Commander 1 Alela, Artful Provocateur (ELD) 324
Deck 1 Righteous Valkyrie (KHM) 24 1 Glacial Floodplain (KHM) 257 6 Snow-Covered Swamp (KHM) 281 1 Lagonna-Band Storyteller (THB) 27 1 Demonic Embrace (M21) 95 6 Snow-Covered Plains (KHM) 276
brew reinstall openssl gettext readline sqlite3 xz zlib tcl-tk |
# Stash the changes: This will take your current changes and stash them. | |
git reset HEAD~1 | |
# Copy code | |
git stash | |
#Switch to the desired branch: | |
git checkout [branch-name] | |
# Apply the stash to the branch: |
<template> | |
<div class="flex justify-between"> | |
<div> | |
<label class="tw-inline-block tw-pt-2 tw-leading-tight tw-mb-1 tw-text-base mr-2">Start Date</label> | |
<input type="date" id="start_date" v-model="start_date" class="mb-4 w-32 h-8" /> | |
</div> | |
<div> | |
<label class="tw-inline-block tw-pt-2 tw-leading-tight tw-mb-1 tw-text-base mr-2">End Date</label> | |
<input type="date" id="end_date" v-model="end_date" class="mb-4 w-32 h-8" /> | |
</div> |
trying https://github.com/obukhov/redis-inventory first | |
install go 1.15 | |
https://www.5gfundamental.com/2021/04/install-go-lang-latest-version-1155-in.html | |
git clone https://github.com/obukhov/redis-inventory | |
sudo wget https://golang.org/dl/go1.15.5.linux-amd64.tar.gz | |
sudo tar -C /usr/local -xzf go1.15.5.linux-amd64.tar.gz | |
Dijkstra's algorithm is a popular algorithm used to find the shortest path between two nodes in a graph. It is a greedy algorithm that iteratively expands the frontier of visited nodes from the starting node towards the target node, while updating the cost of each node. The algorithm maintains a priority queue of nodes to visit, with the node with the lowest current cost at the front of the queue. | |
Here are the basic steps of Dijkstra's algorithm: | |
Initialize the cost of the starting node to 0, and the cost of all other nodes to infinity. | |
Add the starting node to the priority queue. | |
While the priority queue is not empty: | |
Remove the node with the lowest cost from the priority queue (call it "current"). | |
For each neighbor of "current": | |
Calculate the cost of getting to that neighbor through "current". |
const fs = require('fs') | |
if (process.argc < 3) { | |
console.log('Usage: node timing.js <filename>') | |
process.exit(1) | |
} | |
const sFile = process.argv[2] | |
console.log({sFile}) |
export default function AppWs() { | |
const [isPaused, setPause] = useState(false); | |
const ws = useRef(null); | |
useEffect(() => { | |
ws.current = new WebSocket("wss://ws.kraken.com/"); | |
ws.current.onopen = () => console.log("ws opened"); | |
ws.current.onclose = () => console.log("ws closed"); | |
const wsCurrent = ws.current; |
from multiprocessing import Process, Manager | |
manager = Manager() | |
d = manager.dict() | |
def f(): | |
d[1].append(4) | |
# the __str__() method of a dict object invokes __repr__() on each of its items, | |
# so explicitly invoking __str__() is required in order to print the actual list items | |
print({k: str(v) for k, v in d.items()} |
Commander 1 Alela, Artful Provocateur (ELD) 324
Deck 1 Righteous Valkyrie (KHM) 24 1 Glacial Floodplain (KHM) 257 6 Snow-Covered Swamp (KHM) 281 1 Lagonna-Band Storyteller (THB) 27 1 Demonic Embrace (M21) 95 6 Snow-Covered Plains (KHM) 276
[[{"score":5.141071428571431,"points":[{"lat":30.27594797018001,"lng":-97.74167025909962},{"lat":30.264482588643258,"lng":-97.74167025909962},{"lat":30.26512499911168,"lng":-97.73080697363837},{"lat":30.2765905258849,"lng":-97.73080697363837},{"lat":30.27594797018001,"lng":-97.74167025909962}]},{"score":2.126785714285714,"points":[{"lat":30.275304409960153,"lng":-97.75253521988041},{"lat":30.26383917389268,"lng":-97.75253521988041},{"lat":30.264482588643258,"lng":-97.74167025909962},{"lat":30.27594797018001,"lng":-97.74167025909962},{"lat":30.275304409960153,"lng":-97.75253521988041}]},{"score":1.2714285714285711,"points":[{"lat":30.26512499911168,"lng":-97.73080697363837},{"lat":30.25365847735911,"lng":-97.73080697363837},{"lat":30.254299738793186,"lng":-97.71994536457991},{"lat":30.26576640566484,"lng":-97.71994536457991},{"lat":30.26512499911168,"lng":-97.73080697363837}]},{"score":0.9375,"points":[{"lat":30.25493999691198,"lng":-97.70908543300678},{"lat":30.243472191103944,"lng":-97.70908543300678},{"lat" |