Disclaimer: This piece is written anonymously. The names of a few particular companies are mentioned, but as common examples only.
This is a short write-up on things that I wish I'd known and considered before joining a private company (aka startup, aka unicorn in some cases). I'm not trying to make the case that you should never join a private company, but the power imbalance between founder and employee is extreme, and that potential candidates would
In my recent post analyzing 1.1 billion NYC taxi and Uber trips, I included a section about privacy concerns which showed how precise latitude/longitude coordinates of taxi pickups and drop offs could potentially be used to reveal personal information about where people live, work, socialize, etc.
I wrote that if the Taxi & Limousine Commission wanted to avoid disclosing personal information, they would have to remove latitude/longitude from the dataset, perhaps replacing them with coarser census tract location data. Now it seems like maybe census tracts are still too precise.
I hadn't previously investigated how well census tracts uniquely identify pickups and drop offs, but **it turns out that if you
You got your hands on some data that was leaked from a social network and you want to help the poor people.
Luckily you know a government service to automatically block a list of credit cards.
The service is a little old school though and you have to upload a CSV file in the exact format. The upload fails if the CSV file contains invalid data.
The CSV files should have two columns, Name and Credit Card. Also, it must be named after the following pattern:
YYYYMMDD.csv.
(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.
As of version 3.3, python includes the very promising concurrent.futures module, with elegant context managers for running tasks concurrently. Thanks to the simple and consistent interface you can use both threads and processes with minimal effort.
For most CPU bound tasks - anything that is heavy number crunching - you want your program to use all the CPUs in your PC. The simplest way to get a CPU bound task to run in parallel is to use the ProcessPoolExecutor, which will create enough sub-processes to keep all your CPUs busy.
We use the context manager thusly:
with concurrent.futures.ProcessPoolExecutor() as executor:
| (defun get-previous-indentation () | |
| "Get the column of the previous indented line" | |
| (interactive) | |
| (save-excursion | |
| (progn | |
| (move-beginning-of-line nil) | |
| (skip-chars-backward "\n \t") | |
| (back-to-indentation)) | |
| (current-column))) |
Hi there!
The docker cheat sheet has moved to a Github project under https://github.com/wsargent/docker-cheat-sheet.
Please click on the link above to go to the cheat sheet.
Eric Bidelman has documented some of the common workflows possible with headless Chrome over in https://developers.google.com/web/updates/2017/04/headless-chrome.
If you're looking at this in 2016 and beyond, I strongly recommend investigating real headless Chrome: https://chromium.googlesource.com/chromium/src/+/lkgr/headless/README.md
Windows and Mac users might find using Justin Ribeiro's Docker setup useful here while full support for these platforms is being worked out.
This tutorial guides you through creating your first Vagrant project.
We start with a generic Ubuntu VM, and use the Chef provisioning tool to:
Afterwards, we'll see how easy it is to package our newly provisioned VM
L1 cache reference ......................... 0.5 ns
Branch mispredict ............................ 5 ns
L2 cache reference ........................... 7 ns
Mutex lock/unlock ........................... 25 ns
Main memory reference ...................... 100 ns
Compress 1K bytes with Zippy ............. 3,000 ns = 3 µs
Send 2K bytes over 1 Gbps network ....... 20,000 ns = 20 µs
SSD random read ........................ 150,000 ns = 150 µs
Read 1 MB sequentially from memory ..... 250,000 ns = 250 µs