Files
superset2/superset/db_engine_specs/postgres.py
2026-02-03 12:22:49 -08:00

781 lines
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Python

# Licensed to the Apache Software Foundation (ASF) under one
# or more contributor license agreements. See the NOTICE file
# distributed with this work for additional information
# regarding copyright ownership. The ASF licenses this file
# to you under the Apache License, Version 2.0 (the
# "License"); you may not use this file except in compliance
# with the License. You may obtain a copy of the License at
#
# http://www.apache.org/licenses/LICENSE-2.0
#
# Unless required by applicable law or agreed to in writing,
# software distributed under the License is distributed on an
# "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY
# KIND, either express or implied. See the License for the
# specific language governing permissions and limitations
# under the License.
from __future__ import annotations
import logging
import re
from datetime import datetime
from re import Pattern
from typing import Any, Optional, TYPE_CHECKING
from flask_babel import gettext as __
from sqlalchemy.dialects.postgresql import DOUBLE_PRECISION, ENUM, JSON
from sqlalchemy.dialects.postgresql.base import PGInspector
from sqlalchemy.engine.reflection import Inspector
from sqlalchemy.engine.url import URL
from sqlalchemy.types import Date, DateTime, String
from superset.constants import TimeGrain
from superset.db_engine_specs.base import (
BaseEngineSpec,
BasicParametersMixin,
DatabaseCategory,
)
from superset.errors import ErrorLevel, SupersetError, SupersetErrorType
from superset.exceptions import SupersetException, SupersetSecurityException
from superset.models.sql_lab import Query
from superset.sql.parse import process_jinja_sql
from superset.utils import core as utils, json
from superset.utils.core import GenericDataType, QuerySource
if TYPE_CHECKING:
from superset.models.core import Database # pragma: no cover
logger = logging.getLogger()
# Regular expressions to catch custom errors
CONNECTION_INVALID_USERNAME_REGEX = re.compile(
'role "(?P<username>.*?)" does not exist'
)
CONNECTION_INVALID_PASSWORD_REGEX = re.compile(
'password authentication failed for user "(?P<username>.*?)"'
)
CONNECTION_INVALID_PASSWORD_NEEDED_REGEX = re.compile("no password supplied")
CONNECTION_INVALID_HOSTNAME_REGEX = re.compile(
'could not translate host name "(?P<hostname>.*?)" to address: '
"nodename nor servname provided, or not known"
)
CONNECTION_PORT_CLOSED_REGEX = re.compile(
r"could not connect to server: Connection refused\s+Is the server "
r'running on host "(?P<hostname>.*?)" (\(.*?\) )?and accepting\s+TCP/IP '
r"connections on port (?P<port>.*?)\?"
)
CONNECTION_HOST_DOWN_REGEX = re.compile(
r"could not connect to server: (?P<reason>.*?)\s+Is the server running on "
r'host "(?P<hostname>.*?)" (\(.*?\) )?and accepting\s+TCP/IP '
r"connections on port (?P<port>.*?)\?"
)
CONNECTION_UNKNOWN_DATABASE_REGEX = re.compile(
'database "(?P<database>.*?)" does not exist'
)
COLUMN_DOES_NOT_EXIST_REGEX = re.compile(
r'postgresql error: column "(?P<column_name>.+?)" '
r"does not exist\s+LINE (?P<location>\d+?)"
)
SYNTAX_ERROR_REGEX = re.compile('syntax error at or near "(?P<syntax_error>.*?)"')
def parse_options(connect_args: dict[str, Any]) -> dict[str, str]:
"""
Parse ``options`` from ``connect_args`` into a dictionary.
"""
if not isinstance(connect_args.get("options"), str):
return {}
tokens = (
tuple(token.strip() for token in option.strip().split("=", 1))
for option in re.split(r"-c\s?", connect_args["options"])
if "=" in option
)
return {token[0]: token[1] for token in tokens}
class PostgresBaseEngineSpec(BaseEngineSpec):
"""Abstract class for Postgres 'like' databases"""
engine = ""
engine_name = "PostgreSQL"
supports_multivalues_insert = True
_time_grain_expressions = {
None: "{col}",
TimeGrain.SECOND: "DATE_TRUNC('second', {col})",
TimeGrain.FIVE_SECONDS: "DATE_TRUNC('minute', {col}) + INTERVAL '5 seconds' * FLOOR(EXTRACT(SECOND FROM {col}) / 5)", # noqa: E501
TimeGrain.THIRTY_SECONDS: "DATE_TRUNC('minute', {col}) + INTERVAL '30 seconds' * FLOOR(EXTRACT(SECOND FROM {col}) / 30)", # noqa: E501
TimeGrain.MINUTE: "DATE_TRUNC('minute', {col})",
TimeGrain.FIVE_MINUTES: "DATE_TRUNC('hour', {col}) + INTERVAL '5 minutes' * FLOOR(EXTRACT(MINUTE FROM {col}) / 5)", # noqa: E501
TimeGrain.TEN_MINUTES: "DATE_TRUNC('hour', {col}) + INTERVAL '10 minutes' * FLOOR(EXTRACT(MINUTE FROM {col}) / 10)", # noqa: E501
TimeGrain.FIFTEEN_MINUTES: "DATE_TRUNC('hour', {col}) + INTERVAL '15 minutes' * FLOOR(EXTRACT(MINUTE FROM {col}) / 15)", # noqa: E501
TimeGrain.THIRTY_MINUTES: "DATE_TRUNC('hour', {col}) + INTERVAL '30 minutes' * FLOOR(EXTRACT(MINUTE FROM {col}) / 30)", # noqa: E501
TimeGrain.HOUR: "DATE_TRUNC('hour', {col})",
TimeGrain.DAY: "DATE_TRUNC('day', {col})",
TimeGrain.WEEK: "DATE_TRUNC('week', {col})",
TimeGrain.MONTH: "DATE_TRUNC('month', {col})",
TimeGrain.QUARTER: "DATE_TRUNC('quarter', {col})",
TimeGrain.YEAR: "DATE_TRUNC('year', {col})",
}
custom_errors: dict[Pattern[str], tuple[str, SupersetErrorType, dict[str, Any]]] = {
CONNECTION_INVALID_USERNAME_REGEX: (
__('The username "%(username)s" does not exist.'),
SupersetErrorType.CONNECTION_INVALID_USERNAME_ERROR,
{"invalid": ["username"]},
),
CONNECTION_INVALID_PASSWORD_REGEX: (
__('The password provided for username "%(username)s" is incorrect.'),
SupersetErrorType.CONNECTION_INVALID_PASSWORD_ERROR,
{"invalid": ["username", "password"]},
),
CONNECTION_INVALID_PASSWORD_NEEDED_REGEX: (
__("Please re-enter the password."),
SupersetErrorType.CONNECTION_ACCESS_DENIED_ERROR,
{"invalid": ["password"]},
),
CONNECTION_INVALID_HOSTNAME_REGEX: (
__('The hostname "%(hostname)s" cannot be resolved.'),
SupersetErrorType.CONNECTION_INVALID_HOSTNAME_ERROR,
{"invalid": ["host"]},
),
CONNECTION_PORT_CLOSED_REGEX: (
__('Port %(port)s on hostname "%(hostname)s" refused the connection.'),
SupersetErrorType.CONNECTION_PORT_CLOSED_ERROR,
{"invalid": ["host", "port"]},
),
CONNECTION_HOST_DOWN_REGEX: (
__(
'The host "%(hostname)s" might be down, and can\'t be '
"reached on port %(port)s."
),
SupersetErrorType.CONNECTION_HOST_DOWN_ERROR,
{"invalid": ["host", "port"]},
),
CONNECTION_UNKNOWN_DATABASE_REGEX: (
__('Unable to connect to database "%(database)s".'),
SupersetErrorType.CONNECTION_UNKNOWN_DATABASE_ERROR,
{"invalid": ["database"]},
),
COLUMN_DOES_NOT_EXIST_REGEX: (
__(
'We can\'t seem to resolve the column "%(column_name)s" at '
"line %(location)s.",
),
SupersetErrorType.COLUMN_DOES_NOT_EXIST_ERROR,
{},
),
SYNTAX_ERROR_REGEX: (
__(
"Please check your query for syntax errors at or "
'near "%(syntax_error)s". Then, try running your query again.'
),
SupersetErrorType.SYNTAX_ERROR,
{},
),
}
@classmethod
def fetch_data(cls, cursor: Any, limit: int | None = None) -> list[tuple[Any, ...]]:
if not cursor.description:
return []
return super().fetch_data(cursor, limit)
@classmethod
def epoch_to_dttm(cls) -> str:
return "(timestamp 'epoch' + {col} * interval '1 second')"
@classmethod
def convert_dttm(
cls, target_type: str, dttm: datetime, db_extra: dict[str, Any] | None = None
) -> str | None:
sqla_type = cls.get_sqla_column_type(target_type)
if isinstance(sqla_type, Date):
return f"TO_DATE('{dttm.date().isoformat()}', 'YYYY-MM-DD')"
if isinstance(sqla_type, DateTime):
dttm_formatted = dttm.isoformat(sep=" ", timespec="microseconds")
return f"""TO_TIMESTAMP('{dttm_formatted}', 'YYYY-MM-DD HH24:MI:SS.US')"""
return None
class PostgresEngineSpec(BasicParametersMixin, PostgresBaseEngineSpec):
engine = "postgresql"
engine_name = "PostgreSQL"
engine_aliases = {"postgres"}
supports_dynamic_schema = True
supports_catalog = True
supports_dynamic_catalog = True
default_driver = "psycopg2"
sqlalchemy_uri_placeholder = (
"postgresql://user:password@host:port/dbname[?key=value&key=value...]"
)
metadata = {
"description": "PostgreSQL is an advanced open-source relational database.",
"logo": "postgresql.svg",
"homepage_url": "https://www.postgresql.org/",
"categories": [
DatabaseCategory.TRADITIONAL_RDBMS,
DatabaseCategory.OPEN_SOURCE,
],
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
"default_port": 5432,
"parameters": {
"username": "Database username",
"password": "Database password",
"host": "For localhost: localhost or 127.0.0.1. For AWS: endpoint URL",
"port": "Default 5432",
"database": "Database name",
},
"notes": "The psycopg2 library comes bundled with Superset Docker images.",
"connection_examples": [
{
"description": "Basic connection",
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
},
{
"description": "With SSL required",
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
"?sslmode=require"
),
},
],
"docs_url": "https://www.postgresql.org/docs/",
"sqlalchemy_docs_url": (
"https://docs.sqlalchemy.org/en/13/dialects/postgresql.html"
),
"compatible_databases": [
{
"name": "Hologres",
"description": (
"Alibaba Cloud real-time interactive analytics service, "
"fully compatible with PostgreSQL 11."
),
"logo": "hologres.png",
"homepage_url": "https://www.alibabacloud.com/product/hologres",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql+psycopg2://{username}:{password}"
"@{host}:{port}/{database}"
),
"parameters": {
"username": "AccessKey ID of your Alibaba Cloud account",
"password": "AccessKey secret of your Alibaba Cloud account",
"host": "Public endpoint of the Hologres instance",
"port": "Port number of the Hologres instance",
"database": "Name of the Hologres database",
},
"categories": [DatabaseCategory.PROPRIETARY],
},
{
"name": "TimescaleDB",
"description": (
"Open-source relational database for time-series and analytics, "
"built on PostgreSQL."
),
"logo": "timescale.png",
"homepage_url": "https://www.timescale.com/",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
"connection_examples": [
{
"description": "Timescale Cloud (SSL required)",
"connection_string": (
"postgresql://{username}:{password}"
"@{host}:{port}/{database}?sslmode=require"
),
},
],
"notes": "psycopg2 comes bundled with Superset Docker images.",
"docs_url": "https://docs.timescale.com/",
"categories": [DatabaseCategory.OPEN_SOURCE],
},
{
"name": "YugabyteDB",
"description": ("Distributed SQL database built on top of PostgreSQL."),
"logo": "yugabyte.png",
"homepage_url": "https://www.yugabyte.com/",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
"notes": "psycopg2 comes bundled with Superset Docker images.",
"docs_url": "https://www.yugabyte.com/",
"categories": [DatabaseCategory.OPEN_SOURCE],
},
{
"name": "Supabase",
"description": (
"Open-source Firebase alternative built on top of PostgreSQL, "
"providing a full backend-as-a-service with a hosted Postgres "
"database."
),
"logo": "supabase.svg",
"homepage_url": "https://supabase.com/",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
"connection_examples": [
{
"description": "Supabase project (connection pooler)",
"connection_string": (
"postgresql://{username}.{project_ref}:{password}"
"@aws-0-{region}.pooler.supabase.com:6543/{database}"
),
},
],
"parameters": {
"username": "Database user (default: postgres)",
"password": "Database password",
"host": "Supabase project host (from project settings)",
"port": "Default 5432 (direct) or 6543 (pooler)",
"database": "Database name (default: postgres)",
"project_ref": "Supabase project reference (from project settings)",
"region": "Supabase project region (e.g., us-east-1)",
},
"notes": (
"Find connection details in your Supabase project dashboard under "
"Settings > Database. Use the connection pooler (port 6543) for "
"better connection management."
),
"docs_url": "https://supabase.com/docs/guides/database/connecting-to-postgres",
"categories": [
DatabaseCategory.HOSTED_OPEN_SOURCE,
],
},
{
"name": "Google AlloyDB",
"description": (
"Google Cloud's PostgreSQL-compatible database service "
"for demanding transactional and analytical workloads."
),
"logo": "alloydb.png",
"homepage_url": "https://cloud.google.com/alloydb",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}@{host}:{port}/{database}"
),
"parameters": {
"username": "Database user (default: postgres)",
"password": "Database password",
"host": "AlloyDB instance IP or Auth Proxy address",
"port": "Default 5432",
"database": "Database name",
},
"notes": (
"For public IP connections, use the AlloyDB Auth Proxy for "
"secure access. Private IP connections can connect directly."
),
"docs_url": "https://cloud.google.com/alloydb/docs",
"categories": [
DatabaseCategory.CLOUD_GCP,
DatabaseCategory.HOSTED_OPEN_SOURCE,
],
},
{
"name": "Neon",
"description": (
"Serverless PostgreSQL with branching, scale-to-zero, "
"and bottomless storage."
),
"logo": "neon.png",
"homepage_url": "https://neon.tech/",
"pypi_packages": ["psycopg2"],
"connection_string": (
"postgresql://{username}:{password}"
"@{host}/{database}?sslmode=require"
),
"parameters": {
"username": "Neon role name",
"password": "Neon role password",
"host": (
"Neon hostname (e.g., "
"ep-cool-name-123456.us-east-2.aws.neon.tech)"
),
"database": "Database name (default: neondb)",
},
"notes": (
"SSL is required for all connections. Find connection "
"details in the Neon console under Connection Details."
),
"docs_url": "https://neon.tech/docs/connect/connect-from-any-app",
"categories": [
DatabaseCategory.HOSTED_OPEN_SOURCE,
],
},
{
"name": "Amazon Aurora PostgreSQL",
"description": (
"Amazon Aurora PostgreSQL is a fully managed, "
"PostgreSQL-compatible relational database with up to 5x "
"the throughput of standard PostgreSQL."
),
"logo": "aws-aurora.jpg",
"homepage_url": "https://aws.amazon.com/rds/aurora/",
"pypi_packages": ["sqlalchemy-aurora-data-api"],
"connection_string": (
"postgresql+auroradataapi://{aws_access_id}:{aws_secret_access_key}@/"
"{database_name}?aurora_cluster_arn={aurora_cluster_arn}&"
"secret_arn={secret_arn}&region_name={region_name}"
),
"parameters": {
"aws_access_id": "AWS Access Key ID",
"aws_secret_access_key": "AWS Secret Access Key",
"database_name": "Database name",
"aurora_cluster_arn": "Aurora cluster ARN",
"secret_arn": "Secrets Manager ARN for credentials",
"region_name": "AWS region (e.g., us-east-1)",
},
"notes": (
"Uses the Data API for serverless access. "
"Standard PostgreSQL connections also work with psycopg2."
),
"categories": [
DatabaseCategory.CLOUD_AWS,
DatabaseCategory.HOSTED_OPEN_SOURCE,
],
},
],
}
# https://www.postgresql.org/docs/9.1/libpq-ssl.html#LIBQ-SSL-CERTIFICATES
encryption_parameters = {"sslmode": "require"}
max_column_name_length = 63
try_remove_schema_from_table_name = False # pylint: disable=invalid-name
# Sensitive fields that should be masked in encrypted_extra.
# This follows the pattern used by other engine specs (bigquery, snowflake, etc.)
# that specify exact paths rather than using the base class's catch-all "$.*".
encrypted_extra_sensitive_fields = {
"$.aws_iam.external_id",
"$.aws_iam.role_arn",
}
column_type_mappings = (
(
re.compile(r"^double precision", re.IGNORECASE),
DOUBLE_PRECISION(),
GenericDataType.NUMERIC,
),
(
re.compile(r"^array.*", re.IGNORECASE),
String(),
GenericDataType.STRING,
),
(
re.compile(r"^json.*", re.IGNORECASE),
JSON(),
GenericDataType.STRING,
),
(
re.compile(r"^enum.*", re.IGNORECASE),
ENUM(),
GenericDataType.STRING,
),
)
@classmethod
def get_schema_from_engine_params(
cls,
sqlalchemy_uri: URL,
connect_args: dict[str, Any],
) -> str | None:
"""
Return the configured schema.
While Postgres doesn't support connecting directly to a given schema, it allows
users to specify a "search path" that is used to resolve non-qualified table
names; this can be specified in the database ``connect_args``.
One important detail is that the search path can be a comma separated list of
schemas. While this is supported by the SQLAlchemy dialect, it shouldn't be used
in Superset because it breaks schema-level permissions, since it's impossible
to determine the schema for a non-qualified table in a query. In cases like
that we raise an exception.
Note that because the DB engine supports dynamic schema this method is never
called. It's left here as an implementation reference.
"""
options = parse_options(connect_args)
if search_path := options.get("search_path"):
schemas = search_path.split(",")
if len(schemas) > 1:
raise Exception( # pylint: disable=broad-exception-raised
"Multiple schemas are configured in the search path, which means "
"Superset is unable to determine the schema of unqualified table "
"names and enforce permissions."
)
return schemas[0]
return None
@classmethod
def get_default_schema_for_query(
cls,
database: Database,
query: Query,
template_params: Optional[dict[str, Any]] = None,
) -> str | None:
"""
Return the default schema for a given query.
This method simply uses the parent method after checking that there are no
malicious path setting in the query.
"""
script = process_jinja_sql(query.sql, database, template_params).script
settings = script.get_settings()
if "search_path" in settings:
raise SupersetSecurityException(
SupersetError(
error_type=SupersetErrorType.QUERY_SECURITY_ACCESS_ERROR,
message=__(
"Users are not allowed to set a search path for security reasons." # noqa: E501
),
level=ErrorLevel.ERROR,
)
)
return super().get_default_schema_for_query(database, query, template_params)
@classmethod
def adjust_engine_params(
cls,
uri: URL,
connect_args: dict[str, Any],
catalog: str | None = None,
schema: str | None = None,
) -> tuple[URL, dict[str, Any]]:
"""
Set the catalog (database).
"""
if catalog:
uri = uri.set(database=catalog)
return uri, connect_args
@staticmethod
def update_params_from_encrypted_extra(
database: Database,
params: dict[str, Any],
) -> None:
"""
Extract sensitive parameters from encrypted_extra.
Handles AWS IAM authentication if configured, then merges any
remaining encrypted_extra keys into params (standard behavior).
"""
if not database.encrypted_extra:
return
try:
encrypted_extra = json.loads(database.encrypted_extra)
except json.JSONDecodeError as ex:
logger.error(ex, exc_info=True)
raise
# Handle AWS IAM auth: pop the key so it doesn't reach create_engine()
iam_config = encrypted_extra.pop("aws_iam", None)
if iam_config and iam_config.get("enabled"):
from superset.db_engine_specs.aws_iam import AWSIAMAuthMixin
# Preserve a stricter existing sslmode (e.g. verify-full) if present
connect_args = params.get("connect_args") or {}
previous_sslmode = connect_args.get("sslmode")
AWSIAMAuthMixin._apply_iam_authentication(
database,
params,
iam_config,
ssl_args={"sslmode": "require"},
default_port=5432,
)
# Restore stricter sslmode if it was previously configured
if previous_sslmode in ("verify-ca", "verify-full"):
params.setdefault("connect_args", {})["sslmode"] = previous_sslmode
# Standard behavior: merge remaining keys into params
if encrypted_extra:
params.update(encrypted_extra)
@classmethod
def get_default_catalog(cls, database: Database) -> str:
"""
Return the default catalog for a given database.
"""
return database.url_object.database
@classmethod
def get_prequeries(
cls,
database: Database,
catalog: str | None = None,
schema: str | None = None,
) -> list[str]:
"""
Set the search path to the specified schema.
This is important for two reasons: in SQL Lab it will allow queries to run in
the schema selected in the dropdown, resolving unqualified table names to the
expected schema.
But more importantly, in SQL Lab this is used to check if the user has access to
any tables with unqualified names. If the schema is not set by SQL Lab it could
be anything, and we would have to block users from running any queries
referencing tables without an explicit schema.
"""
return [f'set search_path = "{schema}"'] if schema else []
@classmethod
def get_allow_cost_estimate(cls, extra: dict[str, Any]) -> bool:
return True
@classmethod
def estimate_statement_cost(
cls, database: Database, statement: str, cursor: Any
) -> dict[str, Any]:
"""
Run a SQL query that estimates the cost of a given statement.
:param database: A Database object
:param statement: A single SQL statement
:param cursor: Cursor instance
:return: JSON response from Trino
"""
sql = f"EXPLAIN {statement}"
cursor.execute(sql)
result = cursor.fetchone()[0]
match = re.search(r"cost=([\d\.]+)\.\.([\d\.]+)", result)
if match:
return {
"Start-up cost": float(match.group(1)),
"Total cost": float(match.group(2)),
}
return {}
@classmethod
def query_cost_formatter(
cls, raw_cost: list[dict[str, Any]]
) -> list[dict[str, str]]:
return [{k: str(v) for k, v in row.items()} for row in raw_cost]
@classmethod
def get_catalog_names(
cls,
database: Database,
inspector: Inspector,
) -> set[str]:
"""
Return all catalogs.
In Postgres, a catalog is called a "database".
"""
return {
catalog
for (catalog,) in inspector.bind.execute(
"""
SELECT datname FROM pg_database
WHERE datistemplate = false;
"""
)
}
@classmethod
def get_table_names(
cls, database: Database, inspector: PGInspector, schema: str | None
) -> set[str]:
"""Need to consider foreign tables for PostgreSQL"""
return set(inspector.get_table_names(schema)) | set(
inspector.get_foreign_table_names(schema)
)
@staticmethod
def get_extra_params(
database: Database, source: QuerySource | None = None
) -> dict[str, Any]:
"""
For Postgres, the path to a SSL certificate is placed in `connect_args`.
:param database: database instance from which to extract extras
:raises CertificateException: If certificate is not valid/unparseable
:raises SupersetException: If database extra json payload is unparseable
"""
try:
extra = json.loads(database.extra or "{}")
except json.JSONDecodeError as ex:
raise SupersetException("Unable to parse database extras") from ex
if database.server_cert:
engine_params = extra.get("engine_params", {})
connect_args = engine_params.get("connect_args", {})
connect_args["sslmode"] = connect_args.get("sslmode", "verify-full")
path = utils.create_ssl_cert_file(database.server_cert)
connect_args["sslrootcert"] = path
engine_params["connect_args"] = connect_args
extra["engine_params"] = engine_params
return extra
@classmethod
def get_datatype(cls, type_code: Any) -> str | None:
# pylint: disable=import-outside-toplevel
from psycopg2.extensions import binary_types, string_types
types = binary_types.copy()
types.update(string_types)
if type_code in types:
return types[type_code].name
return None
@classmethod
def get_cancel_query_id(cls, cursor: Any, query: Query) -> str | None:
"""
Get Postgres PID that will be used to cancel all other running
queries in the same session.
:param cursor: Cursor instance in which the query will be executed
:param query: Query instance
:return: Postgres PID
"""
cursor.execute("SELECT pg_backend_pid()")
row = cursor.fetchone()
return row[0]
@classmethod
def cancel_query(cls, cursor: Any, query: Query, cancel_query_id: str) -> bool:
"""
Cancel query in the underlying database.
:param cursor: New cursor instance to the db of the query
:param query: Query instance
:param cancel_query_id: Postgres PID
:return: True if query cancelled successfully, False otherwise
"""
try:
cursor.execute(
"SELECT pg_terminate_backend(pid) " # noqa: S608
"FROM pg_stat_activity "
f"WHERE pid='{cancel_query_id}'"
)
except Exception: # pylint: disable=broad-except
return False
return True