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sqlbackend.py
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sqlbackend.py
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from typing import Hashable, Generator, Optional, Iterable
import time
import pandas as pd
import sqlalchemy
from sqlalchemy.pool import NullPool
from sqlalchemy.sql import select
from sqlalchemy import and_, or_, func
from .backend import Backend
_DEFAULT_SQL_URL = "sqlite:///"
_DEFAULT_SQL_STR_LEN = 64
class SQLBackend(Backend):
"""
A graph datastore that uses a SQL-like store for persistance and queries.
"""
def __init__(
self,
directed: bool = False,
node_table_name: str = None,
edge_table_name: str = None,
db_url: str = _DEFAULT_SQL_URL,
primary_key: str = "ID",
sqlalchemy_kwargs: dict = None,
) -> None:
"""
Create a new SQL-backed graph store.
Arguments:
node_table_name (str: "grand_Nodes"): The name to use for the node
table in DynamoDB.
edge_table_name (str: "grand_Edges"): The name to use for the edge
table in DynamoDB.
db_url (str: _DEFAULT_SQL_URL): The URL to use for the SQL db.
primary_key (str: "ID"): The default primary key to use for the
tables. Note that this key cannot exist in your metadata dicts.
"""
self._directed = directed
self._node_table_name = node_table_name or "grand_Nodes"
self._edge_table_name = edge_table_name or "grand_Edges"
self._primary_key = primary_key
self._edge_source_key = "Source"
self._edge_target_key = "Target"
sqlalchemy_kwargs = sqlalchemy_kwargs or {}
self._engine = sqlalchemy.create_engine(db_url, **sqlalchemy_kwargs)
self._connection = self._engine.connect()
self._metadata = sqlalchemy.MetaData()
if not self._engine.dialect.has_table(self._connection, self._node_table_name):
self._node_table = sqlalchemy.Table(
self._node_table_name,
self._metadata,
sqlalchemy.Column(
self._primary_key,
sqlalchemy.String(_DEFAULT_SQL_STR_LEN),
primary_key=True,
),
sqlalchemy.Column("_metadata", sqlalchemy.JSON),
)
self._node_table.create(self._engine)
else:
self._node_table = sqlalchemy.Table(
self._node_table_name,
self._metadata,
autoload=True,
autoload_with=self._engine,
)
if not self._engine.dialect.has_table(self._connection, self._edge_table_name):
self._edge_table = sqlalchemy.Table(
self._edge_table_name,
self._metadata,
sqlalchemy.Column(
self._primary_key,
sqlalchemy.String(_DEFAULT_SQL_STR_LEN),
primary_key=True,
),
sqlalchemy.Column("_metadata", sqlalchemy.JSON),
sqlalchemy.Column(
self._edge_source_key, sqlalchemy.String(_DEFAULT_SQL_STR_LEN)
),
sqlalchemy.Column(
self._edge_target_key, sqlalchemy.String(_DEFAULT_SQL_STR_LEN)
),
)
self._edge_table.create(self._engine)
else:
self._edge_table = sqlalchemy.Table(
self._edge_table_name,
self._metadata,
autoload=True,
autoload_with=self._engine,
)
# def __del__(self):
# self._connection.close()
def is_directed(self) -> bool:
"""
Return True if the backend graph is directed.
Arguments:
None
Returns:
bool: True if the backend graph is directed.
"""
return self._directed
def teardown(self, yes_i_am_sure: bool = False):
"""
Tear down this graph, deleting all evidence it once was here.
"""
if yes_i_am_sure:
self._node_table.drop(self._engine)
self._edge_table.drop(self._engine)
def add_node(self, node_name: Hashable, metadata: dict) -> Hashable:
"""
Add a new node to the graph.
Insert a new document into the nodes table.
Arguments:
node_name (Hashable): The ID of the node
metadata (dict: None): An optional dictionary of metadata
Returns:
Hashable: The ID of this node, as inserted
"""
self._connection.execute(
self._node_table.insert(),
**{self._primary_key: node_name, "_metadata": metadata},
)
return node_name
def all_nodes_as_iterable(self, include_metadata: bool = False) -> Generator:
"""
Get a generator of all of the nodes in this graph.
Arguments:
include_metadata (bool: False): Whether to include node metadata in
the response
Returns:
Generator: A generator of all nodes (arbitrary sort)
"""
results = self._connection.execute(self._node_table.select()).fetchall()
if include_metadata:
return [(row[self._primary_key], row["_metadata"]) for row in results]
return [row[self._primary_key] for row in results]
def has_node(self, u: Hashable) -> bool:
"""
Return true if the node exists in the graph.
Arguments:
u (Hashable): The ID of the node to check
Returns:
bool: True if the node exists
"""
return len(
self._connection.execute(
self._node_table.select().where(
self._node_table.c[self._primary_key] == u
)
).fetchall()
)
def add_edge(self, u: Hashable, v: Hashable, metadata: dict):
"""
Add a new edge to the graph between two nodes.
If the graph is directed, this edge will start (source) at the `u` node
and end (target) at the `v` node.
Arguments:
u (Hashable): The source node ID
v (Hashable): The target node ID
metadata (dict): Optional metadata to associate with the edge
Returns:
Hashable: The edge ID, as inserted.
"""
pk = f"__{u}__{v}"
if not self.has_node(u):
self.add_node(u, {})
if not self.has_node(v):
self.add_node(v, {})
try:
self._connection.execute(
self._edge_table.insert(),
**{
self._primary_key: pk,
self._edge_source_key: u,
self._edge_target_key: v,
"_metadata": metadata,
},
)
except sqlalchemy.exc.IntegrityError:
# Edge already exists
pass
return pk
def all_edges_as_iterable(self, include_metadata: bool = False) -> Generator:
"""
Get a list of all edges in this graph, arbitrary sort.
Arguments:
include_metadata (bool: False): Whether to include edge metadata
Returns:
Generator: A generator of all edges (arbitrary sort)
"""
return iter(
[
(e.Source, e.Target, e._metadata)
if include_metadata
else (e.Source, e.Target)
for e in self._connection.execute(self._edge_table.select()).fetchall()
]
)
def get_node_by_id(self, node_name: Hashable):
"""
Return the data associated with a node.
Arguments:
node_name (Hashable): The node ID to look up
Returns:
dict: The metadata associated with this node
"""
res = (
self._connection.execute(
self._node_table.select().where(
self._node_table.c[self._primary_key] == node_name
)
)
.fetchone()
._metadata
)
return res
def get_edge_by_id(self, u: Hashable, v: Hashable):
"""
Get an edge by its source and target IDs.
Arguments:
u (Hashable): The source node ID
v (Hashable): The target node ID
Returns:
dict: Metadata associated with this edge
"""
if self._directed:
return (
self._connection.execute(
self._edge_table.select().where(
and_(
(self._edge_table.c[self._edge_source_key] == u),
(self._edge_table.c[self._edge_target_key] == v),
)
)
)
.fetchone()
._metadata
)
else:
return (
self._connection.execute(
self._edge_table.select().where(
or_(
and_(
(self._edge_table.c[self._edge_source_key] == u),
(self._edge_table.c[self._edge_target_key] == v),
),
and_(
(self._edge_table.c[self._edge_source_key] == v),
(self._edge_table.c[self._edge_target_key] == u),
),
)
)
)
.fetchone()
._metadata
)
def get_node_neighbors(
self, u: Hashable, include_metadata: bool = False
) -> Generator:
"""
Get a generator of all downstream nodes from this node.
Arguments:
u (Hashable): The source node ID
Returns:
Generator
"""
if self._directed:
res = self._connection.execute(
self._edge_table.select().where(
self._edge_table.c[self._edge_source_key] == u
)
).fetchall()
else:
res = self._connection.execute(
self._edge_table.select().where(
or_(
(self._edge_table.c[self._edge_source_key] == u),
(self._edge_table.c[self._edge_target_key] == u),
)
)
).fetchall()
if include_metadata:
return {
(
r[self._edge_source_key]
if r[self._edge_source_key] != u
else r[self._edge_target_key]
): r["_metadata"]
for r in res
}
return iter(
[
(
r[self._edge_source_key]
if r[self._edge_source_key] != u
else r[self._edge_target_key]
)
for r in res
]
)
def get_node_predecessors(
self, u: Hashable, include_metadata: bool = False
) -> Generator:
"""
Get a generator of all upstream nodes from this node.
Arguments:
u (Hashable): The source node ID
Returns:
Generator
"""
if self._directed:
res = self._connection.execute(
self._edge_table.select().where(
self._edge_table.c[self._edge_target_key] == u
)
).fetchall()
else:
res = self._connection.execute(
self._edge_table.select().where(
or_(
(self._edge_table.c[self._edge_target_key] == u),
(self._edge_table.c[self._edge_source_key] == u),
)
)
).fetchall()
if include_metadata:
return {
(
r[self._edge_source_key]
if r[self._edge_source_key] != u
else r[self._edge_target_key]
): r["_metadata"]
for r in res
}
return iter(
[
(
r[self._edge_source_key]
if r[self._edge_source_key] != u
else r[self._edge_target_key]
)
for r in res
]
)
def get_node_count(self) -> Iterable:
"""
Get an integer count of the number of nodes in this graph.
Arguments:
None
Returns:
int: The count of nodes
"""
return self._connection.execute(
select([func.count()]).select_from(self._node_table)
).scalar()
def ingest_from_edgelist_dataframe(
self, edgelist: pd.DataFrame, source_column: str, target_column: str
) -> None:
"""
Ingest an edgelist from a Pandas DataFrame.
"""
# Produce edge list:
edge_tic = time.time()
newlist = edgelist.rename(
columns={
source_column: self._edge_source_key,
target_column: self._edge_target_key,
}
)
newlist[self._primary_key] = edgelist.apply(
lambda x: f"__{x[source_column]}__{x[target_column]}", axis="columns"
)
newlist["_metadata"] = edgelist.apply(
lambda x: {
k: v for k, v in x.items() if k not in [source_column, target_column]
},
axis="columns",
)
newlist[
[
self._edge_source_key,
self._edge_target_key,
self._primary_key,
"_metadata",
]
].to_sql(
self._edge_table_name,
self._engine,
index=False,
if_exists="append",
dtype={"_metadata": sqlalchemy.JSON},
)
edge_toc = time.time() - edge_tic
# now ingest nodes:
node_tic = time.time()
nodes = edgelist[source_column].append(edgelist[target_column]).unique()
pd.DataFrame(
[
{
self._primary_key: node,
# no metadata:
"_metadata": {},
}
for node in nodes
]
).to_sql(
self._node_table_name,
self._engine,
index=False,
if_exists="replace",
dtype={"_metadata": sqlalchemy.JSON},
)
return {
"node_count": len(nodes),
"node_duration": time.time() - node_tic,
"edge_count": len(edgelist),
"edge_duration": edge_toc,
}