Read CSV rows as dictionaries.
Read a CSV file using its header row as dictionary keys, so each column can be accessed by name.
import csv
with open("people.csv", newline="", encoding="utf-8") as file:
for row in csv.DictReader(file):
print(f"{row['name']}: {row['city']}")Expected output EXAMPLE
Ada: London Grace: New York
Details
Uses only the Python standard library; no pip packages are required. See the verification record below for the exact Python version tested.
Use a people.csv file with name and city headers. newline="" lets the csv module handle line endings correctly.
Tested on Ubuntu 24.04.5 LTS · · Python 3.12.3 · python3 3.12.3-0ubuntu2.1
Test inputs, results and environment
The exact published code ran in a dedicated Linux test container with prepared inputs. Unprivileged snippet process, external networking disabled, read-only root filesystem, and a fresh temporary working directory. Fixtures and output records are isolated from the application database. Testing covers this example and its stated checks, not every input, operating system, or runtime version. The Linux container shares its host's kernel; this is not a native Windows test.
- Architecture / host kernel
- x86_64 / 6.18.54.1-microsoft-standard-WSL2
- Snippet identity / locale
- uid=65534, gid=65534 (unprivileged) / C.UTF-8
- Interpreter invocation
python3 -c <published code>- Container image ID
sha256:32dc2d998158b6554c99b73b533f423696a0f3e31e8cbea9db10b5eee9a2fadd- Code SHA-256
842bc3cc099fb1c752e047e6488a94cbc1f5be5cd17511fe6d8bda84d536d218- Dependencies
- python3 3.12.3-0ubuntu2.1
Test input setup
These are the prepared inputs used by the test harness. See Details above for the prerequisites and how to run this example.
printf 'name,city\nAda,London\nGrace,New York\n' > people.csv
Observed standard output
Ada: London Grace: New York
Exit code: 0. Standard error: empty. Validation: Exact stdout comparison. System-dependent values above are one recorded run.