{
"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.\n",
"\n",
"## Contents\n",
"\n",
"- [Finding Datasets](#Finding-datasets)\n",
" - [Data types and data type groups](#Data-types-and-data-type-groups)\n",
" - [Datasets and Properties](#Datasets-and-Properties)\n",
"- [Basic impact calculation](#Basic-impact-calculation)\n",
" - [Wrapper functions to open datasets as CLIMADA objects](#Wrapper-functions-to-open-datasets-as-CLIMADA-objects)\n",
" - [Calculate the impact](#Calculate-the-impact)\n",
"- [Technical Information](#Technical-Information)\n",
" - [Server](#Server)\n",
" - [Client](#Client)\n",
" - [Metadata](#Metadata)\n",
" - [Download](#Download)"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"## Finding datasets"
]
},
{
"cell_type": "code",
"execution_count": 3,
"metadata": {},
"outputs": [],
"source": [
"from climada.util.api_client import Client\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": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
data_type
\n",
"
data_type_group
\n",
"
status
\n",
"
description
\n",
"
properties
\n",
"
\n",
" \n",
" \n",
"
\n",
"
3
\n",
"
crop_production
\n",
"
exposures
\n",
"
active
\n",
"
None
\n",
"
[{'property': 'crop', 'mandatory': True, 'desc...
\n",
"
\n",
"
\n",
"
0
\n",
"
litpop
\n",
"
exposures
\n",
"
active
\n",
"
None
\n",
"
[{'property': 'res_arcsec', 'mandatory': False...
\n",
"
\n",
"
\n",
"
5
\n",
"
centroids
\n",
"
hazard
\n",
"
active
\n",
"
None
\n",
"
[]
\n",
"
\n",
"
\n",
"
2
\n",
"
river_flood
\n",
"
hazard
\n",
"
active
\n",
"
None
\n",
"
[{'property': 'res_arcsec', 'mandatory': False...
\n",
"
\n",
"
\n",
"
4
\n",
"
storm_europe
\n",
"
hazard
\n",
"
active
\n",
"
None
\n",
"
[{'property': 'country_iso3alpha', 'mandatory'...
\n",
"
\n",
"
\n",
"
1
\n",
"
tropical_cyclone
\n",
"
hazard
\n",
"
active
\n",
"
None
\n",
"
[{'property': 'res_arcsec', 'mandatory': True,...
\n",
"
\n",
" \n",
"
\n",
"
"
],
"text/plain": [
" data_type data_type_group status description \\\n",
"3 crop_production exposures active None \n",
"0 litpop exposures active None \n",
"5 centroids hazard active None \n",
"2 river_flood hazard active None \n",
"4 storm_europe hazard active None \n",
"1 tropical_cyclone hazard active None \n",
"\n",
" properties \n",
"3 [{'property': 'crop', 'mandatory': True, 'desc... \n",
"0 [{'property': 'res_arcsec', 'mandatory': False... \n",
"5 [] \n",
"2 [{'property': 'res_arcsec', 'mandatory': False... \n",
"4 [{'property': 'country_iso3alpha', 'mandatory'... \n",
"1 [{'property': 'res_arcsec', 'mandatory': True,... "
]
},
"execution_count": 2,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"import pandas as pd\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(litpop_dataset_infos, known_property_values = {'spatial_coverage':'global'})"
]
},
{
"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(litpop_dataset_infos, known_property_values = {'country_name':'Switzerland'})"
]
},
{
"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",
" 'climate_scenario': ['rcp26', 'rcp45', 'rcp85', 'historical', 'rcp60'],\n",
" 'ref_year': ['2040', '2060', '2080'],\n",
" 'nb_synth_tracks': ['50', '10'],\n",
" 'spatial_coverage': ['country'],\n",
" 'tracks_year_range': ['1980_2020'],\n",
" 'country_iso3alpha': ['HTI'],\n",
" 'country_name': ['Haiti'],\n",
" 'country_iso3num': ['332'],\n",
" 'resolution': ['150 arcsec']}"
]
},
"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(tc_dataset_infos, known_property_values = {'country_name':'Haiti'})"
]
},
{
"cell_type": "code",
"execution_count": 4,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"https://climada.ethz.ch/data-api/v1/dataset\tclimate_scenario=rcp45\tcountry_name=Haiti\tdata_type=tropical_cyclone\tlimit=100000\tname=None\tnb_synth_tracks=10\tref_year=2040\tstatus=active\tversion=None\n",
"2022-07-01 15:55:23,593 - climada.util.api_client - WARNING - Download failed: /Users/szelie/climada/data/hazard/tropical_cyclone/tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040/v1/tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040.hdf5 has the wrong size:8189651 instead of 7781902, retrying...\n",
"2022-07-01 15:55:26,786 - climada.hazard.base - INFO - Reading /Users/szelie/climada/data/hazard/tropical_cyclone/tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040/v1/tropical_cyclone_10synth_tracks_150arcsec_rcp45_HTI_2040.hdf5\n",
"2022-07-01 15:55:27,129 - climada.util.plot - WARNING - Error parsing coordinate system 'GEOGCRS[\"WGS 84\",ENSEMBLE[\"World Geodetic System 1984 ensemble\",MEMBER[\"World Geodetic System 1984 (Transit)\"],MEMBER[\"World Geodetic System 1984 (G730)\"],MEMBER[\"World Geodetic System 1984 (G873)\"],MEMBER[\"World Geodetic System 1984 (G1150)\"],MEMBER[\"World Geodetic System 1984 (G1674)\"],MEMBER[\"World Geodetic System 1984 (G1762)\"],ELLIPSOID[\"WGS 84\",6378137,298.257223563,LENGTHUNIT[\"metre\",1]],ENSEMBLEACCURACY[2.0]],PRIMEM[\"Greenwich\",0,ANGLEUNIT[\"degree\",0.0174532925199433]],CS[ellipsoidal,2],AXIS[\"geodetic latitude (Lat)\",north,ORDER[1],ANGLEUNIT[\"degree\",0.0174532925199433]],AXIS[\"geodetic longitude (Lon)\",east,ORDER[2],ANGLEUNIT[\"degree\",0.0174532925199433]],USAGE[SCOPE[\"Horizontal component of 3D system.\"],AREA[\"World.\"],BBOX[-90,-180,90,180]],ID[\"EPSG\",4326]]'. Using projection PlateCarree in plot.\n"
]
},
{
"data": {
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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"client = Client()\n",
"tc_haiti = client.get_hazard('tropical_cyclone', properties={'country_name': 'Haiti', 'climate_scenario': 'rcp45', 'ref_year':'2040', 'nb_synth_tracks':'10'})\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": 10,
"metadata": {},
"outputs": [],
"source": [
"litpop_default = client.get_property_values(litpop_dataset_infos, known_property_values = {'fin_mode':'pc', 'exponents':'(1,1)'})"
]
},
{
"cell_type": "code",
"execution_count": 5,
"metadata": {
"scrolled": true
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"https://climada.ethz.ch/data-api/v1/dataset\tcountry_name=Haiti\tdata_type=litpop\texponents=(1,1)\tlimit=100000\tname=None\tstatus=active\tversion=None\n",
"2022-07-01 15:55:31,047 - climada.entity.exposures.base - INFO - Reading /Users/szelie/climada/data/exposures/litpop/LitPop_150arcsec_HTI/v1/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": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"2022-01-31 22:30:21,359 - climada.entity.impact_funcs.base - WARNING - For intensity = 0, mdd != 0 or paa != 0. Consider shifting the origin of the intensity scale. In impact.calc the impact is always null at intensity = 0.\n"
]
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"centroids = client.get_centroids()\n",
"centroids.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"For many hazards, limiting the latitude extent to [-60,60] is sufficient and will reduce the computational ressources required"
]
},
{
"cell_type": "code",
"execution_count": 12,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"https://climada.ethz.ch/data-api/v1/dataset\tdata_type=centroids\textent=(-180, 180, -90, 90)\tlimit=100000\tname=None\tres_arcsec_land=150\tres_arcsec_ocean=1800\tstatus=active\tversion=None\n",
"2022-07-01 15:59:27,602 - climada.hazard.centroids.centr - INFO - Reading /Users/szelie/climada/data/centroids/earth_centroids_150asland_1800asoceans_distcoast_regions/v1/earth_centroids_150asland_1800asoceans_distcoast_region.hdf5\n",
"2022-07-01 15:59:29,255 - climada.util.plot - WARNING - Error parsing coordinate system 'GEOGCRS[\"WGS 84\",ENSEMBLE[\"World Geodetic System 1984 ensemble\",MEMBER[\"World Geodetic System 1984 (Transit)\"],MEMBER[\"World Geodetic System 1984 (G730)\"],MEMBER[\"World Geodetic System 1984 (G873)\"],MEMBER[\"World Geodetic System 1984 (G1150)\"],MEMBER[\"World Geodetic System 1984 (G1674)\"],MEMBER[\"World Geodetic System 1984 (G1762)\"],MEMBER[\"World Geodetic System 1984 (G2139)\"],ELLIPSOID[\"WGS 84\",6378137,298.257223563,LENGTHUNIT[\"metre\",1]],ENSEMBLEACCURACY[2.0]],PRIMEM[\"Greenwich\",0,ANGLEUNIT[\"degree\",0.0174532925199433]],CS[ellipsoidal,2],AXIS[\"geodetic latitude (Lat)\",north,ORDER[1],ANGLEUNIT[\"degree\",0.0174532925199433]],AXIS[\"geodetic longitude (Lon)\",east,ORDER[2],ANGLEUNIT[\"degree\",0.0174532925199433]],USAGE[SCOPE[\"Horizontal component of 3D system.\"],AREA[\"World.\"],BBOX[-90,-180,90,180]],ID[\"EPSG\",4326]]'. Using projection PlateCarree in plot.\n"
]
},
{
"data": {
"text/plain": [
""
]
},
"execution_count": 12,
"metadata": {},
"output_type": "execute_result"
},
{
"data": {
"image/png": 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\n",
"text/plain": [
"
"
]
},
"metadata": {
"needs_background": "light"
},
"output_type": "display_data"
}
],
"source": [
"centroids_nopoles = client.get_centroids(extent=[-180,180,-60,50])\n",
"centroids_nopoles.plot()"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"centroids are also available per country:"
]
},
{
"cell_type": "code",
"execution_count": 18,
"metadata": {
"scrolled": false
},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"https://climada.ethz.ch/data-api/v1/dataset\tdata_type=centroids\textent=(-180, 180, -90, 90)\tlimit=100000\tname=None\tres_arcsec_land=150\tres_arcsec_ocean=1800\tstatus=active\tversion=None\n",
"2022-07-01 16:01:24,328 - climada.hazard.centroids.centr - INFO - Reading /Users/szelie/climada/data/centroids/earth_centroids_150asland_1800asoceans_distcoast_regions/v1/earth_centroids_150asland_1800asoceans_distcoast_region.hdf5\n"
]
}
],
"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": 16,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[1;31mInit signature:\u001b[0m \u001b[0mClient\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mDocstring:\u001b[0m \n",
"Python wrapper around REST calls to the CLIMADA data API server.\n",
" \n",
"\u001b[1;31mInit docstring:\u001b[0m\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",
"\u001b[1;31mFile:\u001b[0m c:\\users\\me\\polybox\\workshop\\climada_python\\climada\\util\\api_client.py\n",
"\u001b[1;31mType:\u001b[0m type\n",
"\u001b[1;31mSubclasses:\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"Client?"
]
},
{
"cell_type": "code",
"execution_count": 17,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"8192"
]
},
"execution_count": 17,
"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": 18,
"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='active', 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=None)"
]
},
"execution_count": 18,
"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": 19,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[1;31mInit signature:\u001b[0m\n",
"\u001b[0mDatasetInfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0muuid\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mdata_type\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mclimada\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mutil\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mapi_client\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mDataTypeShortInfo\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mname\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mversion\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mstatus\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mproperties\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mdict\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mfiles\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mlist\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mdoi\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mdescription\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mlicense\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mactivation_date\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mexpiration_date\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mDocstring:\u001b[0m dataset data from CLIMADA data API.\n",
"\u001b[1;31mFile:\u001b[0m c:\\users\\me\\polybox\\workshop\\climada_python\\climada\\util\\api_client.py\n",
"\u001b[1;31mType:\u001b[0m type\n",
"\u001b[1;31mSubclasses:\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from climada.util.api_client import DatasetInfo\n",
"DatasetInfo?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"where files is a list of `FileInfo` objects:"
]
},
{
"cell_type": "code",
"execution_count": 20,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[1;31mInit signature:\u001b[0m\n",
"\u001b[0mFileInfo\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0muuid\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0murl\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mfile_name\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mfile_format\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mfile_size\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mint\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mcheck_sum\u001b[0m\u001b[1;33m:\u001b[0m \u001b[0mstr\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m\u001b[1;33m)\u001b[0m \u001b[1;33m->\u001b[0m \u001b[1;32mNone\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mDocstring:\u001b[0m file data from CLIMADA data API.\n",
"\u001b[1;31mFile:\u001b[0m c:\\users\\me\\polybox\\workshop\\climada_python\\climada\\util\\api_client.py\n",
"\u001b[1;31mType:\u001b[0m type\n",
"\u001b[1;31mSubclasses:\u001b[0m \n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"from climada.util.api_client import FileInfo\n",
"FileInfo?"
]
},
{
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Convert into DataFrame\n",
"There are conveinience functions to easily convert datasets into pandas DataFrames, `get_datasets` and `expand_files`:"
]
},
{
"cell_type": "code",
"execution_count": 21,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[1;31mSignature:\u001b[0m \u001b[0mclient\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0minto_datasets_df\u001b[0m\u001b[1;33m(\u001b[0m\u001b[0mdataset_infos\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mDocstring:\u001b[0m\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[1;31mFile:\u001b[0m c:\\users\\me\\polybox\\workshop\\climada_python\\climada\\util\\api_client.py\n",
"\u001b[1;31mType:\u001b[0m function\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"source": [
"client.into_datasets_df?"
]
},
{
"cell_type": "code",
"execution_count": 22,
"metadata": {},
"outputs": [
{
"data": {
"text/html": [
"
\n",
"\n",
"
\n",
" \n",
"
\n",
"
\n",
"
data_type
\n",
"
data_type_group
\n",
"
uuid
\n",
"
name
\n",
"
version
\n",
"
status
\n",
"
doi
\n",
"
description
\n",
"
license
\n",
"
activation_date
\n",
"
expiration_date
\n",
"
res_arcsec
\n",
"
exponents
\n",
"
fin_mode
\n",
"
spatial_coverage
\n",
"
date_creation
\n",
"
climada_version
\n",
"
country_iso3alpha
\n",
"
country_name
\n",
"
country_iso3num
\n",
"
\n",
" \n",
" \n",
"
\n",
"
0
\n",
"
litpop
\n",
"
exposures
\n",
"
b1c76120-4e60-4d8f-99c0-7e1e7b7860ec
\n",
"
LitPop_assets_pc_150arcsec_SGS
\n",
"
v1
\n",
"
active
\n",
"
None
\n",
"
LitPop asset value exposure per country: Gridd...
\n",
"
Attribution 4.0 International (CC BY 4.0)
\n",
"
2021-09-13 09:08:28.358559+00:00
\n",
"
None
\n",
"
150
\n",
"
(3,0)
\n",
"
pc
\n",
"
country
\n",
"
2021-09-23
\n",
"
v2.2.0
\n",
"
SGS
\n",
"
South Georgia and the South Sandwich Islands
\n",
"
239
\n",
"
\n",
"
\n",
"
1
\n",
"
litpop
\n",
"
exposures
\n",
"
3d516897-5f87-46e6-b673-9e6c00d110ec
\n",
"
LitPop_pop_150arcsec_SGS
\n",
"
v1
\n",
"
active
\n",
"
None
\n",
"
LitPop population exposure per country: Gridde...
\n",
"
Attribution 4.0 International (CC BY 4.0)
\n",
"
2021-09-13 09:09:10.634374+00:00
\n",
"
None
\n",
"
150
\n",
"
(0,1)
\n",
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pop
\n",
"
country
\n",
"
2021-09-23
\n",
"
v2.2.0
\n",
"
SGS
\n",
"
South Georgia and the South Sandwich Islands
\n",
"
239
\n",
"
\n",
"
\n",
"
2
\n",
"
litpop
\n",
"
exposures
\n",
"
a6864a65-36a2-4701-91bc-81b1355103b5
\n",
"
LitPop_150arcsec_SGS
\n",
"
v1
\n",
"
active
\n",
"
None
\n",
"
LitPop asset value exposure per country: Gridd...
\n",
"
Attribution 4.0 International (CC BY 4.0)
\n",
"
2021-09-13 09:09:30.907938+00:00
\n",
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None
\n",
"
150
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(1,1)
\n",
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pc
\n",
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\n",
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2021-09-23
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v2.2.0
\n",
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SGS
\n",
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South Georgia and the South Sandwich Islands
\n",
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239
\n",
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\n",
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\n",
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],
"text/plain": [
" data_type data_type_group uuid \\\n",
"0 litpop exposures b1c76120-4e60-4d8f-99c0-7e1e7b7860ec \n",
"1 litpop exposures 3d516897-5f87-46e6-b673-9e6c00d110ec \n",
"2 litpop exposures a6864a65-36a2-4701-91bc-81b1355103b5 \n",
"\n",
" name version status doi \\\n",
"0 LitPop_assets_pc_150arcsec_SGS v1 active None \n",
"1 LitPop_pop_150arcsec_SGS v1 active None \n",
"2 LitPop_150arcsec_SGS v1 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 2021-09-13 09:08:28.358559+00:00 None 150 (3,0) \n",
"1 2021-09-13 09:09:10.634374+00:00 None 150 (0,1) \n",
"2 2021-09-13 09:09:30.907938+00:00 None 150 (1,1) \n",
"\n",
" fin_mode spatial_coverage date_creation climada_version country_iso3alpha \\\n",
"0 pc country 2021-09-23 v2.2.0 SGS \n",
"1 pop country 2021-09-23 v2.2.0 SGS \n",
"2 pc country 2021-09-23 v2.2.0 SGS \n",
"\n",
" country_name country_iso3num \n",
"0 South Georgia and the South Sandwich Islands 239 \n",
"1 South Georgia and the South Sandwich Islands 239 \n",
"2 South Georgia and the South Sandwich Islands 239 "
]
},
"execution_count": 22,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"from climada.util.api_client import Client\n",
"client = Client()\n",
"litpop_datasets = client.list_dataset_infos(data_type='litpop', properties={'country_name': 'South Georgia and the South Sandwich Islands'})\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": 23,
"metadata": {
"tags": []
},
"outputs": [
{
"data": {
"text/plain": [
"\u001b[1;31mSignature:\u001b[0m\n",
"\u001b[0mclient\u001b[0m\u001b[1;33m.\u001b[0m\u001b[0mdownload_dataset\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mdataset\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0mtarget_dir\u001b[0m\u001b[1;33m=\u001b[0m\u001b[0mWindowsPath\u001b[0m\u001b[1;33m(\u001b[0m\u001b[1;34m'C:/Users/me/climada/data'\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m \u001b[0morganize_path\u001b[0m\u001b[1;33m=\u001b[0m\u001b[1;32mTrue\u001b[0m\u001b[1;33m,\u001b[0m\u001b[1;33m\n",
"\u001b[0m\u001b[1;33m)\u001b[0m\u001b[1;33m\u001b[0m\u001b[1;33m\u001b[0m\u001b[0m\n",
"\u001b[1;31mDocstring:\u001b[0m\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[1;31mFile:\u001b[0m c:\\users\\me\\polybox\\workshop\\climada_python\\climada\\util\\api_client.py\n",
"\u001b[1;31mType:\u001b[0m method\n"
]
},
"metadata": {},
"output_type": "display_data"
}
],
"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": 24,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(WindowsPath('C:/Users/me/climada/data/exposures/litpop/LitPop_assets_pc_150arcsec_SGS/v1/LitPop_assets_pc_150arcsec_SGS.hdf5'),\n",
" True)"
]
},
"execution_count": 24,
"metadata": {},
"output_type": "execute_result"
}
],
"source": [
"# Let's have a look at an example for downloading a litpop dataset first\n",
"ds = litpop_datasets[0] # 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": 8,
"metadata": {},
"outputs": [
{
"data": {
"text/plain": [
"(PosixPath('/home/yuyue/climada/data/hazard/tropical_cyclone/tropical_cyclone_50synth_tracks_150arcsec_rcp26_BRA_2040/v1/tropical_cyclone_50synth_tracks_150arcsec_rcp26_BRA_2040.hdf5'),\n",
" True)"
]
},
"execution_count": 8,
"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": {
"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": null,
"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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