This License is currently being reviewed and may be updated any time. The changes made to this License have immediate effect after its update.
You can use the Drawings for whatever you want except redistributing or reselling them in any of their forms, separated or packaged.
You can use them for unlimited End Products, either paid or free, for unlimited End Clients, as long as the End Product is not directly related or in competition with the Drawings and/or excalidraw.art.
Create a template service file at /etc/systemd/system/[email protected]. The template parameter will correspond to the name
of target host:
[Unit]
Description=Setup a secure tunnel to %I
After=network.target
| import asyncio | |
| import smtplib | |
| import ssl | |
| from email.mime.multipart import MIMEMultipart | |
| from email.mime.text import MIMEText | |
| from socket import gaierror | |
| import base64 | |
| import datetime as dt | |
| import imghdr | |
| import json |
| Latency Comparison Numbers (~2012) | |
| ---------------------------------- | |
| L1 cache reference 0.5 ns | |
| Branch mispredict 5 ns | |
| L2 cache reference 7 ns 14x L1 cache | |
| Mutex lock/unlock 25 ns | |
| Main memory reference 100 ns 20x L2 cache, 200x L1 cache | |
| Compress 1K bytes with Zippy 3,000 ns 3 us | |
| Send 1K bytes over 1 Gbps network 10,000 ns 10 us | |
| Read 4K randomly from SSD* 150,000 ns 150 us ~1GB/sec SSD |
| import inspect | |
| from functools import partial, wraps | |
| from typing import Union | |
| from app import schemas | |
| from app.db import database | |
| from pydantic.main import ModelMetaclass | |
| from shortuuid import uuid | |
| # The following 2 functions parse raw results from the SQL queries |
| # docd.py | |
| def doc(f): | |
| with open("docs.txt") as d: | |
| docfile = d.read() | |
| # save old docstring | |
| if f.__doc__: | |
| prev_doc = f.__doc__ | |
| f.__doc__ = prev_doc + "\n\n# docdoc\n" + docfile |
| -- walkthrough of: https://mystery.knightlab.com | |
| -- | |
| /* A crime has taken place and the detective needs | |
| * your help. The detective gave you the crime | |
| * scene report, but you somehow lost it. You | |
| * vaguely remember that the crime was a murder | |
| * that occurred sometime on Jan.15, 2018 and that | |
| * it took place in SQL City. Start by retrieving | |
| * the corresponding crime scene report from the | |
| * police department’s database. */ |
| new_cols_nodrug = [c for c in df.columns.to_list() if c not in all_drug_cols] | |
| new_cols = new_cols_nodrug.copy() | |
| for i in range(len(drugs)): | |
| new_cols.append(f"drug_{i}") | |
| new_cols.append(f"pasi_inicial_{i}") | |
| new_cols.append(f"tiempo_{i}") | |
| new_cols.append(f"motivo_{i}") | |