-
Notifications
You must be signed in to change notification settings - Fork 0
/
uriToData.py
126 lines (103 loc) · 4.42 KB
/
uriToData.py
1
2
3
4
5
6
7
8
9
10
11
12
13
14
15
16
17
18
19
20
21
22
23
24
25
26
27
28
29
30
31
32
33
34
35
36
37
38
39
40
41
42
43
44
45
46
47
48
49
50
51
52
53
54
55
56
57
58
59
60
61
62
63
64
65
66
67
68
69
70
71
72
73
74
75
76
77
78
79
80
81
82
83
84
85
86
87
88
89
90
91
92
93
94
95
96
97
98
99
100
101
102
103
104
105
106
107
108
109
110
111
112
113
114
115
116
117
118
119
120
121
122
123
124
125
126
# import requests
# import pandas as pd
# from concurrent.futures import ThreadPoolExecutor, as_completed
# MAX_THREADS = 100
# def fetch_boris_info(id):
# endpoint = f"https://boris.unibe.ch/cgi/search/advanced/export_BORIS_JSON.js?screen=Search&_action_export=1&output=JSON&exp=0%7C1%7C-date%2Fcreators_name%2Ftitle%7Carchive%7C-%7Ceprintid%3Aeprintid%3AANY%3AEQ%3A{id}%7C-%7Ceprint_status%3Aeprint_status%3AANY%3AEQ%3Aarchive%7Cmetadata_visibility%3Ametadata_visibility%3AANY%3AEQ%3Ashow&n="
# try:
# response = requests.get(endpoint + str(id))
# if response.status_code == 200:
# data = response.json()
# return data
# else:
# return []
# except Exception as e:
# print(f"Error fetching data for id {id}: {e}")
# return []
# def process_uri(uri):
# try:
# id = uri.split("/")[-1]
# boris_info = fetch_boris_info(id)
# if boris_info:
# retdata = {
# "uri": uri,
# "date": str(boris_info[0].get("date"))[:4],
# "creators": f"{boris_info[0]['creators'][0]['name']['given']} {boris_info[0]['creators'][0]['name']['family']}",
# "full_text_status": boris_info[0].get("full_text_status"),
# "title": boris_info[0]['title'][0]['text'],
# "divisions": boris_info[0].get("divisions", [])[0]
# }
# print(retdata)
# return retdata
# except Exception as e:
# print(f"Error processing uri {uri}: {e}")
# return None
# def main():
# input_csv = "uri.csv"
# output_csv = "publicationRecord.csv"
# df = pd.read_csv(input_csv)
# uri_list = df["uri"].tolist()
# records = []
# with ThreadPoolExecutor(max_workers=MAX_THREADS) as executor:
# futures = [executor.submit(process_uri, uri) for uri in uri_list]
# for future in as_completed(futures):
# record = future.result()
# if record:
# records.append(record)
# output_df = pd.DataFrame(records)
# output_df.to_csv(output_csv, index=False)
# print(f"Processed BORIS info saved to {output_csv}")
# if __name__ == "__main__":
# main()
import requests
import pandas as pd
from concurrent.futures import ThreadPoolExecutor, as_completed
MAX_THREADS = 100
def fetch_boris_info(id):
endpoint = f"https://boris.unibe.ch/cgi/search/advanced/export_BORIS_JSON.js?screen=Search&_action_export=1&output=JSON&exp=0%7C1%7C-date%2Fcreators_name%2Ftitle%7Carchive%7C-%7Ceprintid%3Aeprintid%3AANY%3AEQ%3A{id}%7C-%7Ceprint_status%3Aeprint_status%3AANY%3AEQ%3Aarchive%7Cmetadata_visibility%3Ametadata_visibility%3AANY%3AEQ%3Ashow&n="
try:
response = requests.get(endpoint + str(id))
if response.status_code == 200:
data = response.json()
return data
else:
return []
except Exception as e:
print(f"Error fetching data for id {id}: {e}")
return []
def process_uri(uri, institute):
try:
id = uri.split("/")[-1]
boris_info = fetch_boris_info(id)
if boris_info:
retdata = {
"uri": uri,
"institute": institute,
"date": str(boris_info[0].get("date"))[:4],
"creators": f"{boris_info[0]['creators'][0]['name']['given']} {boris_info[0]['creators'][0]['name']['family']}",
"full_text_status": boris_info[0].get("full_text_status"),
"title": boris_info[0]['title'][0]['text'],
"divisions": boris_info[0].get("divisions", [])[0]
}
print(retdata)
return retdata
except Exception as e:
print(f"Error processing uri {uri}: {e}")
return None
def main():
input_csv = "uri.csv"
output_csv = "publicationRecord.csv"
df = pd.read_csv(input_csv)
uri_institute_pairs = df[["uri", "institute"]].values.tolist()
records = []
with ThreadPoolExecutor(max_workers=MAX_THREADS) as executor:
futures = [executor.submit(process_uri, uri, institute) for uri, institute in uri_institute_pairs]
for future in as_completed(futures):
record = future.result()
if record:
records.append(record)
output_df = pd.DataFrame(records)
output_df.to_csv(output_csv, index=False)
print(f"Processed BORIS info saved to {output_csv}")
if __name__ == "__main__":
main()