File and folder naming convention for React.js components
/actions/...
/components/common/Link.js
/components/common/...
/components/forms/TextBox.js
/components/forms/TextBox.res/style.css
Johnny Chan Atlas7
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| <html> | |
| <head> | |
| <script src="//cdnjs.cloudflare.com/ajax/libs/underscore.js/1.4.2/underscore-min.js"></script> | |
| <script src="//ajax.googleapis.com/ajax/libs/jquery/1.8.2/jquery.min.js"></script> | |
| <script src="//cdnjs.cloudflare.com/ajax/libs/modernizr/2.6.2/modernizr.min.js"></script> | |
| <script src="//ajax.cdnjs.com/ajax/libs/json2/20110223/json2.js"></script> | |
| <!-- | |
| TODO: |
koistya
/ React-Directory-Layout.md
Last active
April 7, 2024 19:01
File and folder naming convention for React.js components
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| export const doTheThing = () => (dispatch, getState) => { | |
| const users = getState(); | |
| dispatch({ | |
| type: 'THE_THING', | |
| users, | |
| }); | |
| }; |
hugobowne
/ tweet_listener.py
Last active
October 6, 2023 18:48
NOTE: this code is for a previous version of the Twitter API and I will not be updating in the near future. If someone else would like to, I'd welcome that! Feel free to ping me. END NOTE. Here I define a Tweet listener that creates a file called 'tweets.txt', collects streaming tweets as .jsons and writes them to the file 'tweets.txt'; once 100…
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| class MyStreamListener(tweepy.StreamListener): | |
| def __init__(self, api=None): | |
| super(MyStreamListener, self).__init__() | |
| self.num_tweets = 0 | |
| self.file = open("tweets.txt", "w") | |
| def on_status(self, status): | |
| tweet = status._json | |
| self.file.write( json.dumps(tweet) + '\n' ) | |
| self.num_tweets += 1 |
gunjanpatel
/ revert-a-commit.md
Last active
May 30, 2024 17:11
Git HowTo: revert a commit already pushed to a remote repository
Sometimes you may want to undo a whole commit with all changes. Instead of going through all the changes manually, you can simply tell git to revert a commit, which does not even have to be the last one. Reverting a commit means to create a new commit that undoes all changes that were made in the bad commit. Just like above, the bad commit remains there, but it no longer affects the the current master and any future commits on top of it.
git revert {commit_id}
Deleting the last commit is the easiest case. Let's say we have a remote origin with branch master that currently points to commit dd61ab32. We want to remove the top commit. Translated to git terminology, we want to force the master branch of the origin remote repository to the parent of dd61ab32:
wangruohui
/ Install NVIDIA Driver and CUDA.md
Last active
May 17, 2024 09:02
Install NVIDIA Driver and CUDA on Ubuntu / CentOS / Fedora Linux OS
In this article, I will share some of my experience on installing NVIDIA driver and CUDA on Linux OS. Here I mainly use Ubuntu as example. Comments for CentOS/Fedora are also provided as much as I can.
luiscape
/ install_packages.sh
Created
January 16, 2017 14:36
Install Python dependency packages from requirements.txt using conda.
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| # | |
| # Original solution via StackOverflow: | |
| # http://stackoverflow.com/questions/35802939/install-only-available-packages-using-conda-install-yes-file-requirements-t | |
| # | |
| # | |
| # Install via `conda` directly. | |
| # This will fail to install all | |
| # dependencies. If one fails, | |
| # all dependencies will fail to install. |
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| pre.highlight, | |
| .highlight pre { background-color: #272822; } | |
| .highlight .hll { background-color: #22282A } | |
| .highlight .c { color: #99AA8A } /* Comment */ | |
| .highlight .err { color: #960050; background-color: #1e0010 } /* Error */ | |
| .highlight .k { color: #93C763 } /* Keyword */ | |
| .highlight .l { color: #ae81ff } /* Literal */ | |
| .highlight .n { color: #F1F2F3 } /* Name */ | |
| .highlight .o { color: #E8E2B7 } /* Operator */ | |
| .highlight .p { color: #F1F2F3 } /* Punctuation */ |
avloss
/ test_import.md
Created
March 10, 2017 17:24
TensorFlow SERVING is Googles' recommended way to deploy TensorFlow models. Without proper computer engineering background, it can be quite intimidating, even for people who feel comfortable with TensorFlow itself. Few things that I've found particularly hard were:
- Tutorial examples have C++ code (which I don't know)
- Tutorials have Kubernetes, gRPG, Bezel (some of which I saw for the first time)
- It needs to be compiled. That process takes forever!
After all, it worked just fine. Here I present an easiest possible way to deploy your models with TensorFlow Serving. You will have your self-built model running inside TF-Serving by the end of this tutorial. It will be scalable, and you will be able to query it via REST.