What is Python MySQL - Insert Into?

Python MySQL - Insert Into is a MySQL lesson that explains python mysql - insert into in MySQL. Add rows safely with parameterized queries, and insert many rows at once. Copy the samples and run them in the MySQL editor. It is written for beginners who want a clear definition and working examples.

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Python Tutorial

Python MySQL - Insert Into

Add rows safely with parameterized queries, and insert many rows at once.

← MySQL Create Table MySQL Select →

Insert a Single Row

Use placeholders (%s) and pass the values separately — never build SQL with string formatting. After a write you must commit() to save it.

import mysql.connector

conn = mysql.connector.connect(
    host="localhost", user="root", password="secret", database="mydatabase")
cursor = conn.cursor()

sql = "INSERT INTO customers (name, address) VALUES (%s, %s)"
values = ("John", "Highway 21")
cursor.execute(sql, values)

conn.commit()                       # save the change
print(cursor.rowcount, "record inserted.")   # 1 record inserted.

Placeholders are always %s regardless of the Python type — do not add quotes around them. This is what prevents SQL injection.

Why Parameterized Queries Matter

Building SQL by concatenation lets malicious input change your query — a SQL injection attack. The driver escapes parameterized values for you.

# DANGEROUS - never do this:
# cursor.execute("INSERT INTO customers (name) VALUES ('" + name + "')")

# SAFE:
cursor.execute("INSERT INTO customers (name) VALUES (%s)", (name,))

Insert Many Rows with executemany

Passing a list of tuples to executemany is far faster than a loop of single inserts.

sql = "INSERT INTO customers (name, address) VALUES (%s, %s)"
rows = [
    ("Peter", "Lowstreet 4"),
    ("Amy",   "Apple st 652"),
    ("Hannah","Mountain 21"),
]
cursor.executemany(sql, rows)
conn.commit()
print(cursor.rowcount, "records inserted.")   # 3 records inserted.

Get the Inserted ID

After inserting into a table with an auto-increment key, read the new id from cursor.lastrowid.

cursor.execute("INSERT INTO customers (name) VALUES (%s)", ("Mia",))
conn.commit()
print("New id:", cursor.lastrowid)

Transactions: All or Nothing

Group related writes so they either all succeed or all roll back, keeping data consistent.

try:
    cursor.execute("INSERT INTO customers (name) VALUES (%s)", ("A",))
    cursor.execute("INSERT INTO customers (name) VALUES (%s)", ("B",))
    conn.commit()                   # commit both together
except mysql.connector.Error:
    conn.rollback()                 # undo everything on any failure
    raise

Best Practices

Always use %s placeholders — never string formatting.
Call commit() after inserts/updates/deletes, or nothing is saved.
Use executemany for bulk inserts.
Wrap multi-step writes in a try/except with rollback().

Try It Yourself

Exercise 1: What is wrong with "INSERT INTO t (name) VALUES ('" + name + "')"?

Show solution

It is vulnerable to SQL injection. Use a placeholder instead: cursor.execute("INSERT INTO t (name) VALUES (%s)", (name,)).

Exercise 2: After inserting rows, what must you call to save them?

Show solution

conn.commit() — without it the changes are rolled back when the connection closes.

📘 Real-World Deep Dive

Knowing <strong>MySQL Insert (MySQL)</strong> well is what turns MySQL from a curiosity into a daily tool — you'll reach for it in nearly every real project.

Real-Life Scenario

An end-to-end usage of MySQL Insert that you'd actually see in a data pipeline or analytics notebook.

Real-Life Example

import mysql.connector
conn = mysql.connector.connect(database="shop")
cur = conn.cursor()
cur.executemany(
    "INSERT INTO users (name, email) VALUES (%s, %s)",
    [("Ada", "ada@x"), ("Bo", "bo@x")],
)
conn.commit(); print("rows:", cur.rowcount)

Expected Output

(see source)

Common mistakes

Reading with the default cursor returns tuples — switch to DictCursor for named access.
Strings without parameter binding produce SQL-injection holes — never use f-strings in queries.
Connecting through a long-lived daemon pool: make sure pool_reset_connection is on to avoid session state leakage.
Treating MySQL Insert as a black box without reading the docs — the API has subtle defaults that bite when you scale.

🚀 Performance & Best Practices

Use prepared statements (cursor.executemany) for bulk inserts.
Fetch with cursor.fetchmany(1000) in streams instead of fetchall().
Use pymysql's server-side cursors for very large result sets.
When working with MySQL, prefer vectorised / batched operations over Python loops.

🧪 Try It Yourself

Reproduce the snippet on a representative slice of your own data.
Profile the snippet with cProfile or timeit and find the single biggest improvement.
Generalise the snippet into a small, reusable function you can drop into future projects.