Saravanan666/pypi-org huggingface dataset:
Package: dsinternals
![](./.github/banner.png)
</br></br># pydsinternals - Directory Services Internals Library[![MIT License](https://img.shields.io/badge/License-MIT-green.svg)](../LICENSE.md)
![PyPI - Python Version](https://img.shields.io/pypi/pyversions/dsinternals)
![PyPI](https://img.shields.io/pypi/v/dsinternals)
[![Build Status](https://travis-ci.com/p0dalirius/pydsinternals.svg?branch=main)](https://travis-ci.com/p0dalirius/pydsinternals)A Python native library containing necessary classes, functions and structures to interact with Windows Active Directory.## Installation` python3-mpip install dsinternals `## ContributingPull requests are welcome. Feel free to open an issue if you want to add other features.## CreditsThis code base was heavily inspired by [MichaelGrafnetter](https://twitter.com/MGrafnetter)’s[DS Internals](https://github.com/MichaelGrafnetter/DSInternals) library.## Referenceshttps://github.com/MichaelGrafnetter/DSInternals
Package: dsize
工具介绍这是用来找目录中大文件的工具。
使用方法：./dsize\-d~/\-e~/Downloads~/Desktop\-k30如上的参数意义是：-d：起始目录
-e：要忽略的目录，可以有数个
-k：最后要显示的占据空间最大的几个目录eg:$ dsize -d ~/ -e ~/Library
exclude_dirs {'/Users/wh/Library'}
-Size--|-----Directions-------
9 MB	/Users/wh/Zotero/translators
12 MB	/Users/wh/Documents/git_clones/sentence-transformers/examples/applications/image-search
12 MB	/Users/wh/Zotero
15 MB	/Users/wh/Desktop/net_lecture
16 MB	/Users/wh/Documents/git_clones/sentence-transformers/.git/objects/pack
86 MB	/Users/wh/Documents/LearnRecords/PPT
110 MB	/Users/wh/Documents/MarginNote 3 User Guide videos
147 MB	/Users/wh/usr/bin
176 MB	/Users/wh/Documents/group_meeting/2021-10-10
Package: dsjobs
DesignSafe Jobsdsjobsis a library that simplifies the process of submitting, running, and monitoringTAPIS v2 / AgavePyjobs onDesignSafeviaJupyter Notebooks.FeaturesSimplified TAPIS v2 Calls: No need to fiddle with complex API requests.dsjobsabstracts away the complexities.Seamless Integration with DesignSafe Jupyter Notebooks: Launch DesignSafe applications directly from the Jupyter environment.InstallationInstalldsjobsvia pippip3installdsjobsTo install the current development version of the library use:pipinstallgit+https://github.com/DesignSafe-CI/dsjobs.git--quietExample usage:Jupyter Notebook Templatesusing DSJobs.ViewDSJobs API docOnDesignSafe Jupyter:Install the latest version ofdsjobsand restart the kernel (Kernel >> Restart Kernel):# Remove any previous installations!pipuninstalldsjobs-y# Install!pipinstalldsjobs--quietImportdsjobslibraryimportdsjobsasdsTo list all functions indsjobsdir(ds)DocumentationViewDSJobs API docTo generate API docs:pdoc --html --output-dir docs dsjobs --forceSupportFor any questions, issues, or feedback submit anissueDevelopmentTo develop or test the library locally. InstallPoetry. In the current repository run the following commandspoetryshell
poetryinstall
poetrybuildTo run the unit testpoetryrunpytest-vLicensedsjobsis licensed under theMIT License.AuthorsProf. Pedro Arduino, University of WashingtonKrishna Kumar, University of Texas at Austin
Package: dskmgr
dskmgrTwo dimensional, dynamic desktop/workspace manager for bspwm.DescriptionDskmgr handles bspwm operations such as creating new desktops, focusing desktops and moving around based on directions. For example, it can allow your desktop layout to look like this:[0-2]       [2-2]
[0-1]       [2-1] [3-1]
[0-0] [1-0] [2-0] [3-0]Where each number pair is a unique desktop, and you can navigate around in 4 directions. The program also remembers you vertical position's history, so if you were in[0-1]and moved right to1-0, when you will move left again you will return to[0-1]rather than[0-0].Installpython3 -m pip install dskmgrUsagePutdskmgrd &in youbspwmrc, and then change you desktop-managing shortcuts to usedskmgrrather thanbspc.TODOsAdd proper tests.Make it so that when an error occurs (or even when an incorrect command is revieved) thedskmgrscript will know to return an error code.Improve logging support indskmgrd.Find a better name (maybe "meja"? It means "desk" in Indonesian)
Package: dsk-server
dsk-serverFAT12形式のDSKファイルに含まれるファイルをダウンロードできるサーバアプリケーションですインストールpip install dsk-serverUsageNAME
    dsk-server start - Start the DSK server.

SYNOPSIS
    dsk-server start [DSKFILE | PATH] <flags>

DESCRIPTION
    Start the DSK server.

POSITIONAL ARGUMENTS
    DSKFILE

FLAGS
    -h, --host=HOST
        Default: '0.0.0.0'
    -p, --port=PORT
        Default: 8000例1：
DSKイメージ内のファイルをホスティングします$ dsk-server start ./MSXDSK.DSK例2：
ホスト上の指定パス内のファイルをホスティングします$ dsk-server start ./work_dirAPIサーバを起動して、以下を参照くださいhttp://127.0.0.1/docs
Package: dsl2html
DescriptionA Python package to convert DSL into HTML, written in modern C++.The part that parses DSL into a DOM tree comes fromGoldenDict-ng, and I have made a number of changes:Use 8-bitstd::stringthroughout.Use standard library equivalents of Qt classes/functions.Use functional programming wherever appropriate.Some tags are ignored.
And some other adjustments.The part that converts the DOM tree into HTML is written by me, under influence from bothpyglossaryand GoldenDict-ng. Any bug here is mine :)Installationpipinstalldsl2htmlBuildingpython3setup.pybuildNeedless to say, you should have the development package of Python installed. Nothing other thanPython.his needed. Your compiler should support C++11, though.Usage>>>importdsl>>>dsl.to_html(''' [m0][b]com·mu·ta·tor[/b] [p]7[/p] {{id=000008943}} [c rosybrown]\[[/c][c darkslategray][b]commutator[/b][/c] [c darkslategray][b]commutators[/b][/c][c rosybrown]\][/c] [p]BrE[/p] [c darkgray] [/c][c darkcyan]\[ˈkɒmjuteɪtə(r)\][/c] [s]z_commutator__gb_1.wav[/s] [p]NAmE[/p] [c darkgray] [/c][c darkcyan]\[ˈkɑːmjuteɪtər\][/c] [s]z_commutator__us_1.wav[/s] [c orange] noun[/c] [c darkgray] ([/c][c green]physics[/c][c darkgray])[/c]...  [m1][c darkmagenta][b]1.[/b][/c] {{d}}a device that connects a motor to the electricity supply{{/d}}...  [m1][c darkmagenta][b]2.[/b][/c] {{d}}a device for changing the direction in which electricity flows{{/d}}''','test')(' <div style="margin-left: 0px;"><b>com·mu·ta·tor</b> <i><font color="green">7</font></i>  <span style="color: rosybrown;">[</span><span style="color: darkslategray;"><b>commutator</b></span> <span style="color: darkslategray;"><b>commutators</b></span><span style="color: rosybrown;">]</span> <i><font color="green">BrE</font></i> <span style="color: darkgray;"> </span><span style="color: darkcyan;">[ˈkɒmjuteɪtə(r)]</span> <audio controls autoplay src="/api/cache/test/z_commutator__gb_1.wav">z_commutator__gb_1.wav</audio> <i><font color="green">NAmE</font></i> <span style="color: darkgray;"> </span><span style="color: darkcyan;">[ˈkɑːmjuteɪtər]</span> <audio controls src="/api/cache/test/z_commutator__us_1.wav">z_commutator__us_1.wav</audio> <span style="color: orange;"> noun</span> <span style="color: darkgray;"> (</span><span style="color: green;">physics</span><span style="color: darkgray;">)</span> </div><div style="margin-left: 9px;"><span style="color: darkmagenta;"><b>1.</b></span> a device that connects a motor to the electricity supply </div><div style="margin-left: 9px;"><span style="color: darkmagenta;"><b>2.</b></span> a device for changing the direction in which electricity flows</div>',['z_commutator__gb_1.wav','z_commutator__us_1.wav'])The module has only one function:to_html, which takes two arguments: the DSL string and the dictionary name, and returns a tuple of two elements: the HTML string and a list of media file names.
Package: dslb
Dead Simple Linux BackupsA rsync wrapper that makes the Linux full system backups and restores easier than ever.DemoInstallationInstall dslb with git clonegitclonehttps://github.com/RemiZlatinis/DSLBcdDSLBUsage/Examples# Creates a new backup on /home/user/system_backup/ # Default backup path
$ python3 dslb.py

# Creates a new backup on /mnt/storage/system_backup/
$ python3 dslb.py /mnt/storage/system_backup

# Updates the backup on /home/user/system_backup/
$ python3 dslb.py -u

# Updates the backup on /mnt/storage/system_backup/
$ python3 dslb.py -u --update /mnt/storage/system_backup

# Restores system from /home/user/system_backup/ to /
$ python3 dslb.py -r

# Restores system from /mnt/storage/system_backup/ to /
$ python3 dslb.py -r /mnt/storage/system_backup

# Restores system from /mnt/storage/system_backup/ to /run/media/user/writable/
$ python3 dslb.py -r /mnt/storage/system_backup /run/media/user/writable/FAQDoes the backup path cause an infinite loop?No, the backup path will always be excluded.Where I can find that cool shell setup?https://github.com/RemiZlatinis/my-settings/tree/main/zsh-configsAuthors@RemiZlatinisFeedbackIf you have any feedback, please reach out to us atremizlatinis@gmail.comLicense
Package: dslclib
dslc6対話システムライブコンペティションに使用できるPythonライブラリリファレンスはhttps://yuta0306.github.io/dslclib/にあります．このライブラリに関する要望や質問は，yubo1336[at]lr.pi.titech.ac.jpまでお願いします．Changelog2023/06/30v0.1.2をリリースしました．https://yuta0306.github.io/dslclib/にリファレンスを公開しました．FaceRecognitinClient→FaceRecognitionClientとタイポを修正しました．2023/06/30v0.1.3をリリースしました．タイポを修正しました。2023/07/06v0.2.0をリリースしました。EmotionType.fearをEmotionType.Fearに修正しました。FaceRecognitionServerの更新に伴い、face_recognition.pyにおけるモジュールをアップデートしました。OutputFor...とクライアントの出力をデータクラスで定義しました。OutputForFaceRecognition.emotionとOutputForFaceRecognition["emotion"]の二つのアクセス方法を可能にしました。型ヒントの一部をstrからLiteralに変更しました。2023/09/28v0.2.1をリリースしました稀に音声合成ができなくなるバグが発生したため，軽微な修正を加えました
Package: dslibs-baosws
Find yourself doing these over and over again everytime you start a new project or notebook?pip3 install pandas scikit-learn matplotlib numpy statmodels scipy seaborn ...andimport numpy as np
import pandas as pd
import seaborn as sns
import matplotlib.pyplot as plt
import scipy
...dslibseases your pain with anunified modulethat automatically installs and imports frequently used data science modules like numpy, pandas, scikit-learn, etc. in just a sec.Installationpip install dslibs-baoswsUsageJustfrom dslibs import *:>>> from dslibs import *
-------------------------------------------------------
Following modules was installed and imported by dslibs:
"numpy" as "np"
"pandas" as "pd"
"sklearn" as "skl"
"sklearn.preprocessing" as "spp"
"sklearn.model_selection" as "sms"
"sklearn.pipeline" as "spl"
"sklearn.metrics" as "smt"
"sklearn.feature_selection" as "sfs"
"matplotlib.pyplot" as "plt"
"statsmodels.api" as "sma"
"scipy" as "sp"
-------------------------------------------------------
>>>  # now we can use 'pd' without 'import pandas as pd' as usual
>>> df = pd.DataFrame({'A': [1, 2, 3], 'B': [4, 5, 6]})
>>> df
A  B
0  1  4
1  2  5
2  3  6Currently supported importsmodulealiasnumpynppandaspdsklearnsklsklearn.preprocessingsppsklearn.model_selectionsmssklearn.pipelinesplsklearn.metricssmtsklearn.feature_selectionsfsmatplotlib.pyplotpltstatsmodels.apismascipyspseabornsns
Package: dsl-james
james - at your serviceCLI tool for starting up a new projectBefore:Go to Azure DevOpsselect projectgo to Reposcreate new repocopy clone urlRun cookiecutterget cookiecutter url and startpaste clone urlfill in stuffSetup local repogit remote set-urlgit add template filesgit commit & pushgit create dev branchCreate python envAfter:james initfill in stuffjames goWhat it does is:prompt for settingscreate a new git repositoryapply cookiecutter templatesetup a local git repo and link it to the remotecreate python environmentUsageOne time setup:pip install dsl-james(can be in your base Python environment)james setupfor some general settingsStarting a new project:james initwill define a new project and prompt your for configuration settingsjames showwill show configuration (optional)when inside a project dir, it will show configuration of that specific projectwhen inside any other dir, it will show the default configurationjames statuswill show the status of ignition phases (optional)james goto executejames reviewfor code inspectionInfojames will create.james.iniconfig files:One in your home dir (~). This will contain base info (from thesetup), as well as project-specific info from the last project you defined withinit.One for each project, located in<projects-dir>/<your-project>. This is basically a copy of the generic file.
When calling amy james command, james will use the project's config fileTo DoAzure setupAzure DevOps setupProject setupCreate git repositoryCookiecutterSupport for multiple cookiecutter templatesCreditsThis package was created with Cookiecutter and theaudreyr/cookiecutter-pypackageproject template.Cookiecutter:https://github.com/audreyr/cookiecutteraudreyr/cookiecutter-pypackage:https://github.com/audreyr/cookiecutter-pypackageHistoryv0.1.3 (2021-06-03)Code review addedGeneral bugfixesv0.1.2 (2021-01-14)Ignore this releasev0.1.1 (2021-01-14)Ignore this releasev0.1.0 (2021-01-14)First release on PyPI
Package: dslogparser
dslogparserParse FIRST FRC Driver Station log files.The DSLogParser class can parse FRC .dslog files and extract each entry, which are returned as dictionaries.The DSEventParser class parses FRC .dsevents, including extracting the match information.The script dslog2csv.py can read one or many .dslog files to produce CSV file(s).
It can combine .dslog and .dsevents files if the filenames match. Seedslog2csv.py -hfor usage information.
Package: dsm
dsmDamn simple finite state machineAboutDSM is a observable simple finite state machine implementation for Python.
Transitions may be programmed declaratively or imperatively.
Inputs and state changes are emitting observable events.RequirementsPython 2.7, 3.5, 3.6observablesixfor compatibility between Python 2 and Python 3Installationpip install dsmUsageDjango integrationIt is possible to integratedsmwith Django models by
declaring aStateMachineField.fromdjango.dbimportmodelsfromdsm.fieldsimportStateMachineFieldclassOrder(models.Model):status=StateMachineField(transitions=(('new',['confirmed'],'processing'),('processing',['cancel'],'cancelled'),('processing',['send'],'sending'),('sending',['deliver'],'finished'),),max_length=16,choices=(('new',_('New')),('processing',_('Processing')),('sending',_('Sending')),('finished',_('Finished')),('canceled',_('Cancelled')),),db_index=True,default='new')Now you can create anOrderand check it's status:>>>order=Order.objects.create()>>>order.statusnew>>>type(order.status)dsm.fields.MachineStateThe string representation ofstatusfield is same as state name
provided in transitions declaration, but internally there is alwaysdsm.fields.MachineStateinstance.DeclarativeFSM declaration:importstringimportdsmclassSumatorMachine(dsm.StateMachine):classMeta:initial='init'transitions=(('init',list(string.digits),'digit_enter'),('digit_enter',list(string.digits),'digit_enter'),('digit_enter','=','summarize'),)Usage:Initialization:fsm=SumatorMachine()Processing one value:fsm.process(value)Processing multiple values:fsm.process_many(iterable)Gathering the current state:>>>fsm.state'summarize'Resetting to the intial state:fsm.reset()Listening on events:fsm.when('state',func)Events example:>>>the_sum=0>>>defadd_digit(x):globalthe_sum;the_sum+=int(x)>>>defreset(x):globalthe_sum;the_sum=0>>>fsm=SumatorMachine()>>>fsm.when('digit_enter',add_digit)>>>fsm.when('init',reset)>>>fsm.process_many('666=')'summarize'>>>the_sum18Events example (class based):>>>classSumator(object):...def__init__(self):...self.total=0...self.fsm=SumatorMachine()...self.fsm.when('digit_enter',self.add)...self.fsm.when('init',self.reset)......defadd(self,x):...self.total+=int(x)......defreset(self,x):...self.total=0......defsummarize(self,values):...self.fsm.reset()...self.fsm.process_many(values+'=')...returnself.total>>>s=Sumator()>>>s.summarize('666')18Imperativeimportstringimportdsmfsm=dsm.StateMachine(initial='init',transitions=dsm.Transitions((('init',list(string.digits),'digit_enter'),('digit_enter',list(string.digits),'digit_enter'),('digit_enter','=','summarize'),)))LicenseBSD
Package: dsmc
dsmc python moduledsmc (DontStealMyCode) is a python-based complete "framework" to encrypt and decrypt code or whatever file you want. Please the global repository for further details.Installationpip install dsmcorclone the repository via gitgit clone https://github.com/Atepir/DontStealMyCode-DSMC-console-web-code-encrypter/dontstealmycodeI. Tests run1. dsmc as a python filea. Encrypting and decrypting the Haskell exampleEncryptingpython__init__.py-e1-c"tests/Haskell/example.hs"--f1"factor1"--f2"factor2"-o"../tests/Haskell/example_encrypted.hs"Decryptingpython__init__.py-d1-c"tests/Haskell/example_encrypted.hs"--f1"factor1"--f2"factor2"-o"../tests/Haskell/example_decrypted.hs"b. Encrypting and decrypting general modelEncryptingpython__init__.py-e1-c"path/to/the/file/to/encrypt"--f1"<password-first-factor>"--f2"<password-second-factor>"-o"path/then/name/to/the/output/encrypted/file"Decryptingpython__init__.py-d1-c"path/then/name/to/the/output/encrypted/file/to/decrypt"--f1"<password-first-factor>"--f2"<password-second-factor>"-o"path/then/name/to/the/output/decrypted/file"c. For further details on the command line use of dsmc.py, please typepythondsmc.py--helporpythondsmc.py-h2. dsmc as a python modulePlease, see the example of use of dsmc as python module in the tests/ folder@author: Nongma Sorgho@date: 06.28.2020
Package: dsmcp
dsmcpinstallationpip install dsmcprun the applicationby passing a config filepython3 -m dsmcp -c [config file].ini basicor by passing params in command linepython3 -m dsmcpreplace host by the host url and port by the host portconfig file structure[GLOBAL]
loglevel=info
host=host:portThePyDapi2library offers a Python implementation of the Dassym API version 2.Dassym API version 2 akaDAPI2is the application programming interface (API) used to
control Dassym electronic boards.This library was created to meet internal needs in Dassym.Version : 0.0.3 (2021-05-17)
Package: dsm-django-masterdata
Django Master datainstall dsm-django-masterdatapip install pip install dsm-django-masterdatainstall django app insettings.pyINSTALLED_APPS=[...'dsm_django_masterdata.hscode','dsm_django_masterdata.area',...]migrate databasepython manage.py migratecheck data in admin pageHow to useHScodefromdsm_django_masterdata.hscode.modelsimportHScodehs_code=HScode.objects.all()Areafromdsm_django_masterdata.area.modelsimportAreaarea=Area.objects.all()
Package: dsmemail
DSM Emailinstallpip install dsmemailhow to useset envDSM_EMAIL_URI=<DSM_EMAIL_URI>
DSM_EMAIL_APIKEY=<DSM_EMAIL_APIKEY>send emailimportdsmemailstatus,msg=dsmemail.sendEmail(subject="test",message="helloworld",emails=["admin@admin.com"],attachments=["test.txt"])print(status,msg)variabledtypedescriptionsubjectstrsubject of emailmessagestremail body can contains html stringemailsList[str]email to send messageattachmentsList[str]list of filepath(str) to attach filesoutput(True, 'email send sucess')statusTrue = send email sucess
False = send email failmsgstring describe status
Package: dsmlibrary-viz
dsmlibrary-vizinstallpip install dsmlibrary-vizusefromdsmlibrary_viz.data_vizimportDataVizdataviz=DataViz(token="<token>",dataplatform_api_uri="<dataplatform_api_uri>",object_storage_uri="<object_storage_uri>")data=dataviz.query("""SELECT * FROM 'DISCOVERY:<FILE_ID>'LIMIT 10""")print(data)
Package: dsmsfilepackager
Add select files or directories to a bundle of files, generate a manifest,
and upload or download from an SFTP server. For use with DSMS.Please note that filepackages are not thread safe. It is up to you to ensure
that only one process is manipulating a package at any point in time. For this
reason, it’s recommended that you use a uuid such as the Celery task ID to
ensure each process has its own space.How to use when writing a new package:from dsmsfilepackager.filepackage import DSMSFilePackage
import uuid

fpack = DSMSFilePackage(target_id=111, job_id=13244, uid=uuid.uuid4(),
                        hostname="remote_sagenth.example.com",
                        hostport="1222", username="theuser",
                        priv_key="/home/theuser/.sagenth/key",
                        local_root="/tmp/cache",
                        remote_root="/upload_target")

# register in manifest
fpack.add("myfile.txt")
fpack.add_dir("docs/")

fpack.finish_and_upload()  # generate a manifest and uploadOnce package generation has finished, the files will be both locally at
/tmp/cache/111/13244/[uuid], as well as on the FTP server under
/upload_target/111/13244/[uuid].Now, other processes can either access the locally cached files if they’re
available, or they’ll be fetched via SFTP and moved into the local cache if
not.How to fetch a previously stored package:# auto-get remote files, reading from cache when available

 >>> fpack = filepackage.fetch(target_id=111, job_id=13244, uid=uuid.uuid4(),
                               host="remote_sagenth.example.com",
                               hostport="1222", username="theuser",
                               priv_key="/home/theuser/.sagenth/key",
                               local_root="/tmp/cache",
                               remote_root="/upload_target")
 >>> print fpack.manifest.files
 ["myfile.txt", "docs/readme.txt", "docs/2.py"]
 >>> file_info = fpack.manifest.get("myfile.txt")
 >>> file_info.size
 1246
 >>> file_info.sha256
 "d8d5d29645ce8552646ad236244304892bb9e0df633e2603a1fa616682e1c431"
 >>> file_info.type
"Python script, ASCII text executable"
 >> fh = fpack.open("myfile.txt")  # will be made available locally
Package: dsms-sdk
DSMS-SDKPython SDK core-package for interacting with the Dataspace Management System (DSMS)AuthorsMatthias Büschelberger(Fraunhofer Institute for Mechanics of Materials IWM)Yoav Nahshon(Fraunhofer Institute for Mechanics of Materials IWM)Pablo De Andres(Fraunhofer Institute for Mechanics of Materials IWM)LicenseThis project is licensed under the BSD 3-Clause. See the LICENSE file for more information.UsageThe SDK provides a general Python interface to a remote DSMS deployment, allowing users to access, store and link data in a DSMS instance easily and safely. The package provides the following main capabilities:Managing Knowledge-Items (KItems), which are data instances of an explicitly defined semantic class type (KType)Creating, updating and deleting meta data and properties, e.g. date, operator, material response data for a conducted tensile testAdministrating authorship, contact information and supplementary information upon making changes or adding KItemsSemantic annotation of KItemsConduct simple free-text searches within the DSMS instance including filters (e.g. limiting the search for certain materials) as well as a more experts-aware SPARQL interfaceLinking KItems to other KItemsLinking Apps to KItems, triggererd, for example, during a file uploadPerforming simple file upload and download using attachments to KItemsExport of a knowledge (sub) graph as common serializations (.ttl, .json)For the basic usage, please have a look on the Jupyter Notebook underexamples/basic_usage.ipynb. This tutorial provides a basic overview of using the dsms package to interact with Knowledge Items.DisclaimerCopyright (c) 2014-2024, Fraunhofer-Gesellschaft zur Förderung der angewandten Forschung e.V. acting on behalf of its Fraunhofer IWM.Contact:Matthias Büschelberger