PubmedZenbu


NamePubmedZenbu JSON
Version 0.3.7 PyPI version JSON
download
home_pagehttps://github.com/dogrun-inc/pubmed-zenbu/tree/2023_dev_suzuki
SummaryPubmedZenbu
upload_time2024-01-13 08:28:52
maintainerSora Yonezawa, Mitsuo Shintani, Naoya Oec, Takayuki Suzuki
docs_urlNone
authorSora Yonezawa, Mitsuo Shintani, Naoya Oec, Takayuki Suzuki
requires_python
licenseMIT
keywords pubmed scraping article dogrun
VCS
bugtrack_url
requirements No requirements were recorded.
Travis-CI No Travis.
coveralls test coverage No coveralls.
            # pubmed-zenbu
1. This tool collects literature data (title_only or title_and_abstract) of your interest.
2. This tool also extracts metadata from literature data using ChatGPT if you set the parameters.

## How to use 
- `conda create -n pubmedzenbu python=3.9`
- Create a `config.yml` 
```
# Sample config.yml

pubmed_search:
  # (Required) NCBI API Key
  ncbi_api_key: YOUR_NCBI_API_KEY
  # (Required) Search query to obtain the PubMed articles of your interest
  search_query: prime editing pig
  # (Required) How far back in time you want to search. 
  search_oldest_year: 2010
  # (Required) `title` or `abstract`. If choose `abstract`, it means you get the joined string of title and abstract.
  which_text_to_use: title
openai:
  # (Required) if use, add 'yes'. If not, keep it empty.
  use_openai: yes
  # (Optional) if use_openai is true, add your openai_api_key. Otherwise, keep it empty.
  openai_api_key: YOUR_OPENAI_API_KEY
  # (Optional) Prompt to ask ChatGPT. If you don't use it, keep it empty.
  prompt: "extract gene and species from the following text \n"
  # (Required) Set the output path. If use_openai is false, literature data will be written out.
  output_path: ./extract_result_20231004.csv
```

- `pubmedzenbu PATH_TO_YOUR_config.yml_FILE`

            

Raw data

            {
    "_id": null,
    "home_page": "https://github.com/dogrun-inc/pubmed-zenbu/tree/2023_dev_suzuki",
    "name": "PubmedZenbu",
    "maintainer": "Sora Yonezawa, Mitsuo Shintani, Naoya Oec, Takayuki Suzuki",
    "docs_url": null,
    "requires_python": "",
    "maintainer_email": "oec@dogrun.jp",
    "keywords": "pubmed scraping article dogrun",
    "author": "Sora Yonezawa, Mitsuo Shintani, Naoya Oec, Takayuki Suzuki",
    "author_email": "oec@dogrun.jp",
    "download_url": "https://files.pythonhosted.org/packages/33/11/61f50dae798242904daa451ffa3af20e2e381390f68bc7cb6024083b5a86/PubmedZenbu-0.3.7.tar.gz",
    "platform": null,
    "description": "# pubmed-zenbu\n1. This tool collects literature data (title_only or title_and_abstract) of your interest.\n2. This tool also extracts metadata from literature data using ChatGPT if you set the parameters.\n\n## How to use \n- `conda create -n pubmedzenbu python=3.9`\n- Create a `config.yml` \n```\n# Sample config.yml\n\npubmed_search:\n  # (Required) NCBI API Key\n  ncbi_api_key: YOUR_NCBI_API_KEY\n  # (Required) Search query to obtain the PubMed articles of your interest\n  search_query: prime editing pig\n  # (Required) How far back in time you want to search. \n  search_oldest_year: 2010\n  # (Required) `title` or `abstract`. If choose `abstract`, it means you get the joined string of title and abstract.\n  which_text_to_use: title\nopenai:\n  # (Required) if use, add 'yes'. If not, keep it empty.\n  use_openai: yes\n  # (Optional) if use_openai is true, add your openai_api_key. Otherwise, keep it empty.\n  openai_api_key: YOUR_OPENAI_API_KEY\n  # (Optional) Prompt to ask ChatGPT. If you don't use it, keep it empty.\n  prompt: \"extract gene and species from the following text \\n\"\n  # (Required) Set the output path. If use_openai is false, literature data will be written out.\n  output_path: ./extract_result_20231004.csv\n```\n\n- `pubmedzenbu PATH_TO_YOUR_config.yml_FILE`\n",
    "bugtrack_url": null,
    "license": "MIT",
    "summary": "PubmedZenbu",
    "version": "0.3.7",
    "project_urls": {
        "Download": "https://github.com/dogrun-inc/pubmed-zenbu/tree/2023_dev_suzuki",
        "Homepage": "https://github.com/dogrun-inc/pubmed-zenbu/tree/2023_dev_suzuki"
    },
    "split_keywords": [
        "pubmed",
        "scraping",
        "article",
        "dogrun"
    ],
    "urls": [
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "2eb2f15e6e18478979bc8c067e9a7efe864c45ecfccf50e8ab7b8621df0a4d81",
                "md5": "5c8a5cab34fc3d234e8abbc3308938be",
                "sha256": "423a8a3d04af692d2c2b63f7e20a6d32d77dcad55aa888d6de5601106c6a0661"
            },
            "downloads": -1,
            "filename": "PubmedZenbu-0.3.7-py3-none-any.whl",
            "has_sig": false,
            "md5_digest": "5c8a5cab34fc3d234e8abbc3308938be",
            "packagetype": "bdist_wheel",
            "python_version": "py3",
            "requires_python": null,
            "size": 7585,
            "upload_time": "2024-01-13T08:28:49",
            "upload_time_iso_8601": "2024-01-13T08:28:49.917690Z",
            "url": "https://files.pythonhosted.org/packages/2e/b2/f15e6e18478979bc8c067e9a7efe864c45ecfccf50e8ab7b8621df0a4d81/PubmedZenbu-0.3.7-py3-none-any.whl",
            "yanked": false,
            "yanked_reason": null
        },
        {
            "comment_text": "",
            "digests": {
                "blake2b_256": "331161f50dae798242904daa451ffa3af20e2e381390f68bc7cb6024083b5a86",
                "md5": "eaec5891d7faf563c79b5363743f8cc9",
                "sha256": "390593d3d896cb887d054e9a743f07a7f8cc101061eb16991e80e1253e5050d3"
            },
            "downloads": -1,
            "filename": "PubmedZenbu-0.3.7.tar.gz",
            "has_sig": false,
            "md5_digest": "eaec5891d7faf563c79b5363743f8cc9",
            "packagetype": "sdist",
            "python_version": "source",
            "requires_python": null,
            "size": 7087,
            "upload_time": "2024-01-13T08:28:52",
            "upload_time_iso_8601": "2024-01-13T08:28:52.995377Z",
            "url": "https://files.pythonhosted.org/packages/33/11/61f50dae798242904daa451ffa3af20e2e381390f68bc7cb6024083b5a86/PubmedZenbu-0.3.7.tar.gz",
            "yanked": false,
            "yanked_reason": null
        }
    ],
    "upload_time": "2024-01-13 08:28:52",
    "github": true,
    "gitlab": false,
    "bitbucket": false,
    "codeberg": false,
    "github_user": "dogrun-inc",
    "github_project": "pubmed-zenbu",
    "travis_ci": false,
    "coveralls": false,
    "github_actions": false,
    "lcname": "pubmedzenbu"
}
        
Elapsed time: 0.18624s