Skip to content
master
Switch branches/tags
Code

Latest commit

 

Git stats

Files

Permalink
Failed to load latest commit information.
Type
Name
Latest commit message
Commit time
R
 
 
 
 
man
 
 
 
 
 
 
 
 
 
 

thredds: THREDDS Crawler for R using xml2 package

THREDDS catalogs are well described. This package provides only client-side functionality where the user provides prior knowledge about how the catalog is organized, as on the server side the provider has some latitude in how to design the catalog system.

A user's workflow likely is to fetch a top-level catalog, then drill down to a particular sub-catalog by hop-skipping through lightweight catalog references. Often, but not always these catalogs are organized around date (a year of observation, a month of observation, etc) or a data source ("MODISA" vs "MODIST"), etc. Catalogs may contain references to other catalogs or to datasets (often OPeNDAP resources.)

This package replaces threddscrawler which is based upon the XML. Instead this package is based upon xml2, and uses R6 classes.

Requirements

R6

magrittr

httr

xml2

Installation

It is easy to install with devtools

library(devtools)
install_github("BigelowLab/thredds")

An example from OBPG

Start with this page and it's XML companion. We find a top level catalog with a number of sub-catalogs.

library(ncdf4)
library(thredds)
top_uri <- 'https://oceandata.sci.gsfc.nasa.gov/opendap/catalog.xml'
Top <- thredds::CatalogNode$new(top_uri, prefix = "thredds")
Top
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: thredds
#   url: https://oceandata.sci.gsfc.nasa.gov/opendap/catalog.xml
#   services [3]: OPeNDAP HTTPServer WMS
#   catalogRefs [10]: CZCS MODISA MODIST Merged_ATV OCTS SE1 SeaWiFS VIIRS VIIRSJ1 mig-tmp
#   datasets [0]: none

Top$browse()

We'll drill down into MODISA which only contains one sub-catalog, L3SMI - the gridded level 3 standard mapped image. Knowing that we'll actually chain the methods to get the contents of the L3SMI catalog, where thinsg get interesting. Note the get_catalogs always returns a list, so you must index into it if you want just one result.

L3 <- Top$get_catalogs("MODISA")[["MODISA"]]$get_catalogs()
L3
# $L3SMI
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: thredds
#   url: https://oceandata.sci.gsfc.nasa.gov/opendap/MODISA/L3SMI/catalog.xml
#   services [3]: OPeNDAP HTTPServer WMS
#   catalogRefs [19]: 2002 2003 2004 ... 2018 2019 2020
#   datasets [0]: none
L3[[1]]$browse()

Let's drill down into 2009, and see what is available on January 20.

catalog2009 <- L3[[1]]$get_catalogs("2009")
# $`2009`
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: thredds
#   url: https://oceandata.sci.gsfc.nasa.gov/opendap/MODISA/L3SMI/2009/catalog.xml
#   services [3]: OPeNDAP HTTPServer WMS
#   catalogRefs [730]: 001 002 003 ... 363 364 365
#   datasets [0]: none

Hmmm. We have to conver '2009-01-20' to a three digit day of year (or 4 digit mmdd if looking for SST).

doy <- format(as.Date("2009-01-20"), "%j")
doy
# "020"

Ehem, I suppose I could have thought of that without help.

catalog20 <- catalog2009[['2009']]$get_catalogs("020")
$`020`
CatalogNode (R6): 
  verbose: FALSE    tries: 3    namespace prefix: thredds
  url: https://oceandata.sci.gsfc.nasa.gov/opendap/MODISA/L3SMI/2009/020/catalog.xml
  services [3]: OPeNDAP HTTPServer WMS
  catalogRefs [0]: none
  datasets [113]: A2009020.L3m_DAY_CHL_chl_ocx_4km.nc A2009020.L3m_DAY_CHL_chl_ocx_9km.nc ... A2009020.L3m_DAY_ZLEE_Zeu_lee_4km.nc A2009020.L3m_DAY_ZLEE_Zeu_lee_9km.nc

Let's did out just the 9km chlor_a data for that day.

chl <- catalog20[['020']]$get_datasets("A2009020.L3m_DAY_CHL_chlor_a_9km.nc")
# $A2009020.L3m_DAY_CHL_chlor_a_9km.nc
# DatasetNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: thredds
#   url: /MODISA/L3SMI/2009/020/A2009020.L3m_DAY_CHL_chlor_a_9km.nc
#   children: dataSize date access
#   name: A2009020.L3m_DAY_CHL_chlor_a_9km.nc
#   dataSize: 3742166
#   date: 2017-12-30T22:43:20

Now we need only retrieve the relative URL, and add it to the base URL for the service. Somewhat awkwardly, the relaive URL comes prepended with a path separator, so we use straight up paste0 to append to the base_uri.

base_uri <- "https://oceandata.sci.gsfc.nasa.gov:443/opendap"
uri <- paste0(base_uri, chl[["A2009020.L3m_DAY_CHL_chlor_a_9km.nc"]]$url)
NC <- ncdf4::nc_open(uri)

Alternatively, you can provide the base URL to the service when you instantiate the top level catalog. The base URL will be passed down to it's children.

An example from GoMOFS

GOMOFS provides a different THREDDS catalog that has no explicit prefix for the namespace. So we use the default 'd1' prefix instead.

Start with the XML companion to this catalog page. It isn't super obvious browsing the resource, but it is important to specify the namespace prefix for searching the thredds genealogy - in this case there isn't any so the default, 'd1', would suffice. Even though it is the default, we specify it explicitly for clarity. Also, note that this catalog hase changed over time, so the example may be out of date.

library(ncdf4)
library(thredds)
uri = "https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/catalog.xml"
top = thredds::get_catalog(uri, prefix = 'd1')
top
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: d1
#   url: https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/catalog.xml
#   children: service dataset
#   services [4]: Compound OPENDAP HTTPServer WMS
#   catalogRefs [1]: 
#   datasets [0]: none
#
# top$browse()  

A CatalogNode may contain zero or more service and zero or more dataset nodes.
If there is a dataset node, it, it turn, may contain zero of more catalogRef nodes or dataset nodes. In the above only catalogs are listed implying that there are no datasets listed at this level. Below we retrieve a complete listing of catalog names, and then retrieve just one by name. Note that a list of catalogs are returned, even if just one is requested. Also, note that the "name attribute is an empty string. In lieu of name we then take the first non-empty instance of title, ID, urlPath, and finally href.

top$get_catalog_names()
# "2020""

cata = top$get_catalogs(index = "2020")
cata
# $`2020`
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: d1
#   url: https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/2020/catalog.xml
#   children: service dataset
#   services [4]: Compound OPENDAP HTTPServer WMS
#   catalogRefs [3]: 09 08 07
#   datasets [0]: none
  

Note that this is a Catalog - a pointer to other catalogs and/or datasets. It looks like Jcatalogs for July, Aug and Sep of 2020. Let's get September.

Months <- cata[["2020"]]$get_catalogs("09")
Months
# $`09`
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: d1
#   url: https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/2020/09/catalog.xml
#   children: service dataset
#   services [4]: Compound OPENDAP HTTPServer WMS
#   catalogRefs [28]: 28 27 26 ... 03 02 01
#   datasets [0]: none

So, they appear to be listed by day. So, let's get the most recent...

Recent = Months[["09"]]$get_catalogs("28")
Recent
# $`28`
# CatalogNode (R6): 
#   verbose: FALSE    tries: 3    namespace prefix: d1
#   url: https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/2020/09/28/catalog.xml
#   children: service dataset
#   services [4]: Compound OPENDAP HTTPServer WMS
#   catalogRefs [0]: none
#   datasets [396]: nos.gomofs.stations.nowcast.20200928.t12z.nc nos.gomofs.stations.nowcast.20200928.t06z.nc ... # nos.gomofs.2ds.f001.20200928.t06z.nc nos.gomofs.2ds.f001.20200928.t00z.nc

Note that we are down to a level without any further catalogs, but instead we have 396 datasets. Datasets hold the relative file specification for the resource it identifies. Let's retrieve the dataset for the second item listed.

nowcast <- Recent[['28']]$get_datasets('nos.gomofs.stations.nowcast.20200928.t06z.nc')
nowcast
  $nos.gomofs.stations.nowcast.20200928.t06z.nc
  DatasetNode (R6): 
    verbose: FALSE    tries: 3    namespace prefix: d1
    url: NOAA/GOMOFS/MODELS/2020/09/28/nos.gomofs.stations.nowcast.20200928.t06z.nc
    children: dataSize date
    name: nos.gomofs.stations.nowcast.20200928.t06z.nc
    dataSize: 4.871
    date: 2020-09-28T07:25:47Z

If we know the URL for the base service, then we append the relative URL to that.

base_uri <- 'https://opendap.co-ops.nos.noaa.gov/thredds/dodsC'
nowcast_uri <- file.path(base_uri, 
                           nowcast[['nos.gomofs.stations.nowcast.20200928.t06z.nc']]$url)
NC <- ncdf4::nc_open(nowcast_uri)

Note on searching within a prefixed namespace

A given implementation of a THREDDS catalog system may rely upon an XML namespace with a prefix. We have encountered these: d1, another d1 and thredds.

uri = "https://opendap.co-ops.nos.noaa.gov/thredds/catalog/NOAA/GOMOFS/MODELS/catalog.xml"
thredds::get_xml_ns(uri)
# d1    <-> http://www.unidata.ucar.edu/namespaces/thredds/InvCatalog/v1.0
# xlink <-> http://www.w3.org/1999/xlink

xlink is a standard xml namespace. Other ones we have encountered include bes, which is part of the THREDDS specification for back end server, and thredds which is used for thredds-centric elements. In general, you can specify the prefix in a call to \code{build_xpath()} or provide it when you instatiate a new \code{CatalogNode} object, but the reality is that you have to have some awareness of how the server is configured. These crawler tools can't successfully navigate without some higher level management provided by the user.

About

THREDDS Crawler for R using xml2 package

Resources

License

Releases

No releases published

Packages

No packages published

Languages