{
 "cells": [
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "# Data API\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "This tutorial is separated into three main parts: the first two parts shows how to find and get data to do impact calculations and should be enough for most users. The third part provides more detailed information on how the API is built."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Finding datasets"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 1,
   "metadata": {},
   "outputs": [],
   "source": [
    "from climada.util.api_client import Client\n",
    "\n",
    "client = Client()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Data types and data type groups\n",
    "The datasets are first separated into 'data_type_groups', which represent the main classes of CLIMADA (exposures, hazard, vulnerability, ...). So far, data is available for exposures and hazard. Then, data is separated into data_types, representing the different hazards and exposures available in CLIMADA"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 2,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "application/vnd.microsoft.datawrangler.viewer.v0+json": {
       "columns": [
        {
         "name": "index",
         "rawType": "int64",
         "type": "integer"
        },
        {
         "name": "data_type",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "data_type_group",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "status",
         "rawType": "object",
         "type": "string"
        },
        {
         "name": "description",
         "rawType": "object",
         "type": "unknown"
        },
        {
         "name": "properties",
         "rawType": "object",
         "type": "unknown"
        },
        {
         "name": "key_reference",
         "rawType": "object",
         "type": "unknown"
        },
        {
         "name": "version_notes",
         "rawType": "object",
         "type": "unknown"
        }
       ],
       "ref": "07cb21f2-a151-4bcf-9425-678abb1fd699",
       "rows": [
        [
         "6",
         "centroids",
         "centroids",
         "active",
         null,
         "[{'property': 'res_arcsec_land', 'mandatory': True, 'description': 'resolution over land in arc seconds'}, {'property': 'res_arcsec_ocean', 'mandatory': True, 'description': 'resolution over oceans in arc seconds (provided for consistency)'}, {'property': 'extent', 'mandatory': True, 'description': 'spatial extend in degrees'}, {'property': 'date_creation', 'mandatory': False, 'description': 'date of data creation'}, {'property': 'climada_version', 'mandatory': False, 'description': 'the version of CLIMADA used to produce the dataset'}]",
         "[]",
         "[]"
        ],
        [
         "4",
         "crop_production",
         "exposures",
         "active",
         "Historical and twenty-first century crop production in tons. Global gridded (4km resolution) crop yield simulations for maize, rice, soybean, and wheat, encompassing an ensemble of transient yield simulation output from eight global gridded crop models driven by bias-corrected output from five global climate models, as facilitated by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, isimip.org).",
         "[{'property': 'crop', 'mandatory': True, 'description': 'crop type, such as whe[at], soy, ric[e], mai[ze]'}, {'property': 'irrigation_status', 'mandatory': True, 'description': 'without (noirr) or with (firr) irrigation'}, {'property': 'unit', 'mandatory': True, 'description': 'the unit of the values stored'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.3929/ethz-b-000489485', 'key_reference': 'Eberenz, S., 2021: Globally Consistent Assessment of Climate-related Physical Risk. A Conceptual Framework and its Application in Asset Valuation. Doctoral Thesis, ETH Zurich, Switzerland. https://doi.org/10.3929/ethz-b-000489485'}]",
         "[]"
        ],
        [
         "10",
         "crops",
         "exposures",
         "active",
         "Crop exposure for Switzerland in 2021 obtained from geoddienste.ch (https://geodienste.ch/services/lwb_nutzungsflaechen). Including a crop mask, the number of fields and the total crop area at 1, 2, 4, and 8 km resolution for the following crop types: winter wheat, maize (incl. silage and forage maize), winter barley, rapeseed, and grapevine as well as an aggregate crop class field crops (incl. wheat, maize, barley, and rapeseed).\nThe dataset can be used for any kind of risk assessment studies for these crops in Switzerland.",
         "[{'property': 'crop', 'mandatory': True, 'description': 'crop type, such as wheat, maize, barley, rapeseed, grapevine, field_crops'}, {'property': 'res_km', 'mandatory': True, 'description': 'resolution in kilometers: 1, 2, 4, or 8'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.5194/egusphere-2023-2598', 'key_reference': 'Portmann, R., Schmid, T., Villiger, L., Bresch, D. N., and Calanca, P.: Modelling crop hail damage footprints with single-polarization radar: The roles of spatial resolution, hail intensity, and cropland density, EGUsphere [preprint], 2023.'}]",
         "[]"
        ],
        [
         "0",
         "litpop",
         "exposures",
         "active",
         "A global high-resolution asset exposure dataset produced using “lit population” (LitPop), a globally consistent methodology to disaggregate asset value data proportional to a combination of nightlight intensity and geographical population data. Exposure data for population, asset values and productive capital at 4km spatial resolution globally, consistent across country borders. The dataset offers value for manifold use cases, including globally consistent economic disaster risk assessments and climate change adaptation studies, especially for larger regions, yet at considerably high resolution.",
         "[{'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'climada_version', 'mandatory': True, 'description': 'the version of CLIMADA used to produce the dataset'}, {'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'date_creation', 'mandatory': True, 'description': 'date of data creation'}, {'property': 'fin_mode', 'mandatory': True, 'description': \"Socio-economic value to be used as an asset base that is disaggregated to the grid points within the country. 'pc': produced capital (Source: World Bank), incl. manufactured or built assets such as machinery, equipment, and physical structures, in constant 2014 USD. 'pop': population count (source: GPW, same as gridded population), unit is 'people'.\"}, {'property': 'exponents', 'mandatory': True, 'description': 'the Lit^n*Pop^m exponents, see reference'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.5194/essd-12-817-2020', 'key_reference': 'Eberenz, S., Stocker, D., Röösli, T., and Bresch, D. N., 2020: Asset exposure data for global physical risk assessment, Earth Syst. Sci. Data, 12, 817–833, https://doi.org/10.5194/essd-12-817-2020. Dataset for 224 countries also archived in the ETH Research Repository with the link https://doi.org/10.3929/ethz-b-000331316 (Eberenz et al., 2019).'}]",
         "[{'version': 'v2', 'notes': 'Countries with no exposure value and update metadata and tag of global files removed.'}, {'version': 'v3', 'notes': 'Previous versions had a deprecated binary data format for geometry point data.\\nIn order to keep the files readable all datasets have been converted to the format up to date.\\nThe climada_version property for these datasets also contains the version from the original datasets in parenthesis.\\nFor climada_python v3.3 and blow these datasets are unreadable. Update the climada version or specify the dataset version in the api query.'}]"
        ],
        [
         "13",
         "aqueduct_coastal_flood",
         "hazard",
         "active",
         "Global probabilistic coastal flood maps for baseline and future climates at ~1 km resolution. Maps are available for the 2-, 5-, 10-, 25-, 50-, 100-, 250-, 500- and 1000-years return periods in 2030, 2050, 2080 under RCPs 4.5 and 8.5, under three sea level rise projections and including or excluding subsidence.",
         "[{'property': 'climate_scenario', 'mandatory': True, 'description': \"Climate scenario description, reference concentration pathways 'rcp45' for RCP 4.5, 'rcp85' for RCP 8.5, or 'hist' for historical\"}, {'property': 'subsidience', 'mandatory': True, 'description': \"Whether simulating subsidence or not: 'nosub' or 'wtsub'\"}, {'property': 'percentile', 'mandatory': True, 'description': 'Sea level rise projection: 0_perc_05, 0_perc_50 or 0'}, {'property': 'year', 'mandatory': False, 'description': \"Simulation year: 2030, 2050, 2080; Relevant when property 'climate_scenario' is 'rcp45' or 'rcp85' or when property 'subsidence' is 'wtsub'\"}]",
         "[{'ref_no': 1, 'ref_url': 'https://www.wri.org/research/aqueduct-floods-methodology', 'key_reference': 'Aqueduct Floods Methodology'}, {'ref_no': 2, 'ref_url': 'https://wri-projects.s3.amazonaws.com/AqueductFloodTool/download/v2/index.html', 'key_reference': 'Aqueduct Data Page'}]",
         "[]"
        ],
        [
         "8",
         "earthquake",
         "hazard",
         "active",
         "Earthquake hazard sets at 150 arcsec (ca. 4km) resolution, available for the entire globe and per country. Available as historic records from the USGS epicentres database and as a simple probabilistic sampling starting from the historic earthquake catalog, with 9 synthetic events per historic record.",
         "[{'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'event_type', 'mandatory': False, 'description': 'The underlying event type of the hazard, i.e. a historically observed real event, or a synthetically produced one.\\npossible values: {synthetic, observed}. '}]",
         "[{'ref_no': 1, 'ref_url': None, 'key_reference': 'https://github.com/CLIMADA-project/climada_petals/tree/feature/quake. Please note that there is currently no peer-reviewed publication documenting this hazard set.'}]",
         "[]"
        ],
        [
         "9",
         "flood",
         "hazard",
         "active",
         "Flood footprint of historical events at a 200m x 200m resolution based on the cloud to street database with events ranging from the years 2002-2018 (see https://www.cloudtostreet.ai). The events have been processed into one hazard dataset per country.",
         "[{'property': 'date_creation', 'mandatory': True, 'description': 'date of data creation'}, {'property': 'climada_version', 'mandatory': True, 'description': 'the version of CLIMADA used to produce the dataset'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}, {'property': 'res_meter', 'mandatory': False, 'description': 'spatial resolution in meters'}, {'property': 'year_range', 'mandatory': False, 'description': 'year range of historic data'}]",
         "[]",
         "[]"
        ],
        [
         "12",
         "hail",
         "hazard",
         "active",
         "Radar-based daily hail hazard data at 1km spatial resolution for 12 hail days in Switzerland between 2017 and 2021 provided by the Swiss Federal Office of Meteorology and Climatology (MeteoSwiss). Included dates are the ones where hail damage information is available from the hail_damage_crops impact dataset (YYYY-MM-DD): 2017-06-27, 2017-07-08, 2017-08-01, 2019-06-15, 2019-06-30, 2019-07-01, 2021-06-20, 2021-06-21, 2021-06-28, 2021-07-12, 2021-07-13, 2021-07-24. The dataset contains two variables based on single-polarization radar data: the Maximum Expected Severe Hail Size (MESHS) and the Probability of Hail (POH). For more details on these two products refer to the referenced report by MeteoSwiss.",
         "[{'property': 'variable', 'mandatory': True, 'description': 'MESHS (Maximum Expected Severe Hail Size), POH (Probability Of Hail)'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.3390/rs14030503', 'key_reference': 'Germann U, Boscacci M, Clementi L, Gabella M, Hering A, Sartori M, Sideris IV, Calpini B. Weather Radar in Complex Orography. Remote Sensing. 2022; 14(3):503.'}, {'ref_no': 2, 'ref_url': 'https://doi.org/10.5194/egusphere-2023-2598', 'key_reference': 'Portmann, R., Schmid, T., Villiger, L., Bresch, D. N., and Calanca, P.: Modelling crop hail damage footprints with single-polarization radar: The roles of spatial resolution, hail intensity, and cropland density, EGUsphere [preprint], 2023.'}]",
         "[]"
        ],
        [
         "7",
         "relative_cropyield",
         "hazard",
         "active",
         "Historical and twenty-first century crop production in relative terms. Global gridded (4km resolution) crop yield simulations for maize, rice, soybean, and wheat, encompassing an ensemble of transient yield simulation output from eight global gridded crop models driven by bias-corrected output from five global climate models, as facilitated by the Inter-Sectoral Impact Model Intercomparison Project (ISIMIP, isimip.org).",
         "[{'property': 'climate_scenario', 'mandatory': True, 'description': 'climate scenario description, usually reference concentration pathways (such as rcp26 for RCP 2.6) or historical'}, {'property': 'crop', 'mandatory': True, 'description': 'crop type, such as whe[at], soy, ric[e], mai[ze]'}, {'property': 'irrigation_status', 'mandatory': True, 'description': 'without (noirr) or with (firr) irrigation'}, {'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'year_range', 'mandatory': True, 'description': 'year range of historic data'}, {'property': 'date_creation', 'mandatory': True, 'description': 'date of data creation'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.3929/ethz-b-000489485', 'key_reference': 'Eberenz, S., 2021: Globally Consistent Assessment of Climate-related Physical Risk. A Conceptual Framework and its Application in Asset Valuation. Doctoral Thesis, ETH Zurich, Switzerland. https://doi.org/10.3929/ethz-b-000489485'}]",
         "[]"
        ],
        [
         "3",
         "river_flood",
         "hazard",
         "active",
         "River flood [flood depth in meters and flooded area fraction] footprints worldwide at 150 arcsec (approx 4 kilometers at equator) resolution. Based on isimip.org CaMa flood output derived from a series of global circulation model output, combined into a composite hazard event set. Data available for each (flood exposed) country worldwide. Versions exist for flood hazard today today plus select IPCC representative concentration pathways (rcp) emission scenarios for select future time periods.",
         "[{'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'date_creation', 'mandatory': True, 'description': 'date of data creation'}, {'property': 'climada_version', 'mandatory': True, 'description': 'the version of CLIMADA used to produce the dataset'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'climate_scenario', 'mandatory': False, 'description': 'climate scenario description, usually reference concentration pathways (such as rcp26 for RCP 2.6) or historical'}, {'property': 'year_range', 'mandatory': False, 'description': 'year range of historic data'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}]",
         "[{'ref_no': 1, 'ref_url': 'https://www.nature.com/articles/s41467-021-22153-9', 'key_reference': 'Sauer, I., Reese, R., Otto, C., Geiger, T., Willner, S. N., Guillod, B., David N. Bresch and Frieler, K., 2021: Climate signals in river flood damages emerge under sound regional disaggregation. Nature Communications, 12(1), 1-11. https://www.nature.com/articles/s41467-021-22153-9.'}, {'ref_no': 2, 'ref_url': 'https://doi.org/10.1088/1748-9326/abd26c', 'key_reference': 'Kam, P. M., Aznar-Siguan, G., Schewe, J., Milano, L., Ginnetti, J., Willner, S., McCaughey, J., and Bresch, D., N., 2021: Global warming and population change both heighten future risk of human displacement due to river floods. Environ. Res. Lett. 16, 044026. https://doi.org/10.1088/1748-9326/abd26c'}]",
         "[{'version': 'v2', 'notes': 'Higher resolution for land definition in centroids, resulting in a better definition of coastal areas and islands. Extend centroids from -60,60lat to -90,90lat.'}]"
        ],
        [
         "5",
         "storm_europe",
         "hazard",
         "active",
         "European winter storm [gust in meters per second] footprints for Europe. Data is available from two projects: 1. Based on Coperncus WISC (https://wisc.climate.copernicus.eu/wisc) historical event footprints 1940-2014 plus 50 probabilistic events per original event, at 4 kilometers resolution. Data available for European countries, and corresponds to the storm hazard today. See key reference Röösli et al. 2021. 2. Winter storm hazards generated from ERA5 (1980-2010) and CMIP6 models (1980-2010 and 2070-2100). In that second case, only Europe wide datasets are available, with lower resolution (depending on the GCM or ERA5 model). See Severino et al. 2023. For each storm day, the specific ensemble member of the climate model which has been used to model the data  can be read in the \"event_name\" property (e.g. 'event_name': 'IPSL-CM6A-LR_ssp585_mem0' corresponds to a storm day  which has been generated by the ensemble member 0 of the climate model IPSL-CM6A-LR for the ssp585 experiment).",
         "[{'property': 'data_source', 'mandatory': False, 'description': 'source of the data used to generate the storm Europe hazard data. WISC (based on Copernicus WISC), ERA5 (based on ERA5 reanalysis), CMIP6 (based on general calculation models participating in CMIP6).'}, {'property': 'spatial_coverage', 'mandatory': False, 'description': 'spatial coverage by country (one file each) or Europe (for the entire domain). Only European countries are currently available.'}, {'property': 'climate_scenario', 'mandatory': False, 'description': 'climate scenario description. Either a reference concentration pathways (such as rcp26 for RCP 2.6), a shared socioeconomic pathways (such as ssp126 for SSP1-2.6), historical for historical experiments, or None when the data is based on observations.'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'res_km', 'mandatory': False, 'description': 'spatial resolution in kilometers'}]",
         "[{'ref_no': 1, 'ref_url': 'https://www.nat-hazards-earth-syst-sci-discuss.net/nhess-2020-115', 'key_reference': 'Welker, C., Röösli, T., and Bresch, D. N., 2021: Comparing an insurer’s perspective on building damages with modelled damages from pan-European winter windstorm event sets: a case study from Zurich, Switzerland. Nat. Hazards Earth Syst. Sci., 21, 279-299. https://www.nat-hazards-earth-syst-sci-discuss.net/nhess-2020-115.'}, {'ref_no': 2, 'ref_url': 'http://dx.doi.org/10.1002/met.2035', 'key_reference': 'Röösli, T., Appenzeller, C., and Bresch, D. N., 2021: Towards operational impact forecasting of building damage from winter windstorms in Switzerland. Meteorol Appl. 28:e2035. http://dx.doi.org/10.1002/met.2035'}, {'ref_no': 3, 'ref_url': 'https://doi.org/10.5194/egusphere-2023-205', 'key_reference': 'Severino, L. G., Kropf, C. M., Afargan-Gerstman, H., Fairless, C., de Vries, A. J., Domeisen, D. I. V., and Bresch, D. N.: Projections and uncertainties of future winter windstorm damage in Europe, EGUsphere [preprint], https://doi.org/10.5194/egusphere-2023-205, 2023.'}]",
         "[]"
        ],
        [
         "1",
         "tropical_cyclone",
         "hazard",
         "active",
         "Tropical cyclone wind footprints (m/s) at 150 arcsec (approx 4 kilometers at equator) resolution. Available as global files and per country; available for historically observed records, and synthetically created, probabilistic events, from various modelling sources, for present and future climate scenarios.",
         "[{'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'climate_scenario', 'mandatory': False, 'description': 'climate scenario description, usually reference concentration pathways (such as rcp26 for RCP 2.6) or historical'}, {'property': 'ref_year', 'mandatory': False, 'description': 'reference year of track set, nan for historic'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'genesis_basin', 'mandatory': False, 'description': 'Tropical cyclone genesis basin name, this property is only available for the historical tracks and random_walk model. The basins are: NA for North Altantic, EP East Pacific, NI North Indian, SA South Atlantic, SI South Indian, SP South Pacific, WP West Pacific'}, {'property': 'gcm', 'mandatory': False, 'description': 'General circulation model driving the tropical cyclone model. Property only valid for the STORM model, the random_track model is based on the mean of multiple GCMs.'}, {'property': 'basin', 'mandatory': False, 'description': 'Basin for which to get the tracks, storms that have at least one position in the specified basin are saved in the dataset. This property is only available for the STORM model for now. The basins are: North Atlantic/Eastern Pacific (AP), North Indian Ocean (IO), Southern Hemisphere (SH), Western Pacific (WP).'}, {'property': 'event_type', 'mandatory': False, 'description': 'The underlying event type of the hazard, i.e. a historically observed real event, or a synthetically produced one.\\npossible values: {synthetic, observed}. '}, {'property': 'model_name', 'mandatory': False, 'description': 'the model name specifying the exact model used for calculating the hazard.\\npossible values - for TCs: random_walk, kerry, storm - for others: tbd'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.5194/nhess-21-393-2021', 'key_reference': 'Eberenz, S., Lüthi, S., and Bresch, D. N., 2021: Regional tropical cyclone impact functions for globally consistent risk assessments, Nat. Hazards Earth Syst. Sci., 21, 393-415, https://doi.org/10.5194/nhess-21-393-2021.'}, {'ref_no': 2, 'ref_url': 'https://doi.org/10.5194/gmd-12-3085-2019', 'key_reference': 'Aznar-Siguan, G., and Bresch, D. N., 2019: CLIMADA v1: a global weather and climate risk assessment platform, Geosci. Model Dev., 12, 3085–3097. https://doi.org/10.5194/gmd-12-3085-2019.'}, {'ref_no': 3, 'ref_url': 'https://doi.org/10.5194/gmd-14-351-2021', 'key_reference': 'Bresch, D. N. and Aznar-Siguan, G., 2021: CLIMADA v1.4.1: towards a globally consistent adaptation options appraisal tool, Geosci. Model Dev., 14, 351-363, https://doi.org/10.5194/gmd-14-351-2021'}]",
         "[{'version': 'v2', 'notes': 'Higher resolution for land definition in centroids, resulting in a better definition of coastal areas and islands.'}]"
        ],
        [
         "2",
         "wildfire",
         "hazard",
         "active",
         "Global wildfire dataset at 4km resolution, based on MODIS satellite data 2000-2021 (cf https://firms.modaps.eosdis.nasa.gov).",
         "[{'property': 'res_arcsec', 'mandatory': True, 'description': 'spatial resolution in arc seconds'}, {'property': 'climate_scenario', 'mandatory': True, 'description': 'climate scenario description, usually reference concentration pathways (such as rcp26 for RCP 2.6) or historical'}, {'property': 'year_range', 'mandatory': True, 'description': 'year range of historic data'}, {'property': 'climada_version', 'mandatory': True, 'description': 'the version of CLIMADA used to produce the dataset'}, {'property': 'date_creation', 'mandatory': True, 'description': 'date of data creation'}, {'property': 'spatial_coverage', 'mandatory': True, 'description': 'spatial coverage by country (one file each) or global (in one file), for some also other groups, such as tropical cyclone genesis basin'}, {'property': 'country_iso3alpha', 'mandatory': False, 'description': 'ISO3 alpha code for country, such as CHE for Switzerland'}, {'property': 'country_name', 'mandatory': False, 'description': 'Explicit country name (please do not use for referencing, see ISO3alpha and ISO3num)'}, {'property': 'country_iso3num', 'mandatory': False, 'description': 'ISO3 country number, such as 756 for Switzerland'}]",
         "[{'ref_no': 1, 'ref_url': 'https://gmd.copernicus.org/articles/14/7175/2021/', 'key_reference': 'Lüthi, Aznar-Siguan, G., Fairless, C., and Bresch, D. N., 2021: Globally consistent assessment of economic impacts of wildfires in CLIMADA v2.2, Geosci. Model Dev., 14, 7175-7187, https://gmd.copernicus.org/articles/14/7175/2021/'}]",
         "[]"
        ],
        [
         "11",
         "hail_damage_crops",
         "impact",
         "active",
         "Hail damage to crops for 10-12 hail days (depending on the crop) between 2017 and 2021 from the Swiss Hail insurance company including the number of damaged fields at 1, 2, 4, and 8 km resolution for the following crop types: winter wheat, maize (incl. silage and forage maize), winter barley, rapeseed, and grapevine as well as an aggregate crop class field crops (incl. wheat, maize, barley, and rapeseed).\nThe dataset can be used to calibrate and verify crop hail damage models.",
         "[{'property': 'crop', 'mandatory': True, 'description': 'crop type, such as wheat, maize, barley, rapeseed, grapevine, field_crops'}, {'property': 'res_km', 'mandatory': True, 'description': 'resolution in kilometers: 1, 2, 4, or 8'}]",
         "[{'ref_no': 1, 'ref_url': 'https://doi.org/10.5194/egusphere-2023-2598', 'key_reference': 'Portmann, R., Schmid, T., Villiger, L., Bresch, D. N., and Calanca, P.: Modelling crop hail damage footprints with single-polarization radar: The roles of spatial resolution, hail intensity, and cropland density, EGUsphere [preprint], 2023.'}]",
         "[]"
        ]
       ],
       "shape": {
        "columns": 7,
        "rows": 14
       }
      },
      "text/html": [
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       "\n",
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       "    }\n",
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       "    .dataframe thead th {\n",
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       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_type</th>\n",
       "      <th>data_type_group</th>\n",
       "      <th>status</th>\n",
       "      <th>description</th>\n",
       "      <th>properties</th>\n",
       "      <th>key_reference</th>\n",
       "      <th>version_notes</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>6</th>\n",
       "      <td>centroids</td>\n",
       "      <td>centroids</td>\n",
       "      <td>active</td>\n",
       "      <td>None</td>\n",
       "      <td>[{'property': 'res_arcsec_land', 'mandatory': ...</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>4</th>\n",
       "      <td>crop_production</td>\n",
       "      <td>exposures</td>\n",
       "      <td>active</td>\n",
       "      <td>Historical and twenty-first century crop produ...</td>\n",
       "      <td>[{'property': 'crop', 'mandatory': True, 'desc...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>10</th>\n",
       "      <td>crops</td>\n",
       "      <td>exposures</td>\n",
       "      <td>active</td>\n",
       "      <td>Crop exposure for Switzerland in 2021 obtained...</td>\n",
       "      <td>[{'property': 'crop', 'mandatory': True, 'desc...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>litpop</td>\n",
       "      <td>exposures</td>\n",
       "      <td>active</td>\n",
       "      <td>A global high-resolution asset exposure datase...</td>\n",
       "      <td>[{'property': 'spatial_coverage', 'mandatory':...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[{'version': 'v2', 'notes': 'Countries with no...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>13</th>\n",
       "      <td>aqueduct_coastal_flood</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Global probabilistic coastal flood maps for ba...</td>\n",
       "      <td>[{'property': 'climate_scenario', 'mandatory':...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://www.wri.org...</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>8</th>\n",
       "      <td>earthquake</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Earthquake hazard sets at 150 arcsec (ca. 4km)...</td>\n",
       "      <td>[{'property': 'res_arcsec', 'mandatory': True,...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': None, 'key_reference...</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>9</th>\n",
       "      <td>flood</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Flood footprint of historical events at a 200m...</td>\n",
       "      <td>[{'property': 'date_creation', 'mandatory': Tr...</td>\n",
       "      <td>[]</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>12</th>\n",
       "      <td>hail</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Radar-based daily hail hazard data at 1km spat...</td>\n",
       "      <td>[{'property': 'variable', 'mandatory': True, '...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>7</th>\n",
       "      <td>relative_cropyield</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Historical and twenty-first century crop produ...</td>\n",
       "      <td>[{'property': 'climate_scenario', 'mandatory':...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>3</th>\n",
       "      <td>river_flood</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>River flood [flood depth in meters and flooded...</td>\n",
       "      <td>[{'property': 'res_arcsec', 'mandatory': True,...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://www.nature....</td>\n",
       "      <td>[{'version': 'v2', 'notes': 'Higher resolution...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>5</th>\n",
       "      <td>storm_europe</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>European winter storm [gust in meters per seco...</td>\n",
       "      <td>[{'property': 'data_source', 'mandatory': Fals...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://www.nat-haz...</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>tropical_cyclone</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Tropical cyclone wind footprints (m/s) at 150 ...</td>\n",
       "      <td>[{'property': 'spatial_coverage', 'mandatory':...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[{'version': 'v2', 'notes': 'Higher resolution...</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>wildfire</td>\n",
       "      <td>hazard</td>\n",
       "      <td>active</td>\n",
       "      <td>Global wildfire dataset at 4km resolution, bas...</td>\n",
       "      <td>[{'property': 'res_arcsec', 'mandatory': True,...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://gmd.coperni...</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>11</th>\n",
       "      <td>hail_damage_crops</td>\n",
       "      <td>impact</td>\n",
       "      <td>active</td>\n",
       "      <td>Hail damage to crops for 10-12 hail days (depe...</td>\n",
       "      <td>[{'property': 'crop', 'mandatory': True, 'desc...</td>\n",
       "      <td>[{'ref_no': 1, 'ref_url': 'https://doi.org/10....</td>\n",
       "      <td>[]</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "                 data_type data_type_group  status  \\\n",
       "6                centroids       centroids  active   \n",
       "4          crop_production       exposures  active   \n",
       "10                   crops       exposures  active   \n",
       "0                   litpop       exposures  active   \n",
       "13  aqueduct_coastal_flood          hazard  active   \n",
       "8               earthquake          hazard  active   \n",
       "9                    flood          hazard  active   \n",
       "12                    hail          hazard  active   \n",
       "7       relative_cropyield          hazard  active   \n",
       "3              river_flood          hazard  active   \n",
       "5             storm_europe          hazard  active   \n",
       "1         tropical_cyclone          hazard  active   \n",
       "2                 wildfire          hazard  active   \n",
       "11       hail_damage_crops          impact  active   \n",
       "\n",
       "                                          description  \\\n",
       "6                                                None   \n",
       "4   Historical and twenty-first century crop produ...   \n",
       "10  Crop exposure for Switzerland in 2021 obtained...   \n",
       "0   A global high-resolution asset exposure datase...   \n",
       "13  Global probabilistic coastal flood maps for ba...   \n",
       "8   Earthquake hazard sets at 150 arcsec (ca. 4km)...   \n",
       "9   Flood footprint of historical events at a 200m...   \n",
       "12  Radar-based daily hail hazard data at 1km spat...   \n",
       "7   Historical and twenty-first century crop produ...   \n",
       "3   River flood [flood depth in meters and flooded...   \n",
       "5   European winter storm [gust in meters per seco...   \n",
       "1   Tropical cyclone wind footprints (m/s) at 150 ...   \n",
       "2   Global wildfire dataset at 4km resolution, bas...   \n",
       "11  Hail damage to crops for 10-12 hail days (depe...   \n",
       "\n",
       "                                           properties  \\\n",
       "6   [{'property': 'res_arcsec_land', 'mandatory': ...   \n",
       "4   [{'property': 'crop', 'mandatory': True, 'desc...   \n",
       "10  [{'property': 'crop', 'mandatory': True, 'desc...   \n",
       "0   [{'property': 'spatial_coverage', 'mandatory':...   \n",
       "13  [{'property': 'climate_scenario', 'mandatory':...   \n",
       "8   [{'property': 'res_arcsec', 'mandatory': True,...   \n",
       "9   [{'property': 'date_creation', 'mandatory': Tr...   \n",
       "12  [{'property': 'variable', 'mandatory': True, '...   \n",
       "7   [{'property': 'climate_scenario', 'mandatory':...   \n",
       "3   [{'property': 'res_arcsec', 'mandatory': True,...   \n",
       "5   [{'property': 'data_source', 'mandatory': Fals...   \n",
       "1   [{'property': 'spatial_coverage', 'mandatory':...   \n",
       "2   [{'property': 'res_arcsec', 'mandatory': True,...   \n",
       "11  [{'property': 'crop', 'mandatory': True, 'desc...   \n",
       "\n",
       "                                        key_reference  \\\n",
       "6                                                  []   \n",
       "4   [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "10  [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "0   [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "13  [{'ref_no': 1, 'ref_url': 'https://www.wri.org...   \n",
       "8   [{'ref_no': 1, 'ref_url': None, 'key_reference...   \n",
       "9                                                  []   \n",
       "12  [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "7   [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "3   [{'ref_no': 1, 'ref_url': 'https://www.nature....   \n",
       "5   [{'ref_no': 1, 'ref_url': 'https://www.nat-haz...   \n",
       "1   [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "2   [{'ref_no': 1, 'ref_url': 'https://gmd.coperni...   \n",
       "11  [{'ref_no': 1, 'ref_url': 'https://doi.org/10....   \n",
       "\n",
       "                                        version_notes  \n",
       "6                                                  []  \n",
       "4                                                  []  \n",
       "10                                                 []  \n",
       "0   [{'version': 'v2', 'notes': 'Countries with no...  \n",
       "13                                                 []  \n",
       "8                                                  []  \n",
       "9                                                  []  \n",
       "12                                                 []  \n",
       "7                                                  []  \n",
       "3   [{'version': 'v2', 'notes': 'Higher resolution...  \n",
       "5                                                  []  \n",
       "1   [{'version': 'v2', 'notes': 'Higher resolution...  \n",
       "2                                                  []  \n",
       "11                                                 []  "
      ]
     },
     "execution_count": 2,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "import pandas as pd\n",
    "\n",
    "data_types = client.list_data_type_infos()\n",
    "\n",
    "dtf = pd.DataFrame(data_types)\n",
    "dtf.sort_values([\"data_type_group\", \"data_type\"])"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Datasets and Properties\n",
    "For each data type, the single datasets can be differentiated based on properties. The following function provides a table listing the properties and possible values. This table does not provide information on properties that can be combined but the search can be refined in order to find properties to query a unique dataset. Note that a maximum of 10 property values are shown here, but many more countries are available for example."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 3,
   "metadata": {},
   "outputs": [],
   "source": [
    "litpop_dataset_infos = client.list_dataset_infos(data_type=\"litpop\")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 4,
   "metadata": {},
   "outputs": [],
   "source": [
    "all_properties = client.get_property_values(litpop_dataset_infos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 5,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "dict_keys(['res_arcsec', 'exponents', 'fin_mode', 'spatial_coverage', 'country_iso3alpha', 'country_name', 'country_iso3num'])"
      ]
     },
     "execution_count": 5,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "all_properties.keys()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Refining the search:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 6,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'res_arcsec': ['150'],\n",
       " 'exponents': ['(0,1)', '(1,1)', '(3,0)'],\n",
       " 'fin_mode': ['pop', 'pc'],\n",
       " 'spatial_coverage': ['global']}"
      ]
     },
     "execution_count": 6,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# as datasets are usually available per country, chosing a country or global dataset reduces the options\n",
    "# here we want to see which datasets are available for litpop globally:\n",
    "client.get_property_values(\n",
    "    litpop_dataset_infos, known_property_values={\"spatial_coverage\": \"global\"}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 7,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'res_arcsec': ['150'],\n",
       " 'exponents': ['(3,0)', '(0,1)', '(1,1)'],\n",
       " 'fin_mode': ['pc', 'pop'],\n",
       " 'spatial_coverage': ['country'],\n",
       " 'country_iso3alpha': ['CHE'],\n",
       " 'country_name': ['Switzerland'],\n",
       " 'country_iso3num': ['756']}"
      ]
     },
     "execution_count": 7,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# and here for Switzerland:\n",
    "client.get_property_values(\n",
    "    litpop_dataset_infos, known_property_values={\"country_name\": \"Switzerland\"}\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Basic impact calculation\n",
    "We here show how to make a basic impact calculation with tropical cyclones for Haiti, for the year 2040, rcp4.5  and generated with 10 synthetic tracks. For more technical details on the API, see below.\n",
    "\n"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Wrapper functions to open datasets as CLIMADA objects"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The wrapper functions client.get_hazard() \n",
    "gets the dataset information, downloads the data and opens it as a hazard instance\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 8,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'res_arcsec': ['150'],\n",
       " 'event_type': ['synthetic', 'observed'],\n",
       " 'model_name': ['random_walk', 'STORM'],\n",
       " 'spatial_coverage': ['country'],\n",
       " 'climate_scenario': ['rcp26', 'rcp45', 'None', 'rcp60', 'rcp85'],\n",
       " 'ref_year': ['2040', '2060', '2080'],\n",
       " 'country_iso3alpha': ['HTI'],\n",
       " 'country_name': ['Haiti'],\n",
       " 'country_iso3num': ['332'],\n",
       " 'gcm': ['CMCC-CM2-VHR4', 'CNRM-CM6-1-HR', 'EC-Earth3P-HR', 'HadGEM3-GC31-HM']}"
      ]
     },
     "execution_count": 8,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "tc_dataset_infos = client.list_dataset_infos(data_type=\"tropical_cyclone\")\n",
    "client.get_property_values(\n",
    "    tc_dataset_infos, known_property_values={\"country_name\": \"Haiti\"}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 9,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-07-11 11:19:49,740 - climada.hazard.io - INFO - Reading C:\\Users\\timschmi\\climada\\data\\hazard\\tropical_cyclone\\tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040\\v2.1\\tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040.hdf5\n"
     ]
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x1300 with 2 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "client = Client()\n",
    "tc_haiti = client.get_hazard(\n",
    "    \"tropical_cyclone\",\n",
    "    properties={\n",
    "        \"country_name\": \"Haiti\",\n",
    "        \"climate_scenario\": \"rcp45\",\n",
    "        \"ref_year\": \"2040\",\n",
    "        # \"nb_synth_tracks\": \"10\",\n",
    "    },\n",
    ")\n",
    "tc_haiti.plot_intensity(0);"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### The wrapper functions client.get_litpop() \n",
    "gets the default litpop, with exponents (1,1) and 'produced capital' as financial mode. If no country is given, the global dataset will be downloaded."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 22,
   "metadata": {},
   "outputs": [],
   "source": [
    "litpop_default = client.get_property_values(\n",
    "    litpop_dataset_infos, known_property_values={\"fin_mode\": \"pc\", \"exponents\": \"(1,1)\"}\n",
    ")"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 23,
   "metadata": {
    "scrolled": true
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-07-04 14:36:24,838 - climada.entity.exposures.base - INFO - Reading C:\\Users\\timschmi\\climada\\data\\exposures\\litpop\\LitPop_150arcsec_HTI\\v3\\LitPop_150arcsec_HTI.hdf5\n"
     ]
    }
   ],
   "source": [
    "litpop = client.get_litpop(country=\"Haiti\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Get the default impact function for tropical cyclones"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 24,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 640x480 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "from climada.entity.impact_funcs import ImpactFuncSet, ImpfTropCyclone\n",
    "\n",
    "imp_fun = ImpfTropCyclone.from_emanuel_usa()\n",
    "imp_fun.check()\n",
    "imp_fun.plot()\n",
    "\n",
    "imp_fun_set = ImpactFuncSet([imp_fun])\n",
    "\n",
    "litpop.impact_funcs = imp_fun_set"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Calculate the impact"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 25,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-07-04 14:36:34,432 - climada.entity.exposures.base - INFO - No specific impact function column found for hazard TC. Using the anonymous 'impf_' column.\n",
      "2025-07-04 14:36:34,432 - climada.entity.exposures.base - INFO - Matching 1329 exposures with 1332 centroids.\n",
      "2025-07-04 14:36:34,432 - climada.util.coordinates - INFO - No exact centroid match found. Reprojecting coordinates to nearest neighbor closer than the threshold = 100\n",
      "2025-07-04 14:36:34,432 - climada.engine.impact_calc - INFO - Calculating impact for 3987 assets (>0) and 43560 events.\n"
     ]
    }
   ],
   "source": [
    "from climada.engine import ImpactCalc\n",
    "\n",
    "impact = ImpactCalc(litpop, imp_fun_set, tc_haiti).impact()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Getting other Exposures"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 26,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "{'crop': ['whe', 'soy', 'ric', 'mai'],\n",
       " 'irrigation_status': ['noirr', 'firr'],\n",
       " 'unit': ['USD', 'Tonnes'],\n",
       " 'spatial_coverage': ['global']}"
      ]
     },
     "execution_count": 26,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "crop_dataset_infos = client.list_dataset_infos(data_type=\"crop_production\")\n",
    "\n",
    "client.get_property_values(crop_dataset_infos)"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 27,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "2025-07-04 14:36:49,797 - climada.entity.exposures.base - INFO - Reading C:\\Users\\timschmi\\climada\\data\\exposures\\crop_production\\crop_production_ric-noirr_spamray-mirca_USD\\v1\\crop_production_ric-noirr_spamray-mirca_USD.hdf5\n"
     ]
    }
   ],
   "source": [
    "rice_exposure = client.get_exposures(\n",
    "    exposures_type=\"crop_production\",\n",
    "    properties={\"crop\": \"ric\", \"unit\": \"USD\", \"irrigation_status\": \"noirr\"},\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Getting base centroids to generate new hazard files"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 28,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<GeoAxes: >"
      ]
     },
     "execution_count": 28,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x1300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "centroids = client.get_centroids()\n",
    "centroids.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "By default the latitude extent is limited to [-60,60], which is sufficient for many hazards and will reduce the computational ressources required. If a complete latitude extent [-90,90] or a smaller extent is desired, it can be specified with the `extent` keyword agrument.\n",
    "\n"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 34,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "<GeoAxes: >"
      ]
     },
     "execution_count": 34,
     "metadata": {},
     "output_type": "execute_result"
    },
    {
     "data": {
      "image/png": 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",
      "text/plain": [
       "<Figure size 900x1300 with 1 Axes>"
      ]
     },
     "metadata": {},
     "output_type": "display_data"
    }
   ],
   "source": [
    "centroids_complete = client.get_centroids(extent=[-180, 180, -90, 90])\n",
    "centroids_complete.plot()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "centroids are also available per country:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 35,
   "metadata": {},
   "outputs": [],
   "source": [
    "centroids_hti = client.get_centroids(country=\"HTI\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "## Technical Information\n",
    "\n",
    "For programmatical access to the CLIMADA data API there is a specific REST call wrapper class: `climada.util.client.Client`."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Server\n",
    "The CLIMADA data file server is hosted on https://data.iac.ethz.ch that can be accessed via a REST API at https://climada.ethz.ch.\n",
    "For REST API details, see the [documentation](https://climada.ethz.ch/rest/docs)."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "### Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 36,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mInit signature:\u001b[39m Client(cache_enabled=\u001b[38;5;28;01mNone\u001b[39;00m)\n",
      "\u001b[31mDocstring:\u001b[39m      Python wrapper around REST calls to the CLIMADA data API server.\n",
      "\u001b[31mInit docstring:\u001b[39m\n",
      "Constructor of Client.\n",
      "\n",
      "Data API host and chunk_size (for download) are configurable values.\n",
      "Default values are 'climada.ethz.ch' and 8096 respectively.\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "cache_enabled : bool, optional\n",
      "    This flag controls whether the api calls of this client are going to be cached to the\n",
      "    local file system (location defined by CONFIG.data_api.cache_dir).\n",
      "    If set to true, the client can reload the results from the cache in case there is no\n",
      "    internet connection and thus work in offline mode.\n",
      "    Default: None, in this case the value is taken from CONFIG.data_api.cache_enabled.\n",
      "\u001b[31mFile:\u001b[39m           c:\\users\\timschmi\\documents\\phd\\code\\climada_python\\climada\\util\\api_client.py\n",
      "\u001b[31mType:\u001b[39m           type\n",
      "\u001b[31mSubclasses:\u001b[39m     "
     ]
    }
   ],
   "source": [
    "?Client"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 37,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "8192"
      ]
     },
     "execution_count": 37,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client = Client()\n",
    "client.chunk_size"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "The url to the API server and the chunk size for the file download can be configured in 'climada.conf'. Just replace the corresponding default values:\n",
    "\n",
    "```json\n",
    "    \"data_api\": {\n",
    "        \"host\": \"https://climada.ethz.ch\",\n",
    "        \"chunk_size\": 8192,\n",
    "        \"cache_db\": \"{local_data.system}/.downloads.db\"\n",
    "    }\n",
    "```\n",
    "\n",
    "The other configuration value affecting the data_api client, `cache_db`, is the path to an SQLite database file, which is keeping track of the files that are successfully downloaded from the api server. Before the Client attempts to download any file from the server, it checks whether the file has been downloaded before and if so, whether the previously downloaded file still looks good (i.e., size and time stamp are as expected). If all of this is the case, the file is simply read from disk without submitting another request."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Metadata\n",
    "\n",
    "#### Unique Identifiers\n",
    "Any dataset can be identified with **data_type**, **name** and **version**. The combination of the three is unique in the API servers' underlying database.\n",
    "However, sometimes the name is already enough for identification.\n",
    "All datasets have a UUID, a universally unique identifier, which is part of their individual url. \n",
    "E.g., the uuid of the dataset https://climada.ethz.ch/rest/dataset/b1c76120-4e60-4d8f-99c0-7e1e7b7860ec is \"b1c76120-4e60-4d8f-99c0-7e1e7b7860ec\".\n",
    "One can retrieve their meta data by:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 38,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "DatasetInfo(uuid='b1c76120-4e60-4d8f-99c0-7e1e7b7860ec', data_type=DataTypeShortInfo(data_type='litpop', data_type_group='exposures'), name='LitPop_assets_pc_150arcsec_SGS', version='v1', status='expired', properties={'res_arcsec': '150', 'exponents': '(3,0)', 'fin_mode': 'pc', 'spatial_coverage': 'country', 'date_creation': '2021-09-23', 'climada_version': 'v2.2.0', 'country_iso3alpha': 'SGS', 'country_name': 'South Georgia and the South Sandwich Islands', 'country_iso3num': '239'}, files=[FileInfo(uuid='b1c76120-4e60-4d8f-99c0-7e1e7b7860ec', url='https://data.iac.ethz.ch/climada/b1c76120-4e60-4d8f-99c0-7e1e7b7860ec/LitPop_assets_pc_150arcsec_SGS.hdf5', file_name='LitPop_assets_pc_150arcsec_SGS.hdf5', file_format='hdf5', file_size=1086488, check_sum='md5:27bc1846362227350495e3d946dfad5e')], doi=None, description=\"LitPop asset value exposure per country: Gridded physical asset values by country, at a resolution of 150 arcsec. Values are total produced capital values disaggregated proportionally to the cube of nightlight intensity (Lit^3, based on NASA Earth at Night). The following values were used as parameters in the LitPop.from_countries() method:{'total_values': 'None', 'admin1_calc': 'False','reference_year': '2018', 'gpw_version': '4.11'}Reference: Eberenz et al., 2020. https://doi.org/10.5194/essd-12-817-2020\", license='Attribution 4.0 International (CC-BY-4.0)', activation_date='2021-09-13 09:08:28.358559+00:00', expiration_date='2022-06-27 14:35:55.203081+00:00')"
      ]
     },
     "execution_count": 38,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "client.get_dataset_info_by_uuid(\"b1c76120-4e60-4d8f-99c0-7e1e7b7860ec\")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "or by filtering:"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Data Set Status\n",
    "The datasets of climada.ethz.ch may have the following stati:\n",
    "- **active**: the default for real life data\n",
    "- **preliminary**: when the dataset is already uploaded but some information or file is still missing\n",
    "- **expired**: when a dataset is inactivated again\n",
    "- **test_dataset**: data sets that are used in unit or integration tests have this status in order to be taken seriously by accident\n",
    "When collecting a list of datasets with `get_datasets`, the default dataset status will be 'active'. With the argument `status=None` this filter can be turned off."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### DatasetInfo Objects and DataFrames\n",
    "\n",
    "As stated above `get_dataset` (or `get_dataset_by_uuid`) return a `DatasetInfo` object and `get_datasets` a list thereof."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 39,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mInit signature:\u001b[39m\n",
      "DatasetInfo(\n",
      "    uuid: str,\n",
      "    data_type: climada.util.api_client.DataTypeShortInfo,\n",
      "    name: str,\n",
      "    version: str,\n",
      "    status: str,\n",
      "    properties: dict,\n",
      "    files: list,\n",
      "    doi: str,\n",
      "    description: str,\n",
      "    license: str,\n",
      "    activation_date: str,\n",
      "    expiration_date: str,\n",
      ") -> \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "\u001b[31mDocstring:\u001b[39m      dataset data from CLIMADA data API.\n",
      "\u001b[31mFile:\u001b[39m           c:\\users\\timschmi\\documents\\phd\\code\\climada_python\\climada\\util\\api_client.py\n",
      "\u001b[31mType:\u001b[39m           type\n",
      "\u001b[31mSubclasses:\u001b[39m     "
     ]
    }
   ],
   "source": [
    "from climada.util.api_client import DatasetInfo\n",
    "\n",
    "?DatasetInfo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "where files is a list of `FileInfo` objects:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 40,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mInit signature:\u001b[39m\n",
      "FileInfo(\n",
      "    uuid: str,\n",
      "    url: str,\n",
      "    file_name: str,\n",
      "    file_format: str,\n",
      "    file_size: int,\n",
      "    check_sum: str,\n",
      ") -> \u001b[38;5;28;01mNone\u001b[39;00m\n",
      "\u001b[31mDocstring:\u001b[39m      file data from CLIMADA data API.\n",
      "\u001b[31mFile:\u001b[39m           c:\\users\\timschmi\\documents\\phd\\code\\climada_python\\climada\\util\\api_client.py\n",
      "\u001b[31mType:\u001b[39m           type\n",
      "\u001b[31mSubclasses:\u001b[39m     "
     ]
    }
   ],
   "source": [
    "from climada.util.api_client import FileInfo\n",
    "\n",
    "?FileInfo"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Convert into DataFrame\n",
    "There is a conveinience function to easily convert dataset lists into pandas DataFrames, `into_datasets_df`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 41,
   "metadata": {},
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mSignature:\u001b[39m client.into_datasets_df(dataset_infos)\n",
      "\u001b[31mDocstring:\u001b[39m\n",
      "Convenience function providing a DataFrame of datasets with properties.\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "dataset_infos : list of DatasetInfo\n",
      "     as returned by list_dataset_infos\n",
      "\n",
      "Returns\n",
      "-------\n",
      "pandas.DataFrame\n",
      "    of datasets with properties as found in query by arguments\n",
      "\u001b[31mFile:\u001b[39m      c:\\users\\timschmi\\documents\\phd\\code\\climada_python\\climada\\util\\api_client.py\n",
      "\u001b[31mType:\u001b[39m      function"
     ]
    }
   ],
   "source": [
    "?client.into_datasets_df"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 42,
   "metadata": {},
   "outputs": [
    {
     "data": {
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         "name": "data_type_group",
         "rawType": "object",
         "type": "string"
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         "name": "uuid",
         "rawType": "object",
         "type": "string"
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         "name": "name",
         "rawType": "object",
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         "name": "version",
         "rawType": "object",
         "type": "string"
        },
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         "name": "status",
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         "name": "doi",
         "rawType": "object",
         "type": "unknown"
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         "name": "description",
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         "type": "string"
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         "name": "license",
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         "name": "res_arcsec",
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         "v3",
         "active",
         null,
         "LitPop asset value exposure per country: Gridded physical asset values by country, at a resolution of 150 arcsec. Values are total produced capital values disaggregated proportionally to the cube of nightlight intensity (Lit^3, based on NASA Earth at Night). The following values were used as parameters in the LitPop.from_countries() method:{'total_values': 'None', 'admin1_calc': 'False','reference_year': '2018', 'gpw_version': '4.11'}Reference: Eberenz et al., 2020. https://doi.org/10.5194/essd-12-817-2020",
         "Attribution 4.0 International (CC-BY-4.0)",
         "2024-06-07 08:21:45.775654+00:00",
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         "active",
         null,
         "LitPop population exposure per country: Gridded population count by country, at a resolution of 150 arcsec,based on Gridded Population of the World, Version 4.1.{'total_values': 'None', 'admin1_calc': 'False','reference_year': '2018', 'gpw_version': '4.11'}Reference: Eberenz et al., 2020. https://doi.org/10.5194/essd-12-817-2020",
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         "v3",
         "active",
         null,
         "LitPop asset value exposure per country: Gridded physical asset values by country, at a resolution of 150 arcsec. Values are total produced capital values disaggregated proportionally to the normalised product of nightlight intensity (Lit, based on NASA Earth at Night) and population count (Pop, based on Gridded Population of the World, Version 4.1). {'total_values': 'None', 'admin1_calc': 'False','reference_year': '2018', 'gpw_version': '4.11'}Reference: Eberenz et al., 2020. https://doi.org/10.5194/essd-12-817-2020",
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      "text/html": [
       "<div>\n",
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       "\n",
       "    .dataframe tbody tr th {\n",
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       "\n",
       "    .dataframe thead th {\n",
       "        text-align: right;\n",
       "    }\n",
       "</style>\n",
       "<table border=\"1\" class=\"dataframe\">\n",
       "  <thead>\n",
       "    <tr style=\"text-align: right;\">\n",
       "      <th></th>\n",
       "      <th>data_type</th>\n",
       "      <th>data_type_group</th>\n",
       "      <th>uuid</th>\n",
       "      <th>name</th>\n",
       "      <th>version</th>\n",
       "      <th>status</th>\n",
       "      <th>doi</th>\n",
       "      <th>description</th>\n",
       "      <th>license</th>\n",
       "      <th>activation_date</th>\n",
       "      <th>expiration_date</th>\n",
       "      <th>res_arcsec</th>\n",
       "      <th>exponents</th>\n",
       "      <th>fin_mode</th>\n",
       "      <th>spatial_coverage</th>\n",
       "      <th>climada_version</th>\n",
       "      <th>date_creation</th>\n",
       "      <th>country_iso3alpha</th>\n",
       "      <th>country_name</th>\n",
       "      <th>country_iso3num</th>\n",
       "    </tr>\n",
       "  </thead>\n",
       "  <tbody>\n",
       "    <tr>\n",
       "      <th>0</th>\n",
       "      <td>litpop</td>\n",
       "      <td>exposures</td>\n",
       "      <td>5a3e72fb-a8e0-48b5-b2ec-d6d9b845b687</td>\n",
       "      <td>LitPop_assets_pc_150arcsec_DEU</td>\n",
       "      <td>v3</td>\n",
       "      <td>active</td>\n",
       "      <td>None</td>\n",
       "      <td>LitPop asset value exposure per country: Gridd...</td>\n",
       "      <td>Attribution 4.0 International (CC-BY-4.0)</td>\n",
       "      <td>2024-06-07 08:21:45.775654+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>150</td>\n",
       "      <td>(3,0)</td>\n",
       "      <td>pc</td>\n",
       "      <td>country</td>\n",
       "      <td>v4.1.1 (v3.1.2)</td>\n",
       "      <td>2022-6-30</td>\n",
       "      <td>DEU</td>\n",
       "      <td>Germany</td>\n",
       "      <td>276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>1</th>\n",
       "      <td>litpop</td>\n",
       "      <td>exposures</td>\n",
       "      <td>552ce473-953f-44db-9504-0bf078ba7cb7</td>\n",
       "      <td>LitPop_pop_150arcsec_DEU</td>\n",
       "      <td>v3</td>\n",
       "      <td>active</td>\n",
       "      <td>None</td>\n",
       "      <td>LitPop population exposure per country: Gridde...</td>\n",
       "      <td>Attribution 4.0 International (CC-BY-4.0)</td>\n",
       "      <td>2024-06-07 08:21:51.998009+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>150</td>\n",
       "      <td>(0,1)</td>\n",
       "      <td>pop</td>\n",
       "      <td>country</td>\n",
       "      <td>v4.1.1 (v3.1.2)</td>\n",
       "      <td>2022-6-30</td>\n",
       "      <td>DEU</td>\n",
       "      <td>Germany</td>\n",
       "      <td>276</td>\n",
       "    </tr>\n",
       "    <tr>\n",
       "      <th>2</th>\n",
       "      <td>litpop</td>\n",
       "      <td>exposures</td>\n",
       "      <td>ca0b1390-0ccc-4bac-8867-c6f9c0ef7703</td>\n",
       "      <td>LitPop_150arcsec_DEU</td>\n",
       "      <td>v3</td>\n",
       "      <td>active</td>\n",
       "      <td>None</td>\n",
       "      <td>LitPop asset value exposure per country: Gridd...</td>\n",
       "      <td>Attribution 4.0 International (CC-BY-4.0)</td>\n",
       "      <td>2024-06-07 08:21:55.563907+00:00</td>\n",
       "      <td>None</td>\n",
       "      <td>150</td>\n",
       "      <td>(1,1)</td>\n",
       "      <td>pc</td>\n",
       "      <td>country</td>\n",
       "      <td>v4.1.1 (v3.1.2)</td>\n",
       "      <td>2022-6-26</td>\n",
       "      <td>DEU</td>\n",
       "      <td>Germany</td>\n",
       "      <td>276</td>\n",
       "    </tr>\n",
       "  </tbody>\n",
       "</table>\n",
       "</div>"
      ],
      "text/plain": [
       "  data_type data_type_group                                  uuid  \\\n",
       "0    litpop       exposures  5a3e72fb-a8e0-48b5-b2ec-d6d9b845b687   \n",
       "1    litpop       exposures  552ce473-953f-44db-9504-0bf078ba7cb7   \n",
       "2    litpop       exposures  ca0b1390-0ccc-4bac-8867-c6f9c0ef7703   \n",
       "\n",
       "                             name version  status   doi  \\\n",
       "0  LitPop_assets_pc_150arcsec_DEU      v3  active  None   \n",
       "1        LitPop_pop_150arcsec_DEU      v3  active  None   \n",
       "2            LitPop_150arcsec_DEU      v3  active  None   \n",
       "\n",
       "                                         description  \\\n",
       "0  LitPop asset value exposure per country: Gridd...   \n",
       "1  LitPop population exposure per country: Gridde...   \n",
       "2  LitPop asset value exposure per country: Gridd...   \n",
       "\n",
       "                                     license  \\\n",
       "0  Attribution 4.0 International (CC-BY-4.0)   \n",
       "1  Attribution 4.0 International (CC-BY-4.0)   \n",
       "2  Attribution 4.0 International (CC-BY-4.0)   \n",
       "\n",
       "                    activation_date expiration_date res_arcsec exponents  \\\n",
       "0  2024-06-07 08:21:45.775654+00:00            None        150     (3,0)   \n",
       "1  2024-06-07 08:21:51.998009+00:00            None        150     (0,1)   \n",
       "2  2024-06-07 08:21:55.563907+00:00            None        150     (1,1)   \n",
       "\n",
       "  fin_mode spatial_coverage  climada_version date_creation country_iso3alpha  \\\n",
       "0       pc          country  v4.1.1 (v3.1.2)     2022-6-30               DEU   \n",
       "1      pop          country  v4.1.1 (v3.1.2)     2022-6-30               DEU   \n",
       "2       pc          country  v4.1.1 (v3.1.2)     2022-6-26               DEU   \n",
       "\n",
       "  country_name country_iso3num  \n",
       "0      Germany             276  \n",
       "1      Germany             276  \n",
       "2      Germany             276  "
      ]
     },
     "execution_count": 42,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from climada.util.api_client import Client\n",
    "\n",
    "client = Client()\n",
    "litpop_datasets = client.list_dataset_infos(\n",
    "    data_type=\"litpop\",\n",
    "    properties={\"country_name\": \"Germany\"},\n",
    ")\n",
    "litpop_df = client.into_datasets_df(litpop_datasets)\n",
    "litpop_df"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Download\n",
    "\n",
    "The wrapper functions `get_exposures` or `get_hazard` fetch the information, download the file and opens the file as a climada object. But one can also just download dataset files using the method `download_dataset` which takes a `DatasetInfo` object as argument and downloads all files of the dataset to a directory in the local file system."
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 43,
   "metadata": {
    "tags": []
   },
   "outputs": [
    {
     "name": "stdout",
     "output_type": "stream",
     "text": [
      "\u001b[31mSignature:\u001b[39m\n",
      "client.download_dataset(\n",
      "    dataset,\n",
      "    target_dir=WindowsPath(\u001b[33m'C:/Users/timschmi/climada/data'\u001b[39m),\n",
      "    organize_path=\u001b[38;5;28;01mTrue\u001b[39;00m,\n",
      ")\n",
      "\u001b[31mDocstring:\u001b[39m\n",
      "Download all files from a given dataset to a given directory.\n",
      "\n",
      "Parameters\n",
      "----------\n",
      "dataset : DatasetInfo\n",
      "    the dataset\n",
      "target_dir : Path, optional\n",
      "    target directory for download, by default `climada.util.constants.SYSTEM_DIR`\n",
      "organize_path: bool, optional\n",
      "    if set to True the files will end up in subdirectories of target_dir:\n",
      "    [target_dir]/[data_type_group]/[data_type]/[name]/[version]\n",
      "    by default True\n",
      "\n",
      "Returns\n",
      "-------\n",
      "download_dir : Path\n",
      "    the path to the directory containing the downloaded files,\n",
      "    will be created if organize_path is True\n",
      "downloaded_files : list of Path\n",
      "    the downloaded files themselves\n",
      "\n",
      "Raises\n",
      "------\n",
      "Exception\n",
      "    when one of the files cannot be downloaded\n",
      "\u001b[31mFile:\u001b[39m      c:\\users\\timschmi\\documents\\phd\\code\\climada_python\\climada\\util\\api_client.py\n",
      "\u001b[31mType:\u001b[39m      method"
     ]
    }
   ],
   "source": [
    "?client.download_dataset"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "#### Cache\n",
    "The method avoids superfluous downloads by keeping track of all downloads in a sqlite db file. The client will make sure that the same file is never downloaded to the same target twice.\n",
    "\n",
    "#### Examples"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 44,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(WindowsPath('C:/Users/timschmi/climada/data/exposures/litpop/LitPop_assets_pc_150arcsec_DEU/v3/LitPop_assets_pc_150arcsec_DEU.hdf5'),\n",
       " True)"
      ]
     },
     "execution_count": 44,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Let's have a look at an example for downloading a litpop dataset first\n",
    "ds = litpop_datasets[\n",
    "    0\n",
    "]  # litpop_datasets is a list and download_dataset expects a single object as argument.\n",
    "download_dir, ds_files = client.download_dataset(ds)\n",
    "ds_files[0], ds_files[0].is_file()"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 45,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "(WindowsPath('C:/Users/timschmi/climada/data/hazard/tropical_cyclone/tropical_cyclone_10synth_tracks_150arcsec_rcp26_global_2040/v2.1/tropical_cyclone_10synth_tracks_150arcsec_rcp26_global_2040.hdf5'),\n",
       " True)"
      ]
     },
     "execution_count": 45,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "# Another example for downloading a hazard (tropical cyclone) dataset\n",
    "ds_tc = tc_dataset_infos[0]\n",
    "download_dir, ds_files = client.download_dataset(ds_tc)\n",
    "ds_files[0], ds_files[0].is_file()"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "If the dataset contains only one file (which is most commonly the case) this file can also be downloaded and accessed in a single step, using the `get_dataset_file` method:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 46,
   "metadata": {},
   "outputs": [
    {
     "data": {
      "text/plain": [
       "WindowsPath('C:/Users/timschmi/climada/data/exposures/litpop/LitPop_pop_150arcsec_SGS/v3/LitPop_pop_150arcsec_SGS.hdf5')"
      ]
     },
     "execution_count": 46,
     "metadata": {},
     "output_type": "execute_result"
    }
   ],
   "source": [
    "from climada.util.api_client import Client\n",
    "\n",
    "Client().get_dataset_file(\n",
    "    data_type=\"litpop\",\n",
    "    properties={\n",
    "        \"country_name\": \"South Georgia and the South Sandwich Islands\",\n",
    "        \"fin_mode\": \"pop\",\n",
    "    },\n",
    ")"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "#### Local File Cache\n",
    "\n",
    "By default, the API Client downloads files into the `~/climada/data` directory.\n",
    "\n",
    "In the course of time obsolete files may be accumulated within this directory, because there is a newer version of these files available from the [CLIMADA data API](https://climada.ethz.ch), or because the according dataset got expired altogether.\\\n",
    "To prevent file rot and free disk space, it's possible to remove all outdated files at once, by simply calling `Client().purge_cache()`. This will remove all files that were ever downloaded with the `api_client.Client` and for which a newer version exists, even when the newer version has not been downloaded yet."
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {
    "tags": []
   },
   "source": [
    "### Offline Mode\n",
    "\n",
    "The API Client is silently used in many methods and functions of CLIMADA, including the installation test that is run to see whether the CLIMADA installation was successful.\n",
    "Most methods of the client send GET requests to the API server assuming the latter is accessible through a working internet connection.\n",
    "If this is not the case, the functionality of CLIMADA is severely limited if not altogether lost. Often this is an unnecessary restriction, \n",
    "e.g., when a user wants to access a file through the API Client that is already downloaded and available in the local filesystem.\n",
    "\n",
    "In such cases the API Client runs in _offline mode_.\n",
    "In this mode the client falls back to previous results for the same call in case there is no internet connection or the server is not accessible.\n",
    "\n",
    "To turn this feature off and make sure that all results are current and up to date - at the cost of failing when there is no internet connection - one has to disable tha _cache_.\n",
    "This can be done programmatically, by initializing the API Client with the optional argument `cache_enabled`:"
   ]
  },
  {
   "cell_type": "code",
   "execution_count": 47,
   "metadata": {},
   "outputs": [],
   "source": [
    "client = Client(cache_enabled=False)"
   ]
  },
  {
   "cell_type": "markdown",
   "metadata": {},
   "source": [
    "Or it can be done through configuration. Edit the `climada.conf` file in the working directory or in ~/climada/ and change the \"cache_enabled\" value, like this:\n",
    "\n",
    "```javascript\n",
    "...\n",
    "    \"data_api\": {\n",
    "        ...\n",
    "        \"cache_enabled\": false\n",
    "    },\n",
    "...\n",
    "```\n",
    "\n",
    "While `cache_enabled` is `true` (default), every result from the server is stored as a json file in ~/climada/data/.apicache/ by a unique name derived from the method and arguments of the call.\n",
    "If the very same call is made again later, at a time where the server is not accessible, the client just comes back to the cached result from the previous call."
   ]
  }
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