Use Python’s built-in csv module to read CSV rows as lists or dictionaries and to write rows back to a file. Open text files with newline='', specify an encoding when you know the file’s encoding, and configure the CSV dialect when the file does not use the defaults. The examples below work with the standard library and need no third-party package.
Read a CSV file as rows
csv.reader returns each record as a list of strings. It does not automatically convert values such as numbers or dates into application types.
import csv
with open("input.csv", newline="", encoding="utf-8") as f:
reader = csv.reader(f)
for row in reader:
print(row)Use encoding="utf-8" when UTF-8 matches the file. The CSV module works with text strings; choosing and decoding the file’s encoding is the responsibility of open(). If you omit encoding, Python uses the platform’s default text encoding.
A row is a CSV record, not necessarily one physical line: a quoted field can contain a newline. If you need to track consumed input lines, the reader’s line_num attribute counts source lines read.
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Read records as dictionaries
Use csv.DictReader when you want to access values by column name. By default, it uses the first record as field names and does not return that record as data.
import csv
with open("people.csv", newline="", encoding="utf-8") as f:
for row in csv.DictReader(f):
print(row["first_name"], row["last_name"])If the file has no header, or you want to define the names yourself, pass fieldnames explicitly. Extra values in a record go under restkey (whose default is None); missing values receive restval (also defaulting to None).
Write CSV rows
Open the output file in write mode and pass it to csv.writer. The writer accepts iterable rows; non-string values are converted with str(), while None is written as an empty field. That conversion of None cannot be reversed reliably when reading.
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import csv
with open("output.csv", "w", newline="", encoding="utf-8") as f:
writer = csv.writer(f)
writer.writerow(["name", "score"])
writer.writerow(["Ada", 98])Use writerows(rows) to write multiple rows. The default dialect is Excel-style; if another application expects a different delimiter, quoting rule, or line ending, set the appropriate format parameters.
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Write dictionaries with a defined column order
csv.DictWriter requires a fieldnames sequence. Its order determines the output columns. Call writeheader() if the file should include a header row.
import csv
with open("people_out.csv", "w", newline="", encoding="utf-8") as f:
writer = csv.DictWriter(f, fieldnames=["first_name", "last_name"])
writer.writeheader()
writer.writerow({"first_name": "Ada", "last_name": "Lovelace"})By default, a dictionary containing keys absent from fieldnames raises an error (extrasaction="raise"). Missing keys are filled using restval, which defaults to None.
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Why open CSV files with newline=''?
Python’s csv module documentation recommends opening file objects with newline='' for both reading and writing. This lets the CSV layer handle newline conventions itself instead of text I/O changing record boundaries. Use it in the open() call, as in the examples above.
Match the file’s delimiter and dialect
CSV files do not all use the same settings. The module’s default Excel dialect is a useful default, not a universal format. For a semicolon-separated file, pass delimiter=';'; for tab-separated values, pass delimiter='t'.
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for row in csv.reader(f, delimiter=";"):
print(row)Other dialect settings let you control the quote character, escape character, quoting policy, handling of spaces after delimiters, strictness, and—when writing—the line terminator. A dialect can be supplied by name or configured with format parameters.
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Choose a quoting policy deliberately
QUOTE_MINIMALquotes fields only when needed for special characters.QUOTE_ALLquotes every field.QUOTE_NONNUMERICwrites nonnumeric values quoted and converts unquoted input fields to floats when reading. It is not general-purpose type inference.QUOTE_NONEdisables quote processing. When writing values that need escaping, provide anescapechar.QUOTE_NOTNULLandQUOTE_STRINGSare available starting in Python 3.12. They treatNoneand empty unquoted values specially; use them only when both the Python runtime and the receiving format support the behavior.
The reader recognizes r and n as line endings; its behavior does not depend on the writer’s lineterminator setting.
Convert values after parsing
For ordinary csv.reader and csv.DictReader use, values arrive as strings. Convert them explicitly where your application needs numbers, dates, or other types, and handle invalid values according to your data requirements. For example:
with open("scores.csv", newline="", encoding="utf-8") as f:
reader = csv.DictReader(f)
for row in reader:
name = row["name"]
score = int(row["score"])
print(name, score)This conversion makes the expected type clear and gives your code a place to handle malformed or missing values. QUOTE_NONNUMERIC is narrower: it only converts unquoted fields to floats when reading.
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Should you use Sniffer?
csv.Sniffer can guess a dialect from a sample with sniff(sample), and has_header(sample) estimates whether the sample begins with a header. The documentation characterizes header detection as a rough heuristic that can produce false positives and negatives.
For a known file format or stable data contract, set the delimiter and header handling explicitly. Use sniffing only when inputs are genuinely variable, and validate its guess before relying on it.
Quick Recap
Choose the right CSV interface
| Need | Use | Behavior to account for |
|---|---|---|
| Positional rows | csv.reader / csv.writer |
Rows are sequences; reading returns strings by default. |
| Named columns | csv.DictReader / csv.DictWriter |
DictReader uses the first row as names unless specified; DictWriter needs ordered fieldnames. |
| Non-default format | Dialect or format parameters | Configure delimiter, quoting, escaping, or other settings to match the producer or recipient. |
| Unknown or inconsistent input | Sniffer plus validation |
Inference is sample-based; header detection can be wrong. |
| Application-specific types | Explicit conversion after reading | Standard reader values remain strings; handle conversion failures in your code. |
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