- Install Atom from https://atom.io/.
- Launch Atom and select
"Atom - Install Shell Commands"
menu to installatom
andapm
commands - Add
/usr/local/bin
toPATH
environment varibale
"Atom - Install Shell Commands"
menu to install atom
and apm
commands/usr/local/bin
to PATH
environment varibalepackage main | |
import ( | |
"bufio" | |
"fmt" | |
"net" | |
"net/http" | |
"net/url" | |
"crypto/tls" |
The following instructions describe a set of processes allowing you to run Django database migrations against a production database without having to bring the web service down.
Note that in the below instructions, migrations are all run manually at explicit points, and are not an automatic part of the deployment process.
brew options ffmpeg | |
brew install ffmpeg \ | |
--with-chromaprint \ | |
--with-fdk-aac \ | |
--with-fontconfig \ | |
--with-freetype \ | |
--with-frei0r \ | |
--with-game-music-emu \ | |
--with-libass \ |
Largely based on the Tensorflow 1.6 gist, this should hopefully simplify things a bit. Mixing homebrew python2/python3 with pip ends up being a mess, so here's an approach to uses the built-in python27.
# 清华大学: | |
cd "$(brew --repo)" | |
git remote set-url origin https://mirrors.tuna.tsinghua.edu.cn/git/homebrew/brew.git | |
cd "$(brew --repo)/Library/Taps/homebrew/homebrew-core" | |
git remote set-url origin https://mirrors.tuna.tsinghua.edu.cn/git/homebrew/homebrew-core.git | |
# 手动修改 bottles 地址: | |
export HOMEBREW_BOTTLE_DOMAIN=https://mirrors.tuna.tsinghua.edu.cn/homebrew-bottles | |
# 或: |
class Python < Formula | |
desc "Interpreted, interactive, object-oriented programming language" | |
homepage "https://www.python.org/" | |
url "https://www.python.org/ftp/python/3.8.6/Python-3.8.6.tar.xz" | |
sha256 "a9e0b79d27aa056eb9cce8d63a427b5f9bab1465dee3f942dcfdb25a82f4ab8a" | |
head "https://github.com/python/cpython.git" | |
license "Python-2.0" | |
revision 1 | |
bottle do |
Lecture 1: Introduction to Research — [📝Lecture Notebooks] [
Lecture 2: Introduction to Python — [📝Lecture Notebooks] [
Lecture 3: Introduction to NumPy — [📝Lecture Notebooks] [
Lecture 4: Introduction to pandas — [📝Lecture Notebooks] [
Lecture 5: Plotting Data — [📝Lecture Notebooks] [[