Saravanan666/pypi-org huggingface dataset:
Package: satlink
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⠀⠀⠀⠀⠈⠻⠋⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀⠀SatlinkLet me introduce Satlink. Satlink is a light web framework, that aims to beeasy to get started with,easy to build inandeasy to grow in, by focusing on core design principles, such as"Low Barrier to Entry"and"Self-documenting code". This framework was part of a project in Frameworks at HiØ, written with love in Python <3All seriousness aside, this is a highly unstable and experimental framework, where the API might change without a moment's notice. It's simply a playground for trying out stuff. Use at your own risk.Getting startedDependenciesThere are almost none!Satlink uses only bits from the Python Standard Library.All you need is Python 3.11 or greater.Not tested with earlier versions.InstallationStep 1: Start by installing the package from pip.pipinstallsatlinkStep 2: Let's create a file calledsat.py.touchsat.pyStep 4: Now, populate the sat.py file with the following code:fromsatlinkimportSatellite,Uplink,Downlinksat=Satellite()@sat.datalink('/')defindex(uplink:Uplink,downlink:Downlink):returndownlink.text('Hello, Earth!')sat.transmit()Step 5: Lastly, let's boot up our satellite.python3sat.pyWhen you visithttp://localhost:3000/you should see the text "Hello, Earth!".To learn more, take a look at theAPI documentation.
Package: satmad
SatMAD: Satellite Mission Analysis and DesignSatMAD is an open source Python package, aiming at providing the base functionality to solve satellite mission analysis and design as well as orbital mechanics problems with enough precision and performance to be used in the design and operation of real satellites. The target audience is academics and amateur satellite community, including Cubesats (and anyone else who might be interested).The focus is on good documentation and good test coverage to produce a reliable flight dynamics library.Current functionality is:Loading a list of TLEs from fileInitialising an orbit with a TLE or Keplerian Orbital ElementsPropagating the orbit analytically via the SGP4 propagatorPropagating an orbit numerically via the Scipy ODE Solvers (two-body force model) around the Earth or another planetOccultations, shadow geometry and illuminations findingGood infrastructure for time interval management and event findingHarnessing the extensiveAstropyfunctionalities
(e.g. finding azimuth and elevation over a ground location and coordinate frame
transformations)Documentation and ExamplesThe documentation for SatMAD is here:https://satmad.readthedocs.io/As a quick-start, you can find some hands-on Jupyter examples in thetutorials directory(or in thedocumentationfor a text version).In addition, there is a repository of how-to guides and analyses in a dedicated project called SatMAD Applications,available at Github(for Jupyter notebooks) andin plain document format.Installing SatMADThe SatMAD package is onPyPIand you can install it simply by running:pip install satmadYou can also install it viaconda-forge:conda install -c conda-forge satmadDo not installsatmadusingsudo.You can find the source code on GitHub:https://github.com/egemenimre/satmadRequirementsNumPy and SciPy are used for the underlying mathematical algorithmsMatplotlib is used for plotsAstropy handles all time and reference frame computationsPyERFAhandles lower level coordinate and time transformationsPortionhandles the time interval mechanicsSgp4provides the TLE manipulation and SGP4 propagation engineJplephemfor JPL Ephemeris calculationsPytest provides the testing frameworkLicenseThis project is Copyright (c) Egemen Imre and licensed under the terms of the GNU GPL v3+ license.
Package: sat-mapping-cyborg-ai
Sentinel 2 Data FetcherInstallationCreate a Virtual Environment and activate it.python3-mvenvvenv
.venv/bin/activateInstall the Package via pip.pipinstallsat-mapping-cyborg-aiUsageImport the Libraryfromsat_mappingimportFolderData,folders_time_frame,Paths,downloadSet the Path to where you want to store the Satellite Data.paths=Paths("<ANY/VALID/PATH>")Start the Download. (Note: One year needs around 110 GB Disk Space.)The download uses gsutil so if there is no gsutil configuration (.boto) in your home directory,
gsutil config will be called to generate one.
Gsutil config asks the user for a token and a project id.download(paths,years=[2019],tiles=["32TMT"],months=[7])Load a folder.folder_name=paths.folders[0]upper_left=(100000.0,0.0)# Postion on tile in [m]lower_right=(109800.0,10000.0)# Postion on tile in [m]data=FolderData(join(paths.data_path,folder_name),upper_left,lower_right)Display the image. (if matplotlib is not installed usepip install matplotlib)importmatplotlib.pyplotaspltpicture=data.data[:,:,[3,1,2]]# NIR, GREEN, BLUEfig:plt.Figure=plt.figure()plt.imshow(picture)plt.show()
Package: satmetrix
Usage:from satmetrix import Satmetrix
    sm = Satmetrix(domain, auth)Retrieve one page of feedback:data = sm.feedback(page_limit=1)
contact_id = data[0]['contact_record_id']Retrieve one feedback record using contact_record_id:r = sm.feedback_record(contact_id)Update feedback record:r = sm.update_feedback(contact_record_id, data=[{'contact_record_id': contact_record_id, 'comment_text': 'Called customer, left vm. Will call back to cust next week.'}])Retrieve invitation record using contact_record_id:r = sm.invitation_record(contact_record_id)Nominate Contact:r = sm.nominate_contact(data=[{'contact_id': 'email', 'email': 'email'}])
r = sm.nominate_contact(contact_record_id)The above will return all the feedback you have. You can pass in the following arguments offset, limit, page_limit, callback. You can also pass in additional args which are passed to as json data in the post request.NoteSatmetrix has said there isn’t an endpoint other than searching.Building New versions:python2.7 setup.py bdist bdist_wheel
twine upload --skip-existing dist/*
Package: satnet
SATNet •Bridging deep learning and logical reasoning using a differentiable satisfiability solver.This repository contains the source code to reproduce the experiments in the ICML 2019 paperSATNet: Bridging deep learning and logical reasoning using a differentiable satisfiability solverbyPo-Wei Wang,Priya L. Donti,Bryan Wilder, andJ. Zico Kolter.What is SATNetSATNet is a differentiable (smoothed) maximum satisfiability (MAXSAT) solver that can be integrated into the loop of larger deep learning systems. This (approximate) solver is based upon a fast coordinate descent approach to solving the semidefinite program (SDP) associated with the MAXSAT problem.How SATNet worksA SATNet layer takes as input the discrete or probabilistic assignments of known MAXSAT variables, and outputs guesses for the assignments of unknown variables via a MAXSAT SDP relaxation with weightsS. A schematic depicting the forward pass of this layer is shown below. To obtain the backward pass, we analytically differentiate through the SDP relaxation (see the paper for more details).Overview of experimentsWe show that by integrating SATNet into end-to-end learning systems, we can learn the logical structure of challenging problems in a minimally supervised fashion. In particular, we show that we can:Learn theparity functionusing single-bit supervision (a traditionally hard task for deep networks)Learn how to play9×9 Sudoku (original and permuted)solely from examples.Solve a"visual Sudoku"problem that maps images of Sudoku puzzles to their associated logical solutions. (A sample "visual Sudoku" input is shown below.)InstallationVia pippipinstallsatnetFrom sourcegitclonehttps://github.com/locuslab/SATNetcdSATNet&&pythonsetup.pyinstallPackage Dependenciesconda install -c pytorch tqdmThe package also depends on the nvcc compiler. If it doesn't exist (try nvcc from commandline), you can install it viaconda install -c conda-forge cudatoolkit-devVia Docker imagecddocker
sh./build.sh
sh./run.shRunning experimentsJupyter Notebook and Google ColabJupyter notebookandGoogle ColabRun them manuallyGetting the datasetsTheSudoku datasetandParity datasetcan be downloaded viawget-cqpowei.tw/sudoku.zip&&unzip-qqsudoku.zip
wget-cqpowei.tw/parity.zip&&unzip-qqparity.zipSudoku experiments (original, permuted, and visual)pythonexps/sudoku.py
pythonexps/sudoku.py--perm
pythonexps/sudoku.py--mnist--batchSz=50Parity experimentspythonexps/parity.py--seq=20pythonexps/parity.py--seq=40
Package: satori-python
satori-python基于Satori协议的 Python 开发工具包协议介绍Satori Protocol协议端目前提供了satori协议实现的有：ChronocatKoishi （搭配@koishijs/plugin-server）安装安装完整体：pipinstallsatori-python只安装基础部分：pipinstallsatori-python-core只安装客户端部分：pipinstallsatori-python-client只安装服务端部分：pipinstallsatori-python-server使用客户端：fromsatoriimportEvent,WebsocketsInfofromsatori.clientimportAccount,Appapp=App(WebsocketsInfo(port=5140))@app.registerasyncdefon_message(account:Account,event:Event):ifevent.userandevent.user.id=="xxxxxxxxxxx":awaitaccount.send(event,"Hello, World!")app.run()服务端：fromsatoriimportApifromsatori.serverimportServerserver=Server(port=5140)@server.route(Api.MESSAGE_CREATE)asyncdefon_message_create(*args,**kwargs):return[{"id":"1234","content":"example"}]server.run()文档请阅读仓库文档示例客户端：client.py服务端：server.py服务端(使用适配器)：server_with_adapter.py客户端(webhook)：client_webhook服务端(webhook)：server_webhook适配器：adapter.py架构graph LR
    subgraph Server
        server -- run --> asgi
        server -- register --> router -- mount --> asgi
        server -- apply --> provider -- mount  --> asgi
        provider -- event,logins --> server
    end
    subgraph Client
        config -- apply --> app -- run --> network
        app -- register --> listener
        network -- account,event --> listener
        listener -- handle --> account -- session --> api
    end
    
    api -- request --> asgi -- response --> api
    server -- raw-event --> asgi -- websocket/webhook --> network
Package: satori-python-client
satori-python基于Satori协议的 Python 开发工具包协议介绍Satori Protocol协议端目前提供了satori协议实现的有：ChronocatKoishi （搭配@koishijs/plugin-server）安装安装完整体：pipinstallsatori-python只安装基础部分：pipinstallsatori-python-core只安装客户端部分：pipinstallsatori-python-client只安装服务端部分：pipinstallsatori-python-server使用客户端：fromsatoriimportEvent,WebsocketsInfofromsatori.clientimportAccount,Appapp=App(WebsocketsInfo(port=5140))@app.registerasyncdefon_message(account:Account,event:Event):ifevent.userandevent.user.id=="xxxxxxxxxxx":awaitaccount.send(event,"Hello, World!")app.run()服务端：fromsatoriimportApifromsatori.serverimportServerserver=Server(port=5140)@server.route(Api.MESSAGE_CREATE)asyncdefon_message_create(*args,**kwargs):return[{"id":"1234","content":"example"}]server.run()文档请阅读仓库文档示例客户端：client.py服务端：server.py服务端(使用适配器)：server_with_adapter.py客户端(webhook)：client_webhook服务端(webhook)：server_webhook适配器：adapter.py架构graph LR
    subgraph Server
        server -- run --> asgi
        server -- register --> router -- mount --> asgi
        server -- apply --> provider -- mount  --> asgi
        provider -- event,logins --> server
    end
    subgraph Client
        config -- apply --> app -- run --> network
        app -- register --> listener
        network -- account,event --> listener
        listener -- handle --> account -- session --> api
    end
    
    api -- request --> asgi -- response --> api
    server -- raw-event --> asgi -- websocket/webhook --> network
Package: satori-python-core
satori-python基于Satori协议的 Python 开发工具包协议介绍Satori Protocol协议端目前提供了satori协议实现的有：ChronocatKoishi （搭配@koishijs/plugin-server）安装安装完整体：pipinstallsatori-python只安装基础部分：pipinstallsatori-python-core只安装客户端部分：pipinstallsatori-python-client只安装服务端部分：pipinstallsatori-python-server使用客户端：fromsatoriimportEvent,WebsocketsInfofromsatori.clientimportAccount,Appapp=App(WebsocketsInfo(port=5140))@app.registerasyncdefon_message(account:Account,event:Event):ifevent.userandevent.user.id=="xxxxxxxxxxx":awaitaccount.send(event,"Hello, World!")app.run()服务端：fromsatoriimportApifromsatori.serverimportServerserver=Server(port=5140)@server.route(Api.MESSAGE_CREATE)asyncdefon_message_create(*args,**kwargs):return[{"id":"1234","content":"example"}]server.run()文档请阅读仓库文档示例客户端：client.py服务端：server.py服务端(使用适配器)：server_with_adapter.py客户端(webhook)：client_webhook服务端(webhook)：server_webhook适配器：adapter.py架构graph LR
    subgraph Server
        server -- run --> asgi
        server -- register --> router -- mount --> asgi
        server -- apply --> provider -- mount  --> asgi
        provider -- event,logins --> server
    end
    subgraph Client
        config -- apply --> app -- run --> network
        app -- register --> listener
        network -- account,event --> listener
        listener -- handle --> account -- session --> api
    end
    
    api -- request --> asgi -- response --> api
    server -- raw-event --> asgi -- websocket/webhook --> network
Package: satori-python-server
satori-python基于Satori协议的 Python 开发工具包协议介绍Satori Protocol协议端目前提供了satori协议实现的有：ChronocatKoishi （搭配@koishijs/plugin-server）安装安装完整体：pipinstallsatori-python只安装基础部分：pipinstallsatori-python-core只安装客户端部分：pipinstallsatori-python-client只安装服务端部分：pipinstallsatori-python-server使用客户端：fromsatoriimportEvent,WebsocketsInfofromsatori.clientimportAccount,Appapp=App(WebsocketsInfo(port=5140))@app.registerasyncdefon_message(account:Account,event:Event):ifevent.userandevent.user.id=="xxxxxxxxxxx":awaitaccount.send(event,"Hello, World!")app.run()服务端：fromsatoriimportApifromsatori.serverimportServerserver=Server(port=5140)@server.route(Api.MESSAGE_CREATE)asyncdefon_message_create(*args,**kwargs):return[{"id":"1234","content":"example"}]server.run()文档请阅读仓库文档示例客户端：client.py服务端：server.py服务端(使用适配器)：server_with_adapter.py客户端(webhook)：client_webhook服务端(webhook)：server_webhook适配器：adapter.py架构graph LR
    subgraph Server
        server -- run --> asgi
        server -- register --> router -- mount --> asgi
        server -- apply --> provider -- mount  --> asgi
        provider -- event,logins --> server
    end
    subgraph Client
        config -- apply --> app -- run --> network
        app -- register --> listener
        network -- account,event --> listener
        listener -- handle --> account -- session --> api
    end
    
    api -- request --> asgi -- response --> api
    server -- raw-event --> asgi -- websocket/webhook --> network
Package: satori-raspberry
RequirementsInstalledpython3andpip3Python3 devel package:sudo apt-get install python3-devor:sudo yum install python-devellibow-devto work with 1-wire sensors, like DHT11 or Temperature:sudo apt-get install libow-devpython3-smbuspackage:sudo apt-get install python3-smbusInstallationThe latest Adafruit sensors library is located on GitHub:https://github.com/adafruit/Adafruit_Python_DHTIn order to install this library we usedependency_links. So use–process-dependency-linksflag when installing the satori-raspberry module:pip3 install satori-raspberry --process-dependency-linksATTENTION: The satori-raspberry framework uses GPIO library that can be compiled only in Raspberry Pi
Package: satori-serpentarium
Satori Python composition framework (alpha release)RequirementsPython 3.6+Run locallypip install serpentarium
python -m serpentariun $CONFIG_PATHSample config:serpentarium/serpentarium/config.ymlWriting your own botSee a realexampleDraw a mod hierarchy graph0. Install graphviz (brew insatll graphviz)
1. Run module with -d True
2. Check __main__.py for more info
Package: satorix-django
satorix-djangoByInternet ExposureSatorix: Get your app from local to liveThesatorix-djangopackage provides a streamlined mechanism for a 12-factor capable Django application to interact with the Satorix ecosystem.Preparing your applicationAdd Satorix to your Django application by including it in yourrequirements.txtwith:satorix-djangoRunpip install satorix-djangoto install it.Next, run the generator from a terminal at the root of your application:$satorix-django-configThis creates a set of files that utilize environment variables created by default with Satorix. These include thePhusion Passenger Rails app serverand the Passenger built in Nginx web server.Configuring your applicationYou can configure your application on a per-environment basis using environment variables.
Thesatorix-django-configcommand attempts to add the import forsatorix_djangothat sets up the database connection for your application.Default environment VariablesThe following default environment variables are used by thesatorix-djangogenerated files and can be managed through the Satorix Dashboard:SATORIX_CANONICAL_URI_HOSTOptional, a domain to rewrite all requests to by default. Setting this will make it so all requests to your site will go to the supplied domain.Common setting:www.domain.domSATORIX_CANONICAL_URI_PROTOCOLOptional, theHTTPprotocol to rewrite requests to.Valid settings:httphttpsSATORIX_PROXY_IPSOptional, used to define proxy IP addresses, for services like CloudFlare. This will allow you to get the actual client IP address accessing your site in the logs and accessible to your application.Valid settings:Space separated list of IPs or network ranges (103.21.244.0/22 103.22.200.0/22 103.31.4.0/22 104.16.0.0/12 108.162.192.0/18 131.0.72.0/22 141.101.64.0/18 162.158.0.0/15 172.64.0.0/13 173.245.48.0/20 188.114.96.0/20 190.93.240.0/20 197.234.240.0/22 198.41.128.0/17 199.27.128.0/21)SATORIX_AUTHENTICATION_HTPASSWDSOptional, used to control access to your site with HTTP Basic authentication. Needs to be generated in the format created by the Apache toolhtpasswd -nb username passwordor using anonline generator.Valid settings:Newline separated list of username and hashed password (username:$apr1$vAxBKb8N$m0en1zabtHktHeFyT3j9y)SATORIX_AUTHENTICATION_ALLOWED_IPSOptional, used to control access to your site by bypassing the above HTTP Basic authentication. If set toallno authentication will be required. Any IP addresses or networks added here will not need to supply the username and password to access the site.Valid settings:All (all)Single IP (192.168.1.2)Network range (192.168.1.0/24)Space separated list of multiple IPs or network ranges (192.168.1.3 192.168.2.0/24)ContributingPlease coordinate contributions using theofficial issue tracker.TestingThis package is tested usingunittest.You can run the same tests that run during CI with:python setup.py testCI/CDSatorix is used to provide continuous integration and continuous deployment for this application.CI is run against every push.CD is used to build and publish the package for the master branch.LicenseThe Satorix package is released under the terms described in theLICENSE file.
Package: satoshi
> satoshiManipulate satoshi-related prices in Python 3, simple and sweet 💵 ₿🍬Why complicate?The idea behind this project is to provide Python programmers with a simple, light and intuitive package to manipulate satoshis.This can be extremely useful on future/perpetual markets and crypto exchanges that don't automatically associate XBT balances to an USD value. With > satoshi you can use a single function to convert your satoshis to any fiat currency :)No need to handle more requests and currency mangling in your code, simply use > satoshi and, therefore,CryptoCompare'sopen API.InstallationpipinstallsatoshiUsageincludesatoshisatoshi.to_fiat(984223)# satoshi to usdsatoshi.to_fiat(18923,'BRL')# satoshi to reaisFeel free to run example.py for a demo.NotesProject idealized while listening tothissong.Feel free to become a collaborator.
Package: satplat-api
Python SatPlat Api Clienta simple module to integrate with SatPlat satellite image api serviceOverviewOverviewInstallationUsageReferencesSwaggerInstallationThis module is a pip package to let you integrate with satplat api service provider. in order to use this module you have to install it by pip command or through setup.pipinstallsatplat_apiImport package into your project by:fromsatplat_api.apiimportSatPlatAPIin order to use the module please consider looking at examples and documentations.UsageIn order to integrate with this service provider you need to first have an account and token. so first of all create an account with the url provided below:https://dashboard.satplat.com/#/loginFor easy implementations i have provided two simple examples, one for creating authenticating and getting access key and one for simple example to get current data from a location# importing satplat modulefromsatplat_api.apiimportSatPlatAPI# creating an instance clientclient=SatPlatAPI()# setting up access tokenclient.set_access_token(access_token="<YOUR_TOKEN>")now that you have access token with unlimited time access then there is no need for authenticating, you can just set the access_token and proceed with other requests.#importing satplat modulefromsatplat_api.apiimportSatPlatAPI# creating an instance clientclient=SatPlatAPI()# setting the access token for headers in client objectclient.set_access_token(access_token="<YOUR_TOKEN>")# to get farms listpprint(client.get_farms_list())ReferencesdocumentSwaggeri even did create a custom swagger for testing purposes
Package: satpy
The Satpy package is a python library for reading and manipulating
meteorological remote sensing data and writing it to various image and
data file formats. Satpy comes with the ability to make various RGB
composites directly from satellite instrument channel data or higher level
processing output. Thepyresamplepackage is used
to resample data to different uniform areas or grids.The documentation is available athttp://satpy.readthedocs.org/.InstallationSatpy can be installed from PyPI with pip:pipinstallsatpyIt is also available fromconda-forgefor conda installations:condainstall-cconda-forgesatpyCode of ConductSatpy follows the same code of conduct as the PyTroll project. For reference
it is copied to this repository inCODE_OF_CONDUCT.md.As stated in the PyTroll home page, this code of conduct applies to the
project space (GitHub) as well as the public space online and offline when
an individual is representing the project or the community. Online examples
of this include the PyTroll Slack team, mailing list, and the PyTroll twitter
account. This code of conduct also applies to in-person situations like
PyTroll Contributor Weeks (PCW), conference meet-ups, or any other time when
the project is being represented.Any violations of this code of conduct will be handled by the core maintainers
of the project including David Hoese, Martin Raspaud, and Adam Dybbroe.
If you wish to report one of the maintainers for a violation and are
not comfortable with them seeing it, please contact one or more of the other
maintainers to report the violation. Responses to violations will be
determined by the maintainers and may include one or more of the following:Verbal warningAsk for public apologyTemporary or permanent ban from in-person eventsTemporary or permanent ban from online communication (Slack, mailing list, etc)For details see the officialCODE_OF_CONDUCT.md.
Package: satseg
SatSeg (WIP)A python package to assist in multispectral satellite image segmentation.Installationpip install satsegUsageTrainingfromsatseg.datasetimportcreate_datasetsfromsatseg.modelimportsave_model,train_model# A list of paths to the satellite image tif files (.TIF)tif_paths=["01.tif"."02.tif"]# A list of paths to the shapefiles (.SHP) of the masksmask_paths=["mask.shp"]# Create the train and validation datasets# The intermediate image files will be saved at ./temp/labeled/train_set,val_set=create_datasets(tif_paths,mask_paths,"temp/labeled")# Train the modelmodel,metrics=train_model(train_set,val_set,"unet")# Save the model at a specified pathmodel_path="model.pt"save_model(model,model_path)Inferencefromsatseg.datasetimportcreate_inference_datasetfromsatseg.modelimportload_model,run_inferencetif_paths=["03.tif","04.tif"]# The intermediate image files will be saved at ./temp/unlabeled/dataset=create_inference_dataset(tif_paths,"temp/unlabeled/",256)# Load a previously saved modelmodel_path="model.pt"model=load_model(model_path)# Run inference on the dataset using the loaded model# Results will be saved ./temp/infer/run_inference(dataset,model,"temp/infer/")