.0: added ability to use raw hid devicesv0.1.1: fix formatting issuev0.2.0: add reconnect commandv0.3.0: add python 3.11 compatibilityv0.3.1: fix inverted vendor ID filter in list_connected_devices