Saravanan666/pypi-org huggingface dataset:
Package: transdoc
Transdoc 💗🤍💙A simple tool for transforming Python docstrings, by embedding results from
Python function calls.UsageCreating rules is as simple as defining Python functions.They can then be used by placing their name within{{double braces}}in
any docstring.>>>importtransdoc>>>defmy_rule()->str:..."""...     A simple rule for rewriting docstrings...     """...returnf"This text was added by Transdoc!"...>>>defsay_hi(name:str)->str:..."""...     Says hello to someone....     {{my_rule}}...     """...returnf"Hello,{name}!"...>>>transdoc.transform(say_hi,[my_rule])defsay_hi(name:str)->str:"""Says hello to someone.This text was added by Transdoc!"""returnf"Hello,{name}!"Rules can be as complex as you need, accepting any number of arguments. You can
call them like you would call the original Python function.>>>defrepeat(text:str,n:int=2)->str:..."""...     Repeat the given text any number of times....     """...return" ".join([textfor_inrange(n)])...>>>defsay_hi(name:str)->str:..."""...     Says hello to someone....     {{repeat('wowee!')}}...     {{repeat('WOWEE!', n=5)}}...     """...returnf"Hello,{name}!"...>>>transdoc.transform(say_hi,[repeat])defsay_hi(name:str)->str:"""Says hello to someone.Wowee! Wowee!WOWEE! WOWEE! WOWEE! WOWEE! WOWEE!"""returnf"Hello,{name}!"Since passing a single string as an argument is so common, Transdoc adds a
special syntax for this. Simply place the string argument in square brackets.>>>defmdn_link(e:str)->str:..."""...     Return a Markdown-formatted link for an HTML element...     """...return(...f"[View <{e}> on MDN]"...f"(https://developer.mozilla.org/en-US/docs/Web/HTML/Element/{e})"...)...>>>defmake_link(text:str,href:str)->str:..."""...     Generate an HTML link....     {{mdn_link[a]}}...     """...# Please don't write code this insecure in real life...returnf"<a href={href}>{text}</a>"...>>>transdoc.transform(make_link,[repeat])defgenerate_link(text:str,href:str)->str:"""Generate an HTML link.[View <a> on MDN](https://developer.mozilla.org/en-US/docs/Web/HTML/Element/a)"""# Please don't write code this insecure in real lifereturnf"<a href={href}>{text}</a>"Note on REPL usageTransdoc doesn't work in a REPL, since Python doesn't store the source code for
functions defined in a REPL environment. The above examples are instead used
to demonstrate Transdoc's capabilities.
Package: transducer
This is a port of thetransducerconcept from Clojure to Python,
with an emphasis on providing as Pythonic as interpretation of
transducers as possible, rather than reproducing Clojurisms more
literally.Installable Python packageThis package is available on the Python Package Index (PyPI) astransducer.StatusBuild status:Note: Documentation is very much a work in progress.What are transducers?Transducers are functions which transform reducers - hence the name.
A reducer, in this case, is any function which you could pass to thereduce()function in the Python Standard Libraryfunctoolsmodule. Such reducers accept an initial or intermediate result and
combine a new value with that result to produce a new (or updated)
result.  Transducers provide us with a convenient means to compose
simple reducers into more complex and capable reducers.Furthermore, transducers facilitate the clean separation of
concerns of how source values are input, how they are
processed by reducers, and the how results output. This allows the
same transducers to be (re)used with many sources and destinations
of data, not just with iterable series.Transducers were developed by Rich Hickey, the driving force behind
the Clojure programming language, and this package aims to bring
the benefits of transducers to Python 3, whilst transforming some of
the Clojurisms into more Pythonic solutions.An extended write-up of the development of Python transducers from
scratch can be found in our series of articlesUnderstanding Transducers Through Python.
The code developed over the course of these articles is substantially
the same as in thistransducerpackage, although the package uses
some further abstractions and tools which are largely irrelevant to
understanding how transducers work.This package, implements simple infrastructure for implementing
transducers in Python, a selection of transducer implementations of
common operations, and some ‘transducible processes’ which allow us
to apply transducers to iterable series (both eagerly and lazily) and
to use transducers to process ‘push’ events implemented as Python
coroutines.
Package: transencoding
Convert encoding of given file from one encoding to another.Installpip install transencodingUsageE:\transencoding>python transencoding.py --help
Usage: transencoding.py [OPTIONS] [INPUT]

Options:
-f, --from-code TEXT  Encoding of original text  [required]
-t, --to-code TEXT    encoding for output  [required]
-o, --output TEXT     output file
--help                Show this message and exit.Example将utf8.txt中的utf8编码的文本转化为gbk编码，并保存到gbk.txt文件中。E:\transencoding>python transencoding.py -f utf8 -t gbk utf8.txt > gbk.txt
Package: transfacpred
TransFacPredA highly accurate method to predict the transcription factors using protein sequences.IntroductionTransFacPred is developed for predicting the transcription factors (TFs) using the protein primary sequence information. In this approach, Hybrid model was implemented in which is a combination of ET-based model and BLAST Search.Webserver and StandaloneAvailable as web-server athttps://webs.iiitd.edu.in/raghava/transfacpredAvailable as standalone athttps://github.com/raghavagps/transfacpred/InstallationTo install the Transfacpred package, use the following command:pipinstalltransfacpredMinimum USAGETo explore the available options for the command-line tool, use:transfacpred-hFull Usageusage:transfacpred[-h][-iINPUT[-oOUTPUT][-tTHRESHOLD][-d{1,2}]Pleaseprovidefollowingargumentsforsuccessfulrun

optionalarguments:-h,--helpshowthishelpmessageandexit-iINPUT,--inputINPUTInput:FilenamecontainingproteinorpeptidesequenceinFASTAformat.-oOUTPUT,--outputOUTPUTOutput:Fileforsavingresultsbydefaultoutfile.csv-tTHRESHOLD,--thresholdTHRESHOLDThreshold:Valuebetween-0.5to1.5bydefault-0.38-d{1,2},--display{1,2}Display:1:TranscriptionFactors,2:AllSequences,bydefault1Input File:It allow users to provide input in the FASTA format.Output File:Program will save the results in the CSV format, in case user do not provide output file name, it will be stored in "outfile.csv".Threshold:User should provide threshold between -0.5 and 1.5.Example usage details:transfacpred.py-iprotein.faThis will predict if the submitted sequences are TFs or Non-TFs and display only the TFs. It will use other parameters by default. It will save the output in "outfile.csv"transfacpred-iprotein.fa-ooutput.csv-t0.55-d2This will predict if the submitted sequences are TFs or Non-TFs and display all. It will save the output in "output.csv" in CSV (comma seperated variables).ReferencePatiyal et al. (2022) A hybrid approach for predicting transcription factors.Bioxriv doi:https://doi.org/10.1101/2022.07.13.499865
Package: transfat
transfatPurposetransfat's purpose is to make playing music files on your car stereo over USB not a total nightmare. Some car stereos play audio files from a (FAT-only) USB device in the order that the files were transfered to the device. In general, this is not an alphanumeric order. This means that when you put on an album, it might start from track 6, then go to track 9 or something. To make things worse, many of these stereos demand that your audio files be either MP3s or WMAs; so say good-bye to your FLACs and Oggs.Ideally, car stereos should not depend on these small details, but unfortunately many do. That's where transfat comes in:transfat transfers audio files to FAT devices and worries about the annoying details of your car stereo so that you don't have to.What exactly does this do?Say we run$ transfat source drive/destinationthen transfat does some/all of the following:Filters out any unwanted .logs, .cues, etc. insourceConverts non-MP3s fromsourceto temporary MP3sTransfers files todestinationUnmountsdriveand sorts into alphanumeric orderCleans up intermediate filesGreat, how do I install this?First you need to get some dependencies. Make sure you havefatsortandffmpeg. On Ubuntu you can get them withsudo apt install fatsort ffmpegOnce that's done, install transfat usingsudo pip3 install transfator just run therun_transfat.pyscript directly.
Package: transferchain-python-sdk
Transferchain SDKThe Transferchain SDK is a Python library that provides easy integration with the Transferchain platform. With this SDK, you can interact with Transferchain's blockchain technology to create and manage user accounts, perform transactions, and more. To get started, you need to define several environment variables, and this README will guide you through the process.SDK and User DocumentationSDK Docshttps://transferchain-python-sdk.readthedocs.io/User Docshttps://docs.transferchain.io/Getting StartedPrerequisitesBefore using the Transferchain SDK, make sure you have the following prerequisites in place:Python 3.6 or later installed on your system.Access to the Transferchain platform and API credentials (API token and secret).InstallationYou can install the SDK via pip:pipinstalltransferchain-python-sdkEnvironment VariablesTo use this SDK, add the following environment variables to your environment:TRANSFERCHAIN_USER_ID (int): Your account's user ID.TRANSFERCHAIN_API_TOKEN (str): Your Transferchain API token.TRANSFERCHAIN_API_SECRET (str): Your Transferchain API secret.TRANSFERCHAIN_WALLET_UUID (str): An optional value, a random UUID or your current wallet UUID.TRANSFERCHAIN_MNEMONICS (str): Your account mnemonics.Example UsagesHere are some example usages of the Transferchain SDK:Create a Master Userfromtransferchain.clientimportTransferChaintc=TransferChain()result=tc.add_master_user()user=result.dataRestore a Master Userfromtransferchain.clientimportTransferChaintc=TransferChain()result=tc.restore_master_user()Add a Userfromtransferchain.clientimportTransferChaintc=TransferChain()result=tc.add_master_user()user_result=tc.add_user()user_object=user_result.dataGet a Userfromtransferchain.clientimportTransferChaintc=TransferChain()result=tc.add_master_user()user_result=tc.add_user()user_object=user_result.datauser=tc.get_user(user_object.id)Load Users From DBfromtransferchain.clientimportTransferChaintc=TransferChain()tc.load_users()Save Userfromtransferchain.clientimportTransferChaintc=TransferChain()result=tc.add_master_user()user_result=tc.add_user()user_object=user_result.datatc.save_user(user_object.id,user_object)For more examples and detailed usage instructions, don't forget to check out thetransferchain.clientmodule.Important NotePlease note that the time it takes for a transaction to be broadcast on the blockchain is approximately 2 seconds. Ensure that you handle this delay appropriately in your application.For further information and updates, please visit the Transferchain Python SDK GitHub repository.If you encounter any issues or have questions, feel free to reach out to our support team.LICENSEtransferchain-go-sdk is licensed under the MIT. SeeLICENSEfor the full license text.
Package: transferfile
transferfile介绍sftp、ftp、scp、rsync 传输文件的统一接口，无论哪一种传输方式，都可以适配。程序适用于数据服务系统，如数据仓库对下游系统分发数据文件。安装pipinstalltransferfile使用说明采用简单工厂模式，传入的 type 有：ftpsftpscprsyncftp请注意原路径和目标路径都是带文件名的路径传输 /path/to/src.txt 到 /path/to/dist.txtfromtransferfileimportTransferFactoryclient=TransferFactory.create(type="ftp",host="172.17.0.2",username="admin",password="admin")client.put("/path/to/src.txt","/path/to/dist.txt")如果目标路径/path/to/不存在，会递归创建。如果程序运行在 linux 环境（utf8编码），而 ftp 服务器在 Windows 环境（GBK编码），为了文件名看起来不是乱码，可以指定服务端的编码方式为 GBK，指定特殊端口也是可以的，默认是 21fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="ftp",host="172.17.0.2",port=21,username="admin",password="admin",encoding='gbk')client.put("/path/to/src.txt","/path/to/dist.txt")下载文件使用 get，下载远程 /path/to/remote.txt 到本地 /path/to/local.txt：fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="ftp",host="172.17.0.2",port=21,username="admin",password="admin",encoding='gbk')client.get("/path/to/local.txt","/path/to/remote.txt")sftp，scp请注意原路径和目标路径都是带文件名路径用 scp 或 sftp 时只需要修改 type 参数为 scp 或 sftp 即可：fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="sftp",host="172.17.0.2",username="admin",password="admin")client.put("/path/to/src.txt","/path/to/dist.txt")也可以指定 rsa_私钥文件，从而不需要密码fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="scp",host="172.17.0.2",username="admin",rsa_file="/root/.ssh/id_rsa")client.put("/path/to/src.txt","/path/to/dist.txt")如果已经做好了 ssh 的授信，可以传入参数 load_system_host_keys = True，从而不需要密码fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="scp",host="172.17.0.2",username="admin",load_system_host_keys=True)client.put("/path/to/src.txt","/path/to/dist.txt")rsync请注意原路径和目标路径可以是文件名，也可以是目录rsync 目前需要配置好授信才可以使用，暂时不支持用户名和密码登录。fromtransferfileimportTransferFactoryclient=TransferFactory.create(type="rsync",host="172.17.0.2",username="admin",load_system_host_keys=True)client.put("/path/to/src.txt","/path/to/dist.txt")扩展点由于 ftp 不支持传输目录，这里就没有做出传输整个目录的接口，要实现也不复杂，如果要实现就是递归读取目录的文件，然后一个一个传输。也可以压缩成一个文件后上传。目前工作中暂时没有这个需求，都是生成好一个文件就传输这个文件，不需要上传整个目录。因此就没有实现。更新日志0.7: sftp 增加递归创建目标路径功能 。0.6: ftp 增加 windows 类型目录的支持。0.5: ftp 增加链接类型目录的支持。ftp 创建目录前会判定目录是否存在，如果不存在就递归创建目录。增加链接型的目录的支持。例如 /data_file -> /home/user/data_file之前目标路径必须是 /home/user/data_file/path/dist.dat0.5 版本之后可以是 /data_file/path/dist.dat联系我有问题，欢迎交流讨论。公众号 「Python七号」，分享 Python 编程技能。个人微信 「somenzz」
Package: transfer_learning_vision_classifiers
transfer_learning_vision_classifiersPackage for creating classifiers for computer vision, based on transfer learning.Installationpip install transfer_learning_vision_classifiersUsage examplefromtransfer_learning_vision_classifiersimportclassifiersclassifier1=classifiers.TransferLearningVisionClassifier("effnet_b2",["cat","dog"],False)
Package: transfer-lmir
Functions to perform calibration transfer by likelihood maximization: a standard-free approach capable of handling non-overlapping wavelength ranges.In this approach, calibration for spectral data on primary instrument is performed by likelihood maximization inverse regression (LMIR).Based on a limited number of spectra from a secondary instrument and the corresponding reference values, an estimation model is created based on block pairs.The latter can then be used to estimate spectra from secondary instrument in the domain of primary instrument to be able to use to primary calibration.Cf: F.B. Lavoie, A. Langlet, K. Muteki, R. Gosselin, Likelihood Maximization Inverse Regression: A novel non-linear multivariate model, Chemom. Intell. Lab. Syst. 194 (2019) 103844.https://doi.org/10.1016/j.chemolab.2019.103844.F.B. Lavoie, G. Robert, A. Langlet, R. Gosselin, Calibration transfer by likelihood maximization : A standard-free approach capable of handling non-overlapping wavelength ranges, Chemom. Intell. Lab. Syst. 234 (2023) 104766.https://doi.org/10.1016/j.chemolab.2023.104766.Call functionmodel, ypred = LMIR_create(X1,Y1,linear=True)R1_all, g1_all, R2_all, g2_all = estimation_model(X1, Y1, X2c, Y2c,factor_k,nb_pairs=30,B)ypred_ct, x1hat_ct, covx1_ct = estimation_exploit(R1_all,g1_all,R2_all,g2_all,X2v,X1,model)Input argumentsX1 (n1,k1): spectral data from primary instrumentY1 (n1,1): reference values for spectra from primary instrumentX2c (n2,k2): spectral data from secondary instrumentY2c (n2,1): reference values for spectra from secondary instrumentfactor_k: parameter for supervised selection of observations for estimation modelX2v: spectral data from secondary instrument for validationOptional input argumentslinear: option to create linear or non-linear models linking y to each varibale in X for LMIR modeling (default_value=True for linear modeling)nb_pairs: number of block pairs in estimation model (default_value=30)B: number of variable bootstrapping trials (default_value=3*max(k1,k2))Outputsmodel: model created by LMIRypred: predicted values by LMIRR1_all, g1_all, R2_all, g2_all: blocks pairs in estimation modelypred_ct: predicted values using estimation model and LMIR model from spectra from secondary instrumentx1hat_ct: estimated spectra in domain of primary instrumentcovx1_ct: uncertainty associated to estimation of spectra in domain of primary instrumentExamplesTwo full examples, along with datasets are provided in folder 'tests' of 'Download Files'.Example 1: Tablet shootout datasetExample 2: Coating times datasetExample 3: Wheat shootout datasetCompatibilitytransfer_lmir tested on Python 3.8 using the following modules:numpy 1.20.1matplotlib 3.3.4SciPy 1.6.2
Package: transfernet
transfernetCode to help transfer learned weights from neural networks to other datasets. The GitHub repo can be found inhere.Coding StylePython scripts follow PEP 8 guidelines. A usefull tool to use to check a coding style is pycodestyle.pycodestyle <script>AuthorsGraduate StudentsLane Schultz-Main Contributer-leschultzAcknowledgmentsTheComputational Materials Group (CMG)at the University of Wisconsin - MadisonProfessor Dane Morganddmorganand Dr. Ryan Jacobsrjacobs914for computational material science guidence
Package: transfer.py
hello, you may use this programit was originally intended for transfer of AIs between computers,
but this functionaly allows for variables to be stored in disk, and not ram
this can be built on to allow the transfer of veriables in say a hosted
python notebook. this means you can build and save a value easily. just
remember to import all required modules for the pyobject, otherwise
it will not work.Functions:read_obj(filename)takes a filename as input and returns a pyobject contained in the filewrite_obj(content, filename)takes 2 args, the filename, and the content. the content is the variable to be written, the filename
is the location of the file to write.
Package: transferPyobjects
hello, you may use this programit was originally intended for transfer of AIs between computers,
but this functionaly allows for variables to be stored in disk, and not ram
this can be built on to allow the transfer of veriables in say a hosted
python notebook. this means you can build and save a value easily. just
remember to import all required modules for the pyobject, otherwise
it will not work.Functions:read_obj(filename)takes a filename as input and returns a pyobject contained in the filewrite_obj(content, filename)takes 2 args, the filename, and the content. the content is the variable to be written, the filename
is the location of the file to write.
Package: transfer-pyobjects
hello, you may use this programit was originally intended for transfer of AIs between computers,
but this functionaly allows for variables to be stored in disk, and not ram
this can be built on to allow the transfer of veriables in say a hosted
python notebook. this means you can build and save a value easily. just
remember to import all required modules for the pyobject, otherwise
it will not work.Functions:read_obj(filename)takes a filename as input and returns a pyobject contained in the filewrite_obj(content, filename)takes 2 args, the filename, and the content. the content is the variable to be written, the filename
is the location of the file to write.
Package: transfer.sh
transfer.shTransfer.sh command line program, Now file sharing from the command line.InstallationOne command installationWith Pythonrun commands on terminal.$ pip install -U transfer.shHave multipls versions of python?$ python3.x -m pip install -U transfer.shLinuxAMD64$ curl --silent "https://api.github.com/repos/MayankFawkes/transfer.sh/releases/latest" | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/' | { tag=($(< /dev/stdin)); sudo curl -L "https://github.com/MayankFawkes/transfer.sh/releases/download/$tag/transfer-linux-amd64" -o /usr/local/bin/transfer; sudo chmod +x /usr/local/bin/transfer;}i386$ curl --silent "https://api.github.com/repos/MayankFawkes/transfer.sh/releases/latest" | grep '"tag_name":' | sed -E 's/.*"([^"]+)".*/\1/' | { tag=($(< /dev/stdin)); sudo curl -L "https://github.com/MayankFawkes/transfer.sh/releases/download/$tag/transfer-linux-i386" -o /usr/local/bin/transfer; sudo chmod +x /usr/local/bin/transfer;}CLICommand line helpUpload file$ transfer upload file.txtRemove file$ transfer remove <uploaded file hash>List uploaded files$ transfer list --show
Package: transfersh-client
Usage:After installation, you can run this package directly in command line. Launching it without arguments starts it in interactive mode:Sample output:Github|⇒ transfer_files
Enter path to file or directory: ./sysinfo
Creating zipfile from files in... /home/path/to/directory/sysinfo
Added file:  cython_tut.cpython-34m.so
Added file:  cython_tut.pyx
Added file:  setup.py
Added file:  build
Added file:  fib.cpython-34m.so
Added file:  primes.c
Added file:  .idea
Added file:  fib.c
Added file:  parse_proc_files.py
Added file:  fib.pyx
Added file:  primes.pyx
Added file:  cython_tut.c
Added file:  primes.cpython-34m.so

Sending zipfile: files_archive_09-02_18:34.zip (size of the file: 0.407897 MB)
Link to download zipfile(will be saved till 2017-09-16):
Could not save metadata

Link copied to clipboard
Remove archive? (y/n, yes/no):yes
Removing file... /home/path/to/directory/sysinfo/files_archive_09-02_18:34.zip
Removed.Besides that, you can start it with arguments:-i –interactive - keys that will start app with prompts (same as running it without arguments)-d –directory - enter path to directory (relative or absolute), which files will be sent in an archive-f –file - same as –directory, but enter path to file—ra –rm-archive - delete created archive, after it was sent–rf –rm-file - delete file after it was sent-h –help - display help messageSample outputtransfer.sh_client|dev⚡ ⇒ transfer_files -f test.txt --rf

Sending file: /home/path/to/directory/transfer.sh_client/test.txt (size of the file: 0.000113 MB)
Link to download file(will be saved till 2017-09-16):
https://transfer.sh/CtaJs/test.txt
Link copied to clipboard
Removing file... /home/path/to/directory/transfer.sh_client/test.txt
Removed.Example of usage inside scripts#!/usr/bin/env python3

from transfersh_client.app import send_to_transfersh, create_zip, remove_file


def send_files_from_dir():
    directory = './'
    zip_file = create_zip(directory)  # creates zip archive and returns it's absolute path
    send_to_transfersh(zip_file)  # sends archive to transfer.sh
    remove_file(zip_file)  # removes it


if __name__ == '__main__':
    send_files_from_dir()Downloadpip3 install transfersh_clientRequirementspypercliprequests
Package: transfershpy
transfer.pyUse transfer.sh with pythonMaybe u can donate me on Bitcoin :
bc1q6kyex89x9ppqw0kww9qfrtfrta6sdhnvgjz87rInstallationInstall transfer.py with pippipinstalltransfershpyUsage/ExamplesDownload a file:downloadFile('https://transfer.sh/2olwuBElm6/hello.txt','hello.txt')Upload a file (simple way):print(uploadFile('hello.txt','https://transfer.sh/hello.txt'))Upload a file (complete way):print(uploadFile('hello.txt','https://transfer.sh/hello.xt',maxDays=30,maxDownloads=5))Get direct download of a file:print(getDownloadPage("https://transfer.sh/sdk282/hello.txt"))Get raw file in browser:print(getRawFile("https://transfer.sh/fsadfe/hello.txt"))Roadmap18/11/23: 1.1 (get raw file and direct download function, some bugs fixed)
17/11/23: First version (download and upload function)