Saravanan666/pypi-org huggingface dataset:
Package: annotypes
Adding annotations to Python types while still being compatible withmypyandPyCharmYou can write things like:fromannotypesimportAnno,WithCallTypeswithAnno("The exposure time for the camera"):AExposure=floatwithAnno("The full path to the text file to write"):APath=strclassSimple(WithCallTypes):def__init__(self,exposure,path="/tmp/file.txt"):# type: (AExposure, APath) -> Noneself.exposure=exposureself.path=pathor the Python3 alternative:fromannotypesimportAnno,WithCallTypeswithAnno("The exposure time for the camera"):AExposure=floatwithAnno("The full path to the text file to write"):APath=strclassSimple(WithCallTypes):def__init__(self,exposure:AExposure,path:APath="/tmp/file.txt"):self.exposure=exposureself.path=pathAnd at runtime see what you should pass to call it and what it will return:>>>fromannotypes.py2_examples.simpleimportSimple>>>list(Simple.call_types)['exposure', 'path']>>>Simple.call_types['exposure']Anno(name='AExposure', typ=<type 'float'>, description='The exposure time for the camera')>>>Simple.return_typeAnno(name='Instance', typ=<class 'annotypes.py2_examples.simple.Simple'>, description='Class instance')For more examples see thePython 2 examplesorPython 3 examples.InstallationTo install the latest release, type:pip install annotypesTo install the latest code directly from source, type:pip install git+git://github.com/dls-controls/annotypes.gitChangelogSeeCHANGELOGContributingSeeCONTRIBUTINGLicenseAPACHE License. (seeLICENSE)
Package: announcer
announcerThis tool:takes ankeepachangelog-style CHANGELOG.md fileextracts all changes for a particular versionand sends a formatted message to a Slack or Microsoft Teams webhook.It is available as a Python package, or as a Docker container for use in CI.InstallationInstall this tool using pip:pip install announcerTool usageusage: announce [-h] (--webhook WEBHOOK | --slackhook WEBHOOK) [--target {slack,teams}] --changelogversion CHANGELOGVERSION --changelogfile CHANGELOGFILE --projectname PROJECTNAME
                [--username USERNAME] [--compatibility-teams-sections] [--iconurl ICONURL | --iconemoji ICONEMOJI]

Announce CHANGELOG changes on Slack and Microsoft Teams

optional arguments:
  -h, --help            show this help message and exit
  --webhook WEBHOOK     The incoming webhook URL
  --slackhook WEBHOOK   The incoming webhook URL. (Deprecated)
  --target {slack,teams}
                        The type of announcement that should be sent to the webhook
  --changelogversion CHANGELOGVERSION
                        The changelog version to announce (e.g. 1.0.0)
  --changelogfile CHANGELOGFILE
                        The file containing changelog details (e.g. CHANGELOG.md)
  --projectname PROJECTNAME
                        The name of the project to announce (e.g. announcer)
  --username USERNAME   The username that the announcement will be made as (e.g. announcer). Valid for: Slack
  --compatibility-teams-sections
                        Compatibility option - sends Teams messages in multiple sections
  --iconurl ICONURL     A URL to use for the user icon in the announcement. Valid for: Slack
  --iconemoji ICONEMOJI
                        An emoji code to use for the user icon in the announcement (e.g. party_parrot). Valid for: SlackGitlab UsageAnnouncer builds and publishes a Docker image that you can integrate into your.gitlab-ci.yml:announce:
  stage: announce
  image: metaswitch/announcer:5.0.0
  script:
   - announce --webhook <webhook address>
              --changelogversion $CI_COMMIT_REF_NAME
              --changelogfile <CHANGELOG.md file>
              --projectname <Project name>
              --iconemoji party_parrot
  only:
    - tags
Package: announce-server
Announce ServerA Python library that announces a server to a host.Installationpipinstallannounce-serverDevelopmentTo install the developer dependencies required for testing and publishing:pipinstall-e.[dev,pub]BuildTo build the package, run:rm-rfdist/build/.eggs/.pytest_cache/src/announce_server.egg-info/
python-mbuild--sdist--wheelTo publish:twineuploaddist/*TestTo run the tests, call:pytestUsagefromannounce_serverimportregister_service@register_service(name="server_name",ip="server_ip",port=8000,host_ip="host_server_ip",host_port=5000,retry_interval=5)defyour_function():passRegistryTheannounce_serverCLI provides a simple way to start a registry server. The registry server keeps track of available services and periodically sends heartbeat messages to ensure that registered services are still active.Commandannounce_serverstart_registry[--addressADDRESS][--portPORT][--heartbeat_intervalINTERVAL][--heartbeat_timeoutTIMEOUT]Arguments--address ADDRESS: The IP address of the server. Default:0.0.0.0.--port PORT: The port number of the server. Default:4999.--heartbeat_interval INTERVAL: The interval between heartbeat messages in seconds. Default:5.--heartbeat_timeout TIMEOUT: The timeout for waiting for a response in seconds. Default:3.ExampleTo start the registry server with the default configuration, run:announce_serverstart_registryThe full syntax is equivalent to:announce_serverstart_registry--address0.0.0.0--port4999--heartbeat_interval5--heartbeat_timeout3
Package: annovar-tools
ANNOVAR tools该包是配合ANNOVAR对相关文件进行处理的工具集vcf将ANNOVAR输入文件,AVinput文件转换为VCF4.0格式-i/--avinput: 输入文件,AVinput格式-r/--reference: 参考基因组文件如hg19.fa,请事先使用samtools faidex构建索引-o/--vcf: 输出的VCF文件zhuy@ubuntu:/projects/example$annovar_tools.pyvcf-itest.avinput-rhg19.fa-otest.vcfsplit将ANNOVAR注释结果按照Gene拆分为多行，一次只能拆分一种gene-based数据库-i/--avoutput: 输入文件,ANNVOAR注释结果，如test.hg19_multianno.txt-r/--refgenes: 运行ANNOVAR所用的注释refGene文件，如hg19_ensGene.txt,hg19_knownGene.txt,hg19_refGeneWithVer.txt-g/gene_db: 所需拆分的gene-based数据库, 如refGeneWithVer,即ANNVOAR g参数对应的数据库名称,在ANNOVAR结果中体现为"Func.refGeneWithVer, Gene.refGeneWithVer, GeneDetail.refGeneWithVer, ExonicFunc.refGeneWithVer,
AAChange.refGeneWithVer"-o/--outfile: 输出的拆分后的文件zhuy@ubuntu:/projects/example$annovar_tools.pysplit\-itest.hg19_multianno.txt\-rhg19_refGeneWithVer.txt\-rhg19_ensGene.txt\-rhg19_knownGene.txt\-grefGeneWithVer-otest.hg19_multianno.refGeneWithVer.txt
Package: annoworkapi
annowork-api-python-clientAnnowork WebAPIのPython用クライントライブラリです。RequirementsPython 3.8+Install$ pip install annoworkapiUsage認証情報の設定方法$HOME/.netrcmachine annowork.com
login ${user_id}
password ${password}環境変数に設定する場合環境変数ANNOWORK_USER_IDにユーザID,ANNOWORK_PASSWORDにパスワードを設定する。基本的な使い方importannoworkapiservice=annoworkapi.build()result=service.api.get_my_account()print(result)# {'account_id': 'xxx', ... }応用的な使い方ログの出力importlogginglogging_formatter='%(levelname)-8s:%(asctime)s:%(name)s:%(message)s'logging.basicConfig(format=logging_formatter)logging.getLogger("annoworkapi").setLevel(level=logging.DEBUG)In [1]: c = s.api.get_actual_working_times_by_workspacen_member("a9956d30-b201-418a-a03b-b9b8b55b2e3d", "204bf4d9-4569-4b7b-89b9-84f089201247")
DEBUG    : 2022-01-11 17:36:04,354 : api.py : annoworkapi.api : _request_wrapper : Sent a request :: {'request': {'http_method': 'get', 'url': 'https://annowork.com/api/v1/workspacens/a9956d30-b201-418a-a03b-b9b8b55b2e3d/members/204bf4d9-4569-4b7b-89b9-84f089201247/actual-working-times', 'query_params': None, 'header_params': None, 'request_body': None}, 'response': {'status_code': 200, 'content_length': 209988}}開発者用ドキュメントREADME_for_developer.md参照
Package: annoworkcli
annowork-cliAnnoworkのCLIです。RequirementsPython3.8+Install$ pip install annoworkcliUsage認証情報の設定.netrc$HOME/.netrcファイルに以下を記載する。machine annowork.com
login annowork_user_id
password annowork_password環境変数環境変数ANNOWORK_USER_ID,ANNOWORK_PASSWORDannoworkcli annofabコマンドを利用する場合annoworkcli annofabコマンドはannofabのwebapiにアクセスするため、annofabのwebapiの認証情報を指定する必要があります。環境変数ANNOFAB_USER_ID,ANNOFAB_PASSWORD$HOME/.netrcファイルmachine annofab.com
login annofab_user_id
password annofab_passwordコマンドの使い方# CSV出力
$ annoworkcli actual_working_time list_daily --workspace_id foo \
 --start_date 2022-05-01 --end_date 2022-05-10 --output out.csv

$ cat out.csv
date,job_id,job_name,workspace_member_id,user_id,username,actual_working_hours,notes
2022-05-02,5c39a2e8-90dd-4f20-b0a6-39d7f5129e3d,MOON,52ff73fb-c1d6-4ad6-a185-64386ee7169f,alice,Alice,11.233333333333334,
2022-05-02,5c39a2e8-90dd-4f20-b0a6-39d7f5129e3d,MARS,c66acd58-c893-4908-bdcc-1414978bf06b,bob,Bob,8.0,開発者向けの情報https://github.com/kurusugawa-computer/annowork-cli/blob/main/README_for_developer.md
Package: annoyance
annoyfor theannotation ofcell types.Annoyanceis a simple API for classifying cell types as annotated in anadata.obstable.InstallationpipinstallannoyanceTo install the development versiongitclonehttps://github.com/mvinyard/annoyance.gitcd./annoyance/
pipinstall-e.NotesThis project uses open-source code fromspotify/annoy. However,this repo is in no way affiliated with Spotify.Interested? Questions and discussion may be directed toMichael Vinyardat:mvinyard@broadinstitute.org.
Package: annt
anntSimple annotated file loader for object detection task.DescriptionVarious tools have been developed so far for object detection tasks.
However, there are no standard in annotation tools and formats and
developers still write their own json or xml parser of annotation files.anntis an annotation tool that operates in the form of cloud services such as dropbox.
annt provides not only simple and comfortable annotation exprience, but also powerful library for loading annotated images.This is the python library which can read images annotated with annt.
You can load annotated images in a simple way and focus on the essential AI development.
Also, this library has a basic build-in preprocessing functions. So you can save time to write extra code.Usage and ExampleExample 1. Load annotated imagesimportannt# annotations is list of annotation dataannotations=annt.load('~/Dropbox/app/project_name')# Display ths information of each annotation file.forainannotations:image=a.image# opencv2 image arrayboxes=a.boxes# list of bounding boxesheight,width,colors=image.shape# you canforboxinboxes:# Tag information (str)print(f'~ tag name : box.tag ~')# You can get coordination information of the box by two methods,# Left Top Style and Edge Style.# Coordination information based on left top of the box. (Left-Top Style)print(f'x :{box.x}')print(f'y :{box.y}')print(f'w :{box.w}')print(f'h :{box.h}')# Coordination information based on the distance from each edge of the image. (Edge Style)print(f'left :{box.left}')print(f'right :{box.right}')print(f'top :{box.top}')print(f'bottom :{box.bottom}')# If you change these coordination properties, all of them will recomputed.box.w=300# This operation will also change box.right property.Example 2. Data augumentationimportanntimportrandom# annotations is list of annotation dataannotations=annt.load('./Dropbox/App/annt/test')sample_n=10# Number of samples from one image# Display ths information of each annotation file.augumented=[]forraw_ainannotations:foriinrange(sample_n):# Rotate imagerot_deg=random.choice([0,90,180,270,360])a=raw_a.rotate(rot_deg)# Tilt imagetilt_deg=random.randint(-8,8)a=a.rotate(tilt_deg)# Flip imageflip_x=random.randint(0,1)flip_y=random.randint(0,1)a=a.flip(flip_x,flip_y)augumented.append(a)# Show first augumented image.augumented[0].show()Getting StartedRegister annt and annotate imaes.Install this libary from pip.Develop you own project.Installyou can install from pip.pip install anntDocumentationsSeehttp://doc.annt.ai/Recent Updates0.0.7: Bug fix.
Package: anntonia
Artificial Neural Network to Node-link Immersive Analytics (ANNtoNIA)ANNtoNIA is a framework for building immersive node-link visualizations, designed for Artificial Neural Networks (ANN). It is currently under development and unfinished. For any questions, contact @mbellgardt.Recommended SetupDownload and installAnaconda, then create an environment, by executing:conda create -c conda-forge --name anntonia --file anntonia-env.txtin the anaconda prompt. Activate the environment using:conda activate anntoniaAfterwards you can run one of the examples by, e.g:python linear_model_test_server.pyThis will start the ANNtoNIA server, you can then connect to with theANNtoNIA rendering client.
Package: anntonia-keras
ANNtoNIA_KerasANNtoNIA_Keras is an extension for theANNtoNIAframework, which allows ANNtoNIA to extract the needed data from Keras models to visualize them.Using ANNtoNIA_KerasInstantiate a KerasReader from to path to your Keras model, for example with:model = KerasReader('path_to_your_model')Then, you can use this reader for a visualizer, such as the LinearModelVisualizer from ANNtoNIA:LinearModelVisualizer(model, test_data)
Package: anntoolkit
AnnToolKit - Image annotation toolkitCross-platform, dataset agnostic, "DIY" style image annotation frameworkGetting startedDocumentation -http://anntoolkit.rtfd.io/1. Installpip install anntoolkit2. Hello worldSubclass fromanntoolkit.AppIn init method load some test image.importanntoolkitclassApp(anntoolkit.App):def__init__(self):super(App,self).__init__(title='Test')im=imageio.imread('test_image.jpg')self.set_image(im)Run app:app=App()app.run()Result:
Package: anntools
The anntools package provides various modules to take advantage
of Python 3.0’s new function annotation feature. It supports
validation, conversion and type checking of parameters passed
to functions and their return values. It is useful for adding
security checks and make your code more readable. This package
is useful for Python 2.4 and up, since all functionality is
also provided as keyword arguments for decorators.Read the INSTALL file or see the home page for more information,
documentation, tests and examples:http://code.google.com/p/anntools/
Package: annual-stats
The Archive "annual_stats"This is a quick Python app that generates a Markdown-compatible table of yearly zettelkasting stats for users of The Archive.Usage (Example)Change to the directory where you installed the application and run the following command in Terminal.python main.pyYou'll be prompted to enter the 4 digit year of your oldest note.Earliest year:Look for the output where you specified with thetable_outputvariable.  ``Sample OutputLicienceMITDisclaimerWhen it comes to Python, I am just a hobbyist. So it's very likely I made some mistakes. Please bear with me. Let me know and I'll fix things and in doing so, you'll be teaching me to be a better programmer.
Package: ann_visualizer
ANN Visualizer is a great visualization python library used to work with Keras. It uses python’s graphviz library to create a presentable graph of the neural network you are building.Usage:from ann_visualizer.visualize import ann_viz;
#Build your model here
ann_viz(model)Documentation:ann_viz(model, view=True, filename=”network.gv”)model - The Keras Sequential model
view - If True, it opens the graph preview after executed
filename - Where to save the graph. (.gv file format)
Package: anobbs-client
AnoBBS ClientAnoBBS（A岛所用匿名版架构）API 的 Python 封装库。功能随个人需要增加。注意⚠️：由于本库出发点的项目没有多线程需求，所以本库当前只以单线程使用为目的设计。虽然每个请求都奢侈地专门创建了一个新的 Session，但共用的 CookieJar 并非线程安全。实现功能查看版块页面版块列表/版规介绍/…遍历反向遍历串页面遍历版块页面发布串回应添加订阅/删除订阅装载饼干…术语「卡页」「卡99」访问串的100页之后的页面，响应的会是100页的内容。示例毕竟只是自用，感觉也不会有其他人感兴趣，就不在这方面多费时间了。下面都是些最基础的例子，剩下的就让源代码自己去解释吧 (ゝ∀･)创建客户端client=anobbsclient.Client(# 客户端的 User-Agentuser_agent='…',# 目标服务器的主机名，如 'adnmb3.com'host='…',# 客户端的 appid，可为 `None`appid='…',# 与单次请求相关的一些选项，发送请求时可以选择覆盖这些选项default_request_options={# 在浏览器中以名为 userhash 的 cookie 的形式呈现，登录的凭证。# 领饼干领的就是这个。# 在需要提供此值（如访问超过100页的页面）而此值空缺时# 会直接抛异常'user_cookie':'…',# 要怎么处理登录：# 'enforce':            无论如何都会在请求中包含 user_cookie。#                       无论操作是否需要登录，都要提供 user_cookie# 'when_has_cookie':    只要提供了 user_cookie，就会在请求中包含它# 'when_required':      当需要进行需要登录的操作时，#                       才会在请求中包含 user_cookie# 'always_no':          无论如何都不在请求中包含 user_cookie。#                       遇到需要登录的操作会直接抛异常'login_policy':'when_required',},)获取串内容luwei_thread=client.get_thread_page(49607,page=1)print(luwei_thread.content)#=> '这是芦苇'获取版块内容g_board=client.get_board_page(4,page=1)print(g_board[0].user_id)#=> 'ATM'发布回应try:client.reply_thread("正文内容",to_thread_id=999999999999,title="标题（可选）",name="名称（可选）",email="邮箱（可选）",)exceptanobbsclient.ReplyExceptionase:# 服务器不接受所发回应print(e.raw_error,e.raw_detail)raisee反向遍历串页面Q：为何这么做？A：防止遍历途中有串被抽导致遗漏。例子略，只是表示有这个功能 (ゝ∀･)
Package: anobii.api
==Introduction==============This is a wrapper for the Anobii APIs.see: http://api.anobii.com/api/api_home.phpMy approach is so similar to the one used by flickrApi that I get his code fromhttp://flickrapi.sf.net/and I adapted it to Anobii API.thanks to Sybren Stuvel for his work.This product uses the aNobii API but is not endorsed or certified by aNobii.How to use it=============It's quite easy. first of all istance the AnobiiApi passing key and secret:>>> a = anobii.api.AnobiiAPI(key, secret)then call the api you need. for example to call theanobii.shelf.getSimpleShelf('user', 'limit')you can call:>>> a.shelf_getSimpleShelf(user_id='massimoazzolini', limit='3')note that "anobii" disappears (a is anobii..) and "shelf." is replaced by "shelf_".that's it.Changelog=========0.1 - Unreleased----------------* Initial release
Package: anodi
anodi[1]is a decorator-based backport ofPEP 3107,
function annotations, to Python 2.7, along with a limited set of tools
based on those annotations (e.g.,anodi.tools.document, which hoists
annotations into the docstring, for theSphinxautodocextension to find).[1]Etymology:The Welsh forannotationisanodi(according toGoogle Translate). It won out over translations to other
languages because it’s short, and phonetically (and, thus,
mnemonically), related. It’s also a tribute to my friend,Allen
Briggs, who passed away, unexpectedly, in March of 2012. Allen
was an amateur student of Welsh, when he wasn’t busymaintaining
the mac68k port of NetBSD, or, as a consequence of his *BSD
work, beingcredited in iOS.
Package: anodict
anodict: annotated dictConvert adictto an annotated object.UsageInstallationpipinstallanodictExampleimportanodictclassPerson:name:strage:intperson=anodict.dict_to_class({"name":"bob","age":23},Person)print("type:",type(person))print("name:",person.name)print("age:",person.age)will give:type: <class '__main__.Person'>
name: bob
age: 23
Package: anoexpress
Anophelesgene expression in resistance studiesAuthors:Sanjay Curtis NagiandVictoria A InghamA python package, colab notebooks and results from a meta-analysis of RNA-Sequencing studies investigating insecticide resistance inAnopheles gambiae s.landAnopheles funestus. Analyses can be launched in Google Colab using the badges below, allowing users to explore gene expression in their own genes of interest.Documentation:https://sanjaynagi.github.io/AnoExpress/Contributing datasetsIf you would like to contribute a dataset from a major malaria vector, please raise anissueoremail me!
Package: anole
AnoleLike a anole, fake everything.Currently support user agent and name fake, other will be coming soon.Thanks for use.How to usefromanoleimportUserAgent# Suppose this is the request headersheaders={"referer":"https://leesoar.com"}user_agent=UserAgent()user_agent.fake(headers)It will check if there is "user-agent" in headers. If not, "user-agent" will update with random.fromanoleimportNamename=Name()name.fake()# Whole name's length is between 2 and 3.name.fake(length=2)# You can specify the length of the name.name.fake(surname="李")# And you can specify the surname.Use as fake_useragentfromanoleimportUserAgentuser_agent=UserAgent()user_agent.random# or user_agent.chrome# or other browsers
Package: anomalies
AnomaliesImplement the anomaly free solution ofarXiv:1905.13729[PRL]:Obtain a numpy arrayzofNintegers which satisfy the Diophantine equations>>>z.sum()0>>>(z**3).sum()0The input is two listslandkwith any(N-3)/2and(N-1)/2integers forNodd, orN/2-1andN/2-1forNeven (N>4).
The function is implemented below under the name:free(l,k)Install$pipinstallanomaliesUSAGE>>>fromanomaliesimportanomaly>>>anomaly.free([-1,1],[4,-2])array([3,3,3,-12,-12,15])>>>anomaly.free.gcd3>>>anomaly.free.simplifiedarray([1,1,1,-4,-4,5])ExampleA sample for4<N<13with integers until|30|with~400 000chiral solutions can be download from:[JSON]
Package: anomalous-diffusion
Stochastic Process SimulationRandom generatorsymmetric stable distributiontotally skewed stable distributionpower-law distributiondiscrete finite probability distributionLevy processstable Levy processsubordinatorPoisson processContinuous-time random walk(CTRW)finite and diverging characteristic waiting timefinite and diverging jump length varianceAlternating processtwo-states process with Levy walk and Brownian motionFractional Brownian motionMultiple internal states processfractional compound Poisson processLevy walk
Package: anomaly-detection-models
anomaly_detection_modelsRepository with some useful anomaly detection model definitions.installfor latest stable versionpip install anomaly_detection_models [--user]for most recent version, usegit clone git@github.com:luclepot/anomaly_detection_models.git
pip install . [--user]with the--userargument specifying local installation.usageimport models directly or subclassanomaly_detection_baseto make a new model (instructions in-source)exampleseedemos/test.ipynbfor an example. general usage is like sklearn, asfrom anomaly_detection_models import SACWoLa

sacwola = SACWoLa(epochs=10, lambda_=1.2)
sacwola.fit(x, y_sim, y_sb)

pred = sacwola.predict(x_test)
Package: anomaly-devosmita
IntroductionTODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project.Getting StartedTODO: Guide users through getting your code up and running on their own system. In this section you can talk about:Installation processSoftware dependenciesLatest releasesAPI referencesBuild and TestTODO: Describe and show how to build your code and run the tests.ContributeTODO: Explain how other users and developers can contribute to make your code better.If you want to learn more about creating good readme files then refer the followingguidelines. You can also seek inspiration from the below readme files:ASP.NET CoreVisual Studio CodeChakra Core
Package: anomaly-ensemble-app
https://github.com/devosmitachatterjee2018/Creating_Python_Libraryhttps://github.com/devosmitachatterjee2018/Anomaly_Ensemble_App/blob/main/README.mdIntroductionTODO: Give a short introduction of your project. Let this section explain the objectives or the motivation behind this project.Getting StartedTODO: Guide users through getting your code up and running on their own system. In this section you can talk about:Installation processSoftware dependenciesLatest releasesAPI referencesBuild and TestTODO: Describe and show how to build your code and run the tests.ContributeTODO: Explain how other users and developers can contribute to make your code better.If you want to learn more about creating good readme files then refer the followingguidelines. You can also seek inspiration from the below readme files:ASP.NET CoreVisual Studio CodeChakra Core
Package: anomalyHTM
Numenta Platform for Intelligent Computing: a machine intelligence platform that implements the HTM learning algorithms. HTM is a detailed computational theory of the neocortex. At the core of HTM are time-based continuous learning algorithms that store and recall spatial and temporal patterns. NuPIC is suited to a variety of problems, particularly anomaly detection and prediction of streaming data sources.For more information, seehttp://numenta.orgor the NuPIC wiki athttps://github.com/numenta/nupic/wiki.