start new:
tmux
start new with session name:
tmux new -s myname
(by @andrestaltz)
If you prefer to watch video tutorials with live-coding, then check out this series I recorded with the same contents as in this article: Egghead.io - Introduction to Reactive Programming.
Structured logs are way better than normal logs for a whole bunch of reasons, but they can sometimes be a pain to read in the shell. Take this logline for example:
{"erlang_pid":"#PID<0.1584.0>","level":"error","message":"Got error when retry: :econnrefused, will retry after 1535ms. Have retried 2 times, :infinity times left.","module":"","release":"c2ef629cb357c136f529abec997426d6d58de485","timestamp":"2019-12-17T19:22:11.164Z"}
This format is hard for a human to parse. How about this format instead?
error | 2019-12-17T19:21:02.944Z | Got error when retry: :econnrefused, will retry after 1648ms. Have retried 2 times, :infinity times left.
#!comment: This is a list of the top 100,000 most frequently-used English words | |
#!comment: according to Wiktionary. | |
#!comment: | |
#!comment: It was compiled in August 2005 and coalesced into a handy list for | |
#!comment: use in John the Ripper. | |
#!comment: | |
#!comment: | |
#!comment: Pull date: Sun Jan 15 22:03:54 2012 GMT | |
#!comment: | |
#!comment: Sources: |
# Initialize the scroll | |
page = es.search( | |
index = 'yourIndex', | |
doc_type = 'yourType', | |
scroll = '2m', | |
search_type = 'scan', | |
size = 1000, | |
body = { | |
# Your query's body | |
}) |
#!/usr/bin/env python | |
import smtplib | |
from email.mime.text import MIMEText | |
from subprocess import check_output | |
# Get the git log --stat entry of the new commit | |
log = check_output(['git', 'log', '-1', '--stat', 'HEAD']) | |
# Create a plaintext email message | |
msg = MIMEText("Look, I'm actually doing some work:\n\n%s" % log) |
# coding:utf-8 | |
from elasticsearch import Elasticsearch | |
import json | |
# Define config | |
host = "127.0.0.1" | |
port = 9200 | |
timeout = 1000 | |
index = "index" |
These instructions are based on Mistobaan's gist but expanded and updated to work with the latest tensorflow OSX CUDA PR.
""" | |
Example of a Streamlit app for an interactive Prodigy dataset viewer that also lets you | |
run simple training experiments for NER and text classification. | |
Requires the Prodigy annotation tool to be installed: https://prodi.gy | |
See here for details on Streamlit: https://streamlit.io. | |
""" | |
import streamlit as st | |
from prodigy.components.db import connect | |
from prodigy.models.ner import EntityRecognizer, merge_spans, guess_batch_size |