Skip to content

Commit

Permalink
Create getting_started.md (#90)
Browse files Browse the repository at this point in the history
* Create getting_started.md

---------

Co-authored-by: coderabbitai[bot] <136622811+coderabbitai[bot]@users.noreply.github.com>
Co-authored-by: danshalev7 <[email protected]>
Co-authored-by: Copilot <[email protected]>
  • Loading branch information
4 people authored Dec 6, 2024
1 parent 1a07a8b commit 9fd30bc
Show file tree
Hide file tree
Showing 2 changed files with 159 additions and 0 deletions.
2 changes: 2 additions & 0 deletions .wordlist.txt
Original file line number Diff line number Diff line change
Expand Up @@ -3,6 +3,7 @@ AOF
AST
Aldis
Analytics
APIs
BFS
BLAS
Benchmarking
Expand Down Expand Up @@ -189,6 +190,7 @@ percentileDisc
performant
permalink
php
prem
propCount
propertyKeys
py
Expand Down
157 changes: 157 additions & 0 deletions getting_started.md
Original file line number Diff line number Diff line change
@@ -0,0 +1,157 @@
---
title: "Getting Started"
nav_order: 2
description: >
Getting Started with FalkorDB Graph Database.
---


# Getting Started with FalkorDB

This guide will walk you through setting up FalkorDB, modeling a social network as a graph,
and accessing it using the [FalkorDB Python client](/clients) with [Cypher](/cypher).

---

## Prerequisites

1. **FalkorDB Instance**: Set up FalkorDB (on-prem or cloud).
- [Run FalkorDB Docker](https://hub.docker.com/r/falkordb/falkordb/)
- [Create a FalkorDB Cloud Instance](https://app.falkordb.cloud/signup)
2. **Python Installed**: Ensure you have Python 3.8+ installed.
3. **Install FalkorDB Python Client**:

```bash
pip install falkordb
```

---

## Step 1: Model a Social Network as a Graph

Let's create a simple graph for a social network where:
- **Nodes** represent `User` and `Post`.
- **Relationships** connect `User`s with a `FRIENDS_WITH` relationship, and `User`s are connected via a `CREATED` relationship to `Post`s

### Graph Schema

| Node Type | Properties |
|-----------|--------------------------|
| User | `id`, `name`, `email` |
| Post | `id`, `content`, `date` |

| Relationship Type | Start Node | End Node | Properties |
|-------------------|------------|----------|--------------|
| FRIENDS_WITH | User | User | `since` |
| CREATED | User | Post | `time` |

![FalkorDB-Model a Social Network as a Graph](https://github.com/user-attachments/assets/57d9b837-661e-4500-a9f2-88e754382d29)

---

## Step 2: Load Data into FalkorDB

Here’s how you can model and load the data.

### Cypher Query to Create the Data

```cypher
CREATE (alice:User {id: 1, name: "Alice", email: "[email protected]"})
CREATE (bob:User {id: 2, name: "Bob", email: "[email protected]"})
CREATE (charlie:User {id: 3, name: "Charlie", email: "[email protected]"})
CREATE (post1:Post {id: 101, content: "Hello World!", date: 1701388800})
CREATE (post2:Post {id: 102, content: "Graph Databases are awesome!", date: 1701475200})
CREATE (alice)-[:FRIENDS_WITH {since: 1640995200}]->(bob)
CREATE (bob)-[:FRIENDS_WITH {since: 1684108800}]->(charlie)
CREATE (alice)-[:CREATED {time: 1701388800}]->(post1)
CREATE (bob)-[:CREATED {time: 1701475200}]->(post2)
```

You can execute these commands using the FalkorDB Python client.

---

## Step 3: Access Your Data

### Connect to FalkorDB

```python
from falkordb import FalkorDB

# Connect to FalkorDB
client = FalkorDB(host="localhost", port=6379, password="your-password")
graph = client.select_graph('social')
```

### Execute Cypher Queries

#### Create the Graph

```python
create_query = """
CREATE (alice:User {id: 1, name: "Alice", email: "[email protected]"})
CREATE (bob:User {id: 2, name: "Bob", email: "[email protected]"})
CREATE (charlie:User {id: 3, name: "Charlie", email: "[email protected]"})
CREATE (post1:Post {id: 101, content: "Hello World!", date: 1701388800})
CREATE (post2:Post {id: 102, content: "Graph Databases are awesome!", date: 1701475200})
CREATE (alice)-[:FRIENDS_WITH {since: 1640995200}]->(bob)
CREATE (bob)-[:FRIENDS_WITH {since: 1684108800}]->(charlie)
CREATE (alice)-[:CREATED {time: 1701388800}]->(post1)
CREATE (bob)-[:CREATED {time: 1701475200}]->(post2)
"""

graph.query(create_query)
print("Graph created successfully!")
```

![image](https://github.com/user-attachments/assets/f67c9a1d-4b80-435d-9038-b7e1f931da74)

#### Query the Graph

```python
# Find all friends of Alice
query = """
date and time as they are right now can be confusing, either use Python to create timestamps from actual dates or consider changing the attribute to something else which doesn't require time / date datatype
MATCH (alice:User {name: "Alice"})-[:FRIENDS_WITH]->(friend)
RETURN friend.name AS Friend
"""
result = graph.ro_query(query)

print("Alice's friends:")
for record in result:
print(record["Friend"])
```

#### Query Relationships

```python
# Find posts created by Bob
query = """
MATCH (bob:User {name: "Bob"})-[:CREATED]->(post:Post)
RETURN post.content AS PostContent
"""
result = graph.ro_query(query)

print("Posts created by Bob:")
for record in result:
print(record["PostContent"])
```

---

## Step 4: Explore Further

Congratulations! 🎉 You have successfully modeled, loaded, and queried a social network graph with FalkorDB.

Next, dive deeper into FalkorDB's powerful features:
- [Advanced Cypher](/cypher)
- [Database Operations](/operations)
- [Integration with ML Workflows](/llm_support)

For questions or support, visit our [community forums](https://www.falkordb.com/contact-us/)

0 comments on commit 9fd30bc

Please sign in to comment.