Update code for merging author data by API

This commit is contained in:
Chenxiao Xia 2023-10-09 23:24:58 +08:00
parent 9b33cbabe7
commit 193581cd6a
5 changed files with 186 additions and 67 deletions

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@ -31,8 +31,10 @@ def Division(folder_path):
# Division into 27 files according to the first alpha, # Division into 27 files according to the first alpha,
for Dict in data: for Dict in data:
if Dict.get('last_name') is not None and len(Dict.get('last_name')[0].lower()) < 2 and \ # print(Dict.get('last_name'))
97 <= ord(Dict.get('last_name')[0].lower()) <= 122: # print(len(Dict.get('last_name')[0].lower()))
if Dict.get('last_name') is not None and Dict.get('last_name') != "" and \
len(Dict.get('last_name')[0].lower()) < 2 and 97 <= ord(Dict.get('last_name')[0].lower()) <= 122:
num = ord(Dict.get('last_name')[0].lower()) - 96 num = ord(Dict.get('last_name')[0].lower()) - 96
list[num].append(Dict) list[num].append(Dict)
@ -55,7 +57,7 @@ def Division(folder_path):
Transf(Read(folder_path)) Transf(Read(folder_path))
# ========== Test code ========== # ========== Test code ==========
# Division('./test_buffer/Author_output') Division('./test_buffer/Author_output')

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@ -250,17 +250,18 @@ def SameWeb_merge(folder_path):
print(str(len(temp_list)) + ' copies of incomplete merged data have been added to temporary list\n') print(str(len(temp_list)) + ' copies of incomplete merged data have been added to temporary list\n')
st = time.time() # Start time # Bert model merge
# st = time.time() # Start time
if len(temp_list) > 1: #
executor = ThreadPoolExecutor(max_workers=10) # Thread pool # if len(temp_list) > 1:
futures = [executor.submit(Similarity_merge, temp_list[i]) for i in range(len(temp_list))] # executor = ThreadPoolExecutor(max_workers=10) # Thread pool
for future in as_completed(futures): # futures = [executor.submit(Similarity_merge, temp_list[i]) for i in range(len(temp_list))]
pass # for future in as_completed(futures):
wait(futures) # pass
# wait(futures)
et = time.time() # End time #
print('\nThread pool has been run for ' + str(et-st) + 's') # et = time.time() # End time
# print('\nThread pool has been run for ' + str(et-st) + 's')
# Combine Data with temp_list # Combine Data with temp_list
for i in temp_list: for i in temp_list:
@ -308,7 +309,7 @@ def SameWeb_merge(folder_path):
# =========== input the file path here ========== # =========== input the file path here ==========
# SameWeb_merge('.\EJQTDE\EJQTDE_buffer\Author_output') # SameWeb_merge('.\EJQTDE\EJQTDE_buffer\Author_output')
# SameWeb_merge('.\SpringerOpen\SpringerOpen_buffer\Author_output') # SameWeb_merge('.\SpringerOpen\SpringerOpen_buffer\Author_output')
SameWeb_merge('.\ejde\ejde_buffer\Author_output') # SameWeb_merge('.\ejde\ejde_buffer\Author_output')
SameWeb_merge('.\\nameDivision\\1')

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@ -0,0 +1,132 @@
import json
import os
def SameWeb_merge(folder_path):
# Function
def SameName_merge(i, count1, count2, Data, ml):
# Same name merge
for j in range(i + 1, len(Data)):
if j < len(Data):
a = Data[i]
aa = Data[j]
if isinstance(a, dict) and isinstance(aa, dict):
if len(a['from_article']) == 1 and len(aa['from_article']) == 1:
if a.get("first_name") == aa.get("first_name") and a.get("middle_name") == aa.get(
"middle_name") and a.get("last_name") == aa.get("last_name"):
if a['from_article'] == aa['from_article']: # Remove same data
Data.remove(Data[j])
count2[0] += 1
return SameName_merge(i, count1, count2, Data, ml)
else:
ml.append(aa)
# Update the counter
count1[0] += 1
if count1[0] % 100 == 0 and count1[0] != 0:
print(str(count1[0]) + ' copies of data have been merged by same name.')
# Delete extra elements
Data.remove(Data[j])
return SameName_merge(i, count1, count2, Data, ml)
if len(ml) > 0:
ml.append(Data[i]) # Add first element
Data.remove(Data[i])
ml = sorted(ml, key=lambda x: x.get('affiliation')[0].get('year')) # Sorted by year
# Add into Data list
if len(ml) == 1:
Data.insert(-1, ml[0])
else:
Data.insert(-1, ml)
# ========== Main code ==========
Data = [] # List of all data
count1 = [0] # Same name merged data counter
count2 = [0] # Duplicate data counter
num1 = 0 # Unique data counter
num2 = 0 # Complete merged data counter
num3 = 0 # Incomplete merged data counter
# Add data into list
for num_folder in os.listdir(folder_path):
num_folder_path = os.path.join(folder_path, num_folder)
for filename in os.listdir(num_folder_path):
if filename.endswith('.json'):
file_path = os.path.join(num_folder_path, filename)
with open(file_path, 'r', encoding='utf-8') as file:
data = json.load(file)
if len(data) > 0:
Data.extend(data)
Database = len(Data) # The length of the original data
Data = sorted(Data, key=lambda x: x['affiliation'][0]['year'])
# ========== Merge ==========
# ----- Same name data merge -----
ml = []
if len(Data) > 1:
for i in range(len(Data)):
ml.clear()
SameName_merge(i, count1, count2, Data, ml)
print('\n----- Same name data merge complete -----\n')
# ----- Similarity algorithm merge -----
# Change the index of incomplete data before other data
temp_list = [] # Temp list for incomplete merged data
if len(Data) > 1:
for i in range(len(Data) - 1, -1, -1):
if isinstance(Data[i], list):
temp = Data[i]
Data.remove(Data[i])
temp_list.append(temp)
print(str(len(temp_list)) + ' copies of incomplete merged data have been added to temporary list\n')
print('\n----- Similarity algorithm merge complete -----\n')
# ========== Statistic data ==========
# Data counter update
for a in Data:
if isinstance(a, dict) and len(a['from_article']) == 1:
num1 += 1
elif isinstance(a, dict) and len(a['from_article']) > 1:
num2 += 1
else:
num3 += 1
# Information
print('\n========== Complete ==========\n')
print(str(Database) + ' copies of data in total, before')
print(str(count1[0]) + ' copies of data have been merged by same name.')
print(str(count2[0]) + ' copies of duplicate data have been deleted')
print(str(len(Data)) + ' copies of data in total, now.\n')
print(str(num1) + ' copies of data are unique.')
print(str(num3) + ' copies of data are incomplete merged')
# Save into file
path = os.path.dirname(folder_path) # parent path
path = os.path.join(path, "Author_data(merged)")
os.makedirs(path, exist_ok=True)
path = os.path.join(path, "Author_data(merged).json")
with open(path, 'w', encoding='utf-8') as file:
json.dump(temp_list, file, indent=4)
print('\nData has been added to ' + path)
# =========== input the file path here ==========
SameWeb_merge('.\\nameDivision')

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@ -1,87 +1,71 @@
import os import os
import json import json
from pprint import pprint
''' '''
========== fileReader ========= ========== fileReader =========
1. 本程序用于读取作者信息 json 文件中不包含 email 的数据 1. 本程序用于读取作者信息后获取来源文章的标题并且将其存储到新的字典当中
2. 通过检索作者信息获取 author_id from_article并且返回作者信息中检索来源文章的 title 2. 通过检索作者信息获取 author_id from_article并且返回作者信息中检索来源文章的 title
author_id title 作为一个字典存储到待处理的列表 ar_list 作者信息和标题一并存储到新字典
3. ar_list 作为结果返回 3. 新字典存储到 json 文件中
''' '''
# Function to find the author data which does not have "email" information # Function to find the author data which does not have "email" information
def Read(author_path, article_path): def Read(author_path, article_path):
# Read data list # Read data list
def au_read(path, file_names, list): def au_read(path, list):
for file_name in file_names: with open(path, 'r', encoding='utf-8') as file:
file_path = os.path.join(path, file_name)
with open(file_path, 'r', encoding='utf-8') as file:
data = json.load(file) data = json.load(file)
for Dict in range(len(data)-1, -1, -1): for Dict in range(len(data)-1, -1, -1):
if data[Dict].get('affiliation', [{}])[0].get('email', 0) is None:
list.append(data[Dict]) list.append(data[Dict])
# del data[Dict]
return list return list
def ar_read(path, file_name, list, ar_id, au_id): def ar_read(path, file_name, ar_id, au_data, num):
file_path = os.path.join(path, file_name) file_path = os.path.join(path, file_name)
with open(file_path, 'r', encoding='utf-8') as file: with open(file_path, 'r', encoding='utf-8') as file:
data = json.load(file) data = json.load(file)
for Dict in data: for Dict in data:
if Dict.get('article_id') == ar_id: if Dict.get('article_id') == ar_id[0]:
# A new dictionary to stored key information # A new dictionary to stored information
temp_data = { au_data['from_article_title'] = Dict.get('title')
'title': Dict.get('title'), num[0] += 1
'author_id': au_id
}
list.append(temp_data) # Add into list
return list
# ========== Main code ========== # ========== Main code ==========
au_list = [] # List for author data au_list = [] # List for author data
ar_list = [] # List for article data num = [0] # Data number counter
ar_temp = [] # List for temp stored
num = 0 # Data number counter
# Read the file # Read the file
au_names = os.listdir(author_path)
ar_names = os.listdir(article_path) ar_names = os.listdir(article_path)
# Stored the author data which has no "email" information # Stored the author data which has no "email" information
au_list = au_read(author_path, au_names, au_list) au_list = au_read(author_path, au_list)
# Search the articles where the authors from # Search the articles where the authors from
for au_data in au_list: for au_MergeList in au_list:
if len(ar_temp) == 100: for au_data in au_MergeList:
num += 100 if num[0] % 100 == 0 and num[0] != 0:
ar_list.append(ar_temp) print(str(num[0]) + " copies of data have been done.")
ar_temp.clear()
print(str(num) + " copies of data has been stored.") if int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2009:
ar_read(article_path, ar_names[3], au_data.get('from_article'), au_data, num)
elif int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2009:
ar_temp = ar_read(article_path, ar_names[3], ar_temp, au_data.get('from_article'), au_data.get('author_id'))
elif int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2010: elif int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2010:
ar_temp = ar_read(article_path, ar_names[0], ar_temp, au_data.get('from_article'), au_data.get('author_id')) ar_read(article_path, ar_names[0], au_data.get('from_article'), au_data, num)
elif int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2020: elif int(au_data.get('affiliation', [{}])[0].get('year', 0)) <= 2020:
ar_temp = ar_read(article_path, ar_names[1], ar_temp, au_data.get('from_article'), au_data.get('author_id')) ar_read(article_path, ar_names[1], au_data.get('from_article'), au_data, num)
else: else:
ar_temp = ar_read(article_path, ar_names[2], ar_temp, au_data.get('from_article'), au_data.get('author_id')) ar_read(article_path, ar_names[2], au_data.get('from_article'), au_data, num)
if len(ar_temp) > 0: # Stored remaining data with open('./Author_data(merged)/Author_data(info_supplementary).json', 'w', encoding='utf-8') as file:
ar_list.append(ar_temp) json.dump(au_list, file, indent=4)
print(len(ar_list))
return ar_list
print('All data have been stored into ./Author_data(merged)/Author_data(info_supplementary).json')
# ========== Test code ========== # ========== Test code ==========
# Read('./test_buffer/Author_output', './test_buffer/Article_output') Read('./Author_data(merged)/Author_data(merged).json', './test_buffer/Article_output')