Saravanan666/pypi-org huggingface dataset:
Package: theta
ThetaDeep learning toolbox for end-to-end text information extraction tasks.Theta定位是解决实际工程项目中文本信息抽取任务的实用工具箱，端到端实现从原始文本输入到结构化输出全过程。用户工作聚焦于输入数据格式转换，调整关键参数调度theta完成模型训练推理任务及输出格式化数据利用。Theta应用场景包括国家级重点企业非结构化数据挖掘利用、开放域文本数据结构化抽取、各大在线实体关系抽取类评测赛事等。Theta性能指标要求达到业内主流头部水准，近期参加了包括CCF2019、CHIP2019、CCKS2020、CCL2020等C字头顶级赛事，目前取得10余次决赛奖项，包括7次前三，2次第一。更新2022.09.06 0.50.0nlp.entity_extraction, nlp.relation_extraction安装测试版pip install git+http://github.com/idleuncle/theta.git正式版pip install -U thetaCLUE-CLUENER 细粒度命名实体识别本数据是在清华大学开源的文本分类数据集THUCTC基础上，选出部分数据进行细粒度命名实体标注，原数据来源于Sina News RSS.训练集：10748 验证集：1343标签类别： 数据分为10个标签类别，分别为: 地址（address），书名（book），公司（company），游戏（game），政府（goverment），电影（movie），姓名（name），组织机构（organization），职位（position），景点（scene）数据下载地址：https://github.com/CLUEbenchmark/CLUENER2020排行榜地址：https://cluebenchmarks.com/ner.html完整代码见theta/examples/CLUENER：cluener.ipynb选用bert-base-chinese预训练模型，CLUE测评F1得分77.160。# 训练
make -f Makefile.cluener train

# 推理
make -f Makefile.cluener predict

# 生成提交结果文件
make -f Makefile.cluener submissionCLUE-TNEWS 今日头条中文新闻（短文）分类任务以下样例是CLUE（中文任务基准测评）中今日头条中文新闻（短文）分类任务。数据集来自今日头条的新闻版块，共提取了15个类别的新闻，包括旅游，教育，金融，军事等。数据量：训练集(53,360)，验证集(10,000)，测试集(10,000)例子：
{"label": "102", "label_desc": "news_entertainment", "sentence": "江疏影甜甜圈自拍，迷之角度竟这么好看，美吸引一切事物"}
每一条数据有三个属性，从前往后分别是 分类ID，分类名称，新闻字符串（仅含标题）。选用bert-base-chinese预训练模型，CLUE测评F1得分56.100。完整代码见theta/examples/TNEWS：tnews.ipynbTNEWS数据集下载导入基础库import json
from tqdm import tqdm
from loguru import logger
import numpy as np

from theta.modeling import load_glue_examples
from theta.modeling.glue import GlueTrainer, load_model, get_args
from theta.utils import load_json_file
Package: thetadata
Thetadata Python APITheThetadataPython API provides low latency US equities & options data that may be used for
market research or algorithmic trading applications.Please see this repository'sdocumentationandGitHubfor more details.InstallationJava 11 or higher is required. If you are on Windows, Java 19 will automatically be installed for you. Python 10 or higher ishighlyrecommended.pip install thetadataPlease see ourofficial installation instructionsto get started.ContributingWe welcome all feedback, whether it comes in the form of Github issues, pull requests, or pings in ourDiscord!
Package: theta-etl
Ethereum ETLEthereum ETL lets you convert blockchain data into convenient formats like CSVs and relational databases.Do you just want to query Ethereum data right away? Use thepublic dataset in BigQuery.Full documentation available here.QuickstartInstall Ethereum ETL:pip3installethereum-etlExport blocks and transactions (Schema,Reference):>ethereumetlexport_blocks_and_transactions--start-block0--end-block500000\--blocks-outputblocks.csv--transactions-outputtransactions.csv\--provider-urihttps://mainnet.infura.io/v3/239a1d18eba14f0f9dc1c882de0dc872Export ERC20 and ERC721 transfers (Schema,Reference):>ethereumetlexport_token_transfers--start-block0--end-block500000\--provider-urifile://$HOME/Library/Ethereum/geth.ipc--outputtoken_transfers.csvExport traces (Schema,Reference):>ethereumetlexport_traces--start-block0--end-block500000\--provider-urifile://$HOME/Library/Ethereum/parity.ipc--outputtraces.csvStream blocks, transactions, logs, token_transfers continually to console (Reference):>pip3installethereum-etl[streaming]>ethereumetlstream--start-block500000-eblock,transaction,log,token_transfer--log-filelog.txt\--provider-urihttps://mainnet.infura.io/v3/239a1d18eba14f0f9dc1c882de0dc872Find other commandshere.For the latest version, check out the repo and call>pip3install-e.>python3ethereumetl.pyUseful LinksSchemaCommand ReferenceDocumentationExporting the BlockchainQuerying in Amazon AthenaQuerying in Google BigQueryQuerying in KaggleAirflow DAGsPostgres ETLRunning Tests>pip3install-e.[dev,streaming]>exportETHEREUM_ETL_RUN_SLOW_TESTS=True
>pytest-vvRunning Tox Tests>pip3installtox
>toxRunning in DockerInstall Dockerhttps://docs.docker.com/install/Build a docker image> docker build -t ethereum-etl:latest .
 > docker image lsRun a container out of the image> docker run -v $HOME/output:/ethereum-etl/output ethereum-etl:latest export_all -s 0 -e 5499999 -b 100000 -p https://mainnet.infura.io
 > docker run -v $HOME/output:/ethereum-etl/output ethereum-etl:latest export_all -s 2018-01-01 -e 2018-01-01 -p https://mainnet.infura.ioRun streaming to console or Pub/Sub> docker build -t ethereum-etl:latest -f Dockerfile .
 > echo "Stream to console"
 > docker run ethereum-etl:latest stream --start-block 500000 --log-file log.txt
 > echo "Stream to Pub/Sub"
 > docker run -v /path_to_credentials_file/:/ethereum-etl/ --env GOOGLE_APPLICATION_CREDENTIALS=/ethereum-etl/credentials_file.json ethereum-etl:latest stream --start-block 500000 --output projects/<your-project>/topics/crypto_ethereumProjects using Ethereum ETLGoogle- Public BigQuery Ethereum datasetsNansen by D5- Analytics platform for Ethereum
Package: thetaexif
thetaexifis a Python library for RICOH THETA image.
It provides a EXIF reader class and a rectification tool.RequirementsPython 3.6 or laterPillowScipySetup$ pip install thetaexifUsageIn Python>>> from thetaexif import ExifReader, tag
>>> reader = ExifReader('image.jpg')
>>> reader.makernote[tag.FIRMWARE_VERSION]
b'Rev0102'
>>> reader.theta[tag.ZENITH_ES]
(Fraction(20, 1), Fraction(-24, 1))Show Theta EXIF$ theta-tool info image.jpg
RICOH Marker Note
0x0001 [MakerNoteType]: Rdc
0x0002 [FirmwareVersion]: Rev0102
0x0005 [SerialNumber]: 0000000000102690
0x1000 [RecordingFormat]: 2

THETA Subdir
0x0001 [RicohCameraType]: 1
0x0002 [HDRType]: 0
0x0003 [ZenithEs]: (20, -24)
0x0004 [CompassEs]: 45/2
0x0005 [AbnormalAcceleration]: 0
0x0101 [FilmISO]: (100, 0, 100, 0)
0x0102 [Aperture]: (21/10, 21/10)
0x0103 [ExposureTime]: (1/4000, 1/4000)
0x0104 [SensorSerial1]: A0015348
0x0105 [SensorSerial2]: A0015357Rectificationrectifycommand reads gyroscope and compass data and rotate images to rectify camera pose.Rectify image.jpg and save to image_rectified.jpg:$ theta-tool rectify image.jpgRectify image.jpg using compass data (rotate image to face the north):$ theta-tool rectify -c image.jpgKeep EXIF and rectify:$ theta-tool rectify -e image.jpgChangelog0.2 (2019-05-02)Support Python 3.xRemove the dependency on Cython0.1 (2014-06-22)Initial release
Package: thetaspaceray
Theta Integration for SpaceRayTheta batching for SpaceRay package in order to submit Cobalt jobs and run spaces on different GPU nodes.InstallationIn order to use:In order to use this package on ThetaGPU, you need two things:Definition of objective functionargparseparsed argument space with the following required components:--out: outfile--json: json file of hyperparameter bounds--trials: number of trialsper space, not total--mode: mode to apply duringtune.run, defaults to "max"(optional)--metric: metric used to guidetune.runsearch, defaults to "average_res"(optional)--ray_dir: directory used to store Ray Tune logging files, defaults to/lus/theta-fs0/projects/CVD-Mol-AI/mzvyagin/ray_results(optional)Example Usagefrom argparse import ArgumentParser

### see ray tune docs for more info on how to define objective function and report metrics to ray tune
def objective_func(config):
    ### function training and testing using config from tune.run, then report results
    model.train()
    res = model.test()
    res_dict = {}
    res_dict['res'] = res
    tune.report(**res_dict)
    return res

if __name__ == "__main__":
   print("WARNING: default file locations are used to pickle arguments and hyperspaces. "
         "DO NOT RUN MORE THAN ONE EXPERIMENT AT A TIME.")
   print("Creating spaces.")
   parser = ArgumentParser("Run spaceray hyperparameter search on .")
   startTime = time.time()
   ray.init()
   parser.add_argument("-o", "--out")
   parser.add_argument("-m", "--model")
   parser.add_argument("-t", "--trials")
   parser.add_argument("-n", "--nodes", help="Number of GPU nodes to submit on.")
   parser.add_argument("-j", "--json", help="JSON file defining hyperparameter search space")
   arguments = parser.parse_args()
   theta_spaceray.run(objective_func, arguments)
Package: thetennisplay
thetennisplay더 이상 자리 없어서 🎾 못치는 경우는 그만thetennisplay은thetennisplay(테니스 예약 사이트)에서 자리가 났을 때 알려주는 프로그램 입니다ContentsHow to installDocumentationHow to ContributeCode of ConductLicense📋 How to Install**Chrome,Chromedriver설치를 요구합니다!**Method 1 (PyPI)pip install thetennisplaypython -m thetennisplayMethod 2 (직접 Build하기)git clone https://github.com/jaycho1214/thetennisplaypip install .python -m thetennisplay📖 Documentationthetennisplay watch [OPTIONS]계정 (필수)--username 이메일--password 비밀번호thetennisplay에 로그인할 때 사용되는 계정입니다. 계정은 로그인 할때만 사용되며 어떠한 형태로도 저장되지 않습니다 :)카카오 로그인은 현재 지원하지 않습니다예약 정보--court [코트]예약할려는 코트를 입력합니다현재 예약 가능 코트반포종합운동장 테니스장동작주차공원 테니스장--date [날짜 (YYYY-MM-DD)]예약할려는 날짜를 년-월-일 (예: 2023-10-16)로 입력하면 이때 비어있는 코트를 확인합니다--hour [시간]예약할려는 시간을14또는14-18와 같이 입력하면 이때 시간이 나는 경우 소리로 알려줍니다. 위 값이 없을경우 그 시간대에 아무 시간이나 자리가 있으면 알려줍니다👏 How to Contribute발견된 문제나 피드백은 여기로 알려주세요 :)제보하기📄 License[MIT License]
(https://github.com/jaycho1214/thetennisplay/blob/main/LICENSE)
Package: theto
Theto: workflow automation for exploring location dataAny visualization requires a large number of trivial decisions that, when added up, result in a non-trivial
impact on the quality and usability of the visualization. This is especially true of geospatial visualization,
where data needs to transformed fit a particular map projection or a particular map tile service needs to be
configured to contextualize the plot.Thetoabstracts a lot of this overhead so more time can be devoted
to looking at and understanding the data. AThetoinstance allows users to:Store api keys, palettes, and other static resources repeatedly needed throughout a typical visualization
pipeline.Load data sources, format coordinate data to stage it for all foreseeable downstream needs, and append metadata.Add widgets to interactively filter what the final visualization shows, and infer the appropriate parameters
for those widgets based on the source data.Determine plot bounds, size, map zoom level, and other parameters in ways that accommodate the data.Add layers of visualization, including tooltips and other visual aids, including connections between data points.Render the plot, either in the notebook or by saving to file, optionally appending an interactive legend."Theto" is a transliteration of the Greek word Θέτω, which means "I place" or "I situate", or simply "I put".
That's what the tool does: it puts geospatial data where it needs to be so users can spend their time looking
at and making sense of what's there.A Jupyter notebook demonstrating a lot ofTheto's functionality can be found here:https://nbviewer.jupyter.org/github/Valassis-Digital-Media/theto/blob/master/theto_demo_notebook.ipynbInstallationTo install from PyPI:pip install thetocondainstallation coming soon.Supported data representationsData can be loaded in a variety of formats (geohashes, WKT, shapely objects, GeoJSON, or coordinate pairs). The tool
will automatically detect the format and process it appropriately. Likewise, any input can be rendered as the original
shape itself (a polygon) or as the centroid of the shape (a point). Polygons are rendered using Bokeh'sMultiPolygonsglyph. Points can be rendered using any of Bokeh's marker glyphs.LimitationsThetois designed for interactive exploration, and is therefore appropriate for small-to-medium sized data.
A very rough benchmark indicated that it takes about 5 seconds to plot every 50,000 points (a polygon might contain
very many individual points) in a Jupyer notebook, and the notebook freezes at around 250,000 points. Outputting to
file and viewing in a separate browser window should allow up to around 1 million points. For larger visualization,
seehttp://datashader.org/.ContributingWe welcome issues and pull requests that help improve the variety of data sources and plot elements Theto
supports, its usability, and its re-usability within other tools.LicenseCopyright (c) 2019 Valassis Digital under the terms of the BSD 3-Clause license
Package: the-todo
The-TodoTable of ContentsInstallationDescription of ProjectCustomizationFile DescriptionsLicensingInstallationTo install the app, you can usepip:pipinstallthe-todoTo use the todo, all you have to do is open terminal and type:python-mtodoThe todo app has following options available to manage tasks :DescriptionThis is a simple command-line todo app built in Python. It allows you to add, view, mark as completed, and remove tasks from a todo list using a terminal interface.Options :1.add  : Add task2.ls   : View tasks3.cplt : Mark task as completed4.rm   : Remove task5.exit : ExitYou can then enter one of these commands to perform an action.Examples :Add a new task :todo>>addBuygroceries
Taskaddedsuccessfully!View all tasks :todo>>ls
Tasks:1.BuygroceriesMark a task as completed :todo>>cplt1Taskmarkedascompleted!Remove a task :todo>>rm1Taskremovedsuccessfully!CustomizationBy default, the app creates a todo list called "todo" and stores it in a SQLite database at ~/.todos/todo.db. However, you can specify a different name for the list by using the -n or --name option:python-mtodo--namemylistThis will create a new todo list called "mylist" and store it in a SQLite database at ~/.todos/mylist.db.File Description.
├── README.md
├── LICENCE : contains MIT LICENCE
├── setup.py : Setup file to create distribution packages
└── todo : The todo package
    ├── __init__.py
    ├── __main__.py 
    ├── todo.py : Todo class with modular code
    └── todo_prompt.py : Todo PromptLicensingThis app is released under the MIT License. Feel free to use, modify, and distribute it as you like.
Package: thetool
# thetoolThis script is used to download and install tools from the internet. It is designed to be used with Linux, but it can be used with any operating system that has Python installed.## InstallationTo install thetool, run the following command:`bash python3-mpip install thetool `## UsageTo use thetool, run the following command:`bash thetool install <tool> `To uninstall a tool, run the following command:`bash thetool uninstall <tool> `To see a list of available tools, run the following command:`bash thetool list `To see the list and version of installed tools, run the following command:`bash thetool list--installed`To get information about a tool, run the following command:`bash thetool info <tool> `To update thetool, run the following command:`bash thetool update `To upgrade a tool, run the following command:`bash thetool upgrade <tool> `To upgrade all tools, run the following command:`bash thetool upgrade--all`To clean up the cache, run the following command:`bash thetool clean `## Databasethetool uses a database to store information about tools. The database is stored in another GitHub repository, [thetool-Database](https://github.com/Lunik/thetool_database)## ContributingPull requests are welcome. For major changes, please open an issue first to discuss what you would like to change.
Package: the-useless-cli
The useless CLIWhat is this?This is a useless CLI that does some things that are not really helpful. It is written in Python and is cross-platform. I mainly made this to learn how to use Typer and PyInstaller. I also wanted to make a CLI that does something useful, but I couldn't think of anything. So I made this.InstallationUse pip to download from PyPI:pip install the-useless-cliOr install from the .tar.gz, click this button to install the latest version:pip install the_useless_cli-0.0.1.tar.gzBuild instructions (ignore if you want to install)If you just want to install, don't build it yourself. Download the latest release from pip. If you want to build it yourself, follow these steps:Clone the repositorypyinstaller src/__main__.py --onefile --name uselessMove the executable to a folder in your PATHRunuselessin your terminalEnjoy!CommandsEverything is listed inhere.
If you don't want to read that, just tryuseless --helpin your terminal.LicenseThis project is licensed under the GNU GPLv3 license. SeeLICENSEfor more information.In short:Anyone who modifies or distributes this code must make their modifications or distribution available under the GPL.Anyone who distributes this code must give "ItsQuadrus" credit as the original author.Derivative works must be distributed under the same license terms as the original work.(This is a summary, not the license itself. This is not legal advice. Read the full license for more information.)
Package: th-eventhub-models
th-eventhub-modelsThis Repo Contains The Object Models For The Transform Health Event Hub Operations.To Publish ChangesMake changes to the modelsUpdate the version number insetup.pyInstall dist tools by usingpython -m pip install --user --upgrade setuptools wheelRunpython setup.py sdist bdist_wheelTest locally by runningpip install -e .Install twine bypython -m pip install --user --upgrade twineAfter creating an account in testPy upload it in testPy bypython -m twine upload - repository testpypi dist/*Test if it works as expected by uninstalling the local version and installing the testPy version bypip uninstall th-eventhub-models --yes-i-know-what-i-am-doingand thenpip install -i https://test.pypi.org/th-eventhub-models/th-eventhub-models==<version-number>Upload to PyPI Repository by runningpython -m twine upload dist/*Install in any repository of your choice by usingpip install th-eventhub-modelsand import by usingfrom transformHealthEventHubModels.insertOne import DSEventHubInsertOneObject
Package: the-video-editaneitor
READMEThis README would normally document whatever steps are necessary to get your application up and running.What is this repository for?Quick summaryVersionLearn MarkdownHow do I get set up?Summary of set upConfigurationDependenciesDatabase configurationHow to run testsDeployment instructionsContribution guidelinesWriting testsCode reviewOther guidelinesWho do I talk to?Repo owner or adminOther community or team contact
Package: thevpncompany
TheVPNCompanyTheVPNCompanyis an Open Source VPN company who intends to:Increase transparency, allowing to be audited by anyone.Increase the usage of VPNs around, based on companies and practices that are transparent.This package consists on a set of daemons and scripts required for different subsystems.1 -consumer_orchestration.py, consumer that creates fully configured OpenVPN servers in 120 seconds.2 -consumer_certificates.py, consumer that creates new OpenVPN certificates.The following scripts provides information to Zabbix monitoring systems:1 -zabbix_openvpn_user_discovery.py, which discover connected OpenVPN Users using the management console2 -zabbix_openvpn_usage_per_user.py, which reports the data usage per user3 -zabbix_track_monthly_traffic.py, which reports the OpenVPN data usage per monthInstallationInstall the scripts from the source codepythonsetup.pyinstallInstall the scripts frompippipinstallthevpncompanyDocumentationYou can find the documentation for all the released Open Source code on TheVPNCompany website:https://thevpncompany.com.au
Package: thewalrus
A library for the calculation of hafnians, Hermite polynomials and Gaussian boson sampling. For more information, please see thedocumentation.FeaturesFast calculation of hafnians, loop hafnians, and torontonians of general and certain structured matrices.An easy to use interface to use the loop hafnian for Gaussian quantum state calculations.Sampling algorithms for hafnian and torontonians of graphs.Efficient classical methods for approximating the hafnian of non-negative matrices.Easy to use implementations of the multidimensional Hermite polynomials, which can also be used to calculate hafnians of all reductions of a given matrix.InstallationThe Walrus requires Python version 3.7, 3.8, 3.9, or 3.10. Installation of The Walrus, as
well as all dependencies, can be done using pip:pipinstallthewalrusCompiling from sourceThe Walrus has the following dependencies:Python>= 3.7NumPy>= 1.19.2Numba>= 0.49.1SciPy>=1.2.1SymPy>=1.5.1Dask[delayed]You can compile the latest development version by cloning the git repository, and installing using
pip in development mode.$gitclonehttps://github.com/XanaduAI/thewalrus.git$cdthewalrus&&python-mpipinstall-e.Software testsTo ensure that The Walrus library is working correctly after installation, the test
suite can be run locally using pytest.Additional packages are required to run the tests. These dependencies can be found inrequirements-dev.txtand can be installed usingpip:$pipinstall-rrequirements-dev.txtTo run the tests, navigate to the source code folder and run the command$maketestDocumentationThe Walrus documentation is available online onRead the Docs.Additional packages are required to build the documentation locally as specified indoc/requirements.txt.
These packages can be installed using:$sudoaptinstallpandoc$pipinstall-rdocs/requirements.txtTo build the HTML documentation, go to the top-level directory and run the command$makedocThe documentation can then be found in thedocs/_build/html/directory.Contributing to The WalrusWe welcome contributions - simply fork The Walrus repository, and then make a pull request containing your contribution. All contributors to The Walrus will be listed as authors on the releases.We also encourage bug reports, suggestions for new features and enhancements, and even links to projects, applications or scientific publications that use The Walrus.AuthorsThe Walrus is the work ofmany contributors.If you are doing research using The Walrus, please citeour paper:Brajesh Gupt, Josh Izaac and Nicolas Quesada. The Walrus: a library for the calculation of hafnians, Hermite polynomials and Gaussian boson sampling. Journal of Open Source Software, 4(44), 1705 (2019)SupportSource Code:https://github.com/XanaduAI/thewalrusIssue Tracker:https://github.com/XanaduAI/thewalrus/issuesIf you are having issues, please let us know by posting the issue on our Github issue tracker.LicenseThe Walrus isfreeandopen source, released under the Apache License, Version 2.0.
Package: the-well-maintained-test
the-well-maintained-testProgramatically tries to answer the 12 questions from Adam Johnson'sblog postInstallationInstall this tool usingpip:$ pip install the-well-maintained-testAuthenticationThe GitHub API will rate limit anonymous calls. You can authenticate yourself with a personal token (documentation on how to generate ishere)Run this command and paste in your new token:the-well-maintained-test authThis will create a file called auth.json in your current directory containing the required value. To save the file at a different path or filename, use the--auth=myauth.jsonoption.the-well-maintained-test --helpUsage: the-well-maintained-test [OPTIONS] COMMAND [ARGS]...

  Programatically tries to answer the 12 questions from Adam Johnson's blog post
  https://adamj.eu/tech/2021/11/04/the-well-maintained-test/

  package is a package on pypi you'd like to check:

      the-well-maintained-test package the-well-maintained-test

Options:
  --version  Show the version and exit.
  --help     Show this message and exit.

Commands:
  auth          Generates a json file with your GitHub Personal Token so...
  check         Check your GitHub API Usage Stats
  package       Name of a package on PyPi you'd like to check
  questions     List of questions tested
  requirements  Loop over a requirements.txt fileDevelopmentTo contribute to this tool, first checkout the code. Then create a new virtual environment:cd the-well-maintained-test
python -m venv venv
source venv/bin/activateOr if you are usingpipenv:pipenv shellNow install the dependencies and test dependencies:pip install -e '.[test]'To run the tests:just testTo runmypycommand you'll need to runmypy --install-typesThen, to run mypy:just mypyYou can also do a pre-commit check on the files by runningjust checkThis will run several pre-commit hooks, but before that it will runmypy