Hey! I’ve used google api scholarly for a research project last semester. It’s definitely a bit finicky, especially with filtering.
One thing that helped me was using the `query` parameter more effectively. You can add specific keywords or phrases to narrow down results. Also, try using the `sort_by` parameter to prioritize newer or more cited papers.
Performance-wise, yeah, it can be slow, especially with large datasets. I found that breaking my requests into smaller chunks helped a bit.
If you’re still struggling, check out Semantic Scholar’s API. It’s a bit more user-friendly and has similar functionality.
Here’s a quick snippet for filtering by year:
```python
results = scholarly.search_pubs('your_query', year_low=2018, year_high=2022)
```
Hope that helps!
One thing that helped me was using the `query` parameter more effectively. You can add specific keywords or phrases to narrow down results. Also, try using the `sort_by` parameter to prioritize newer or more cited papers.
Performance-wise, yeah, it can be slow, especially with large datasets. I found that breaking my requests into smaller chunks helped a bit.
If you’re still struggling, check out Semantic Scholar’s API. It’s a bit more user-friendly and has similar functionality.
Here’s a quick snippet for filtering by year:
```python
results = scholarly.search_pubs('your_query', year_low=2018, year_high=2022)
```
Hope that helps!