def find_species(url, species_data):
content = retrieve_document(url, 'content')
for link in content.iterlinks():
element, attribute, tgt = link[:-1]
# looking for links containing the word *species* in their target url
match = re.search("".join(("\/", species_suffix, "\/")), tgt)
if match is not None:
# retrieving species name
sp_name = element.text
#print "<<<", len(species_data), ">>>"
if species_data.has_key(sp_name):
species = species_data[sp_name]
print "\tSpecies '%s' already in database..." % sp_name
else:
spf = SpeciesFinder(sp_name)
species = spf.find_species()
if not species is None and species.is_plant():
species.print_species_data()
species_data[sp_name] = species
def find_species(url, species_data):
content = retrieve_document(url, 'content')
for link in content.iterlinks():
element, attribute, tgt = link[:-1]
# looking for links containing the word *species* in their target url
match = re.search("".join(("\/", species_suffix, "\/")), tgt)
if match is not None:
# retrieving species name
sp_name = element.text
#print "<<<", len(species_data), ">>>"
if species_data.has_key(sp_name):
species = species_data[sp_name]
print "\tSpecies '%s' already in database..." % sp_name
else:
spf = SpeciesFinder(sp_name)
species = spf.find_species()
if not species is None and species.is_plant():
species.print_species_data()
species_data[sp_name] = species
new_df_tokens.append('plot')
new_df_tokens.append('x')
new_df_tokens.append('y')
for token in df_tokens:
if translate_dict.has_key(token):
new_df_tokens.append(translate_dict[token])
else:
match = re.search(df_sp_regex, token)
if not match:
print "Couldn't match species name... %s" % token
else:
if uh_to_df_species.has_key(token):
new_df_token = uh_to_df_species[token]
else:
spf = SpeciesFinder()
spf.set_search_name(token)
sr = spf.search_on_eunis()
(sp_name, sp_type, sp_url), ratio = spf.find_best_match(sr)
found = sp_name
if token == found.replace(" ", ""):
new_df_token = found.replace(" ", "_")
else:
print "Couldn't find new species name for '%s'... Please re-check!" % token
new_df_token = token
new_df_tokens.append(new_df_token)
uh = dict()
uh[2009] = list()
uh[2011] = list()
output.append("\t".join((str(i), ht, str(species.species_id))))
i += 1
print "\n".join(output)
#print species.species_id, species.name, habitat_types
import sys
sys.exit()
spf = SpeciesFinder()
output = list()
for line in lines[:]:
species, habitat_types = line.strip().split("\t")
habitat_types = habitat_types.split("/")
print species, habitat_types
spf.set_search_name(species)
spf.find_species()
spf.get_species_data()
url = spf.species.urls['eunis.eea.europa.eu']
sp_id = int(url.split("/")[-1])
basic_info = "\t".join((str(sp_id), spf.species.name, url, spf.species.author))
taxonomic_info = list()
habitat_types = habitat_types.split("/")
#print species, habitat_types
species = DbSpecies().find(species_name)
for ht in habitat_types:
output.append("\t".join((str(i), ht, str(species.species_id))))
i += 1
print "\n".join(output)
#print species.species_id, species.name, habitat_types
import sys
sys.exit()
spf = SpeciesFinder()
output = list()
for line in lines[:]:
species, habitat_types = line.strip().split("\t")
habitat_types = habitat_types.split("/")
print species, habitat_types
spf.set_search_name(species)
spf.find_species()
spf.get_species_data()
url = spf.species.urls['eunis.eea.europa.eu']
sp_id = int(url.split("/")[-1])
basic_info = "\t".join(
(str(sp_id), spf.species.name, url, spf.species.author))
# adding found information to habitat object
hab.set_description(description)
hab.set_administrative_area(nuts_code)
hab.set_region(region)
hab.set_size(size)
hab.set_url(hab_url)
hab.set_geometry(src_ft)
# retrieving available habitat types and species
for link in contents.iterlinks():
if link[0].find_class('linkint'):
key = link[0].text_content().encode('utf-8')
if not len(key) == 4:
spf = SpeciesFinder(key)
sp = spf.find_species(True)
if sp is not None and sp.is_plant():
hab.species.append(sp)
else:
hab.habitat_types.append(habitat_types[key])
# adding found habitat types to habitat object
habitats[sitecode] = hab
pickle.dump(habitats, open(hab_area_pkl_tgt, 'wb'))
hab.print_habitat_data()
print "==============================================================="
# saving found habitat data in pickle file
print "Dumping habitat area data to %s..." % hab_area_pkl_tgt,
