Decorators do use py2neo library like Spring Data annotations
Project description
# Neo4j Decorator Driver for Python
> All annotations assumes class methods as decorated sources.
## Database connection
Call Neo4j class and setup the connection
```
from neo4jdecorators.db import Neo4j
...
Neo4j.initialize(host, username, password)
```
## Query Decorator Signature
```
from neo4jdecorators.query import Query
...
@Query([cypher statement], asTable=False)
def method_name(...):
...
```
* __asTable__: If true, the method will get the result parameter as a DataFrame Pandas object
## Transactional Decorator Signature
```
from neo4jdecorators.query import Query
...
@Transactional
def method_name(...):
...
```
## Minimum query decorated method signagure
```
def method_name(self, result, *args):
...
```
### Extra args passed could be
* __tx__: A transaction to be used (could be the one injected with Transactional decorator)
* __parameters__: A dictionary with statement parameters
## Minimum Transactional decorated method signature
```
def method_name(self, tx):
...
```
> All annotations assumes class methods as decorated sources.
## Database connection
Call Neo4j class and setup the connection
```
from neo4jdecorators.db import Neo4j
...
Neo4j.initialize(host, username, password)
```
## Query Decorator Signature
```
from neo4jdecorators.query import Query
...
@Query([cypher statement], asTable=False)
def method_name(...):
...
```
* __asTable__: If true, the method will get the result parameter as a DataFrame Pandas object
## Transactional Decorator Signature
```
from neo4jdecorators.query import Query
...
@Transactional
def method_name(...):
...
```
## Minimum query decorated method signagure
```
def method_name(self, result, *args):
...
```
### Extra args passed could be
* __tx__: A transaction to be used (could be the one injected with Transactional decorator)
* __parameters__: A dictionary with statement parameters
## Minimum Transactional decorated method signature
```
def method_name(self, tx):
...
```
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