For a plain-text file, stream through it one line at a time and rotate to a new output file after a chosen number of lines. This keeps memory use low and gives you predictable, numbered parts. First choose the right boundary: a line limit, a byte limit, or complete records such as CSV rows require different methods.
Split a plain-text file by line count
This example writes up to 1,000 lines per part, naming the results part_001.txt, part_002.txt, and so on. Change lines_per_file to set your own limit.
from pathlib import Path
source = Path("input.txt")
out_dir = Path("parts")
lines_per_file = 1000
out_dir.mkdir(parents=True, exist_ok=True)
part_number = 0
line_count = 0
output = None
try:
with source.open("r", encoding="utf-8", newline="") as src:
for line in src:
if output is None or line_count == lines_per_file:
if output is not None:
output.close()
part_number += 1
output_path = out_dir / f"part_{part_number:03}.txt"
output = output_path.open("w", encoding="utf-8", newline="")
line_count = 0
output.write(line)
line_count += 1
finally:
if output is not None:
output.close()Save the script beside input.txt and run it with Python. The parts directory is created if it does not already exist. An empty input produces no part files. The finally block closes the current output even if an error interrupts processing; the source is managed by a with statement. Python recommends context managers for file objects because they close files when the block ends, including when an exception occurs (Python tutorial: Input and Output).
Control overwriting and output placement
The example opens outputs in write mode, which replaces any existing files with the same names. Use a fresh output directory if you need to keep previous results, or add a collision check before opening each output. Keep the output directory separate from the source files when processing multiple inputs, so newly generated parts are not accidentally treated as inputs during a later batch run. Path.mkdir(..., exist_ok=True) creates the directory when needed; Python documents path operations in pathlib.
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Understand line and newline behavior
Python file iteration yields lines including their line terminators when present. With newline="", the example avoids translating newline sequences as it reads and writes text. A final line with no newline remains without one in its output. This preserves the text-level line endings read by Python, but it is not a promise of byte-for-byte copying across encodings or platforms. If exact bytes matter, use binary mode and define the byte boundary instead.
Choose the boundary that matches the file
| Goal | Approach | Important limitation |
|---|---|---|
| Fixed number of plain-text lines | Stream lines and open a new output after N lines, as in the example. | A line is not necessarily a logical record in formats such as CSV. |
| Fixed number of bytes | Read and write in binary mode, rotating after the required byte count. | A raw byte split can divide a multibyte text character or a structured record. |
| Complete CSV records | Parse with Python’s csv module, then write complete records to each part. |
Physical lines are not reliably CSV records because quoted fields may contain line breaks. |
| JSON or another structured format | Identify the format’s record/document structure first, then split at valid boundaries. | Arbitrary text positions can leave each resulting file invalid. |
Split a large file without loading it all into memory
The example reads one line at a time rather than calling read(), readlines(), or converting the file to a list. That distinction matters when an input may exceed available memory: an unbounded read loads the entire file, while iteration over the file object is memory-efficient. The Python 3.11 tutorial describes file-object iteration as “memory efficient, fast, and leads to simple code” (Python tutorial: Methods of File Objects).
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Split CSV files by records, not physical lines
CSV permits line breaks inside quoted fields, so slicing the source by physical lines can cut a record in half. Use csv.reader to parse rows and csv.writer to write them. If each part must be independently usable as a CSV file, write the header row to every output as well as to the first. Python’s standard-library documentation covers these tools in the csv module.
For CSV, decide what your limit means: number of data records per part, whether the header counts toward that number, and whether empty input should produce a header-only output. Those choices affect the splitting loop; they are separate from the physical-line approach above.
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Verify the resulting files
After splitting, check that the outputs are present, ordered, and contain the expected number of lines or records. For a structured format, validate that every part can be parsed and that headers or other required metadata are present. These checks help catch off-by-one limits, accidental overwrites, and boundaries that do not match the file format.
Quick Recap
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