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Psycopg source code is annotated according to PEP 0484 type hints and is checked using the current version of Mypy in --strict mode.

If your application is checked using Mypy too you can make use of Psycopg types to validate the correct use of Psycopg objects and of the data returned by the database.


Psycopg Connection and Cursor objects are Generic objects and support a Row parameter which is the type of the records returned.

By default methods such as Cursor.fetchall() return normal tuples of unknown size and content. As such, the connect() function returns an object of type psycopg.Connection[Tuple[Any, ...]] and Connection.cursor() returns an object of type psycopg.Cursor[Tuple[Any, ...]]. If you are writing generic plumbing code it might be practical to use annotations such as Connection[Any] and Cursor[Any].

conn = psycopg.connect() # type is psycopg.Connection[Tuple[Any, ...]]

cur = conn.cursor()      # type is psycopg.Cursor[Tuple[Any, ...]]

rec = cur.fetchone()     # type is Optional[Tuple[Any, ...]]

recs = cur.fetchall()    # type is List[Tuple[Any, ...]]


If you want to use connections and cursors returning your data as different types, for instance as dictionaries, you can use the row_factory argument of the connect() and the cursor() method, which will control what type of record is returned by the fetch methods of the cursors and annotate the returned objects accordingly. See Row factories for more details.

dconn = psycopg.connect(row_factory=dict_row)
# dconn type is psycopg.Connection[Dict[str, Any]]

dcur = conn.cursor(row_factory=dict_row)
dcur = dconn.cursor()
# dcur type is psycopg.Cursor[Dict[str, Any]] in both cases

drec = dcur.fetchone()
# drec type is Optional[Dict[str, Any]]

示例:将记录作为 Pydantic 模型返回

Using Pydantic it is possible to enforce static typing at runtime. Using a Pydantic model factory the code can be checked statically using Mypy and querying the database will raise an exception if the rows returned is not compatible with the model.

The following example can be checked with mypy --strict without reporting any issue. Pydantic will also raise a runtime error in case the Person is used with a query that returns incompatible data.

from datetime import date
from typing import Optional

import psycopg
from psycopg.rows import class_row
from pydantic import BaseModel

class Person(BaseModel):
    id: int
    first_name: str
    last_name: str
    dob: Optional[date]

def fetch_person(id: int) -> Person:
    with psycopg.connect() as conn:
        with conn.cursor(row_factory=class_row(Person)) as cur:
                SELECT id, first_name, last_name, dob
                FROM (VALUES
                    (1, 'John', 'Doe', '2000-01-01'::date),
                    (2, 'Jane', 'White', NULL)
                ) AS data (id, first_name, last_name, dob)
                WHERE id = %(id)s;
                {"id": id},
            obj = cur.fetchone()

            # reveal_type(obj) would return 'Optional[Person]' here

            if not obj:
                raise KeyError(f"person {id} not found")

            # reveal_type(obj) would return 'Person' here

            return obj

for id in [1, 2]:
    p = fetch_person(id)
    if p.dob:
        print(f"{p.first_name} was born in {p.dob.year}")
        print(f"Who knows when {p.first_name} was born")


The execute() method and similar should only receive a literal string as input, according to PEP 675. This means that the query should come from a literal string in your code, not from an arbitrary string expression.

For instance, passing an argument to the query should be done via the second argument to execute(), not by string composition:

def get_record(conn: psycopg.Connection[Any], id: int) -> Any:
    cur = conn.execute("SELECT * FROM my_table WHERE id = %s" % id)  # BAD!
    return cur.fetchone()

# the function should be implemented as:

def get_record(conn: psycopg.Connection[Any], id: int) -> Any:
    cur = conn.execute("select * FROM my_table WHERE id = %s", (id,))
    return cur.fetchone()

If you are composing a query dynamically you should use the sql.SQL object and similar to escape safely table and field names. The parameter of the SQL() object should be a literal string:

def count_records(conn: psycopg.Connection[Any], table: str) -> int:
    query = "SELECT count(*) FROM %s" % table  # BAD!
    return conn.execute(query).fetchone()[0]

# the function should be implemented as:

def count_records(conn: psycopg.Connection[Any], table: str) -> int:
    query = sql.SQL("SELECT count(*) FROM {}").format(sql.Identifier(table))
    return conn.execute(query).fetchone()[0]

At the time of writing, no Python static analyzer implements this check (mypy doesn’t implement it, Pyre does, but doesn’t work with psycopg yet). Once the type checkers support will be complete, the above bad statements should be reported as errors.