ORM integration
This guide demonstrates how to configure an AEA to interact with a database using python-sql objects.
Discussion¶
Object-relational-mapping (ORM) is the idea of being able to write SQL queries, using the object-oriented paradigm of your preferred programming language. The scope of this guide is to demonstrate how you can create an easily configurable AEA that reads data from a database using ORMs.
- We assume, that you followed the guide for the thermometer-skills.
- We assume, that we have a database
genericdb.dbwith table namedata. This table contains the following columnstimestampandthermometer. - We assume, that we have a hardware thermometer sensor that adds the readings in the
genericdbdatabase (although you can follow the guide without having access to a sensor).
Since the AEA framework enables us to use third-party libraries hosted on PyPI we can directly reference the external dependencies. The aea install command will install each dependency that the specific AEA needs and which is listed in the skill's YAML file.
Communication¶
This diagram shows the communication between the various entities in the case where the thermometer data is successfully sold by the seller AEA to the buyer.
Preparation instructions¶
Dependencies¶
Follow the Preliminaries and Installation sections from the AEA quick start.
Demo instructions¶
This demo involves a true ledger transaction on Fetch.ai's testnet network or Ethereum's ropsten. This demo assumes the buyer trusts the seller AEA to send the data upon successful payment.
Create the seller AEA¶
First, fetch the seller AEA which provides thermometer data:
aea fetch fetchai/thermometer_aea:0.30.1 --alias my_thermometer_aea
cd my_thermometer_aea
aea install
aea build
Alternatively, create from scratch.
The following steps create the seller from scratch:
aea create my_thermometer_aea
cd my_thermometer_aea
aea add connection fetchai/p2p_libp2p:0.27.1
aea add connection fetchai/soef:0.27.2
aea add connection fetchai/ledger:0.21.1
aea add skill fetchai/thermometer:0.27.2
aea config set --type dict agent.dependencies \
'{
"aea-ledger-fetchai": {"version": "<2.0.0,>=1.0.0"}
}'
aea config set agent.default_connection fetchai/p2p_libp2p:0.27.1
aea config set --type dict agent.default_routing \
'{
"fetchai/ledger_api:1.1.2": "fetchai/ledger:0.21.1",
"fetchai/oef_search:1.1.2": "fetchai/soef:0.27.2"
}'
aea install
aea build
Create the buyer client¶
In another terminal, fetch the buyer AEA:
aea fetch fetchai/thermometer_client:0.31.1 --alias my_thermometer_client
cd my_thermometer_client
aea install
aea build
Alternatively, create from scratch.
The following steps create the car data client from scratch:
aea create my_thermometer_client
cd my_thermometer_client
aea add connection fetchai/p2p_libp2p:0.27.1
aea add connection fetchai/soef:0.27.2
aea add connection fetchai/ledger:0.21.1
aea add skill fetchai/thermometer_client:0.26.2
aea config set --type dict agent.dependencies \
'{
"aea-ledger-fetchai": {"version": "<2.0.0,>=1.0.0"}
}'
aea config set agent.default_connection fetchai/p2p_libp2p:0.27.1
aea config set --type dict agent.default_routing \
'{
"fetchai/ledger_api:1.1.2": "fetchai/ledger:0.21.1",
"fetchai/oef_search:1.1.2": "fetchai/soef:0.27.2"
}'
aea install
aea build
Add keys for the seller AEA¶
First, create the private key for the seller AEA based on the network you want to transact. To generate and add a private-public key pair for Fetch.ai Dorado use:
Next, create a private key used to secure the AEA's communications:
aea generate-key fetchai fetchai_connection_private_key.txt
aea add-key fetchai fetchai_connection_private_key.txt --connection
Finally, certify the key for use by the connections that request that:
Add keys and generate wealth for the buyer AEA¶
The buyer needs to have some wealth to purchase the thermometer data.
First, create the private key for the buyer AEA based on the network you want to transact. To generate and add a private-public key pair for Fetch.ai use:
Then, create some wealth for the buyer based on the network you want to transact with. On the Fetch.ai Dorado network:
Next, create a private key used to secure the AEA's communications:
aea generate-key fetchai fetchai_connection_private_key.txt
aea add-key fetchai fetchai_connection_private_key.txt --connection
Finally, certify the key for use by the connections that request that:
Update the seller and buyer AEA skill configurations¶
In my_thermometer_aea/vendor/fetchai/skills/thermometer/skill.yaml, replace the data_for_sale with your data:
models:
...
strategy:
args:
currency_id: FET
data_for_sale:
temperature: 26
has_data_source: false
is_ledger_tx: true
ledger_id: fetchai
location:
latitude: 51.5194
longitude: 0.127
service_data:
key: seller_service
value: thermometer_data
service_id: thermometer_data
unit_price: 10
class_name: Strategy
dependencies:
SQLAlchemy: {}
service_data is used to register the service in the SOEF search node and make your agent discoverable.
In my_thermometer_client/vendor/fetchai/skills/thermometer_client/skill.yaml) ensure you have matching data.
models:
...
strategy:
args:
currency_id: FET
is_ledger_tx: true
ledger_id: fetchai
location:
latitude: 51.5194
longitude: 0.127
max_negotiations: 1
max_tx_fee: 3550000000000000
max_unit_price: 20
search_query:
constraint_type: ==
search_key: seller_service
search_value: thermometer_data
search_radius: 5.0
service_id: thermometer_data
class_name: Strategy
After changing the skill configuration files you should run the following command for both agents to install each dependency:
Modify the seller's strategy¶
Before being able to modify a package we need to eject it from vendor:
This will move the package to your skills directory and reset the version to 0.1.0 and the author to your author handle.
Open strategy.py (in my_thermometer_aea/skills/thermometer/strategy.py) and make the following modifications:
Import the newly installed sqlalchemy library in your strategy.
__init__ function to match the following code:
class Strategy(GenericStrategy):
"""This class defines a strategy for the agent."""
def __init__(self, **kwargs) -> None:
"""
Initialize the strategy of the agent.
:param register_as: determines whether the agent registers as seller, buyer or both
:param search_for: determines whether the agent searches for sellers, buyers or both
:return: None
"""
self._db_engine = db.create_engine("sqlite:///genericdb.db")
self._tbl = self.create_database_and_table()
self.insert_data()
super().__init__(**kwargs)
At the end of the file modify the collect_from_data_source function:
def collect_from_data_source(self) -> Dict[str, str]:
"""Implement the logic to collect data."""
connection = self._db_engine.connect()
query = db.select([self._tbl])
result_proxy = connection.execute(query)
data_points = result_proxy.fetchall()
return {"data": json.dumps(list(map(tuple, data_points)))}
def create_database_and_table(self):
"""Creates a database and a table to store the data if not exists."""
metadata = db.MetaData()
tbl = db.Table(
"data",
metadata,
db.Column("timestamp", db.Integer()),
db.Column("temprature", db.String(255), nullable=False),
)
metadata.create_all(self._db_engine)
return tbl
def insert_data(self):
"""Insert data in the database."""
connection = self._db_engine.connect()
for _ in range(10):
query = db.insert(self._tbl).values( # nosec
timestamp=time.time(), temprature=str(random.randrange(10, 25))
)
connection.execute(query)
After modifying the skill we need to fingerprint it:
Run both AEAs¶
First, run the thermometer (seller) AEA:
Once you see a message of the form To join its network use multiaddr 'SOME_ADDRESS' take note of this address. (Alternatively, use aea get-multiaddress fetchai -c -i fetchai/p2p_libp2p:0.27.1 -u public_uri to retrieve the address.)
This is the entry peer address for the local agent communication network created by the thermometer AEA.
Then, configure the thermometer client (buyer) to connect to this same local ACN by running the following command in the buyer terminal, replacing SOME_ADDRESS with the value you noted above:
aea config set --type dict vendor.fetchai.connections.p2p_libp2p.config \
'{
"delegate_uri": "127.0.0.1:11001",
"entry_peers": ["SOME_ADDRESS"],
"local_uri": "127.0.0.1:9001",
"log_file": "libp2p_node.log",
"public_uri": "127.0.0.1:9001"
}'
Then run the thermometer client AEA:
You will see that the AEAs negotiate and then transact using the configured testnet.
Delete the AEAs¶
When you're done, stop the agents (CTRL+C), go up a level and delete the AEAs.