Saravanan666/pypi-org huggingface dataset:
Package: geordi
Geordi is aDjangomiddlewarethat lets you interactively profile your
site. Add?__geordi__to any URL, browse to it, and you’ll get a PDF
showing the request’s call graph and the time spent in each call.If you’ve setDEBUG = Truein yourDjango settings, anyone can profile
a page–even anonymous users. WithDEBUG = False, only super users can
profile pages.If you’re running your Django site under a server likeGunicornand you’ve
configuredtime limits on requests, you can setGEORDI_CELERY = Trueto
run the profiler in a backgroundCelerytask.If you’re running multiple front-end servers and need PDFs to be saved
to a shared directory, setGEORDI_OUTPUT_DIR. If it’s not set, the
temporary directory provided by the system is used.InstallationBefore you get started, make sure you haveGraphVizinstalled.After you’ve donepip install geordi, add'geordi'to theINSTALLED_APPSsetting, and add'geordi.VisorMiddleware'to theMIDDLEWARE_CLASSESsetting. You’ll probably want to put it after Django’s
authentication middleware and before everything else.For background profiling with Celery, setGEORDI_CELERY = True.
Package: geordpy
GeoRDPyGeoRDPy is a Python library that simplifies geodetic-coordinate polylines using the Ramer-Douglas-Peucker algorithm. By default, it utilizes the distance to great-circle segments as the distance metric to reduce the number of points in a polyline while maintaining accuracy.
Optionally, the segments can be interpolated with rhumb lines instead of great-circle. For both options, the great-circle distance is used internally for finding the smallest distance between the interpolated segment and geodetic-coordinate points.InstallationGeoRDPy releases are available as wheel packages for macOS, Windows and Linux onPyPI.
Install it using pip:$pipinstallgeordpyExample UsageThe GeoRDPy API is designed with simplicity in mind, featuring a single method calledgeordpy.rdp_filter:>>>importgeordpy>>>points=[(latitude1,longitude1),(latitude2,longitude2),...]>>>threshold=15_000# meters>>>mask=geordpy.rdp_filter(points,threshold)>>>trajectory=np.array(points)[mask]For a quick illustration of how to utilize this method, refer to theexample here.For more details, check thedocumentation.ContributingContributions are welcome! If you find any issues or have suggestions for improvements, please feel free to submit a pull request.Development SetupTo set up your development environment, follow these steps:Clone the repository:$gitclonehttps://github.com/avitase/geordpy.gitChange to the project directory:$cdgeordpyInstall the development dependencies usingpip:$pipinstall-e.[dev]Pre-Commit-HooksTo maintain code quality and avoid pushing invalid commits, we recommend using pre-commit hooks. These hooks perform automated checks before commits are made. To set up pre-commit hooks, follow these steps:Install the pre-commit package (if not already installed):$pipinstallpre-commitInstall the hooks:$pre-commitinstallNow, each time you commit changes, the pre-commit hooks will run checks such as formatting, linting, and more. If any issues are found, they will be flagged before the commit is made.Running TestsYou can run tests using the following command:$pytestMake sure to run tests before submitting a pull request to ensure that everything is functioning as expected.
Package: georeader
GeoReaderGeoreader is a module used to read common spatial data formats such as Esri ShapeFiles, GeoPackage, Geography Markup Language, CSV,
GeoJSON, Web Feature Service, Esri Rest Service and Keyhole Markup Language. As well it can also hanlded compressed file type such as 7z, ZIP, KMZ files.This module makes use of other packages to read the data such as GeoPandas, Fiona, GDAL, and FastKMl.Basic Usage>>>fromgeoreaderimportGeoReaderasgr>>>georeader=gr("./cities_borders.gpkg")# List layers.>>>georeader.list_layers()["Belfast","Edinburgh","London",...]# Get Layer Count>>>georeader.get_layer_count()1000# Layer Functions>>>layer=georeader.get_layer("Edinburgh")>>>layer.GetName()"Edinburgh">>>layer.get_schema()["id","district",...]>>>layer.get_feature_count()1234>>>type(layer.get_dataframe())Geopandas.DataframeBuilding Wheel file>python.\setup.pybdist_wheelInstallation>pipinstalldist/georeader-*.*.*-py3-none-any.whlThere are Some issues installing Geopandas through git so will have to install manually.
Navigate tohttps://www.lfd.uci.edu/~gohlke/pythonlibs/in browser and download
the latest version of Fiona, Gdal and Shapely and pip install.tested Versions"GDAL>=3.3.3","Fiona>=1.8.2","Shapely>=1.8.0"once you have done that pip install geopandas :>pipinstallgeopandasand hopefully you should be able to import georeader module as shown above.Running the testsAuthorLicenseNone
Package: georetriever
GeoRetriever 🌋🐕A Python package for array-based retrieval of geological data. In a second step (available in a future version), the data can be converted to localized thermal energy system suitability.Based on the tools used in the greatatlitepackage, GeoRetriever is supported bydaskandxarrayfor parallelized requests of data chunks.When completed, the package will be able to retrieve all data relevant the following thermal systems:Borehole Thermal Energy Storage (BTES)Aquifer Thermal Energy Storage (ATES)Shallow Ground Source Heat Pumps (CSHP)Water Source Heat Pumps (WSHP)Pit Thermal Energy Storage (PTES)Mine Thermal Energy Storage (MTES)The library is under development with more features being added in the future. This is a promise - I need this for my PhD 🧗🏼.| Feature | Data Source | Coverage | Implemented ||---------|-------------|----------|-------------|| Lithology |Macrostrat| global | ✔️|| Surface Temperature |ERA5| global | ✔️ || Soil Temperature |ERA5| global | ✔️ || Aquifer Presence |  | | ❌ || Soil Type |  | | ❌ |InstallationThe package runs onPython>=3.6and is available frompypiviapip install georetrieverNote that for the feauture"temperature", the API toERA5will be used, which requires registration and setting up of the CDS API key ashere.ExampleThe package works through theGeoCutoutobject. During its initialization, the  spatial and temporal scale of the data is defined. Coordinates are in(lon, lat). The actual retrieval of data starts when theprepare(), which takes the features of interest are passed method is called.For instance:from georetriever import GeoCutout



x = slice(-1, 1)

y = slice(50, 52)

dx = 0.05

dy = 0.05

time = "2019-01-01"

dt = "h"



geocutout = GeoCutout(

    x=x,

    y=y,

    dx=dx,

    dy=dy,

    time=time,

    dt=dt,

)



geocutout.prepare(features=["temperature", "lithology"])



print(geocutout.data)Authors and ContactLukas Franken-lukas.franken@ed.ac.ukUniversity of Edinburgh, Alan Turing InstituteBig thanks to the team atTU Berlinforatlite, the package this library is leaning on.
Package: george-lucas
Asciitext version of “A New Hope”, available from Towel.blinkenlights.nlOriginal Work   : Simon Jansen (http://www.asciimation.co.nz/)Telnetification : Sten Spans (http://blinkenlights.nl/)Terminal Tricks : Mike Edwards (pf-asciimation@mirkwood.net)The hard work was done by Simon and Mike and Sten.
I just made a Python wrapper for the Telnet application.
Package: georgescalc
georgescalcUm misto de funÃ§Ãµes matemÃ¡ticas.georgescalc.equationsO mÃ³dulo georges-calc.equations contÃ©m:A funÃ§Ã£o bhaskara(a,b,c): Que retorna o valor de X se houver raÃ­zes reais e None, se nÃ£o houver;A funÃ§Ã£o delta(a,b,c), que retorna o valor de delta.georgescalc.functionsO mÃ³dulo georges-calc.functions contÃ©m:A funÃ§Ã£o fibonacci(n_termos), que retorna uma lista de termos da sequÃªncia de Fibonacci.georgescalc.totalO mÃ³dulo georges-calc.functions contÃ©m:A funÃ§Ã£o total_sum(num), que retorna a soma dos nÃºmeros fornecidos como parÃ¢metro.A funÃ§Ã£o total_product(num), que retorna o produto dos nÃºmeros fornecidos como parÃ¢metro.InstalaÃ§Ã£oUse the package managerpipto install georges_calcpipinstallgeorgescalcUsagefromgeorgescalcimportfunctionsfunctions.fibonacci(7)AuthorGeorge Pontes da CunhaLicenseMIT
Package: georgesngandeu-hello
Simple python packageExplore the docs Â»View DemoÂ·Report BugÂ·Request FeatureTable of ContentsGetting startedUsageLicenseContactAcknowledgementsGetting StartedA simple python package that prints "Hello wolrd"UsageLicenseContactProject Link:https://github.com/Georges-Ngandeu/SimplePythonPackageAcknowledgements
Package: george-walrus
🎁 This repo is forked fromhttps://github.com/pybpc/walrusfor publishing their latest work on PyPi, since the PyPi has not been updated long. Thanks the original authors for their excellent work to support the walrus operator on early Python versions.NB: walrus is currently under reconstruction. It is highly recommended to directly install from the git repo or the pre-release distributions.walrusWriteassignment expressionsin Python 3.8 flavour, and letwalrusworry about back-port issues :beer:SincePEP 572, Python introducedassignment expressionssyntax in version3.8. For those who wish to useassignment expressionsin their code,walrusprovides an
intelligent, yet imperfect, solution of abackport compilerby replacingassignment expressionssyntax with
old-fashioned syntax, which guarantees you to always writeassignment expressionsin Python 3.8 flavour then
compile for compatibility later.DocumentationSeedocumentationfor usage and more details.ContributionContributions are very welcome, especially fixing bugs and providing test cases.
Note that code must remain valid and reasonable.See Alsopybpc(formerly known aspython-babel)f2formatposeurrelaxedecorvermin
Package: georgio
georgioFastgeoRust helper functions for Python.Great CircleTo get the great circle distance between two points in meters, this function will use the IUGG mean Earth radius.distance_in_meters=georgio.great_circle_distance(lon1,lat1,lon2,lat2)If you want to provide your own radius in meters, you can use this function instead.distance_in_meters=georgio.great_circle_distance_with_radius(lon1,lat1,lon2,lat2,radius_in_meters)Line Of Bearing (LOB)Returns the destination coordinates based on a starting position, bearing, and distance in meters.  Bearing is in degrees, clockwise from north.  It uses the IUGG mean Earth radius.dest_lon,dest_lat=georgio.line_of_bearing(start_lon,start_lat,bearing_in_degrees,distance_in_meters)If you want to provide your own radius in meters, you can use this function instead.dest_lon,dest_lat=georgio.line_of_bearing_with_radius(start_lon,start_lat,bearing_in_degrees,distance_in_meters,radius_in_meters)Bounding BoxThis function will return a bounding box that encompasses  the specified distance around a center point.
Note that the bounding box will never extend across the antimeridian (longitude +/-180), below latitude -90, or above latitude 90.west,south,east,north=georgio.bounding_box_for_point(lon,lat,distance_in_meters)Web MercatorTo get the longitude/latitude bounds of a Web Mercator tile, use the following function, which will return the values in west, south, east, north order.west,south,east,north=georgio.wm_bounds(x,y,z)To get the upper left corner of a tile in longitude, latitude order, use the following function.longitude,latitude=georgio.wm_upper_left(x,y,z)To get a bounding box that surrounds a tile at a certain distance, use the following function.
This can be useful when searching for centerpoints of objects that might be outside of the tile, where the object might extend into the tile.
Note that the bounding box size is calculated in the WGS-84 projection based on the tile's longitude/latitude bounds, since Web Mercator is notoriously bad for calculating sizes/distances.
Also note that the bounding box will never extend across the antimeridian (longitude +/-180), below latitude -90, or above latitude 90.west,south,east,north=georgio.wm_tile_expanded_bbox(x,y,z,search_distance_in_meters)
Package: georise
GeoriseGeoriseis a Python library built for interactive visualization of geospatial maps. It leverages the power of GDAL and PyQtGraph to provide a user-friendly, high-performance mapping solution. With its simple, Matplotlib-like API, it aims to make geospatial visualization accessible and easy.Please note:Georise is currently in early development and may not be suitable for major use. However, it is being actively developed and improved every day.FeaturesInteractive visualization of geospatial mapsHandles map distortion, latitude and longitude, and correct multi-dimensional scalingSupports raster type files such as GeoTIFF and DTED (with plans to support point cloud and LIDAR data types)Simple, familiar API for ease of useInstallationBefore installing Georise, you will need to install the following dependencies:OSGeo (which includes GDAL)PyQt5Please consult the respective documentation for detailed installation instructions for your operating system. With the prerequisites installed, you can install georise using pip:pipinstallgeoriseThe following example demonstrates how to use Georise to display a raster terrain from a GeoTIFF file.importgeorise.sceneif__name__=='__main__':# Instantiate the scenegplt=georise.scene.GRRasterScene()# Add terrains from filepath (use skip to save on memory)gplt.raster("test_raster.tif",skip=4)# Show rasters using a matplotlib-like APIgplt.show()DocumentationMore detailed documentation will be provided as the project matures. Keep an eye on this space for updates!ContributingGeorise is an open-source project, and contributions are welcome! If you'd like to report a bug, request a feature, or contribute code, please use the GitHub repository to submit issues or pull requests.LicenseGeorise is released under the MIT License.
Package: georouting
Geo routing for Python users, supporting most of the routing tools, including OSRM, Google Maps, Bing Maps, etc. with a unified API.Warning!!! This project is under active development, wait for the release of version 1.0.0 if you want to use it in production. This package is inspired bygeopy. Please help to improve this package by submitting issues and pull requests.Free software: MIT licenseDocumentation:https://wybert.github.io/georoutingFeaturesSupport most of the routing services, including Google Maps, Bing Maps, OSRM, etc.Provide a unified API for routing servicesSupport calculating the travel distance matrix between multiple origins and destinationsSupport calculating the travel distance according to OD pairs.Easy to visualize the routing resultsReturn the travel distance matrix in a PandasDataframeyou likeReturn the routing results in a GeopandasGeoDataFrameEasy to extend to support more routing servicesInstallationUsing pipTo install georouting, run this command in your terminal:pipinstallgeoroutingor install from GitHub sourcepip install git+https://github.com/wybert/georouting.gitIf you don't havepipinstalled, thisPython installation guidecan guide you through the process.Using condaThis is not yet available on conda-forge,conda install -c conda-forge georoutingor use mambamamba install -c conda-forge georoutingInstall from sourcesThe sources for georouting can be downloaded from the Github repo.You can clone the public repository:git clone git://github.com/wybert/georoutingThen install it with:python setup.py installUsage# how to get routing distance matrix from OSRMRouterimportpandasaspddata=pd.read_csv("https://raw.githubusercontent.com/wybert/georouting/main/docs/data/sample_3.csv",index_col=0)one_od_pair=data.iloc[2]data.head()fromgeorouting.routersimportGoogleRouter# create a router object with the google_keyrouter=GoogleRouter(google_key,mode="driving")# get the route between the origin and destination, this will return a Route object# this will call the Google Maps APIroute=router.get_route([one_od_pair["ZIP_lat"],one_od_pair["ZIP_lon"]],[one_od_pair["AHA_ID_lat"],one_od_pair["AHA_ID_lon"]])# Now you can get the distance and duration of the route in meters and secondsprint("Distance:{}meters".format(route.get_distance()))print("Duration:{}seconds".format(route.get_duration()))df=route.get_route_geopandas()df.head()df.explore(column="speed (m/s)",style_kwds={"weight":11,"opacity":0.8})TODOGoogle MapsBing MapsOSRM Routingadd more documentation for google routeradd more documentation for bing routeradd more documentation for osrm routerbuilt and host documentationFix the update in Pypiadd get_route_distance_batch APIadd visualization for the route, better with o and d markersLimit the number of origins and destinations in the distance matrixavoid repeat documentationadd ESRI routerAdd testAdd more examplesAdd how to contributechange the show case use OSRMadd OSMnx routerstatic plot for the routeadd one API for all routersAdd how to citeCreditsThis package was created withCookiecutterand thegiswqs/pypackageproject template.
Package: georss-client
python-georss-clientThis library is a framework to build concrete libraries for convenient access
toGeoRSSFeeds.Installationpip install georss-clientKnown ImplementationsLibrarySourceTopicpython-georss-generic-clientGeneric GeoRSS Feedsmiscpython-georss-ign-sismologia-clientInstituto Geográfico Nacional SismologíaEarthquakespython-georss-ingv-centro-nazionale-terremoti-clientINGV Centro Nazionale TerremotiEarthquakespython-georss-nrcan-earthquakes-clientNatural Resources CanadaEarthquakespython-georss-qld-bushfire-alert-clientQueensland Bushfire AlertFirespython-georss-tfs-incidents-clientTasmania Fire Service IncidentsFirespython-georss-wa-dfes-clientWestern Australia Department of Fire and Emergency ServicesFiresUsageEach implementation extracts relevant information from the GeoRSS feed. Not all
feeds contain the same level of information, or present their information in
different ways.After instantiating a particular class and supply the required
parameters, you can callupdateto retrieve the feed data. The return
value will be a tuple of a status code and the actual data in the form of a
list of feed entries specific to the selected feed.Status CodesUPDATE_OK: Update went fine and data was retrieved. The library may still return empty data, for example because no entries fulfilled the filter criteria.UPDATE_OK_NO_DATA: Update went fine but no data was retrieved, for example because the server indicated that there was not update since the last request.UPDATE_ERROR: Something went wrong during the updateFeed ManagersThe Feed Managers help managing feed updates over time, by notifying the
consumer of the feed about new feed entries, updates and removed entries
compared to the last feed update.If the current feed update is the first one, then all feed entries will be
reported as new. The feed manager will keep track of all feed entries'
external IDs that it has successfully processed.If the current feed update is not the first one, then the feed manager will
produce three sets:Feed entries that were not in the previous feed update but are in the
current feed update will be reported as new.Feed entries that were in the previous feed update and are still in the
current feed update will be reported as to be updated.Feed entries that were in the previous feed update but are not in the
current feed update will be reported to be removed.If the current update fails, then all feed entries processed in the previous
feed update will be reported to be removed.After a successful update from the feed, the feed manager will provide two
different dates:last_updatewill be the timestamp of the last successful update from the
feed. This date may be useful if the consumer of this library wants to
treat intermittent errors from feed updates differently.last_timestampwill be the latest timestamp extracted from the feed data.
This requires that the underlying feed data actually contains a suitable
date. This date may be useful if the consumer of this library wants to
process feed entries differently if they haven't actually been updated.
Package: georss-emsc-csem-earthquakes-client
python-georss-emsc-csem-earthquakes-clientThis library provides convenient access to theEMSC CSEM.Installationpip install georss_emsc_csem_earthquakes_clientUsageSee below for an example of how this library can be used. After instantiating
the feed class and supplying the required parameters, you can callupdateto
retrieve the feed data. The return value will be a tuple of a status code and
the actual data in the form of a list of specific feed entries.Status CodesUPDATE_OK: Update went fine and data was retrieved. The library may still return empty data, for example because no entries fulfilled the filter criteria.UPDATE_OK_NO_DATA: Update went fine but no data was retrieved, for example because the server indicated that there was not update since the last request.UPDATE_ERROR: Something went wrong during the updateSupported FiltersFilterDescriptionRadiusfilter_radiusRadius in kilometers around the home coordinates in which events from the feed are included.Minimum Magnitudefilter_minimum_magnitudeMinimum magnitude as float value. Only events with a magnitude equal or above this value are included.Time spanfilter_timespanMaximum age of reported event.Examplefromdatetimeimporttimedeltafromgeorss_emsc_csem_earthquakes_clientimportEMSCEarthquakesFeed# Home Coordinates: Latitude: 46.1, Longitude: 14.1# Filter radius: 500 km# Filter minimum magnitude: 2.0# Filter time span: 3 daysfeed=EMSCEarthquakesFeed((46.1,14.1),filter_radius=500,filter_minimum_magnitude=2.0,filter_timespan=timedelta(days=3))status,entries=feed.update()Feed ManagerThe Feed Manager helps managing feed updates over time, by notifying the
consumer of the feed about new feed entries, updates and removed entries
compared to the last feed update.If the current feed update is the first one, then all feed entries will be
reported as new. The feed manager will keep track of all feed entries'
external IDs that it has successfully processed.If the current feed update is not the first one, then the feed manager will
produce three sets:Feed entries that were not in the previous feed update but are in the
current feed update will be reported as new.Feed entries that were in the previous feed update and are still in the
current feed update will be reported as to be updated.Feed entries that were in the previous feed update but are not in the
current feed update will be reported to be removed.If the current update fails, then all feed entries processed in the previous
feed update will be reported to be removed.After a successful update from the feed, the feed manager will provide two
different dates:last_updatewill be the timestamp of the last successful update from the
feed. This date may be useful if the consumer of this library wants to
treat intermittent errors from feed updates differently.last_timestampwill be the latest timestamp extracted from the feed data.
This requires that the underlying feed data actually contains a suitable
date. This date may be useful if the consumer of this library wants to
process feed entries differently if they haven't actually been updated.