foxtrot/utils/file_viewer.py

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"""Standalone utility to download a SAS or delimited text file from S3 and
print a column-level summary of the first *N* rows.
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Supported formats
-----------------
* **SAS** ``.sas7bdat``, ``.xpt``, ``.xport`` (read via *pyreadstat*)
* **Text** ``.csv``, ``.tsv``, ``.txt`` (read via *pandas.read_csv*)
Configure the four constants below **or** use the CLI arguments, then run::
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python3 file_viewer.py
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python3 file_viewer.py --local path/to/file.csv
python3 file_viewer.py --local path/to/data.tsv --delimiter $'\\t'
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Python 3.14 compatible.
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"""
from __future__ import annotations
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import argparse
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import os
import sys
import boto3
import pandas as pd
import pyreadstat
# ---------------------------------------------------------------------------
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# Supported file extensions
# ---------------------------------------------------------------------------
SAS_EXTENSIONS: set[str] = {".sas7bdat", ".xpt", ".xport"}
"""File extensions recognised as SAS data files."""
TEXT_EXTENSIONS: set[str] = {".txt", ".csv", ".tsv"}
"""File extensions recognised as delimited text files."""
SUPPORTED_EXTENSIONS: set[str] = SAS_EXTENSIONS | TEXT_EXTENSIONS
"""Union of all supported file extensions."""
# ---------------------------------------------------------------------------
# Configuration — edit these before running (or use CLI arguments)
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# ---------------------------------------------------------------------------
S3_BUCKET: str = "my-bucket"
"""S3 bucket name."""
S3_KEY: str = "path/to/file.sas7bdat"
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"""Object key (path) within the bucket to a supported data file."""
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LOCAL_FOLDER: str = "./downloads"
"""Local directory to download the file into."""
AWS_PROFILE: str = "default"
"""AWS CLI profile name used for authentication."""
# ---------------------------------------------------------------------------
# Helpers
# ---------------------------------------------------------------------------
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def _ensure_local_copy(bucket: str, key: str, local_path: str) -> None:
"""Download *key* from *bucket* to *local_path*, skipping if already present.
If *local_path* exists and its size matches the S3 object's size, the
download is skipped and a message is printed.
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Supports any file whose extension is in :data:`SUPPORTED_EXTENSIONS`.
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"""
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session = boto3.Session(profile_name=AWS_PROFILE)
s3 = session.client("s3")
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remote_size = s3.head_object(Bucket=bucket, Key=key)["ContentLength"]
if os.path.exists(local_path):
local_size = os.path.getsize(local_path)
if local_size == remote_size:
print(
f"Local file {local_path} already matches s3://{bucket}/{key} "
f"({local_size} bytes); skipping download."
)
return
print(
f"Local file {local_path} size ({local_size} bytes) differs from "
f"S3 ({remote_size} bytes); re-downloading."
)
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print(f"Downloading s3://{bucket}/{key} -> {local_path}")
s3.download_file(bucket, key, local_path)
print("Download complete.")
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# -- SAS readers -------------------------------------------------------------
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def _read_sas_head(path: str, row_count: int = 10) -> pd.DataFrame:
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"""Read the first *row_count* rows of a SAS file (``.sas7bdat``, ``.xpt``, ``.xport``)."""
ext = os.path.splitext(path)[1].lower()
if ext == ".sas7bdat":
df, _ = pyreadstat.read_sas7bdat(path, row_offset=0, row_limit=row_count)
elif ext in {".xpt", ".xport"}:
df, _ = pyreadstat.read_xport(path, row_offset=0, row_limit=row_count)
else:
raise ValueError(f"Unsupported SAS extension: {ext}")
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return df
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# -- Text readers ------------------------------------------------------------
def _read_text_head(
path: str,
row_count: int = 10,
delimiter: str = ",",
encoding: str = "utf-8",
quotechar: str = '"',
) -> pd.DataFrame:
"""Read the first *row_count* rows of a delimited text file.
Parameters
----------
path : str
Path to the ``.csv``, ``.tsv``, or ``.txt`` file.
row_count : int, optional
Number of data rows to read (default ``10``).
delimiter : str, optional
Column delimiter (default ``","``). For ``.tsv`` files the caller
should pass ``"\\t"``.
encoding : str, optional
File encoding (default ``"utf-8"``).
quotechar : str, optional
Character used to quote fields (default ``'"'``).
"""
return pd.read_csv(
path,
sep=delimiter,
encoding=encoding,
quotechar=quotechar,
nrows=row_count,
)
# -- Unified reader ----------------------------------------------------------
def _read_head(
path: str,
row_count: int = 10,
delimiter: str | None = None,
encoding: str = "utf-8",
quotechar: str = '"',
) -> pd.DataFrame:
"""Read the first *row_count* rows of a supported data file.
Auto-detects the file type from its extension and delegates to the
appropriate reader. For ``.tsv`` files the delimiter defaults to tab
(``"\\t"``); for other text files it defaults to ``","``.
Parameters
----------
path : str
Path to the data file.
row_count : int, optional
Number of data rows to read (default ``10``).
delimiter : str or None, optional
Column delimiter for text files. ``None`` means *auto-detect*
(tab for ``.tsv``, comma otherwise).
encoding : str, optional
Encoding for text files (default ``"utf-8"``).
quotechar : str, optional
Quote character for text files (default ``'"'``).
Returns
-------
pandas.DataFrame
"""
ext = os.path.splitext(path)[1].lower()
if ext not in SUPPORTED_EXTENSIONS:
raise ValueError(
f"Unsupported file extension '{ext}'. "
f"Supported extensions: {sorted(SUPPORTED_EXTENSIONS)}"
)
if ext in SAS_EXTENSIONS:
return _read_sas_head(path, row_count=row_count)
# --- Text file path ---
if delimiter is None:
delimiter = "\t" if ext == ".tsv" else ","
return _read_text_head(
path,
row_count=row_count,
delimiter=delimiter,
encoding=encoding,
quotechar=quotechar,
)
# -- Display -----------------------------------------------------------------
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def _sample_values(series: pd.Series, n: int = 3) -> str:
"""Return up to *n* non-null sample values as a comma-separated string."""
non_null = series.dropna()
samples = non_null.head(n).tolist()
if not samples:
return "(all null)"
return ", ".join(repr(v) for v in samples)
def _print_summary(df: pd.DataFrame) -> None:
"""Print a nicely formatted summary table to stdout."""
# Pre-compute column data
rows = []
for col in df.columns:
rows.append((col, str(df[col].dtype), _sample_values(df[col], 3)))
# Determine column widths
hdr_name = "Column Name"
hdr_dtype = "Data Type"
hdr_samples = "Sample Values (up to 3)"
w_name = max(len(hdr_name), *(len(r[0]) for r in rows))
w_dtype = max(len(hdr_dtype), *(len(r[1]) for r in rows))
w_samples = max(len(hdr_samples), *(len(r[2]) for r in rows))
fmt = f" {{:<{w_name}}} {{:<{w_dtype}}} {{:<{w_samples}}}"
sep = f" {'-' * w_name} {'-' * w_dtype} {'-' * w_samples}"
print()
print(f" Summary of first {len(df)} row(s) ({len(df.columns)} columns)")
print(sep)
print(fmt.format(hdr_name, hdr_dtype, hdr_samples))
print(sep)
for name, dtype, samples in rows:
print(fmt.format(name, dtype, samples))
print(sep)
print()
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# ---------------------------------------------------------------------------
# CLI
# ---------------------------------------------------------------------------
def _build_parser() -> argparse.ArgumentParser:
"""Build the argument parser for the file-viewer CLI."""
parser = argparse.ArgumentParser(
description=(
"Download a SAS or delimited text file from S3 (or read a local "
"file) and print a column-level summary of the first N rows.\n\n"
"Supported extensions: "
+ ", ".join(sorted(SUPPORTED_EXTENSIONS))
),
formatter_class=argparse.RawDescriptionHelpFormatter,
)
source = parser.add_mutually_exclusive_group()
source.add_argument(
"--local",
metavar="FILE",
default=None,
help=(
"Path to a local data file to summarise (skips S3 download). "
"Supported extensions: "
+ ", ".join(sorted(SUPPORTED_EXTENSIONS))
),
)
source.add_argument(
"--s3-key",
metavar="KEY",
default=None,
help="Override the S3_KEY constant with this object key.",
)
parser.add_argument(
"--rows",
type=int,
default=10,
metavar="N",
help="Number of rows to read (default: 10).",
)
# Text-file-specific options
text_group = parser.add_argument_group(
"text file options",
"These options apply only to .csv / .tsv / .txt files.",
)
text_group.add_argument(
"--delimiter",
default=None,
help=(
'Column delimiter for text files (default: "," for .csv/.txt, '
'"\\t" for .tsv). Use $\'\\t\' in the shell for a literal tab.'
),
)
text_group.add_argument(
"--encoding",
default="utf-8",
help='File encoding for text files (default: "utf-8").',
)
text_group.add_argument(
"--quotechar",
default='"',
help='Quote character for text files (default: \'"\').',
)
return parser
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# ---------------------------------------------------------------------------
# Main
# ---------------------------------------------------------------------------
if __name__ == "__main__":
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parser = _build_parser()
args = parser.parse_args()
if args.local:
# ---- Local file mode -----------------------------------------------
local_path = args.local
ext = os.path.splitext(local_path)[1].lower()
if ext not in SUPPORTED_EXTENSIONS:
parser.error(
f"Unsupported file extension '{ext}'. "
f"Supported: {sorted(SUPPORTED_EXTENSIONS)}"
)
if not os.path.isfile(local_path):
print(f"File not found: {local_path}", file=sys.stderr)
sys.exit(1)
else:
# ---- S3 download mode ----------------------------------------------
s3_key = args.s3_key or S3_KEY
ext = os.path.splitext(s3_key)[1].lower()
if ext not in SUPPORTED_EXTENSIONS:
parser.error(
f"Unsupported file extension '{ext}' in S3 key. "
f"Supported: {sorted(SUPPORTED_EXTENSIONS)}"
)
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os.makedirs(LOCAL_FOLDER, exist_ok=True)
local_filename = os.path.basename(s3_key)
local_path = os.path.join(LOCAL_FOLDER, local_filename)
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try:
_ensure_local_copy(S3_BUCKET, s3_key, local_path)
except Exception as exc:
print(f"S3 download error: {exc}", file=sys.stderr)
sys.exit(1)
# ---- Read & summarise --------------------------------------------------
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try:
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df = _read_head(
local_path,
row_count=args.rows,
delimiter=args.delimiter,
encoding=args.encoding,
quotechar=args.quotechar,
)
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except Exception as exc:
print(f"File read error: {exc}", file=sys.stderr)
sys.exit(2)
_print_summary(df)