Implement text analyzer core and CLI
This commit is contained in:
3
src/text_analyzer/__init__.py
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3
src/text_analyzer/__init__.py
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"""Text analyzer package."""
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__version__ = "1.0.0"
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159
src/text_analyzer/cli.py
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src/text_analyzer/cli.py
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"""Command-line interface for the text analyzer."""
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import argparse
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import json
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import sys
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from pathlib import Path
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from typing import Final
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from text_analyzer.core import TextStatistics, analyze_file
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DEFAULT_TOP: Final[int] = 10
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DEFAULT_MIN_LEN: Final[int] = 1
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DEFAULT_ENCODING: Final[str] = "utf-8"
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def build_parser() -> argparse.ArgumentParser:
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"""Build command-line parser."""
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parser = argparse.ArgumentParser(
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prog="text-analyzer",
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description="Analyze a text file.",
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)
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parser.add_argument(
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"path",
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type=Path,
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help="Path to the text file.",
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)
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parser.add_argument(
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"--top",
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type=int,
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default=DEFAULT_TOP,
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help="Number of most frequent words.",
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)
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parser.add_argument(
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"--min-len",
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type=int,
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default=DEFAULT_MIN_LEN,
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help="Minimum word length.",
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)
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parser.add_argument(
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"--format",
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choices=("text", "json"),
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default="text",
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help="Output format.",
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)
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parser.add_argument(
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"--encoding",
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default=DEFAULT_ENCODING,
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help="Input file encoding.",
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)
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return parser
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def format_text(statistics: TextStatistics) -> str:
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"""Format statistics as text."""
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lines = [
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f"Lines: {statistics.lines}",
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f"Words: {statistics.words}",
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f"Characters: {statistics.characters}",
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"Top words:",
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]
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if statistics.top_words:
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for word, count in statistics.top_words:
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lines.append(f" {word}: {count}")
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else:
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lines.append(" No words found.")
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return "\n".join(lines)
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def format_json(statistics: TextStatistics) -> str:
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"""Format statistics as JSON."""
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data = {
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"lines": statistics.lines,
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"words": statistics.words,
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"characters": statistics.characters,
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"top_words": [
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{
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"word": word,
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"count": count,
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}
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for word, count in statistics.top_words
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],
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}
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return json.dumps(
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data,
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ensure_ascii=True,
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indent=2,
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)
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def main() -> int:
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"""Run CLI application."""
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parser = build_parser()
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args = parser.parse_args()
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if args.top < 0:
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print(
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"Error: --top must be non-negative.",
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file=sys.stderr,
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)
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return 2
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if args.min_len < 1:
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print(
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"Error: --min-len must be at least 1.",
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file=sys.stderr,
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)
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return 2
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try:
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statistics = analyze_file(
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args.path,
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top=args.top,
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min_len=args.min_len,
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encoding=args.encoding,
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)
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except FileNotFoundError:
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print(
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f"Error: file not found: {args.path}",
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file=sys.stderr,
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)
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return 1
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except UnicodeError:
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print(
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f"Error: cannot decode file using encoding: {args.encoding}",
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file=sys.stderr,
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)
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return 1
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except OSError as exc:
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print(
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f"Error: cannot read file: {exc}",
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file=sys.stderr,
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)
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return 1
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except ValueError as exc:
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print(
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f"Error: {exc}",
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file=sys.stderr,
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)
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return 2
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if args.format == "json":
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print(format_json(statistics))
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else:
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print(format_text(statistics))
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return 0
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if __name__ == "__main__":
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raise SystemExit(main())
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74
src/text_analyzer/core.py
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74
src/text_analyzer/core.py
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"""Core functionality for text analysis."""
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import re
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from collections import Counter
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from dataclasses import dataclass
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from pathlib import Path
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from typing import Final
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WORD_PATTERN: Final[re.Pattern[str]] = re.compile(
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r"[^\W\d_]+(?:['-][^\W\d_]+)*",
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re.UNICODE,
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)
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@dataclass(frozen=True)
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class TextStatistics:
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"""Statistics calculated from a text."""
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lines: int
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words: int
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characters: int
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top_words: list[tuple[str, int]]
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def extract_words(text: str, min_len: int = 1) -> list[str]:
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"""Extract words from text."""
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if min_len < 1:
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raise ValueError("min_len must be at least 1")
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words = WORD_PATTERN.findall(text)
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return [word.lower() for word in words if len(word) >= min_len]
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def count_words(text: str, min_len: int = 1) -> Counter[str]:
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"""Count word frequencies."""
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return Counter(extract_words(text, min_len))
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def analyze_text(
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text: str,
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top: int = 10,
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min_len: int = 1,
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) -> TextStatistics:
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"""Analyze supplied text."""
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if top < 0:
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raise ValueError("top must be non-negative")
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if min_len < 1:
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raise ValueError("min_len must be at least 1")
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frequencies = count_words(text, min_len)
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return TextStatistics(
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lines=len(text.splitlines()),
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words=sum(frequencies.values()),
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characters=len(text),
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top_words=frequencies.most_common(top),
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)
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def analyze_file(
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path: Path,
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top: int = 10,
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min_len: int = 1,
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encoding: str = "utf-8",
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) -> TextStatistics:
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"""Read and analyze a text file."""
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text = path.read_text(encoding=encoding)
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return analyze_text(
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text,
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top=top,
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min_len=min_len,
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)
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