jab

# Ideally, we would manage async access to stdin/stdout/stderr *without*
# setting them to non-blocking mode, because that can break other processes.
# (See https://github.com/python-trio/trio/issues/174 for much more detail.)

# Of course we can call read/write in a separate thread, but then we lose
# cancellation support.

# This file demonstrates a weird hack to make blocking read/write cancellable,
# and thus at least theoretically possible to integrate into Trio as ordinary
# first-class operations.

jamescalam

from flask import Flask
from flask_restful import Resource, Api, reqparse
import pandas as pd
import ast

app = Flask(__name__)
api = Api(app)

class Users(Resource):
    def get(self):

4OH4

from sklearn.feature_extraction.text import TfidfVectorizer
from sklearn.metrics.pairwise import linear_kernel
from nltk import word_tokenize          
from nltk.stem import WordNetLemmatizer
import nltk
from nltk.corpus import stopwords

# Download stopwords list
nltk.download('punkt')
stop_words = set(stopwords.words('english')) 

yaroslavvb

def install_pdb_handler():
    """Signals to automatically start pdb:
      1. CTRL+\\ breaks into pdb.
      2. pdb gets launched on exception.
    """

    import signal
    import pdb

    def handler(_signum, _frame):

Tushar-N

import torch
import torch.nn as nn
import torch.nn.functional as F

import torchvision.models as tmodels
from functools import partial
import collections

# dummy data: 10 batches of images with batch size 16
dataset = [torch.rand(16,3,224,224).cuda() for _ in range(10)]

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)

ro31337

Docker Completion for Zsh (Official)

• mkdir -p ~/.oh-my-zsh/plugins/docker/
• curl -fLo ~/.oh-my-zsh/plugins/docker/_docker https://raw.githubusercontent.com/docker/cli/master/contrib/completion/zsh/_docker
• Add docker to plugins section in ~/.zshrc
• exec zsh

Miserlou

import io
from flask import Flask, send_file

app = Flask(__name__)

@app.route('/logo.jpg')
def logo():
    """Serves the logo image."""

    with open("logo.jpg", 'rb') as bites:

BretFisher

# problem: when presenting, I want to obscure
# my prompt to act like it's at root of file system 
# and be very basic with no git info, etc.

# solution: this theme lets you set a ENV to the path 
# of your presentation, which will help remove unneeded prompt
# features while in that path 

# oh-my-zsh theme for presenting demos
# based off the default rubbyrussell theme

citrusui

How do I dropdown?

This is how you dropdown.

<details>
<summary>How do I dropdown?</summary>
<br>
This is how you dropdown.