ccfontes

; 1. rename attribute: :url/path → :legacy/url-path-v1
(do (require '[datomic.api :as datomic] '[kanasubs.db :as db])
    (datomic/transact @db/connection
      [{:db/id :url/path, :db/ident :legacy/url-path-v1}]))

; 2. repurpose :url/path
(do (in-ns 'kanasubs.db)
    (transact @connection
      [{:db/id #db/id[:db.part/db]
        :db/ident :url/path

protrolium

ffmpeg

Converting Audio into Different Formats / Sample Rates

Minimal example: transcode from MP3 to WMA:
ffmpeg -i input.mp3 output.wma

You can get the list of supported formats with:
ffmpeg -formats

You can get the list of installed codecs with:

pervognsen

(require 'dbg)

(global-set-key (kbd "<C-S-f5>") 'dbg-restart)
(global-set-key (kbd "<f5>") 'dbg-continue)
(global-set-key (kbd "<f9>") 'dbg-toggle-breakpoint)
(global-set-key (kbd "<f8>") 'dbg-watch)
(global-set-key (kbd "<f10>") 'dbg-next)
(global-set-key (kbd "<C-f10>") 'dbg-continue-to-here)
(global-set-key (kbd "<f11>") 'dbg-step)
(global-set-key (kbd "<C-S-f10>") 'dbg-jump)

oakes

Contents

• Why care about Rust?
• The Toolchain
• Creating a New Project
• Modules
• Crates
• Types
• References
• Mutability

mookerji

(ns org.flausenhaus.rocksdb
  "Idiomatic Clojure bindings for the C++ RocksDB library, an embedded
   persistent key-value store for flash storage and server workloads based on
   LevelDB. More details about RocksDB are given at
   https://github.com/facebook/rocksdb/wiki/Rocksdb-Architecture-Guide.
   The implementation here borrows heavily from Factual's clj-leveldb.

   This namespace provides a few things:
   0. Protocols/type definitions: byte serialization (IByteSerializable),
   closeable sequences (CloseableSeq), and mutable

shaharz

(ns friend-oauth
  (:require
   [cemerick.friend :as friend]
   [cemerick.friend.workflows :refer [make-auth]]
   [clj-http.client :as client]
   [oauth.client :as oauth]
   [ring.util.request :as request]))

(defn- which-oauth-uri
  [config request]

yokolet

Datomic pro with Postgresql Setup

Prep

• Get evaluation license key : http://my.datomic.com/eval/request
• Download pro version : http://downloads.datomic.com/pro.html

Setups

1. Dev mode setup

debasishg

General Background and Overview

1. Probabilistic Data Structures for Web Analytics and Data Mining : A great overview of the space of probabilistic data structures and how they are used in approximation algorithm implementation.
2. Models and Issues in Data Stream Systems
3. Philippe Flajolet’s contribution to streaming algorithms : A presentation by Jérémie Lumbroso that visits some of the hostorical perspectives and how it all began with Flajolet
4. Approximate Frequency Counts over Data Streams by Gurmeet Singh Manku & Rajeev Motwani : One of the early papers on the subject.
5. [Methods for Finding Frequent Items in Data Streams](http://citeseerx.ist.psu.edu/viewdoc/download?doi=10.1.1.187.9800&rep=rep1&t

kierendavies

#!/usr/bin/python3

from itertools import product

T = int(input())

for t in range(T):
    N, M = list(map(int, input().split()))
    grid = [list(map(int, input().split())) for n in range(N)]
    rowmax = list(map(max, grid))