Impact Factor Toolkits
Project description
最新SCI期刊影响因子查询系统
- 已更新 2025年数据
- 包含JCR分区表数据
- 包含中科院分区表数据
Installation
python3 -m pip install -U impact_factor
Use in CMD
impact_factor -h
build
build/update the database
# optional, only required when you need build or update the database
impact_factor build -i tests/IF.xlsx
# with a ncbi api_key
impact_factor build -k YOUR_NCBI_API_KEY
# use a new dbfile [*recommend*]
impact_factor -d test.db build -i tests/IF.xlsx
# without nlm_catalog
impact_factor -d test.db build -i tests/IF.xlsx -n
search
search with
journal,journal_abbr,issn,eissnornlm_id
impact_factor search nature # search journal
impact_factor search 'nature c%' # like search journal
impact_factor search 0028-0836 # search ISSN
impact_factor search 1476-4687 # search eISSN
impact_factor search 0410462 # search nlm_id
impact_factor search nature --color # colorful output
filter
filter
factorwithmin_valueandmax_value
impact_factor filter -m 100 -M 200 --color
# output with pubmed filter format
impact_factor filter -m 100 -M 200 --pubmed-filter
Use in Python
from impact_factor.core import Factor
fa = Factor()
print(fa.dbfile)
fa.search('nature')
fa.search('nature c%')
fa.filter(min_value=100, max_value=200)
fa.filter(min_value=100, max_value=200, pubmed_filter=True)
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