For the last couple of months I've been working on a new open source Python project. This is called DimCli and it's a command-line library aimed at making it simpler to work with the Dimensions Analytics API.
The project is available on Github. In a nutshell, DimCli helps people becoming productive with the powerful scholarly analytics API from Dimensions. See the video below for a quick taster of the functionalities available.
I recenlty joined the Dimensions team, so needed a way to get to grips with their feature-rich API (official docs). So, building DimCli has been a fun way for me to dig into the logic of the Dimensions Search Language (DSL).
Plus, this project gave me a chance to learn more about two awesome Python technologies: JupyterLab and its magic commands, as well as the Python Prompt Toolkit library.
>>> import dimcli
>>> dimcli.login(username="mary.poppins", password="chimneysweeper")
>>> dsl = dimcli.Dsl()
>>> res = dsl.query("""search grants for "malaria" return researchers""")
>>> print(res.json)
{'researchers': [{'id': 'ur.01332073522.49',
'count': 75,
'last_name': 'White',
'first_name': 'Nicholas J'},
{'id': 'ur.01343654360.43',
'count': 59,
'last_name': 'Marsh',
'first_name': 'Kevin'},
.............
],
'_stats': {'total_count': 8735}}
DimCli lives on Github, so for any feedback or bug reports, feel free to open an issue there.
Cite this blog post:
Comments via Github:
2024
paper Dimensions: Calculating Disruption Indices at Scale
Quantitative Science Studies, Sep 2024. https://doi.org/10.48550/arXiv.2309.06120
2022
International Conference on Science, Technology and Innovation Indicators (STI 2022), Granada, Sep 2022.
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2011