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Solve the following problem using Python, implementing the functions described below, one line at a time
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Description:
 def ensembl_to_kegg(organism,kegg_db):
 """ Looks up KEGG mappings of KEGG ids to ensembl ids :param organism: an organisms as listed in organismsKEGG() :param kegg_db: a matching KEGG db as reported in databasesKEGG :returns: a Pandas dataframe of with 'KEGGid' and 'ENSid'. """

    print("KEGG API: http://rest.genome.jp/link/"+kegg_db+"/"+organism)
    sys.stdout.flush()
    kegg_ens=urlopen("http://rest.genome.jp/link/"+kegg_db+"/"+organism).read()
    kegg_ens=kegg_ens.split("\n")
    final=[]
    for i in kegg_ens:
        final.append(i.split("\t"))
    df=pd.DataFrame(final[0:len(final)-1])[[0,1]]
    ens_id=pd.DataFrame(df[1].str.split(":").tolist())[1]
    df=pd.concat([df,ens_id],axis=1)
    df.columns=['KEGGid','ensDB','ENSid']
    df=df[['KEGGid','ENSid']]
    return df