The Tool Desk
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Write rows from lists or other sequences
Use csv.writer when each record is an ordered sequence, such as a list or tuple. Include the header as the first row if the file should have column names:
import csv
rows = [
["name", "age", "city"],
["Ada", 36, "London"],
["Grace", 85, "New York"],
]
with open("people.csv", "w", newline="", encoding="utf-8") as file:
writer = csv.writer(file)
writer.writerows(rows)writerows() writes an iterable of rows; use writer.writerow(row) when writing just one row. The "w" mode creates the file or truncates its existing contents. The CSV writer converts non-string values to text; None becomes an empty field, so that conversion cannot be reversed reliably just from the CSV.
Write dictionary records and add a header
For records represented as dictionaries, use csv.DictWriter. Its fieldnames argument sets the column order, and writeheader() writes those names as the first row:
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import csv
fieldnames = ["name", "age", "city"]
rows = [
{"name": "Ada", "age": 36, "city": "London"},
{"name": "Grace", "age": 85, "city": "New York"},
]
with open("people.csv", "w", newline="", encoding="utf-8") as file:
writer = csv.DictWriter(file, fieldnames=fieldnames)
writer.writeheader()
writer.writerows(rows)By default, a record containing a key that is not in fieldnames raises ValueError. If extra keys should be discarded, pass extrasaction="ignore" to DictWriter.
Choose the writer that matches your data
| Input data | Use | How column order is set | Header |
|---|---|---|---|
| Lists, tuples, or other ordered row sequences | csv.writer |
The order of values in each row | Write a header row yourself if needed |
| Dictionaries with named fields | csv.DictWriter |
The fieldnames list |
Call writeheader() if needed |
Avoid blank lines and malformed fields
Open with newline=""
When a file object is passed to a CSV writer, open it with newline="". Without it, embedded newlines in quoted fields can be handled incorrectly, and systems using CRLF line endings can produce extra carriage returns.
Let the writer quote values
The default CSV dialect uses commas and quotes fields when needed, including values containing commas, quote characters, or line breaks. Do not build rows by joining values with commas: a value that contains a comma or newline would make the output ambiguous. Use the writer so it can apply the quoting rules.
Set encoding for the receiving program
The examples specify encoding="utf-8", a practical explicit choice for many workflows. If the application receiving the file requires another encoding, use that encoding in open(); there is no single encoding that is correct for every recipient.
Match the CSV format expected by another application
CSV is not one perfectly uniform format. The default dialect is comma-delimited with standard quoting, but programs may expect different separators, quote characters, quoting behavior, line endings, or encodings. Configure options such as delimiter, quotechar, and quoting, or select a named dialect, when the target program requires it. Check that program’s import requirements rather than assuming one setting works everywhere.
Append rows without duplicating the header
Use file mode "a" to append instead of replacing a file. In an append workflow, decide whether the destination already has a header: writing it every time adds duplicate header rows. The CSV writer does not determine whether a header is already present, so manage that check as part of the surrounding program.
Remember that CSV stores text, not Python types
CSV output does not preserve Python types automatically. Values are represented as text, and ordinary CSV reading returns strings unless specific quoting behavior is selected. If a downstream program needs numbers, dates, or other typed values, define and document how those values should be converted when reading the file.
The Python Software Foundation describes the module as implementing classes to “read and write tabular data in CSV format.” See the Python 3.14.8 csv documentation for the writer options and dialect details.
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