How to Parse a String in Python

To parse a string in Python, break it into pieces with split(), clean each piece with strip(), then convert the pieces you need with int() or float(). For patterns, use the re module:

qty, price = "3, 24.99".split(",")
total = int(qty) * float(price)   # 74.97

Every script below ran in Command Prompt on Python 3.12.5. Save each one as a .py file and run it with python file.py to follow along.

In this tutorial, we’ll parse an order line, key=value settings, a log entry with regex, JSON and date strings, and messy numbers that would crash int().

Parse a delimited string with split() and strip()

For a comma-separated order line, split it, strip the spaces, and unpack the parts:

line = "1042, Emily Carter, Austin TX, 3, 24.99"

order_id, name, city, qty, price = [part.strip() for part in line.split(",")]
qty, price = int(qty), float(price)

print(order_id, name, city, sep=" | ")
print(f"{qty} x ${price:.2f} = ${qty * price:.2f}")

print("Austin TX 78701".split(maxsplit=1))   # stop after the first split

Output:

1042 | Emily Carter | Austin TX
3 x $24.99 = $74.97
['Austin', 'TX 78701']

maxsplit=1 splits once, so the state and ZIP code stay together. There’s more on separators in splitting a string by comma in Python.

Parse key=value text with partition()

partition() splits at the first separator only and always returns three parts, so it won’t raise an error when the separator is missing:

settings = ["region = us-east", "timeout=30", "debug"]

for s in settings:
    key, sep, value = s.partition("=")
    print(repr(key.strip()), repr(value.strip()), "found" if sep else "no '='")

path = "reports/2026/october/sales.csv"
folder, _, filename = path.rpartition("/")
print(folder, "->", filename)

Output:

'region' 'us-east' found
'timeout' '30' found
'debug' '' no '='
reports/2026/october -> sales.csv

rpartition() splits at the last separator, handy for paths. To grab text between two markers instead, see extracting a substring between two characters.

How do you parse a string with regular expressions?

When fields don’t share one delimiter, use a regex. Named groups give you a dictionary, and findall() collects every key=value pair:

import re

log = "2026-10-23 08:15:42 INFO order=1042 user=ecarter total=$74.97"

m = re.search(r"(?P<date>\d{4}-\d{2}-\d{2}) (?P<time>[\d:]+) (?P<level>\w+)", log)
print(m.groupdict())

fields = dict(re.findall(r"(\w+)=(\S+)", log))
print(fields)
print("Total as a number:", float(fields["total"].lstrip("$")))

Output:

{'date': '2026-10-23', 'time': '08:15:42', 'level': 'INFO'}
{'order': '1042', 'user': 'ecarter', 'total': '$74.97'}
Total as a number: 74.97

Strip the dollar sign before float(). For more patterns, read regular expressions in Python, or extracting numbers from a string if digits are all you need.

Parse JSON, list and date strings with the standard library

Don’t split structured text by hand; the standard library has a parser for each format:

import ast
import json
from datetime import datetime

payload = '{"customer": "James Miller", "state": "OH", "paid": true, "amount": 129.50}'
data = json.loads(payload)
print(data["customer"], data["paid"], data["amount"])

items = ast.literal_eval("['laptop', 'mouse', 'monitor']")
print(items, type(items).__name__)

shipped = datetime.strptime("10/23/2026 2:30 PM", "%m/%d/%Y %I:%M %p")
print(shipped, shipped.strftime("%A"))

Output:

James Miller True 129.5
['laptop', 'mouse', 'monitor'] list
2026-10-23 14:30:00 Friday

I use ast.literal_eval(), never eval(), on untrusted text. There are more JSON examples in converting a JSON string to a dictionary and format codes in converting a string to datetime in Python.

Parse numbers from a string without crashing

User input breaks int() fast. Wrap it in try/except ValueError to return a default instead of crashing:

def to_int(text, default=None):
    try:
        return int(text)
    except ValueError:
        return default

for raw in [" 42 ", "3.5", "N/A", "-7", "1,200"]:
    print(f"{raw!r:>8} -> {to_int(raw)}")

Output:

  ' 42 ' -> 42
   '3.5' -> None
   'N/A' -> None
    '-7' -> -7
 '1,200' -> None

int() already ignores surrounding spaces, but not decimals or thousands separators. Remove commas first, as shown in removing commas from a string in Python.

Which Python string parsing method should you use?

Input	Method	Returns
a, b, c	split() + strip()	list of strings
key=value	partition()	3-part tuple
Mixed text, logs	re.search(), re.findall()	match, list
JSON	json.loads()	dict or list
Dates	datetime.strptime()	datetime

A few more string guides pair well with this one:

• Split a string with regex in Python
• Split strings with multiple delimiters
• Convert a string to a list in Python
• Convert a string to an integer in Python

Frequently asked questions