Delete utils/ndc_explorer.py

utils/ndc_explorer.py

@@ -1,90 +0,0 @@
-
-import urllib.request
-import json
-
-link = "https://klimalog.die-gdi.de/ndc/open-data/dataset.json"
-def get_document(country_code: str):
-    """
-    read the country NDC data from 
-    https://klimalog.die-gdi.de/ndc/open-data/dataset.json 
-    using the country code.
-    
-    Params
-    -------
-    country_code:"""
-    with urllib.request.urlopen(link) as urlfile:
-        data =  json.loads(urlfile.read())
-    categoriesData = {}
-    categoriesData['categories']= data['categories']
-    categoriesData['subcategories']= data['subcategories']
-    keys_sub = categoriesData['subcategories'].keys()
-    documentType= 'NDCs'
-    if documentType in data.keys():
-        if country_code in data[documentType].keys():
-            get_dict = {}
-            for key, value in data[documentType][country_code].items():
-                if key not in ['country_name','region_id', 'region_name']:
-                    get_dict[key] = value['classification']
-                else:
-                    get_dict[key] = value
-        else:
-            return None
-    else:
-        return None
-
-    country = {}
-    for key in categoriesData['categories']:
-        country[key]= {}
-    for key,value in categoriesData['subcategories'].items():
-        country[value['category']][key] = get_dict[key]
-    
-    return country
-        
-            
-def countrySpecificCCA(cca_sent:dict, threshold:int, countryCode:str):
-    """
-    based on the countrycode, reads the country data from
-    https://klimalog.die-gdi.de/ndc/open-data/dataset.json
-    using get_documents from utils.ndc_explorer.py
-    then based on thereshold value filters the Climate Change Adaptation
-    targets assigned by NDC explorer team to that country. Using the sentences
-    create by Data services team of GIZ for each target level, tries to find the
-    relevant passages from the document by doing the semantic search.
-
-    Params
-    -------
-    cca_sent: dictionary with key as 'target labels' and manufactured sentences 
-    reflecting the target level. Please see the docStore/ndcs/cca.txt
-
-    threshold: NDC target have many categoriees ranging from [0-5], with 0 
-    refelcting most relaxed attitude and 5 being most aggrisive towards Climate 
-    change. We select the threshold value beyond which we need to focus on.
-
-    countryCode: standard country code to allow us to fetch the country specific
-    data.
-
-    """
-    temp = {}
-    doc = get_document(countryCode)
-    for key,value in cca_sent.items():
-        id_ = doc['climate change adaptation'][key]['id']
-        if id_ >threshold:
-            temp[key] = value['id'][id_]
-    return temp
-
-                
-def countrySpecificCCM(ccm_sent, threshold, countryCode):
-    """
-    see the documentation of countrySpecificCCA. This is same instead of 
-    this gets the data pertaining to Adaptation
-    
-    """
-
-    temp = {}
-    doc = get_document(countryCode)
-    for key,value in ccm_sent.items():
-        id_ = doc['climate change mitigation'][key]['id']
-        if id_ >threshold:
-            temp[key] = value['id'][id_]
-    
-    return temp