BlackHC

Latency Comparison Numbers (~2023)
----------------------------------
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 Snappy            3,000   ns        3 µs
Read 1 MB sequentially from memory      20,000   ns       20 µs          ~50GB/sec DDR5
Read 1 MB sequentially from NVMe       100,000   ns      100 µs          ~10GB/sec NVMe, 5x memory

br3ndonland

Getting the Gist of GitHub Actions

Tutorial and tips for GitHub Actions workflows

Table of Contents

• Introduction
• Workflows and actions

DGrady

Query Oracle databases with Python and SQLAlchemy

N.B. SQLAlchemy now incorporates all of this information in its documentation; I’m leaving this post here, but recommend referring to SQLAlchemy instead of these instructions.

Install requirements

1. We’ll assume you already have SQLAlchemy and Pandas installed; these are included by default in many Python distributions.
2. Install the cx_Oracle package in your Python environment, using either pip or conda, for example: