Hey everyone!
Has anyone here actually used google api scholarly for academic research? I’m trying to get it set up for a project, but man, it’s been a bit of a headache.
Like, I’ve got the basics working, but pulling specific data or filtering results is kinda tricky. Anyone got tips on how to make it smoother? Or maybe some workarounds for the quirks?
Also, how’s the performance for you guys? I feel like it’s a bit slow sometimes, but maybe that’s just me.
Would love to hear your experiences or if you’ve found better alternatives. Cheers!
P.S. If you’ve got any code snippets or config tips for google api scholarly, pls share! 🙏
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!
Yo, I feel your pain! google api scholarly can be a real headache at first. I spent hours trying to get it to work smoothly.
One thing that saved me was using the `max_results` parameter to limit the number of results. It speeds things up and makes it easier to debug. Also, make sure you’re using the latest version of the library—there were some bug fixes in the recent updates.
For alternatives, I’d recommend CrossRef or PubMed APIs if your research is more bio/med-focused. They’re way faster and easier to use.
Good luck!
Hey there! I’ve been using google api scholarly for a while now, and yeah, it’s not the fastest. But once you get the hang of it, it’s pretty powerful.
For filtering, I’d suggest using the `citations` parameter if you’re looking for highly cited papers. Also, try combining it with the `author` parameter to narrow things down.
If you’re dealing with performance issues, try running your queries during off-peak hours. I noticed it’s faster late at night.
As for alternatives, Microsoft Academic Graph is worth checking out. It’s not as well-known, but it’s pretty solid.
Honestly, google api scholarly is a bit of a mixed bag. It’s great for free access to academic papers, but the setup can be a nightmare.
I found that using the `timeout` parameter helps with slow responses. Also, make sure you’re handling errors properly—sometimes the API just times out for no reason.
If you’re open to alternatives, check out Dimensions.ai. It’s a paid service, but the API is way more reliable and faster.
Here’s a quick tip: cache your results locally if you’re running multiple queries. It’ll save you a ton of time.
Wow, thanks so much for all the tips, everyone! I didn’t expect so many helpful replies.
I tried using the `query` parameter like @user1 suggested, and it made a huge difference. Also, caching results locally as @user4 mentioned saved me a ton of time.
I’m still having some issues with performance, though. Has anyone tried using async requests like @user5 mentioned? Does it really make a noticeable difference?
Also, I checked out Semantic Scholar and OpenAlex, and they both look promising. I’ll definitely give them a shot.
Thanks again, everyone! You’ve made this process way less painful. Cheers!
Hey! I’ve been using google api scholarly for a few months now, and it’s been a lifesaver for my thesis.
For filtering, try using the `cluster_id` parameter to group similar papers. It’s super helpful for organizing results. Also, the `citedby` parameter is great for finding related work.
Performance-wise, it’s definitely not the fastest, but I’ve found that using async requests helps a lot.
If you’re looking for alternatives, I’d recommend OpenAlex. It’s free and has a similar dataset.
Oh man, google api scholarly can be a pain, but it’s worth it once you figure it out.
For filtering, I’d suggest using the `source` parameter to limit results to specific journals or conferences. Also, the `abstract` parameter is great for finding papers with specific keywords in the abstract.
If you’re dealing with slow performance, try reducing the number of fields you’re requesting. Sometimes less is more.
For alternatives, check out Lens.org. It’s free and has a pretty intuitive API.
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