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https://github.com/michaelfromyeg/recesearch
A simple Python project to grab Google Scholar data for research at UBC.
https://github.com/michaelfromyeg/recesearch
ece python scholarly
Last synced: 19 days ago
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A simple Python project to grab Google Scholar data for research at UBC.
- Host: GitHub
- URL: https://github.com/michaelfromyeg/recesearch
- Owner: michaelfromyeg
- License: mit
- Created: 2020-07-03T19:13:00.000Z (over 4 years ago)
- Default Branch: master
- Last Pushed: 2023-02-11T00:30:22.000Z (almost 2 years ago)
- Last Synced: 2024-05-02T05:31:04.089Z (8 months ago)
- Topics: ece, python, scholarly
- Language: Python
- Homepage:
- Size: 157 KB
- Stars: 3
- Watchers: 2
- Forks: 0
- Open Issues: 6
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# rECEsearch
A simple Python project to grab Google Scholar data for research at UBC.
[](https://www.python.org/) [](https://lbesson.mit-license.org/)
## Requirements
- Python
- scholarly (in lieu of a Google Scholar API)
- Data, in the form a csv file
Example CSV data:
```csv
Lab, ID, URL
Biomedical Technologies, ZImFmCUAAAAJ, http://ece.sites.olt.ubc.ca/research/biomedical-technologies/
Communication Systems, PhdzKFcAAAAJ, http://ece.sites.olt.ubc.ca/research/communication-systems/
```
(Do not include the spaces if you choose to use this data.)
Virtual environment quick start (for Windows):
```bash
pip install virtualenv
virtualenv env
source ./env/Scripts/activate
pip install -r requirements.txt
pip freeze > requirements.txt
```
### N.B.: As of July 10th, 2020 you should manually tweak the scholarly package to get the desired output from research.py
There's an open issue for this, but for now go to `env/Lib/scholarly/author.py` and change line 10 to read:
```python
_CITATIONAUTH = '/citations?hl=en&user={0}&sortby=pubdate'
```
The "sortby=pubdate" is what we're after here.
### And, as of August 8th, 2020 you should manually tweak one more thing
In `_scholarly.py` change line 85 to contain:
`patents: bool = False`
Patents should be skipped for this use case.
## Usage
Run `python research.py -i -o `, where 'input file' is the name of a CSV file containing professor names. See `research.py` for more information on the anticipated structure of the CSV data. In general, your input file should have three columns: lab, lab ID, and a URL (in that order).
- 'Lab' should be the name of the lab at UBC
- 'Lab ID' should be the Google Scholar ID. For example, if you navigate to [this](https://scholar.google.com/citations?user=EmD_lTEAAAAJ&hl=en) link you want the `user=...` part of the link, so in this case the ID is `EmD_lTEAAAAJ`.
- 'URL' should be the homepage this content is displayed on the UBC website. As of right now, this field is *not* utilized, so don't worry about it to much.
After executing the command, an output CSV file is produced.
- 'Lab' and 'Lab ID' are the same as above
- 'Publications' is a kind-of placeholder for an arbitrary amount of rows (like a file tree); the publication information is printed in the next N rows with the following (rather self-explanatory) headers:
- 'Title'
- 'Author'
- 'Year'
- 'Cited by' (the number of other publications that have cited the give publication)
- 'Publisher'
### Example
Here's an example console call:
And then here would be the generated csv (converted to a Markdown table):
|Lab |Lab ID |Publications|Title |Author |Year|Cited By|Publisher |
|-----------------------|------------|------------|----------------------------------------------------------------------------|--------------------|----|--------|----------------|
|Biomedical Technologies|ZImFmCUAAAAJ|... | | | | | |
| | | |Guidelines for the use and interpretation of assays for monitoring autophagy|Daniel J Klionsky an|2016|8739 |Taylor & Francis|
| | | |On robust Capon beamforming and diagonal loading |Jian Li and Petre St|2003|1431 |IEEE |
Or, in Excel:
## Future
Collect research from more sources, export to RSS feed.