[](https://doi.org/10.5281/zenodo.7539859)
[](https://pepy.tech/project/impact-factor)
# ***最新SCI期刊影响因子查询系统***
- *已更新 **[2024年数据](https://www.researchgate.net/publication/381580823_Journal_Citation_Reports_JCR_Impact_Factor_2024_PDF_Web_of_Science)***
- *包含JCR分区表数据*
## Installation
```bash
python3 -m pip install -U impact_factor
```
## Use in CMD
```bash
impact_factor -h
```
### `build`
> build/update the database
```bash
# 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`, `eissn` or `nlm_id`
```bash
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 `factor` with `min_value` and `max_value`
```bash
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
```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)
```
## Documents
https://impact-factor.readthedocs.io
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"description": "[](https://doi.org/10.5281/zenodo.7539859)\n\n[](https://pepy.tech/project/impact-factor)\n\n\n\n\n\n# ***\u6700\u65b0SCI\u671f\u520a\u5f71\u54cd\u56e0\u5b50\u67e5\u8be2\u7cfb\u7edf***\n- *\u5df2\u66f4\u65b0 **[2024\u5e74\u6570\u636e](https://www.researchgate.net/publication/381580823_Journal_Citation_Reports_JCR_Impact_Factor_2024_PDF_Web_of_Science)***\n- *\u5305\u542bJCR\u5206\u533a\u8868\u6570\u636e*\n\n## Installation\n```bash\npython3 -m pip install -U impact_factor\n```\n\n## Use in CMD\n```bash\nimpact_factor -h\n```\n\n\n### `build`\n> build/update the database\n\n```bash\n# optional, only required when you need build or update the database\nimpact_factor build -i tests/IF.xlsx\n\n# with a ncbi api_key\nimpact_factor build -k YOUR_NCBI_API_KEY\n\n# use a new dbfile [*recommend*]\nimpact_factor -d test.db build -i tests/IF.xlsx\n\n# without nlm_catalog\nimpact_factor -d test.db build -i tests/IF.xlsx -n\n```\n\n### `search`\n> search with `journal`, `journal_abbr`, `issn`, `eissn` or `nlm_id`\n\n```bash\nimpact_factor search nature # search journal\nimpact_factor search 'nature c%' # like search journal\nimpact_factor search 0028-0836 # search ISSN\nimpact_factor search 1476-4687 # search eISSN\nimpact_factor search 0410462 # search nlm_id\nimpact_factor search nature --color # colorful output\n```\n\n\n\n### `filter`\n> filter `factor` with `min_value` and `max_value`\n\n```bash\nimpact_factor filter -m 100 -M 200 --color\n\n# output with pubmed filter format\nimpact_factor filter -m 100 -M 200 --pubmed-filter\n```\n\n\n\n## Use in Python\n```python\nfrom impact_factor.core import Factor\n\nfa = Factor()\n\nprint(fa.dbfile)\n\nfa.search('nature')\nfa.search('nature c%')\n\nfa.filter(min_value=100, max_value=200)\nfa.filter(min_value=100, max_value=200, pubmed_filter=True)\n```\n\n## Documents\nhttps://impact-factor.readthedocs.io\n\n\n",
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