CSV ingestion
Import records from spreadsheet exports into backend or scripting workflows.
Python · Module
csv
Python’s csv module reads and writes tabular data in CSV format, supporting both sequence rows and dictionary rows. Dialects and formatting parameters adapt it to different CSV conventions.
How it works
The csv module converts between CSV text and Python sequences or dictionaries. Use reader and writer for positional rows, or DictReader and DictWriter when column names should map to dictionary keys; dialect and formatting options control how fields are separated and quoted.
Syntax
csv.reader(csvfile, dialect='excel', **fmtparams)
csv.writer(csvfile, dialect='excel', **fmtparams)
csv.DictReader(f, fieldnames=None, restkey=None, restval=None, dialect='excel', *args, **kwds)
csv.DictWriter(f, fieldnames, restval='', extrasaction='raise', dialect='excel', *args, **kwds)Parameters
| Name | Type | Description |
|---|---|---|
csvfile | iterable | Input iterable or file-like object containing CSV lines. |
dialect | str or Dialect | Optional dialect name or dialect object controlling CSV formatting. |
fmtparams | keyword arguments | Additional formatting controls such as delimiter, quotechar, quoting, and lineterminator. |
Returns
reader() returns a reader object; writer() returns a writer object; DictReader yields dictionaries; DictWriter writes dictionary rows.
Key points
- reader and writer provide sequence-based row processing.
- DictReader and DictWriter support column-oriented dictionary workflows.
- csv.reader creates an iterator-like reader over the supplied input.
- csv.writer serializes supplied row data into delimited output.
- DictReader turns each input row into a dictionary keyed by field names.
Common mistakes
- Open file objects with newline='' when passing them to the CSV reader or writer so newline handling remains correct.
- When writing rows, a None value becomes an empty field and cannot be distinguished from an originally empty string.
Example: Read and rewrite CSV rows
import csv
from io import StringIO
source = StringIO("name,age\nAda,36\nGrace,28\n")
rows = csv.DictReader(source)
output = StringIO()
writer = csv.DictWriter(output, fieldnames=["name", "age"])
writer.writeheader()
writer.writerows(rows)
print(output.getvalue(), end="")Reads CSV rows as dictionaries, then writes them with an explicit header.
When to use it
CSV export
Generate files compatible with spreadsheet applications and other CSV consumers.
Named-column transformation
Transform rows while retaining named columns for clearer application logic.
Interview questions
QWhich csv APIs handle positional rows versus named columns?
Use csv.reader for rows represented as sequences and csv.writer to emit sequences. Use DictReader and DictWriter when fields should be addressed by column names.
Follow-up: How would you preserve a supplied schema when writing? Pass fieldnames to DictWriter and call writeheader() before writerows().
QWhat do reader and writer produce or consume?
A reader consumes lines from a CSV input and returns each row as a list of strings by default. A writer accepts row sequences and serializes them according to its dialect and formatting settings.
Follow-up: How can a reader use a nonstandard separator? Supply a dialect or a delimiter formatting parameter when constructing it.
QHow do DictReader and DictWriter determine column names?
DictReader maps values in each row to dictionary keys from fieldnames; if fieldnames are omitted, the first row supplies them. DictWriter maps dictionary keys to output columns named by its fieldnames argument.
Follow-up: What happens with dictionary keys that are not output fields? Configure the extrasaction option to control whether they are ignored or rejected.
Related
DictReaderDictWriterDialectSnifferreaderwriterregister_dialectget_dialect