[](https://github.com/kiarina/falkordb-py)
[](https://github.com/kiarina/falkordb-py/releases/latest)
[](https://badge.fury.io/py/kiarina-falkordb)
# kiarina-falkordb
> **ℹ️ This is a fork of [falkordb-py](https://github.com/FalkorDB/falkordb-py) with additional fixes.**
>
> **Original work by the [FalkorDB team](https://github.com/FalkorDB/falkordb-py).**
>
> This fork includes bug fixes and improvements that are pending upstream merge.
[](https://app.falkordb.cloud)
FalkorDB Python client
see [docs](http://falkordb-py.readthedocs.io/)
## Installation
```sh
pip install kiarina-falkordb
```
## Differences from upstream
- ✅ **redis-py 7.0.0 support** - Compatible with redis-py >= 7.0.0
- ✅ **Python 3.9+ required** - Dropped Python 3.8 support for redis-py 7.x compatibility
- ✅ Fixed async `from_url()` to correctly use host/port from URL
- ✅ All original functionality preserved
- 🔄 Actively maintained with upstream compatibility
## Usage
### Run FalkorDB instance
Docker:
```sh
docker run --rm -p 6379:6379 falkordb/falkordb
```
Or use [FalkorDB Cloud](https://app.falkordb.cloud)
### Synchronous Example
```python
from falkordb import FalkorDB
# Connect to FalkorDB
db = FalkorDB(host='localhost', port=6379)
# Select the social graph
g = db.select_graph('social')
# Create 100 nodes and return a handful
nodes = g.query('UNWIND range(0, 100) AS i CREATE (n {v:1}) RETURN n LIMIT 10').result_set
for n in nodes:
print(n)
# Read-only query the graph for the first 10 nodes
nodes = g.ro_query('MATCH (n) RETURN n LIMIT 10').result_set
# Copy the Graph
copy_graph = g.copy('social_copy')
# Delete the Graph
g.delete()
```
### Asynchronous Example
```python
import asyncio
from falkordb.asyncio import FalkorDB
from redis.asyncio import BlockingConnectionPool
async def main():
# Connect to FalkorDB
pool = BlockingConnectionPool(max_connections=16, timeout=None, decode_responses=True)
db = FalkorDB(connection_pool=pool)
# Select the social graph
g = db.select_graph('social')
# Execute query asynchronously
result = await g.query('UNWIND range(0, 100) AS i CREATE (n {v:1}) RETURN n LIMIT 10')
# Process results
for n in result.result_set:
print(n)
# Run multiple queries concurrently
tasks = [
g.query('MATCH (n) WHERE n.v = 1 RETURN count(n) AS count'),
g.query('CREATE (p:Person {name: "Alice"}) RETURN p'),
g.query('CREATE (p:Person {name: "Bob"}) RETURN p')
]
results = await asyncio.gather(*tasks)
# Process concurrent results
print(f"Node count: {results[0].result_set[0][0]}")
print(f"Created Alice: {results[1].result_set[0][0]}")
print(f"Created Bob: {results[2].result_set[0][0]}")
# Close the connection when done
await pool.aclose()
# Run the async example
if __name__ == "__main__":
asyncio.run(main())
```
## Development
### Running Tests
Start a FalkorDB instance:
```sh
docker run -d --rm --name falkordb-test -p 6379:6379 falkordb/falkordb:latest
```
Install dependencies and run tests:
```sh
poetry install
poetry run pytest -v
```
Stop the test instance:
```sh
docker stop falkordb-test
```
### Release
Build and publish to PyPI:
```sh
poetry build
poetry publish
```
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