Saravanan666/pypi-org huggingface dataset:
Package: geovisio
GeoVisiois a complete solution for storing andserving your own 📍📷 geolocated pictures(likeStreetView/Mapillary).➡️Give it a tryatpanoramax.ign.frorgeovisio.fr!📦 ComponentsGeoVisio ismodularand made of several components, each of them standardized and ♻️ replaceable.All of them are 📖open-sourceand available online:🌐 Server💻 ClientAPIWebsiteBlur APIWeb viewerGeoPic Tag ReaderCommand line🌐 GeoVisio APIThis repository only containsthe backend and web API.FeaturesAweb APIto search and upload pictures collectionsSearch pictures by ID, date, locationCompatible withSpatioTemporal Asset CatalogandOGC WFS 3specificationsUpload your pictures and sequencesAn easy-to-usebackendGenerates automatically thumbnail, small and tiled versions of your picturesCompatible with various filesystems (classic, S3, FTP...)Authentication and blurring API can be plugged-in for production-ready useInstall & runOurdocumentationwill help you install, configure and run a GeoVisio instance.If at some point you're lost or need help, you can contact us throughissuesor byemail.ContributingPull requests are welcome. For major changes, please open anissuefirst to discuss what you would like to change.More information about developing is available indocumentation.🤗 Special thanksGeoVisio was made possible thanks to a group of ✨amazingpeople ✨ :GéoVéloteam, for 💶 funding initial development and for 🔍 testing/improving softwareCarto Citéteam (in particular Antoine Riche), for 💶 funding improvements on viewer (map browser, flat pictures support)La Fabrique des Géocommuns (IGN)for offering long-term support and funding thePanoramaxinitiative and core team (Camille Salou, Mathilde Ferrey, Christian Quest, Antoine Desbordes, Jean Andreani, Adrien Pavie)Manymanywonderful peoplewho worked on various parts of GeoVisio or core dependencies we use : 🧙 Stéphane Péneau, 🎚 Albin Calais & Cyrille Giquello, 📷Damien Sorel, Pascal Rhod, Nick Whitelegg...Adrien Pavie, for ⚙️ initial development of GeoVisioAnd you all ✨GeoVisio usersfor making this project useful !⚖️ LicenseCopyright (c) GeoVisio team 2022-2023,released under MIT license.
Package: geovista-slam
geovista-slamGeoVistautility to convertCF UGRIDLocal Area Model quad-cell meshes
into structured rectilinear or curvilinear grids.⚙️ CI💬 Community✨ Meta📦 Package🧰 RepoInstallationgeovista-slamis available onconda-forgeandPyPI.We recommend usingmambato installgeovista-slam👍condageovista-slamis available onconda-forge, and can be easily installed withconda:condainstall-cconda-forgegeovista-slamor alternatively withmamba:mambainstall-cconda-forgegeovista-slamFor more information see ourconda-forge feedstock.pipgeovista-slamis also available onPyPI:pipinstallgeovista-slamHowever, complications may arise due to thecartopypackage dependencies.Licensegeovista-slamis distributed under the terms of theBSD-3-Clauselicense.#ShowYourStripesGraphics and Lead Scientist:Ed Hawkins, National Centre for Atmospheric Science, University of Reading.Data: Berkeley Earth, NOAA, UK Met Office, MeteoSwiss, DWD, SMHI, UoR, Meteo France & ZAMG.#ShowYourStripesis distributed under aCreative Commons Attribution 4.0 International License
Package: geovis-upload-sdk
使用from geovis_upload_sdk import Uploader

uploader = Uploader(hostURL, appKey, secretKey)
result = uploader.upload(categoryId, file)1 安装pipuninstallgeovis_upload_sdk

pipinstallgeovis_upload_sdk==0.0.12 测试、编译和上传2.1 本地测试pythonsetup.pydevelop编译tar.gz：pythonsetup.pysdist编译whl：pip install wheel
python setup.py bdist_wheel检查pythonsetup.pycheck上传到pypi：pipinstalltwine
twineuploaddist/*更新日志0.0.1基础版测试0.0.2支持分片上传0.0.3优化
Package: geoviz
geovizPlotting library for creating interactive and static choropleths.
Download athttps://pypi.org/project/geoviz.Tutorial:http://locusanalytics.github.io/files/geoviz_tutorial.htmlChoropleths can take in dataframes or csv files, and plot sequential, divergent, and categorical data.
Future updates will allow user to supply their own shapefiles; the package current has functionality to plot US maps at the state, metropolitan statistical area, or county level (all shapefiles include Hawaii and Alaska).Plots can be outputted as as interactive html files or interactive Bokeh plots. The latter can only be done in Jupyter Notebooks. Static png or svg files can be saved manually once the above is generated using a widget button.For more information on usage, please see the tutorial.
Package: geoweaver-cwl
geoweaver_cwlgeoweaver_cwl is a python tool wrapper for translating Geoweaver AI - workflows into Common Workflow Language (CWL). CWL is an open standard for describing how to run command-line tools and connect them to create workflows. Tools and workflows described using CWL are portable across a variety of platforms that support the CWL standards. Researchers who are using Geoweaver can use it to translate their workflows and get the formatted CWL files for the existing workflows.The code is written in Python 3.InstallationFor installation use the following command:pip install geoweaver_cwlExample UsageImport the packagefrom geoweaver_cwl import translator as trThe json file will be converted to CWL format using generate_cwl function. It will also create a subdirectory called elementary_cwl_files, which will translate all the python files used in the workflow to CWL.tr.generate_cwl('workflow.json')The output should look like this and you should be able to see a workflow.cwl file and elementary_cwl_files in the folder:Output file: workflow.cwl
Writing header...
Writing steps...
CWL file written to workflow.cwlThe generate_yml function produces a YML file, which you should see in the exiting directory.
*Note: specify the name you want to give to your yml file in the function; in our example, we've called it "input."tr.generate_yml('input.yml')The output should look like this and you should be able to see a YML file in the folder:Writing YML file...
YML file created ...
Package: geox
GeoXInstallationFor instal this library to your python package library, use commandpipinstallgeoxDocumentationHere are some examples and feature explanation to use this libraryInitialize APIInitialize GeoX using yourapi_keythat can be obtained from Credentials Manager inhttps://geoxdat/credential-managerapp=GeoX(api_key='your-api-key')# checking the credential by seeing your mail address hereyour_email=app.emailRead all of your projectsRead all projects include the detail of eachProjectapp=GeoX(api_key='your-api-key')projects=app.read_all_projects()# list of Project classRead specific projectRead a specific project by using byProject IDapp=GeoX(api_key='your-api-key')project=app.read_project('PROJECT-ID')# Project classRead all project version o specific projectRead all project versions from aProjectapp=GeoX(api_key='your-api-key')project=app.read_project('PROJECT-ID')# Project classproject_versions=project.read_all_project_versions()# List of ProjectVerson classRead specific project versionRead specific project version by project version hashapp=GeoX(api_key='your-api-key')project=app.read_project('PROJECT-ID')# Project classproject_version=project.read_project_version('project-version-hash')# ProjectVersion classRead datasetRead dataset from project versionapp=GeoX(api_key='your-api-key')project=app.read_project('PROJECT-ID')# Project classproject_version=project.read_project_version('project-version-hash')# ProjectVersiondf_collar=project_version.read_collar_data(save_to_file=False)df_survey=project_version.read_survey_data(save_to_file=False)df_alteration=project_version.read_alteration_data(save_to_file=False)df_assay=project_version.read_assay_data(save_to_file=False)df_litho=project_version.read_litho_data(save_to_file=False)df_mineralisation=project_version.read_mineralisation_dat(save_to_file=False)Method parameters:filename:stris the filename if you set thesave_to_fileintoTrue(default:DatasetType)save_to_file:bool, set it toTrue, you will save the dataset dataframe into file (default:True)Dataset TypeThere are some types of dataset, can be obtained fromDatasetTypeobject, can be imported usingfromgeox.entityimportDatasetTypeDataset ColumnTo make it easier for gather information about dataset column, you can use some dataset column objectsfromgeox.entityimportCollarColumn,SurveyColumn,AlterationColumn,AssayColumn,LithoColumn,MineralisationColumnCopyrightThis project is licensed under copyright of GeoX, 2022.Our WebsiteFurther informations about dataset, information, integration services, customer support are available in our main website athttps://geoxdat.com
Package: geoxarray
Free software: Apache 2Documentation:https://geoxarray.github.io/.Geolocation utilities for xarray objects. Geoxarray is meant to bring
together all of the features and conversions needed by various python
packages working with geolocation xarray objects. This means being
able to convert between various coordinate system implementations
(rasterio, cartopy, pyresample, NetCDF CF grid mapping, etc). It also
means providing basic access to properties of the geolocation information
like bounding boxes.InstallationThegeoxarraylibrary is available on PyPI and can be installed with
pip:pipinstallgeoxarrayFor the most recent development versions of geoxarray, it can be installed
directly from the root of the source directory:pipinstall-e.Or to install into an existing conda-based environment:.. code-block:: bashconda install -c conda-forge geoxarrayDependenciesBesides the xarray dependency, thegeoxarraypackage uses CRS objects
from thepyprojlibrary.
Additionally, geoxarray has a lot of optional dependencies when it comes
to converting to other libraries’ CRS or geolocation objects. These
libraries include, but may not be limited to:rasteriocartopypyresampleRelationship with rioxarrayAt the time of writing, rioxarray is an independent project whose features
related to CRS and dimension handling are very similar if not exactly the
same as geoxarray. Rioxarray existed first and paved the way to show how CRS
information can be handled in an xarray-friendly way. Much of geoxarray is
inspired by rioxarray, if not copied directly. Portions of code copied from
rioxarray are noted in docstrings for that code and are under the Apache
License of rioxarray which has been copied asLICENSE_rioxarrayin the
geoxarray package and repository.Development StatusGeoxarray is actively being developed as a side project. Additions and
modifications are done as developers have time. If you would like to
contribute, suggest features, or discuss anything else please file a
bug on github.FeaturesSee the documentation website for how-tos, concepts, and API documentation.Parse various formats of storing Coordinate Reference System information:importgeoxarraypyproj_crs=my_data_arr.geo.crsWrite CRS information in a CF-compatible way or add CRS information
to an object that didn’t have any:importgeoxarraynew_dataset=my_dataset.geo.write_crs("EPSG:4326",inplace=False)
Package: geox-statistics
Deploy------https://codetrips.com/2016/09/19/how-to-publish-a-pyton-package-on-pypi/to deploy:TODO: write about.. code:: shellgit tagCreate a source package:.. code:: shellrm dist/*python setup.py sdist # for building a zip fileTo upload it, first create an account here:https://pypi.python.org/pypi/geox-statistics/0.0.1Then, install twine and upload the source package you build before:.. code:: shellpip install twine # for installationtwine upload dist/* # for uploading the zip file
Package: geoz
Geographic Decision Zones (GeoZ)GeoZ is a Python library integrating several machine learning modules to create Geographic Maps based on the output of
Unsupervised Machine Learning techniques. The library is geared mainly toward delineating the output from Clustering
algorithms, but it can be used for other Machine Learning algorithms. GeoZ is distributed under the 3-Clause BSD license.InstallationTo install GeoZ usingpip:pipinstallgeozUsage DetailsThe library is still in its experimental stage. As such, the user will have to provide the data in a certain format as the library is working with a fixed structure and wont fix or tolerate any deviation from the expected format.Dataset shape and format ExampleThe data provided needs to have two variables, one containing the latitude and longitude (eg. latlong) and another variable that contains the predicted classes of the the points (eg. y_pred). please check the below table for illustration:LATITUDELONGITUDEy_pred30-104232-103135-105233-104235-1023Please make sure to write (LATITUDE, LONGITUDE) in CAPITAL LETTER, otherwise the algorithm will fail.Code ExampleIn this example, we import geoz and then use an already defined variable 'dataset' that contains our above table, the variable can contain the latitude, longitude and the y_pred, but it can also contain only the latitude and longitude without the class. in that case you will need to provide another variable (eg. y_pred) to store the class predictions and use it in the functions calling.importgeozdataset=dataset# This is supposed to be the dataset that you have, it must contain the Latitude and the longitude as well as the class informationmap1=geoz.convex_hull_plot(dataset[['LATITDE','LONGITUDE']],dataset[['y_pred']])# This Function will return a Convex Hull map of the classesmap2=geoz.sklearn_plot(dataset[['LATITDE','LONGITUDE']],dataset[['y_pred']])# This Function will return a map drawn using Scikit-Learn "DecisionBoundaryDisplay"map3=geoz.mlx_plot(dataset[['LATITDE','LONGITUDE']],dataset[['y_pred']])# This Function will return a map drawn using MLextend  "decision_regions"For further infromation or the functions other parameters, please check the functions DocStrings as they contain more details and information.License informationSee the file (LICENSE) for information on the terms & conditions for usage, and a DISCLAIMER OF ALL WARRANTIES.ContactYou can ask me any questions via my Twitter AccountNe-oL. and in case you encountered any bugs, please create an issue inGitHub's issue trackerand I will try my best to address it as soon as possible.CitationPublication is under Process if you use this library in the mean time, please cite the Github repositryCreated By Khalid ElHaj, PhD FellowGeosciences Department @ UAE University
Package: gepard
SynopsisGepard- tool for studying the 3D quark and gluon distributions in the nucleonModelling Generalized Parton Distributions (GPD) and Compton form factors (CFF).Perturbative NLO QCD evolution of GPDsCalculation of deeply virtual Compton scattering (DVCS) and deeply virtual meson production (DVMP) observables to NLO accuracy.Fitting parametrized models to the experimental data.InstallationGepard is a Python package available from standard PyPI repository so you
should be able to install the latest version together with the required
dependencies by simply issuingpip install gepardOf course, you should have Python first (version 3.7 at the least),
as well aspip, which all major Linux distributions have as standard package.
See the documentation for alternative instalation from sources, which is also easy.Gepard is developed on Linux, but is tested also on Windows and MacOS.
Please complain if you have problems.UsingSee the documentation,
available athttps://gepard.phy.hr/.
Also there are lots of examples in thetestssubdirectory.CitingIf you use Gepard for your scientific publications, you might want to cite thearXiv:hep-ph/0703179paper where theoretical
framework that is implemented in the Gepard code is described in some detail.Copyright and licenseCopyright (C) 2022 Krešimir KumeričkiThis program is free software: you can redistribute it and/or modify it under the terms of the
GNU Affero General Public License v3.0 or later. See the fileLICENCEfor details.
Package: gepard-python
gepard-pythonGeneral purpose communication and synchronization layer for distributed
applications / Microservices / events, semaphores, locks and messages
for JavaScript, Java, Python and PHPOverviewThisPythonmodule implements a full featured client for theGEPARDmiddleware for general purpose distributed applications.In order to use thisPythonclient you must have installed theGEPARDmiddleware. This is simply done by executing the command:npminstallgepardPrerequisite for this command is the installation of node and npm. For
more information seegepard on
npmandgessinger-hj/gepard
on github.If you are interested in thePHPclient seegepard-python on
pypiandgepard-python on
githubInstallInstallation is done frompypiwith:pipinstallgepard-python
Package: gepetuto
GepetutoTutorial edition frameworkThis project contains some tools to help authoring and maintaing python tutorials presented on notebooks.InstallAddgepetutoin your pip / PyPI dependenciesUsagecreate a (eg.tp1) directory (tp0can be used to check prerequisites)write python scripts (eg.example_script.py) in this directorydelimit snippets inside those scripts between# %jupyter_snippet example_snippetand# %end_jupyter_snippetcreate a (eg.1-example_notebook.ipynb) notebook, containingimport gepetuto.magicrungepetuto -a generate: this will create atp{i}/generateddirectory with eg.example_script_example_snippetcells can contain either eg.%load tp1/generated/example_script_example_snippetto display some code to students,
or their%do_not_loadversion to let the student write the code themselfrungepetuto -a testto check all python scripts in tp directoriesrungepetuto -a lintto ensure the coding standards are respected in all python scripts in tp directoriesaddgepetuto -a testin your CI, andgepetuto -a lint+gepetuto -a generatein your pre-commitCommand line$ gepetuto -h
usage: gepetuto [-h] [-v] [-a [{lint,test,generate,all}]] [-f [FILE [FILE ...]]] [-F [FILTER [FILTER ...]]]
                [-p PYTHON] [-c] [-C DIRECTORY] [--version] [tp_id [tp_id ...]]

Tutorial edition framework

positional arguments:
  tp_id                 choose which tp to process. Default to all.

optional arguments:
  -h, --help            show this help message and exit
  -v, --verbose         increment verbosity level
  -a [{lint,test,generate,all}], --action [{lint,test,generate,all}]
                        choose what to do. Default to 'generate'.
  -f [FILE [FILE ...]], --file [FILE [FILE ...]]
                        choose which files to process.
  -F [FILTER [FILTER ...]], --filter [FILTER [FILTER ...]]
                        filter files to process.
  -p PYTHON, --python PYTHON
                        choose python interpreter to use.
  -c, --check           check if linters change files.
  -C DIRECTORY, --directory DIRECTORY
                        choose directory to run action on.
  --version             Get gepetuto version.CI Exampleexample of CI using all gepetuto actions on tests folder here :https://github.com/Gepetto/gepetuto/blob/main/.github/workflows/tests.ymlPre commit example- repo: https://github.com/Gepetto/gepetuto
  rev: v1.3.0
  hooks:
  - id: generate-action
  - id: lint-action
  - id: test-actionExampleshttps://github.com/gepetto/supaero2023https://github.com/nmansard/jnrh2023
Package: geprofiler
Geprofileris a Python call stack profiler built on top ofPyinstrumentbut stripped of the unnecessary and focused on supporting features for HTTP Server.Installation$ pip install geprofilerGeprofilersupports Python 3.7+. In addition,curlis required to be installed if you want to usegeprofiler.yaml.UsageThe examples below useDjangoto create a simple HTTP server that will be profiled byGeprofiler.⚡ Quick startTo profileDjangoweb requests:Addgeprofiler.middleware.ProfilerMiddlewaretoMIDDLEWAREin yoursettings.py.Once the server has been started, add?geprofiler(as a query param) to the end of a request URL you want to profile (alsogeprofilercan also be added as a request header). As soon as the request is processed, a new browser tab will be opened to display the profile information.AddGEPROFILER_PROFILE_DIR = 'profiles'to yoursettings.pyif you want the result page to be saved to the folderprofilesin your working directory.📋 Usegeprofiler.yamlSometimes, you need a different solution to solve advanced problems. For example, you might want Geprofiler to automatically profile all the APIs you specified immediately, instead of spending too much time profiling each API manually. In this case, you can define a filegeprofiler.yamlin your working directory with a structure similar to the one below.request:format: the format of your request list.list: a list of request statements corresponding to the format declared above.filter:min_duration: the minimum duration that a request has taken in milliseconds.output_dir: (optional) the folder that you want to save the result page in.Finally, to start profiling, run:$ geprofilerResult:
Package: gera2ld-pyserve
Serve asyncio and aiohttp servers, and show information for development.Installation$pipinstallgera2ld-pyserve# or with extra `aio` if aiohttp applications are to be served$pipinstallgera2ld-pyserve[aio]UsageRun an asynchronous function in an infinite event loop:fromgera2ld.pyserveimportrun_foreverasyncdefmain():# do stuffrun_forever(main())Start a server:fromgera2ld.pyserveimportrun_forever,start_server_asynciodefhandle(reader,writer):# add more code here...run_forever(start_server_asyncio(handle,':4000'))Start a server withaiohttp:fromgera2ld.pyserveimportrun_forever,start_server_aiohttpfromaiohttpimportwebapp=web.Application()# add more code here...run_forever(start_server_aiohttp(app,':4000'))
Package: gera2ld.socks
gera2ld.socksThis is a SOCKS server and client package built withasyncio(requires Python 3.5+).Installation$pip3installgera2ld.socksUsageSOCKS servershell command:# Start a server$python3-mgera2ld.socks.server-b127.0.0.1:1080or python script:fromgera2ld.pyserveimportrun_foreverfromgera2ld.socks.serverimportConfig,SOCKSServerconfig=Config('127.0.0.1:1080')run_forever(SOCKSServer(config).start_server())SOCKS clientimportasynciofromgera2ld.socks.clientimportcreate_clientclient=create_client('socks5://127.0.0.1:1080')loop=asyncio.get_event_loop()loop.run_until_complete(client.handle_connect(('www.google.com',80)))client.writer.write(b'...')print(loop.run_until_complete(client.reader.read()))SOCKS handler forurllibfromurllibimportrequestfromgera2ld.socks.client.handlerimportSOCKSProxyHandlerhandler=SOCKSProxyHandler('socks5://127.0.0.1:1080')opener=request.build_opener(handler)r=opener.open('https://www.example.com')print(r.read().decode())SOCKS client for UDPimportasynciofromgera2ld.socks.clientimportcreate_clientasyncdefmain():client=create_client('socks5://127.0.0.1:1080')udp=awaitclient.handle_udp()udp.write_data(b'\xc9\xa7\x01\x00\x00\x01\x00\x00\x00\x00\x00\x00\x03www\x06google\x03com\x00\x00\xff\x00\x01',('114.114.114.114',53))print(awaitudp.results.get())loop=asyncio.get_event_loop()loop.run_until_complete(main())
Package: gerador
geradorgerador Ã© um simples pacote para criar nomes de personagens fictÃ­cios para jogos de RPG.DependÃªnciasPython 3.6 ou posteriorPacote--> random, que jÃ¡ vem instalado com o pythonFunÃ§Ã£ocreate_name(size) --> retorna um nome com "size" quantidade de sÃ­labas\create_lastname(size) --> retorna um sobrenome com "size" quantidade de sÃ­labas\create_name_and_lastname(size_name, size_lastname) --> retorna um nome e sobrenome com "size_name" e "size_lastname" quantidade de silabas
Package: gerador-de-palavras
geradorgeradorÃ© um simples pacote para gerar palavras aleatorias em Python.basebaseÃ© um simples pacote para salvar as palavras aleatorias em um arquivo txt.DependÃªnciasPython 3.6ou posteriorPacotenumpyComeÃ§ando o usoVocÃª vai precisar instalar os pacotesgeradorebase, para isso basta executar:pip install geradorpip install base## FunÃ§Ã£o

* `main ()` - Gera palavras aleatorias