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No Clocks

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High-level Orchestration of targets Pipelines
High-level Orchestration of targets Pipelines
Provides a simple, high-level interface for creating and executing targets-based workflows, so users can focus on their specific analysis, not on pipeline orchestration. The philosophy of tarflowr is based on the concept of arbitrary "work units." This package is experimental.
·humus.rocks·
High-level Orchestration of targets Pipelines
GDAL in R – hypertidy
GDAL in R – hypertidy
Geospatial data, GDAL, and R — Michael Sumner
·hypertidy.org·
GDAL in R – hypertidy
gdal vector simplify — GDAL documentation
gdal vector simplify — GDAL documentation
gdal vector simplify simplifies geometries, ensuring that the result is a valid geometry having the same dimension and number of components as the input. The simplification uses a maximum distance difference algorithm similar to the one used in the Douglas-Peucker algorithm. This done by the OGRGeometry::SimplifyPreserveTopology() method which preserves the topology per feature, but not for a whole layer. Thus gaps or overlaps between geometries that were initially contiguous may happen. To perform simplification that preserves shared boundaries between geometries, see gdal vector simplify-coverage. This command can also be used as a step of gdal vector pipeline.
GDALG output (on-the-fly / streamed dataset) This program supports serializing the command line as a JSON file using the GDALG output format. The resulting file can then be opened as a vector dataset using the GDALG: GDAL Streamed Algorithm driver, and apply the specified pipeline in a on-the-fly / streamed way.
Program-Specific Options --tolerance <TOLERANCE> The specified value of this option is the tolerance used to merge consecutive points of the output geometry using the OGRGeometry::SimplifyPreserveTopology() method The unit of the distance is in georeferenced units of the source layer.
·gdal.org·
gdal vector simplify — GDAL documentation
geotips
geotips
Collection of tips for faster spatial data processing in R
·kadyb.github.io·
geotips
Scale and Resolution – Making Effective Maps: Cartographic Visualization for GIS
Scale and Resolution – Making Effective Maps: Cartographic Visualization for GIS
The creation of this work was supported by Open CU Boulder 2023-2024, a grant funded by the Colorado Department of Higher Education with additional support from the CU Office of the President, CU Office of Academic Affairs, CU Boulder Office of the Provost, and CU Boulder University Libraries.
·colorado.pressbooks.pub·
Scale and Resolution – Making Effective Maps: Cartographic Visualization for GIS
geoterminal
geoterminal
A Python library for geospatial data processing and H3 operations
·jeronimoluza.github.io·
geoterminal
Antipode Finder
Antipode Finder
Find the exact opposite location on Earth using the Antipode Finder tool.
·antipode-finder.com·
Antipode Finder
blog Archive - Spatial Eye
blog Archive - Spatial Eye
Take the lead with data-driven decisions in your industry
·spatial-eye.com·
blog Archive - Spatial Eye
Google-Microsoft-OSM Open Buildings - combined by VIDA · VIDA · Source Cooperative
Google-Microsoft-OSM Open Buildings - combined by VIDA · VIDA · Source Cooperative
This dataset merges Google's V3 Open Buildings, Microsoft's GlobalMLFootprints, and OpenStreetMap building footprints. It contains 2,705,459,584 footprints and is divided into 200 partitions. Each footprint is labelled with its respective source, either Google, Microsoft, or OpenStreetMap. It can be accessed in cloud-native geospatial formats such as GeoParquet, FlatGeobuf and PMTiles.
·source.coop·
Google-Microsoft-OSM Open Buildings - combined by VIDA · VIDA · Source Cooperative
Columnar Query Engine for Larger-than-RAM Data
Columnar Query Engine for Larger-than-RAM Data
A minimal columnar query engine with lazy execution on datasets larger than RAM. Provides dplyr-like verbs (filter(), select(), mutate(), group_by(), summarise(), joins, window functions) and common aggregations (n(), sum(), mean(), min(), max(), sd(), first(), last()) backed by a pure C11 pull-based execution engine and a custom on-disk format (.vtr).
·gillescolling.com·
Columnar Query Engine for Larger-than-RAM Data
Access EMODnet Web Feature Service data through R
Access EMODnet Web Feature Service data through R
Access and interrogate EMODnet (European Marine Observation and Data Network) Web Feature Service data https://emodnet.ec.europa.eu/en/emodnet-web-service-documentation#data-download-services. This includes listing existing data sources, and getting data from each of them.
·docs.ropensci.org·
Access EMODnet Web Feature Service data through R
Execute and Control System Processes
Execute and Control System Processes
Tools to run system processes in the background. It can check if a background process is running; wait on a background process to finish; get the exit status of finished processes; kill background processes. It can read the standard output and error of the processes, using non-blocking connections. processx can poll a process for standard output or error, with a timeout. It can also poll several processes at once.
·processx.r-lib.org·
Execute and Control System Processes
Go-Like Interfaces and Rust-Like Traits with S7
Go-Like Interfaces and Rust-Like Traits with S7
Contract helpers built with S7 for expressing runtime protocols around ordinary S7 dispatch. Structural interfaces describe small sets of required S7 generics, while explicit traits record registered implementations with optional default methods and associated metadata. Optional runtime checks can validate argument and return specifications in contract-scoped evaluation.
·sounkou-bioinfo.github.io·
Go-Like Interfaces and Rust-Like Traits with S7