The Loopdesk Social Media Scheduler is a modern application for managing and scheduling posts across multiple platforms (YouTube, TikTok, LinkedIn, Facebook, Instagram, and X). This challenge will test your ability to contribute meaningful features to this React + TypeScript application.
To qualify for submission, you must complete tasks totaling at least 5 points.
You can mix and match features from different difficulty levels to reach 5 points. For example:
| from typing import List, Tuple | |
| class UnionFind: | |
| def __init__(self, size: int): | |
| self.parent = [i for i in range(size)] | |
| self.rank = [0] * size | |
| def find(self, x: int) -> int: | |
| if self.parent[x] != x: | |
| self.parent[x] = self.find(self.parent[x]) # Path compression |
| import pandas as pd | |
| import numpy as np | |
| import matplotlib.pyplot as plt | |
| # Set random seed for reproducibility | |
| np.random.seed(42) | |
| # Platforms and other variables | |
| platforms = ['Google', 'Meta', 'Bing', 'LinkedIn'] | |
| campaigns = ['Campaign A', 'Campaign B', 'Campaign C'] |
| # Water is represented by 0 and land is represented by 1. | |
| input_grid = [ | |
| [0,0,1,0,0,0,0,1,0,0,0,0,0], | |
| [0,0,0,0,0,0,0,1,1,1,0,0,0], | |
| [0,1,1,1,1,0,0,0,0,0,0,0,0], | |
| [0,1,0,0,1,1,0,0,1,1,1,0,0], | |
| [0,1,0,1,1,1,0,0,1,1,1,0,0], | |
| [0,0,1,0,0,0,0,0,1,0,1,0,0], | |
| [0,0,0,0,0,0,0,1,1,1,0,0,0], | |
| [0,0,0,0,0,0,0,1,1,0,0,0,0] |
| class FenwickTree: | |
| def __init__(self, size): | |
| self.size = size | |
| self.tree = [0] * (size + 1) | |
| def update(self, index, value): | |
| while index <= self.size: | |
| self.tree[index] += value | |
| index += index & -index |
| from collections import deque, defaultdict | |
| class Graph: | |
| def __init__(self): | |
| self.graph = defaultdict(list) | |
| def add_edge(self, node, neighbour): | |
| self.graph[node].append(neighbour) | |
| self.graph[neighbour].append(node) |
| from collections import defaultdict | |
| class Graph: | |
| def __init__(self): | |
| self.graph = defaultdict(list) | |
| def add_edge(self, node, neighbour): | |
| self.graph[node].append(neighbour) | |
| self.graph[neighbour].append(node) |
| import requests | |
| from typing import Tuple, List | |
| from math import log | |
| currencies = ('PLN', 'EUR', 'USD', 'RUB', 'INR', 'MXN') | |
| api_key = 'fe69bd3037f74f699cf2bf8070b44374' | |
| def get_rates(currencies: Tuple[str, ...], api_key: str) -> List[List[float]]: | |
| rates = [] | |
| response = requests.get(f'https://openexchangerates.org/api/latest.json?app_id={api_key}') |
Identity and Access Management Our customers trust us with some of their most sensitive data, but with thousands of systems and employees around the globe, we've never been systematic about access control. We want to give employees exactly the right set of privileges they need to do their work.
Welcome! You have been appointed the technical lead of a project to build an identity and access management (IAM) system. At a high level, the components are:
• A way of storing access policies (who can do what); • An API to query these access policies; and • An APl to manage these access policies.
Examples of requests that the system should serve
| /* Priority Queue based Heap implementation in TypeScript */ | |
| class BinaryHeap<T> { | |
| private heapArray: T[] = []; | |
| constructor(private lessThan: (a:T, b:T) => boolean) { | |
| } | |
| size() { | |
| return this.heapArray.length; |
