ತಂಗಿ [tangi] Kan. younger sister
ಅಕ್ಕ [akka] Kan. older sister
Lightweight actor library for Web Workers inspired by Akka.
Type-safe, production-ready and lightweight messaging layer for Web Workers.
Picking the right architecture = Picking the right battles + Managing trade-offs
| from apiclient.discovery import build | |
| def build_service(filename): | |
| with open(filename) as f: | |
| key = f.readline() | |
| YOUTUBE_API_SERVICE_NAME = "youtube" | |
| YOUTUBE_API_VERSION = "v3" | |
| return build(YOUTUBE_API_SERVICE_NAME, | |
| YOUTUBE_API_VERSION, |
| <?php | |
| namespace App\Service\Pay; | |
| /** | |
| * TaiwanPay | |
| */ | |
| class TaiwanPay | |
| { | |
| /** |
| .css-selector { | |
| background: linear-gradient(147deg, #6d2ff6, #6dac67); | |
| background-size: 400% 400%; | |
| -webkit-animation: AnimationName 11s ease infinite; | |
| -moz-animation: AnimationName 11s ease infinite; | |
| -o-animation: AnimationName 11s ease infinite; | |
| animation: AnimationName 11s ease infinite; | |
| } | |
| @-webkit-keyframes AnimationName { | |
| 0%{background-position:9% 0%} |
| #predicting the streaming kafka messages | |
| consumer = KafkaConsumer('twitter-stream',bootstrap_servers=\['localhost:9092']) | |
| print("Starting ML predictions.") | |
| for message in consumer: | |
| X_new_counts = count_vect.transform([message.value]) | |
| X_new_tfidf = tfidf_transformer.transform(X_new_counts) | |
| predicted = load_model.predict(X_new_tfidf) | |
| print(message.value+" => "+fetch_train_dataset(categories).target_names[predicted[0]]) |
| #include <algorithm> | |
| #include <iostream> | |
| #include <set> | |
| using namespace std; | |
| struct Node { | |
| int a; | |
| long long w; | |
| Node *prev; |
| // This is an example of how to fetch external data in response to updated props, | |
| // If you are using an async mechanism that does not support cancellation (e.g. a Promise). | |
| class ExampleComponent extends React.Component { | |
| _currentId = null; | |
| state = { | |
| externalData: null | |
| }; |
Given a number of people N and an array of integers, each one representing the amount of people a type of umbrella can handle, output the minimum number of umbrellas needed to handle N people.
No umbrella could have left spaces. Which means if a umbrella can handle 2 people, there should be 2 people under it.
If there's no solution, return -1.