| IDrive e2 - $0.005/GB - $0 for download bandwidth - 1:3 upload:download ratio allowed <- questionable data privacy - custom domains offered - has audit logging - supports event notifications with AWS SQS - $0.01/GB overage on bandwidth - has replication | |
| Backblaze B2 - $0.006/GB - $0 for download bandwidth if through Worker (or $0.01/GB past a 1:3 upload:download ratio) <- decent data privacy record - no custom domains - has audit logging - has replication | |
| Vultr - $0.018/GB - $0.01/GB for download <- https://www.vultr.com/products/object-storage/#pricing | |
| Wasabi - $0.0069/GB - $0 for download bandwidth - 1:1 and billed for 90 days <- has audit logging - no custom domains - min object size billed at 4 kilobytes | |
| Storj - $0.004/GB - $0.007/GB for download <- not good for small files due to segment pricing | |
| Scaleway - $0.013/GB - $0.011/GB for download <- estimate, had to do EUR to USD conversion https://www.scaleway.com/en/pricing/storage/ | |
| Cloudflare R2 - $0.015/GB - $0.00/GB |
This is a collection of the things I believe about software development. I have worked for years building backend and data processing systems, so read the below within that context.
Agree? Disagree? Feel free to let me know at @JanStette.
Keep it simple, stupid. You ain't gonna need it.
| default['sshd']['sshd_config']['AuthenticationMethods'] = 'publickey,keyboard-interactive:pam' | |
| default['sshd']['sshd_config']['ChallengeResponseAuthentication'] = 'yes' | |
| default['sshd']['sshd_config']['PasswordAuthentication'] = 'no' |
| package main | |
| import ( | |
| "net/http" | |
| "compress/gzip" | |
| "io/ioutil" | |
| "strings" | |
| "sync" | |
| "io" | |
| ) |
Just a quickie test in Python 3 (using Requests) to see if Google Cloud Vision can be used to effectively OCR a scanned data table and preserve its structure, in the way that products such as ABBYY FineReader can OCR an image and provide Excel-ready output.
The short answer: No. While Cloud Vision provides bounding polygon coordinates in its output, it doesn't provide it at the word or region level, which would be needed to then calculate the data delimiters.
On the other hand, the OCR quality is pretty good, if you just need to identify text anywhere in an image, without regards to its physical coordinates. I've included two examples:
####### 1. A low-resolution photo of road signs
| #!/usr/bin/env python | |
| import random | |
| import struct | |
| import sys | |
| # Most of the Fat32 class was cribbed from https://gist.github.com/jonte/4577833 | |
| def ppNum(num): | |
| return "%s (%s)" % (hex(num), num) |
Using WebSockets, React and Reflux together can be a beautiful thing, but the intial setup can be a bit of a pain. The below examples attempt to offer one (arguably enjoyable) way to use these tools together.
This trifect works well if you think of things like so:
this.state in react should instead live within stores. Stores can listen to other stores as well as to events being fired.
| #cloud-config | |
| coreos: | |
| etcd: | |
| # generate a new token for each unique cluster from https://discovery.etcd.io/new | |
| discovery: https://discovery.etcd.io/<token> | |
| # multi-region deployments, multi-cloud deployments, and droplets without | |
| # private networking need to use $public_ipv4 | |
| addr: $private_ipv4:4001 | |
| peer-addr: $private_ipv4:7001 |
Standard for US Driver's Licenses defines 9 different barcode standards (AAMVA versions) with over 80 different fields encoded inside a barcode. Some fields exist on all barcode standards, other exist only on some. To standardize the API, we have structured the fields in the following sections:
