How to Query on the Blockchain and Build Open APIs

Blockchain Development: Querying with Open APIs Course

In this blockchain development course, you will learn how to query on the blockchain and build open APIs. This course will teach you how to build your own distributed applications using The Graph. It's like Lego blocks for composing your own protocols. You'll learn how to build your own APIs that query Ethereum, IPFS, and other data sources.

This course is all about querying data on Web3 decentralized applications. You will get an introduction to indexing and querying data on the Ethereum blockchain. Querying data on decentralized networks is very different than what you may be used to on the traditional web.

By the end of this course you will have the knowledge to query data from the Ethereum mainnet as well as a variety of other chains in order to build you own decentralized apps.

You will learn how to use The Graph. It is an indexing protocol for querying networks like Ethereum and IPFS. Anyone can build and publish open APIs, called subgraphs, making data more easily accessible.

⭐️ Course Contents ⭐️
⌨️ (00:00) Intro
⌨️ (00:58) What we will cover
⌨️ (02:44) What is The Graph for?
⌨️ (06:40) SubGraphs
⌨️ (07:20) SubGraph Manifests
⌨️ (09:36) Why build a SubGraph?
⌨️ (11:11) Let’s build a SubGraph!
⌨️ (29:47) Querying from a Frontend
⌨️ (39:33) API Key Management

💻 Code: https://github.com/kubowania/foundation-app-subgraph

#blockchain #api #graph #ethereum 

Algorithms Course - Graph Theory Visualized

Algorithms Course - Graph Theory Visualized

This full course provides a complete introduction to Graph Theory algorithms in computer science. Knowledge of how to create and design excellent algorithms is an essential skill required in becoming a great programmer. Unleash the power of graph theory with cutting-edge algorithms

This full course provides the fundamental concepts and algorithms of graph theory with real life examples and eye-appealing visualizations. The course will cover topics such as graph representation, graph traversal, topological sort, shortest paths, minimum spanning trees, graph coloring... With a total of more than 20 covered algorithms.

Discussed algorithms will be implemented in detail by using a programming language to give a better understanding for students. Captions, practice problems, quizzes, slides, and source code will also be here to make the learning experience way better.

By the end of the course, students will have a strong understanding of graph algorithms and be able to apply their knowledge to solve problems in computer science, mathematics, and beyond.

This course is ideal for students who are looking to pursue careers in computer science, mathematics, or related fields, as well as for professionals who want to expand their knowledge of graph theory algorithms.

Covered algorithms:

   Graph traversal:

•        Depth-first search
•        Breadth-first search

   Topological sorting:

•        Depth-first search based topological sort
•        Breadth-first search based topological sort (Kahn's algorithm)

   Shortest path:

•        Dijkstra's algorithm
•        Bellman-Ford algorithm
•        Floyd-Warshall algorithm
•        Johnson's algorithm
•        Shortest path for unweighted graphs algorithm
•        Shortest path for directed acyclic graphs (1st approach) algorithm
•        Shortest path for directed acyclic graphs (2nd approach) algorithm

   Trees and minimum spanning trees:

•        Spanning tree algorithm
•        Graph to out-tree algorithm
•        Prim's algorithm
•        Kruskal's algorithm

   Eulerian/Hamiltonian paths and cycles:

•        Hierholzer's algorithm
•        Hamiltonian cycle backtracking algorithm

   Graph coloring:

•        2-colorability algorithm
•        k-colorability backtracking algorithm
•        Greedy coloring algorithm
•        Welsh-Powell heuristic
•        DSatur heuristic

What you'll learn

•    Learn graphs terminology and representation
•    Learn graph traversal
•    Learn algorithms related to various graph theory topics (shortest paths, minimum spanning trees...)
•    Solve graph related coding interview problems

#datastructures #algorithms #graph

Graph Algorithms for Beginners - Crash Course (with Java)

Graph Algorithms Crash Course (with Java)

Learn how to use the graph data structures in this full tutorial for beginners. A Graph data structures is a non-linear data structure consisting of vertices and edges. They are used to solve many real-word problems and are commonly needed to solve coding challenges. The course uses Java.

⭐️ Course Contents ⭐️
⌨️ (0:00:00) Introduction to Graphs
⌨️ (0:01:35) Graphical Explanation
⌨️ (0:03:21) Code Implementation
⌨️ (0:06:41) Vertex class
⌨️ (0:09:33) Edge class
⌨️ (0:17:46) Graph class
⌨️ (0:28:06) main method
⌨️ (0:31:31) compile and run
⌨️ (0:32:55) Introduction to Graph Traversals
⌨️ (0:34:49) Traversal Orders
⌨️ (0:35:35) DFS Traversal (Graphical Explanation)
⌨️ (0:41:56) Code Implementation of DFS
⌨️ (0:51:39) BFS Traversal (Graphical Explanation)
⌨️ (0:54:23) Code Implementation of BFS
⌨️ (1:01:09) Compile and Run
⌨️ (1:01:55) Introduction to Dijkstra's Algorithm
⌨️ (1:02:25) Graphical Explanation
⌨️ (1:08:56) Code Implementation
⌨️ (1:12:22) Priority Queue
⌨️ (1:16:31) Iterating through the vertices
⌨️ (1:19:48) while loop
⌨️ (1:28:17) helper method
⌨️ (1:29:56) compile and run
⌨️ (1:30:21) problem occurred
⌨️ (1:30:31) shortestPathBetween()
⌨️ (1:37:27) fix to the problem
⌨️ (1:38:36) Successful Compile and Run

💻 Source Code: https://github.com/codingcleverly/graphs_freeCodeCamp

#graph #algorithms #java #datastructures

JavaScript Algorithms and Data Structures: Graphs - Bridges

In graph theory, a bridge, isthmus, cut-edge, or cut arc is an edge of a graph whose deletion increases its number of connected components. Equivalently, an edge is a bridge if and only if it is not contained in any cycle. A graph is said to be bridgeless or isthmus-free if it contains no bridges.

A graph with 16 vertices and 6 bridges (highlighted in red)

An undirected connected graph with no cut edges

References

• GeeksForGeeks on YouTube
• Wikipedia
• GeeksForGeeks

The Original Article can be found on https://github.com

#javascript #algorithms #datastructures #graph 

D3.js Tutorial - Making a Bar Chart Graph

We’re going to create a bar chart in the browser using d3.js. D3.js (Data Driven Documents) is a popular JavaScript library that can be used to visualize data.

Source code:
https://github.com/kriscfoster/d3-barchart

D3.js can be used to create amazing data visualizations:
https://d3js.org/

Don’t forget to Subscribe here: https://www.youtube.com/channel/UCWkzkhQ3syxBjjAYwqCbzYg?sub_confirmation=1

#d3.js #chart #graph

JavaScript Algorithms and Data Structures: Graph

In computer science, a graph is an abstract data type that is meant to implement the undirected graph and directed graph concepts from mathematics, specifically the field of graph theory

A graph data structure consists of a finite (and possibly mutable) set of vertices or nodes or points, together with a set of unordered pairs of these vertices for an undirected graph or a set of ordered pairs for a directed graph. These pairs are known as edges, arcs, or lines for an undirected graph and as arrows, directed edges, directed arcs, or directed lines for a directed graph. The vertices may be part of the graph structure, or may be external entities represented by integer indices or references.

References

• Wikipedia
• Introduction to Graphs on YouTube
• Graphs representation on YouTube

The Original Article can be found on https://github.com

Read this in other languages: 简体中文, Русский, Português

#javascript #algorithms #datastructures #graph

How to Use and Implement Graph Algorithms

Learn how to implement graph algorithms and how to use them to solve coding challenges.

🔗 Learn data structures and algorithms: https://structy.net/

⭐️ ourse Contents ⭐️
⌨️ (0:00:15) course introduction
⌨️ (0:02:23) graph basics
⌨️ (0:07:10) depth first and breadth first traversal
⌨️ (0:29:13) has path - https://structy.net/problems/has-path
⌨️ (0:42:11) undirected path - https://structy.net/problems/undirected-path
⌨️ (1:00:44) connected components count - https://structy.net/problems/connected-components-count
⌨️ (1:13:29) largest component - https://structy.net/problems/largest-component
⌨️ (1:24:03) shortest path - https://structy.net/problems/shortest-path
⌨️ (1:39:36) island count - https://structy.net/problems/island-count
⌨️ (1:58:52) minimum island - https://structy.net/problems/minimum-island
⌨️ (2:12:05) outro

#graph #algorithms #developer 

An Introduction to Neo4j (Graph Database Tutorial for Beginners)

this tutorial gets you started with neo4j from installation to building your own graph databases. this starts from installing neo4j with docker (even on an apple silicon m1) and then building a graph database in neo4j using CYPHER to create nodes, relationships, labels and properties. finally i bring it altogether with a software supply chain example in graph in neo4j.

this tutorial is suitable for beginners who want to create their own graph db in neo4j from scratch

#neo4j #graph

HTML Table Column Chart Using jQuery Graph

HTML Table Column Chart Using jQuery Graph

How to create html table based column chart (convert table to chart/graph) using jquery graph

Thank you very much for watching my new video on this channel Code Tube. You can contribute to this channel by giving support, make the subtitle, or comments that are supportive.

#jquery #graph

Building on Ethereum with GraphQL, The Graph, and Next.js

In this video I’ll walk through how to build, deploy, and query an API using The Graph. We’ll also build out a front end for querying and displaying data in a Next.js app.

Code from the live stream: https://github.com/dabit3/zora-nextjs-app

#graphql #next #next.js #graph #ethereum

Explore the Microsoft Graph Toolkit with Beth Pan

What is the session about?
The Microsoft Graph Toolkit is a group of reusable, framework-agnostic components and authentication providers for working with Microsoft Graph. You can add components to existing applications, and work in any modern browser. Join us as we chat with Beth Pan about the toolkit. In the previous session we chatted on how you can incorporate otherwise complex functionality, including authentication, with just a few lines of code. This time, we will talk about advanced technics, tips, and tricks in customizing and configuring Microsoft Graph Toolkit components.

Who is it aimed at?
This is for anyone who is a novice with the Microsoft Graph Toolkit and wants to learn more advanced uses.

Why should you attend?
This is a great opportunity to learn more about Microsoft’s Graph Toolkit!

Presenter Info: Beth Pan is a software engineer with Microsoft. She works with 1st and 3rd party developer ecosystems and help them unblock in order to build on top of Microsoft technologies and platforms. Currently she’s working on the Microsoft Graph Toolkit team to make it easier for developers to integrate their apps with Microsoft Graph.

#graph #microsoft

Graph Databases, and Dungeons and Dragons with Guy Royse

How to find the best rooms with the most gold to get better equipment, more powerful monsters and more XP? Well … the answer is GraphQL. Being a developer himself, Guy Royse thought this problem was best solved using a database to figure out the best way to pass the dungeon & maximise gold / minimise danger.

Rewatch more recordings from our past conferences at our video portal
➡️ https://frontenddeveloperlove.com/video

Our upcoming conferences:
➡️ www.vuejsglobal.com
➡️ www.reactlive.nl
➡️ https://frontenddeveloperlove.com/

#jsworldconference #jsworldconferenceusa #frontendlove #vuejsamsterdam #javascript #reactacademy #react #microinteractions #designsystems #artificialintelligence #speaker #conference #frontendlove #frontenddeveloperlove #javascriptconference #frontendconference #vue #angular #react #cfp #meetup #conferences #events #mobx #newyork

#graph #database #graphql

Methods to Plot a Graph - Python Matplotlib Tutorial #1

In this Python tutorial, you will start learning about one of the most important open-source packages in Python (Matplotlib).

In this introductory video you will be presented to Matplot library, learn how to install it and get to know the different methods that Matplotlib provides to create a graph (implicit and explicit).

Playlist: Matplotlib Course | Video #1
Access the code here: https://github.com/rscorrea1/youtube.git

Learn how to use Jupyter Notebooks: https://www.youtube.com/watch?v=gGYaFfAvYtg

Additional Courses:
Beginner Python Tutorials: https://www.youtube.com/watch?v=HG_E6EaKY90&list=PLJgwF35R54crXsGuSKR_MtUG2ABU_BFAq
Intermediate Python Tutorials: https://www.youtube.com/watch?v=oNwaOFZDAWo&list=PLJgwF35R54coNbQXGNJyawp-_3CC6I1B4
NumPy Tutorials: https://www.youtube.com/watch?v=YRes9M71_Ts&list=PLJgwF35R54cqqbFFHdArwQuBUUUoLKJ4V

#matplotlib #python #python matplotlib tutorial #graph

DFS Implementation Using Stack Data Structure | Graph Traversal Algorithm

In this Python Programming video tutorial you will learn about graph traversal operation using DFS algorithm and ow to use stack in dfs in detail.

Data structure is a way of storing and organising the data so that it can be accessed effectively.
Graph is a non linear data structure consisting of nodes and edges.

#datastructures #python #graph

Graph Convolutional Networks (GCNs)

Graph Convolutional Networks (GCNs)

Course website: http://bit.ly/DLSP21-home
Playlist: http://bit.ly/DLSP21-YouTube
Speaker: Alfredo Canziani

Chapters

• 00:00 – Welcome to class
• 00:20 – Recap from lecture 10 → Graph Transformer Networks (GTNs)
• 02:50 – Today plan: tensors/representations living on vertices and edges
• 03:20 – Self-learning resources with Xavier Bresson and Jure Leskovec
• 04:42 – Graph Convolutional Networks (GCNs)
• 23:38 – Connection with Convolutional Nets (CNNs) on grids
• 26:36 – Residual gated GCNs
• 37:26 – Domain sparsity note
• 38:27 – PyTorch implementation using Deep Graph Library (DGL)
• 56:44 – And that was it!

#graph #developer