github-contributions | GitHub account creates a nice contributions calendar | Calendar library
kandi X-RAY | github-contributions Summary
kandi X-RAY | github-contributions Summary
A tool that generates a repository which being pushed into your GitHub account creates a nice contributions calendar.
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Currently covering the most popular Java, JavaScript and Python libraries. See a Sample of github-contributions
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QUESTION
I have an element that shows my GitHub contributions, this file has static width and to make it look nice on smaller devices I decided to use overflow-x
set to auto
to allow horizontal swipe with finger gesture.
I would like to see the scroll position to the very right by default so that the most recent contributions are being shown.
I assume it's not possible with CSS and I need to use some JS?
Here's the basic CSS that I wrote:
...ANSWER
Answered 2021-May-28 at 15:18I knew that I can do this in pure CSS. I forgot about rtl
direction.
QUESTION
I have made the API parsing the GITHUB contribution data of each account and arranging by month, week or day and decorating with JSON.
responding to just one request takes approximately 2 second. (1800ms)
Link to my GitHub repository.
contributions.py
in repository is the python code that does the above things.
THE POINT OF QUESTION : What makes my API slow?
just too many data to parse (about 365)? the way api make the JSON String?
Thank you for answering and helping me in advance.
...ANSWER
Answered 2018-May-13 at 03:06"Why is my code slow?" is a really hard question to answer. There's basically an unlimited number of possible reasons that could be. I may not be able to answer the question, but I can provide some suggestions to hopefully help you answer it for yourself.
There are dozens of questions to ask... What kind of hardware are you using? What kind of network/internet connection do you have? Is it just slow on the first request, or all requests? Is it just slow on the call to one type of request (daily, weekly, monthly) or all? etc. etc.
You are indicating overall request times being ~1800ms, but as you pointed out, there are a lot of things happening during the processing of that request. In my experience, often times one of the best ways to find out is to add some timing code to narrow down the scope of the slowness.
For example, one quick and dirty way to do this is to use the python time module. I quickly added some code to the weekly contributions method:
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