Saravanan666/pypi-org huggingface dataset:
Package: civisml-extensions
scikit-learn-compatible estimators from Civis AnalyticsInstallationInstallation withpipis recommended:$ pip install civisml-extensionsFor development, a few additional dependencies are needed:$ pip install -r dev-requirements.txtContents and UsageThis package containsscikit-learn-compatible estimators for stacking (StackedClassifier,StackedRegressor), non-negative linear regression (NonNegativeLinearRegression), preprocessingpandasDataFrames(DataFrameETL), and usingHyperbandfor cross-validating hyperparameters (HyperbandSearchCV).Usage of these estimators follows the standard sklearn conventions. Here is an
example of using theStackedClassifier:>>>fromsklearn.linear_modelimportLogisticRegression>>>fromsklearn.ensembleimportRandomForestClassifier>>>fromcivismlext.stackingimportStackedClassifier>>>>>># Define some Train data and labels>>>Xtrain,ytrain=<train_features>,<train_labels>>>>>>># Note that the final estimator 'metalr' is the meta-estimator>>>estlist=[('rf',RandomForestClassifier()),>>>('lr',LogisticRegression()),>>>('metalr',LogisticRegression())]>>>>>>mysm=StackedClassifier(estlist)>>># Set some parameters, if you didn't set them at instantiation>>>mysm.set_params(rf__random_state=7,lr__random_state=8,>>>metalr__random_state=9,metalr__C=10**7)>>>>>># Fit>>>mysm.fit(Xtrain,ytrain)>>>>>># Predict!>>>ypred=mysm.predict_proba(Xtest)You can learn more about stacking and see an example use of theStackedRegressorandNonNegativeLinearRegressionestimators ina talk presented at PyData NYCin November, 2017.See the doc strings of the various estimators for more information.ContributingPlease seeCONTRIBUTING.mdfor information about contributing to this project.LicenseBSD-3SeeLICENSE.mdfor details.
Package: civitai
Civitai.com API PackageThis is a small wrapper of thecivitai.com APIUsage Creatorsfromcivitaiimportcreatorsresult=creators.get(query="Lykon")N=result.totalItemscreator=result.items[0]creator.username# Lykoncreator.modelCount# 212Usage Imagesfromcivitaiimportimages# https://civitai.com/posts/442123result=images.get(postId=442123)image=result.items[0]image.urlimage.likeCountimage.dislikeCountUsage Modelsfromcivitaiimportmodels# https://civitai.com/models/4384/dreamshaper?modelVersionId=128713model=models.get_model(modelId=4384)modelVersion=models.get_by_modelVersion(modelVersionId=128713)model.name# DreamShapermodelVersion.name# 8Usage Tagsfromcivitaiimporttagsresult=tags.get(query="realism")tag=result.items[0]result.totalItems# 4tag.modelCount# 383
Package: civitai_comfy_nodes
Civitai Comfy NodesTired of manually downloading and moving models, LoRAs, and more to the right places?Sick of scouring Civitai for that one mystical LoRA someone was using to make that cool image?Want to be share a fully reproducable workflow?This is the set of nodes for you!NodesCheckpoint LoaderLoad checkpoints directly from Civitai using just a ModelAIR(model idorversion id)Resources used in images will be automatically detected on image uploadWorkflows copied from Civitai or shared via image metadata will include everything needed to generate the image including all resourcesLoRA LoaderLoad LoRAs directly from Civitai using just a LoRAAIR(model idorversion id)Resources used in images will be automatically detected on image uploadWorkflows copied from Civitai or shared via image metadata will include everything needed to generate the image including all resourcesEmbedding Loader(Coming Soon)Automatically detect textual inversions in prompts usingembedding:{air}and download all the files needed.Resources used in images will be automatically detected on image uploadWorkflows copied from Civitai or shared via image metadata will include everything needed to generate the image including all resourcesAIR: AI ResourceAn AIR is Civitai's way of universally referencing AI Resources. It follows the Uniform Resource Naming standard. If you're into that kinda thing, you canread more about it here.On Civitai, to keep things brief, an AIR is a combination ofmodel idand optionally at a specificmodel version. Ex.{model_id}or{model_id}@{version_id}.Easy Copy AIRsYou can enable the display of AIRs on the site for easy copying from the Early Access settings of yourAccount Settings.ExamplesThis example would get the base modelIsabelle Fuhrman109395and request the LORA versionisabellefuhrmanV02-000007.safetensors84321109395@84321While using only the ID would fetchIsabelle Fuhrman109395and find it's default model (which is the top most model an author designates)109395
Package: civo
CivoThis project is the python API library for using in python projects.Usage>>> from civo import Civo
>>> from os.path import expanduser
​
>>> civo = Civo('token')
>>> home = expanduser("~/.ssh/")
>>> ssh_file = open('{}id_dsa.pub'.format(home)).read()
​
>>> # you can filter the result
>>> size_id = civo.size.search(filter_by='name:g2.xsmall')[0]['name']
>>> template = civo.templates.search(filter_by='code:debian-stretch')[0]['id']
​
>>> civo.ssh.create(name='default', public_key=ssh_file)
>>> ssh_id = civo.ssh.search(filter_by='name:default')[0]['id']
>>> civo.instances.create(hostname='text.example.com', size=size_id,
                      region='lon1', template_id=template,
                      public_ip='true', ssh_key=ssh_id)Installationpip3 install civoRequirementsrequestsCompatibilitypython 3.7LicenceMit LicenseAuthorscivowas written byAlejandro JNM.
Package: ci-watson
ci_watsonCI helper for STScI Jenkins.
If you ask nicely, it might also help you solve crimes.Nightly regression test results are available only from within the STScI
network at this time.https://plwishmaster.stsci.edu:8081/job/RT/job/ci_watson/test_results_analyzer/InstallationWithpip::pip install ci-watsonWithconda::conda install ci-watson -c http://ssb.stsci.edu/astroconda
Package: ci-yml
The ci-yml utilities read the local .ci.yml file and run a series of action grouped under jobs.The .ci.yml file may define adeployjob and a list of other parallel jobs that can be assigned 1-to-1 with the gitlab-CItestjobs.This is a .ci.yml example file:prepare:
  - <shell command>
  - <shell command>
jobs:
  <jobname>:
    - <shell command>
  <jobname>:
    - <shell command>
deploy:
  - <shell command>
  - <shell command>In the example below we have two jobs, apreparejob used to install additional package:prepare:
  - pip install pyyaml

jobs:
  test1:
    - python ./test1.py
  build_doc:
    - make docThe commands insideprepareblock are executed before that any other jobs is executed and the errors are ignored.Following the example above you should configure two test jobs in you gitlab-ci instance and just call:ci-yml test1and:ci-yml build_docrespectively. If you have also a deploy job you should also setup the gitlab-ci deploy job with the only command:ci-yml deployIf no arguments are provided to`ci-yml`all the jobs are executed until the first one fails or all jobs are runned than deploy action take placeEnvironment variablesci-yml extend the env variables with the follows:CI_YML_JOBTo see the gitlab environment variables seehttps://gitlab.com/gitlab-org/gitlab-ci/tree/master/doc/examples#environmental-variablesTravis envs doc are available athttp://docs.travis-ci.com/user/environment-variables/You can also define extra env vars using theenvsblock, the newly defined vars can also combine other env vars. For example:envs:
  pub_path: "/var/www/$USER/$CI_BUILD_REF"

...

deploy:
  - cp *.out $PUB_PATHNote: For your convenience you can define the vars as lower case inside theenvsblock but they MUST be used upper case inside the command.ci-yml and travisThis project was intended to supply a job configuration method to gitlab-ci that don’t have any one atm, otherwise it could be useful also in others use cases.You can use ci-yml locally during developing and you can also call it inside.travis.yml, see the local travis config file for info.
Package: cizohosubscriptions
ci-zoho-subscriptionCI Zoho Subscription API ModuelsTax Module Added
Subscription Cancel and Delete Module Addedhttps://accounts.zoho.com/oauth/v2/auth?scope=ZohoSubscriptions.invoices.CREATE,ZohoSubscriptions.invoices.READ,ZohoSubscriptions.invoices.UPDATE,ZohoSubscriptions.invoices.DELETE,ZohoSubscriptions.customers.CREATE,ZohoSubscriptions.customers.UPDATE,ZohoSubscriptions.customers.READ,ZohoSubscriptions.customers.DELETE,ZohoSubscriptions.subscriptions.CREATE,ZohoSubscriptions.subscriptions.UPDATE,ZohoSubscriptions.subscriptions.READ,ZohoSubscriptions.subscriptions.DELETE,ZohoSubscriptions.plans.CREATE,ZohoSubscriptions.plans.UPDATE,ZohoSubscriptions.plans.READ,ZohoSubscriptions.plans.DELETE&client_id=1000.KHL2J6X88WDA8ODDESEOZHCY61C39E&state=testing&response_type=code&redirect_uri=https://localhost:3000&access_type=offline
Package: cizsle
Zero-Touch Provisioning (ZTP) Server for Cisco Network DevicesThe goal of this project is to develop a Zero Touch Provisioning (ZTP) Server to simplify and accelerate deployment of
Cisco networking devices.Project TargetsDeveloped in PythonDeployed in Docker containersKey FeaturesSupport ZTP on IOS XE, IOS XR, and NXOS devicesTemplate and scripted device configurationsSoftware image upgradesTopology validationIntuitive web UI and concise CLI
Package: cj
Personal collection of command line utilities. I usually add more functions as
I need them. No particular subject.The idea of this package is to be self-contained and easily installed in any
unix-like system. It should also be safe to install it globally without a
virtual environment. For that matter, I try to avoid at all cost using
external Python dependencies and using Python 3 specific features.The usage varies from command-line utilities, automation scripts to cron tasks.InstallationUsing pip:pip install cjUsagecj COMMANDExamplesBackup a Wordpress site:cj wpCompress a folder:cj zip foldername/LicenseThe source code is released under theMIT License.
Package: cj7
cj7A simple way to send TCP and UDP packets in Python without the need for sockets.ExamplesSending packets in UDPsendPacketUDP(ip, port, data, showSent)Put the target IP as the first variable, the target port as the second, the data to be sent in the third and either True or False in the last variable for whether or not to print a message when the packet has been sent.Sending packets in TCPsendPacketTCP(ip, port, data, showSent)Put the target IP as the first variable, the target port as the second, the data to be sent in the third
and either True or False in the last variable for whether or not to print a message when the packet has b
een sent.
Package: cj7-jack-debug
cj7A simple way to send TCP and UDP packets in Python without the need for sockets.ExamplesSending packets in UDPsendPacketUDP(ip, port, data, showSent)Put the target IP as the first variable, the target port as the second, the data to be sent in the third and either True or False in the last variable for whether or not to print a message when the packet has been sent.Sending packets in TCPsendPackettcp(ip, port, data, showSent)Put the target IP as the first variable, the target port as the second, the data to be sent in the third
and either True or False in the last variable for whether or not to print a message when the packet has b
een sent.
Package: cjapy
Adobe Customer Journey APIThis is a python wrapper for the Adobe Customer Journey API.One important element when starting with CJA API is that you need to have your adobe console.io Project containing access to AEPandCJA.You cannot use the API without having access to both elements.DocumentationDocumentation is split in different places:Core methods to setupcjapy:main documentationMethods provided by the CJA class instance:cja documentationWorkspace class documentation:Workspace classRequestCreator class documentation:RequestCreator classProject class documentation :Project classVersionsA documentation about the releases information can be found here :cjapy releasesFunctionalitiesFunctionalities that are covered :Get Dimensions & MetricsGet, Update and Delete Tags & SharesGet, Update and Delete DataviewGet, Update and Delete Date RangesGet, Update and Delete FiltersGet Top items for a dimensionGet, Update and delete projectsDigest Project Information and analyse them via theProjectclassRun a report (by default returning a Workspace instance)(BETA) Run a multi dimensional reportGetting StartedA documentation is provided to get started quickly with the CJA API wrapper in python.You can find it here:get started oncjapyTo install the library with PIP use:pip install cjapyor, to get the latest version from githubpython -m pip install --upgrade git+<https://github.com/pitchmuc/cjapy.git#egg=cjapy>Logging capabilityA logging capability is present on the module for debugging purposes.There is a proper documentation in place to understand how you can add the logging messages to your runtime.Documentation on logging in cjapyDependenciesIn order to use this API in python, you would need to have those libraries installed :pandasrequestsjsonPyJWTPyJWT[crypto]pathlibpytestTestTBWOthers SourcesYou can find information about the CJA API here :[https://www.adobe.io/cja-apis/docs/api/][https://www.adobe.io/cja-apis/docs/use-cases/]
Package: cjdk
cjdkcjdk(for "cached JDK") is a Python package and command-line tool to
download and run JDK (Java Development Kit) or JRE (Java Runtime Environment)
distributions.Previously used JDKs are kept in the user's cache directory, so that future
invocations do now require a download.What forInstalling exact JDK versions for reproducible testingWorking with multiple versions of JDKsDeploying tools that require JavaUsing the command-line interface ofcjdk, you can run Java programs using a
one-liner, without having to worry about whether the user has installed a new
enough Java runtime and setJAVA_HOMEandPATHto appropriate values.For example, the following command will runCheckstyleusing Temurin JRE 17 (which will be
downloaded if this is the first time it is requested):cjdk--jdk=temurin-jre:11execjava-jarcheckstyle-10.3-all.jar-cstyle.xmlMyApp.javaSee thedocumentationfor detailed
usage.cjdkwas inspired byCoursier'sjavacommand, and uses Coursier'sJDK index). Unlike Coursier,cjdkdoes not require a Java runtime to bootstrap.Installingcjdkrequires Python 3.8.pipinstallcjdkDocumentationLicensingcjdkis distributed under the MIT license. Please see LICENSE.txt.
Package: cjdns
The cjdns python library doesn’t support python3 and is a PITA to install, due
to it’s use of a modified bencode library which is still called “bencode”, among
other things, so I’m cleaning it up.InstallationThe easiest way to install it is:pip install cjdnsBut you could also clone it and run:python setup.py installOnce it’s installed, you’ll findpeerStatsandcexecinstalled in your$PATH, and thecjdnslibrary available for import.UsageUsage is simple. First, import:importcjdnsThen, connect to the running cjdns instance. There are two ways to do this. The normal way is to use the~/.cjdnsadminfile:cjdns=cjdns.connectWithAdminInfo()Or, if you have the IP, port and password and wish to ignore the~/.cjdnsadminfile for whatever reason:cjdns=cjdns.connect(ip,port,password)Once connected, you may call any of thecjdns admin interface functions:peerStats=cjdns.InterfaceController_peerStats()Finally, there is a helper function that allows one to convert a cjdns public key into an IP address:fromcjdnsimportkey_utilskey_utils.to_ipv6('1rfp3guz4jjhfu4dsu5mrz68f7fyp502wcttq6b78xdrjhd4ru80.k')LicenseSame as cjdns, this is a GPLv3 project. Full text of the license is available [here](LICENSE)ContributingI welcome pull requests, please make sure that everything you contribute is pep8 compliant and works on python 2.6, 2.7, 3.2, 3.3 and 3.4. There are some basic tests in place for these things via Travis, but they’re not complete by any means.
Package: cjdnsadmin
cjdnsadmin For Python 3The cjdns python library doesn’t support python3 and is a PITA to
install, due to it’s use of a modified bencode library which is still
called “bencode”, among other things, so I’m cleaning it up.InstallationThe easiest way to install it is:pip install cjdnsadminBut you could also clone it and run:python setup.py installOnce it’s installed, you’ll findpeerStatsandcexecinstalled
in your$PATH, and thecjdnsadminlibrary available for import.UsageUsage is simple. First, import:import cjdnsadminThen, connect to the running cjdns instance. There are two ways to do
this. The normal way is to use the~/.cjdnsadminfile:cjdns = cjdnsadmin.connectWithAdminInfo()Or, if you have the IP, port and password and wish to ignore the~/.cjdnsadminfile for whatever reason:cjdns = cjdnsadmin.connect(ip, port, password)Once connected, you may call any of thecjdns admin interface
functions:peerStats = cjdns.InterfaceController_peerStats()Finally, there is a helper function that allows one to convert a cjdns
public key into an IP address:cjdnsadmin.PublicToIp6('1rfp3guz4jjhfu4dsu5mrz68f7fyp502wcttq6b78xdrjhd4ru80.k')LicenseSame as cjdns, this is a GPLv3 project. Full text of the license is
availablehereContributingI welcome pull requests, please make sure that everything you contribute
is pep8 compliant and works on python 2.6, 2.7, 3.2, 3.3 and 3.4. There
are some basic tests in place for these things via Travis, but they’re
not complete by any means.
Package: cjen
该项目封装了测试人员写自动化代码的常用功能作为装饰器，
目标是能让测试人员更关注业务逻辑的实现，隐藏和业务逻辑无关的细节。
GitHub地址：https://github.com/thcpc/cjenRelease 1.0.1get_mapping, put_mapping, post_mapping, delete_mapping, upload_mapping 增加json_clazz参数，作用同operate.json.factoryRelease 1.0.2修改metaMysql 没有数据时，是警告信息而不是错误信息方便批量检查，增加了 context["cursor"]Release 1.0.2b修改了创建metaMysql后，直接释放数据库连接池（临时修改方案）Release 1.0.3上传的文件支持sqlRelease 1.0.4修改了文件的判断Release 1.0.4.1b测试http请求的写日志文件Release 1.0.4.2bfix a bugRelease 1.0.5增加了http请求的日志文件Release 1.0.5.2增加了封装操作步骤Release 1.0.5.3修复了文件下载日志的bug 和对是否是文件下载的判断Release 1.0.5.4取消了文件下载请求响应的日志Release 1.0.5.5增加了Step的装饰器Release 1.0.5.6bug：不管step是否运行都会注册到BigTangerine
修复：调用接口时才会注册到BigTangerine中Release 1.0.5.7scenario 中的step 都应该使用相同的service, 所以在构造函数中增加了service参数，同时兼容以前的方法Release 1.0.5.8取消FormData中,文件作为必填项Release 1.0.5.9修复了upload 会修改service中的全局headersRelease 1.0.6.0增加了测试装饰器Release 1.0.6.1在Scenario中增加了测试用例的注册机制Release 1.0.6.2修复一些低级错误Release 1.0.71 . 针对 mysql 增加可通过函数参数传递查询参数，而不是一定需要通过上下文传递Release 1.0.71 . 修改查询参数为空时，设置查询参数为Release 1.0.91 . xlsx读取装饰器2 . list_eql 函数Release 1.0.101 . 增加了通用数据结构 树Release 1.0.111 . xlsx 读取装饰器，支持在函数中指定文件路径Release 1.0.121 . property 校验装饰器Release 1.0.131 . 增加DBBigTangerineRelease 1.0.141 . 修复了DatabaseInfo port的BUGRelease 1.0.151 . 增加对数据库字段byte转为Bool
Package: cjeReportingTool
cjeReportingToolThis tool made for CJE(Chishiki Joho Enshu 3) class at Univ. Tsukuba, klis.
This package converts source code comment to markdown text using split words.ja:
筑波大学 KLISのCJE3のマークダウン形式の小レポート用ライブラリです。
特定の文字列##や#$等をコメントに用いると，その記号を用いたコード行末に書いたコメントのみを行番号と合わせて出力します。RequirementThis package does not require on other any packages.InstallationThis package runs on Python 3.6 or higher version. You can install it from PyPI via pip:ja:
このパッケージはPython 3.6以上で動作します。
またpipコマンドで以下のようにインストールできます。pipinstallcjeReportingToolto install.UsageTo use this tool as a package, load as a function.importcjeReportingTool.cjeReportingToolascc.cjeReportingTool(path,outpath,split_str,prefix)Each args:pathRead file pathoutpathExport file pathsplit_strA symbol or string that separates comments from source codeprefixPrefixes to be written outTo use this command as a command,$cjerep-h
usage:cjeReportingTool[-h]pathoutpathsplit_strprefix

ThisToolmadeforCJE(ChishikiJohoEnshu3)classatUniv.Tsukuba,klis.
Thispackageconvertssourcecodecommenttomarkdowntextusingsplitwords.

positionalarguments:pathReadfilepathoutpathExportfilepathsplit_strAsymbolorstringthatseparatescommentsfromsourcecodeprefixAPrefixtobewrittenout

optionalarguments:-h,--helpshowthishelpmessageandexit$cjerepsample.pyout.mdExampleFile.
├── sample.py
├── out.md
└── main.pyRead filesample.py# numi=1##numbern=i*2# outputprint(n)##2Main programmain.pyimport cjeReportingTool.cjeReportingTool as c

c.cjeReportingTool('sample.py', 'out.md', '##', '>')Output fileout.md1   > 2: number
2   
3   > 5: 2Notesplit_struses a string other than the spelling of the symbols used your python code.Good:##,#&,#$,#%Bad:#(No difference from other comments),$(That's not comment)LicenseThis software is released under the MIT License, see LICENSE.
show allhttps://github.com/murataka9/cjeReportingTool/blob/main/LICENSE
Package: cjfx
This module helps ease annoying small tasks especially for data scientists. It has the following main functionalities.cjfx.excelThis module will create an excel file with much ease. You can to rows, columns or target cells, write formulas add sheets and add charts to your excel book. It does not modefy existing ones.cjfx.word_documentThis will help you create word documents including adding figures and basic formating.cjfx.mssql_cinnectionAn easy to use abstraction layer for pyodbc in conjuction with pandas and geopandas to manage MSSQL databases.cjfx.sqlite_connectionAn abstraction layer for sqlite3 for quick management of sqlite databases.functions that you didn't know you neededwrite_to(filepath:str, string_to_write:str) -> writes a string to file on disk
read_from(filepath:str) -> reads from an asci file on disk
exists(path) -> checks if a path exists returns a boolean.
file_name(file_path:str) -> gives you the file basename (with option to include file extension).
list_files(dir_path:str) -> lists all files in a given directory with option to filter by extension. returns a list of paths
list_all_files(dir_path:str) -> same as 'list_files' but includes subfolders.
list_folders(dir_path:str) -> lists all directories in a given folder. returns a list of folder names.
python_variable -> a quick funtion to save or load a python variable to disk.
show_progress -> shows a progress bar for long loops.other functionscopy_file,
    ignore_warnings,
    transparent_image,
    get_file_size,
    merge_documents,
    resize_image,
    download_file,
    get_nse,
    get_pbias,
    delete_path,
    save_array_as_image,
    create_icon,
    unzip_file,

    this_dir,
    copy_projection,
    set_tif_nodata,
    clip_features,
    assign_default_projection,
    plot,
    show,
    copy_directory_tree,
    remove_header_duplicates,
    get_swat_timeseries,
    clip_raster,
    points_to_geodataframe,
    convert_webm_to_mp3,
    download_video_youtube,
    get_relative_path,
    install_package,
    get_usgs_timeseries,
    decode_64,
    wait,
    get_raster_value_for_coords,
    rasterise_shape,
    extract_timeseries_from_netcdf,
    rand_apha_num,
    make_plot,
    goto_dir,
    smart_copy,
    print_dict,
    cd,
    slope_intercept,
    distance,
    download_file2,
    xml_children_attributes,
    report,
    print_list,
    disp,
    create_path,
    flow_duration_curve,
    is_file,
    resample_ts_df,
    raster_statistics,
    empty_line,
    hide_folder,
    time_stamp,
    copy_folder,
    delete_file,
    run_swat_plus,
    open_file_in_code,
    format_timedelta,
    confirm,
    open_tif_as_array,
    single_spaces,
    view,
    quit,
    insert_newlines,
    gdal_datatypes,
    resample_raster,
    create_polygon_geodataframe,
    reproject_raster,
    set_nodata,
    get_extents,
    error,
    strip_characters,