0xDing

port: 7890
socks-port: 7891
redir-port: 7892
allow-lan: true
mode: Rule
log-level: info
external-controller: 0.0.0.0:9090
secret: "xxxxxx"
dns:
  enable: true

markopy

# An Example of how to parse command line arguments in streamlit. 
# This is free and unencumbered software released into the public domain.
import os
import sys
import random
import argparse
import streamlit as st

parser = argparse.ArgumentParser(description='This app lists animals')

mrnabati

Working with submodules in your repository

• Create the submodule:

  git submodule add -b master <git@github.com:MYSUBMODULE.git> <path/to/MYSUBMODULE>

  This creates the submodule and makes it track submodule's master branch. You can change the branch name if you want to track a different branch.

• Change some settings. In the parent repo:

  # make it so that git status will include changes to submodules.

tvst

"""Hack to add per-session state to Streamlit.

Usage
-----

>>> import SessionState
>>>
>>> session_state = SessionState.get(user_name='', favorite_color='black')
>>> session_state.user_name
''

whoisryosuke

Updating a feature branch

First we'll update your local master branch. Go to your local project and check out the branch you want to merge into (your local master branch)

$ git checkout master

Fetch the remote, bringing the branches and their commits from the remote repository. You can use the -p, --prune option to delete any remote-tracking references that no longer exist in the remote. Commits to master will be stored in a local branch, remotes/origin/master

y0ngb1n

Docker Hub 镜像加速器

国内从 Docker Hub 拉取镜像有时会遇到困难，此时可以配置镜像加速器。

Dockerized 实践 https://github.com/y0ngb1n/dockerized

1️⃣ Docker daemon 配置代理（推荐）

参考 Docker daemon 配置代理

arturmartins

#!/bin/bash
# Requirements:
# - homebrew: https://brew.sh/
# - homebrew tap: buo/cask-upgrade - https://github.com/buo/homebrew-cask-upgrade
# - homebrew mas (Mac App Store command-line interface - https://github.com/mas-cli/mas)
# 
# Install the requirements by running: 
# brew tap buo/cask-upgrade && brew install mas

# CONFIG:

dsuess

FROM frolvlad/alpine-miniconda3

RUN conda install -y -c conda-forge bash jupyter jupyter_contrib_nbextensions
RUN conda install -y -c conda-forge xeus-cling xtensor
RUN mkdir /notebooks

HarshTrivedi

import torch
from torch import LongTensor
from torch.nn import Embedding, LSTM
from torch.autograd import Variable
from torch.nn.utils.rnn import pack_padded_sequence, pad_packed_sequence

## We want to run LSTM on a batch of 3 character sequences ['long_str', 'tiny', 'medium']
#
#     Step 1: Construct Vocabulary
#     Step 2: Load indexed data (list of instances, where each instance is list of character indices)

andy0130tw

import sys

import gi
gi.require_version('Gtk', '3.0')
from gi.repository import Gtk, Gio

class Application(Gtk.Application):
    def __init__(self, *args, **kwargs):
        super().__init__(*args, **kwargs)
        self.window = None