pyappcache
A library for application-level caching (by calpaterson)
requests-cache
Transparent persistent cache for python requests (by requests-cache)
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| pyappcache | requests-cache | |
|---|---|---|
| 1 | 7 | |
| 20 | 1,254 | |
| - | 1.9% | |
| 7.3 | 8.7 | |
| 23 days ago | 8 days ago | |
| Python | Python | |
| GNU General Public License v3.0 only | BSD 2-clause "Simplified" License |
The number of mentions indicates the total number of mentions that we've tracked plus the number of user suggested alternatives.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
Stars - the number of stars that a project has on GitHub. Growth - month over month growth in stars.
Activity is a relative number indicating how actively a project is being developed. Recent commits have higher weight than older ones.
For example, an activity of 9.0 indicates that a project is amongst the top 10% of the most actively developed projects that we are tracking.
pyappcache
Posts with mentions or reviews of pyappcache.
We have used some of these posts to build our list of alternatives
and similar projects.
requests-cache
Posts with mentions or reviews of requests-cache.
We have used some of these posts to build our list of alternatives
and similar projects. The last one was on 2022-04-24.
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Web Scraping with Python: from Fundamentals to Practice
For anyone who goes with requests as your HTTP client, I would highly recommend adding requests-cache for a nice performance boost.
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What does the process of web scraping actually look like?
The hardest part is actually running a web scraper at scale and that's where many people fail. We have all of the working pieces - we can find the products and parse the raw data. Time to scale it up! Best tip here is to start off with caching. Using caching libraries like requests-cache or whatever library equivalent will speed up process significantly.
- If I keep making URL requests in a forloop, is that harmful?
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Requests-Cache – An easy way to get better performance with the python requests library
And would you be willing to add some example Terraform config? If you wouldn't mind making a PR for that, it could go under the /examples folder.
What are some alternatives?
When comparing pyappcache and requests-cache you can also consider the following projects:
aiohttp-client-cache - An async persistent cache for aiohttp requests
requests - A simple, yet elegant, HTTP library.
requests - A simple, yet elegant HTTP library. [Moved to: https://github.com/psf/requests]
notionSnapshot - notion web scraper
requests-html - Pythonic HTML Parsing for Humans™
Uplink - A Declarative HTTP Client for Python
parsel-cli - cli for evaluating css and xpath selectors
sqlite_http_csv - simulation kdb+ http behavior for sqlite.
cachew - Transparent and persistent cache/serialization powered by type hints
tmx-solver - ThreatMetrix (anti-bot/fraud-detection) solver, deobfuscator & data harvester
cachecontrol - The httplib2 caching algorithms packaged up for use with requests.
requests-cache vs aiohttp-client-cache
requests-cache vs requests
requests-cache vs requests
requests-cache vs notionSnapshot
requests-cache vs requests-html
requests-cache vs Uplink
requests-cache vs parsel-cli
requests-cache vs sqlite_http_csv
requests-cache vs cachew
requests-cache vs tmx-solver
requests-cache vs cachecontrol