Overview

pip install myspellchecker
myspellchecker --help

myspellchecker check [OPTIONS] [INPUT]

# Check a file
myspellchecker check document.txt

# Check with JSON output
myspellchecker check document.txt -f json -o results.json

# Check from stdin
echo "မြန်မာနိုင်ငံ" | myspellchecker check

# Use specific database
myspellchecker check document.txt --db custom.db

# Fast checking (syllable only)
myspellchecker check document.txt --level syllable

# Thorough checking
myspellchecker check document.txt --level word -p accurate

# With custom config file
myspellchecker check document.txt -c config.yaml

# Force color output in a pipe
myspellchecker check document.txt --color | less -R

# Rich formatted output (default in terminal)
myspellchecker check document.txt -f rich

# WARNING: Myanmar text may not render correctly in your terminal.
# Use a text editor with proper font support to view this output.

document.txt:1:5: invalid_syllable 'xyz' -> Try: [abc, def, ghi]

# Summary: 1 errors found in 10 lines.

{
  "summary": {
    "total_errors": 1,
    "total_lines": 10
  },
  "results": [
    {
      "file": "document.txt",
      "line": 1,
      "text": "...",
      "has_errors": true,
      "errors": [
        {
          "text": "xyz",
          "position": 5,
          "error_type": "invalid_syllable",
          "suggestions": ["abc", "def", "ghi"],
          "confidence": 1.0
        }
      ]
    }
  ]
}

file,line,position,error_type,text,suggestions
document.txt,1,5,invalid_syllable,xyz,"abc,def,ghi"

myspellchecker build [OPTIONS]

# Build sample database
myspellchecker build --sample

# Build from corpus file
myspellchecker build -i corpus.txt -o dictionary.db

# Build from multiple files
myspellchecker build -i "data/*.txt" "extra/*.json"

# Build from directory (auto-detects txt, json, jsonl)
myspellchecker build -i ./corpus/ -o dictionary.db

# Validate before building
myspellchecker build -i corpus.txt --validate

# With POS tagging
myspellchecker build -i corpus.txt --pos-tagger viterbi

# Incremental update
myspellchecker build -i new_data.txt -o dictionary.db --incremental

# Filter by frequency
myspellchecker build -i corpus.txt -o dictionary.db --min-frequency 5

# Build with curated lexicon
myspellchecker build -i corpus.txt --curated-input data/curated_lexicon.csv -o dictionary.db

# Combine corpus with curated lexicon and transformer POS tagger
myspellchecker build -i corpus.txt --curated-input data/curated_lexicon.csv \
  --pos-tagger transformer --pos-device 0 -o dictionary.db

myspellchecker train-model [OPTIONS]

# Train with default settings (RoBERTa architecture)
myspellchecker train-model -i corpus.txt -o ./models/

# Train BERT model with more epochs
myspellchecker train-model -i corpus.txt -o ./models/ --architecture bert --epochs 10

# Train with custom hyperparameters
myspellchecker train-model -i corpus.txt -o ./models/ \
    --learning-rate 3e-5 --warmup-ratio 0.1 --weight-decay 0.01

# Train larger model
myspellchecker train-model -i corpus.txt -o ./models/ \
    --hidden-size 512 --layers 6 --heads 8

# Resume training from checkpoint
myspellchecker train-model -i corpus.txt -o ./models/ \
    --resume ./models/checkpoints/checkpoint-500

# Keep checkpoints and disable metrics
myspellchecker train-model -i corpus.txt -o ./models/ \
    --keep-checkpoints --no-metrics

myspellchecker train-detector [OPTIONS]

# Train with default settings
myspellchecker train-detector -i corpus.txt -o ./detector/

# Train with more epochs and lower corruption
myspellchecker train-detector -i corpus.txt -o ./detector/ \
    --epochs 5 --corruption-ratio 0.10

# Train with custom hyperparameters
myspellchecker train-detector -i corpus.txt -o ./detector/ \
    --learning-rate 3e-5 --batch-size 32

# Skip preprocessing for already-clean corpus
myspellchecker train-detector -i corpus.txt -o ./detector/ \
    --skip-preprocessing

# Keep checkpoints for debugging
myspellchecker train-detector -i corpus.txt -o ./detector/ \
    --keep-checkpoints

myspellchecker segment [OPTIONS] [INPUT]

# Segment text (default text format)
myspellchecker segment document.txt

# Output as JSON
myspellchecker segment document.txt -f json

# Output as TSV
myspellchecker segment document.txt -f tsv

# With POS tags
myspellchecker segment document.txt --tag

# From stdin
echo "မြန်မာနိုင်ငံ" | myspellchecker segment

မြန်မာ/N နိုင်ငံ/N

myspellchecker config [SUBCOMMAND]

# Create config file (default location)
myspellchecker config init

# Create config file at custom path
myspellchecker config init --path ./myspellchecker.yaml

# Overwrite existing config file
myspellchecker config init --force

# Show current config and search paths
myspellchecker config show

myspellchecker infer-pos [OPTIONS]

# Infer POS tags for all untagged words
myspellchecker infer-pos --db dictionary.db

# Infer only for high-frequency words
myspellchecker infer-pos --db dictionary.db --min-frequency 10

# Set minimum confidence threshold
myspellchecker infer-pos --db dictionary.db --min-confidence 0.7

# Preview changes without modifying database
myspellchecker infer-pos --db dictionary.db --dry-run

# Include already-tagged words for re-inference
myspellchecker infer-pos --db dictionary.db --include-tagged

myspellchecker completion --shell [bash|zsh|fish]

# Generate bash completion
myspellchecker completion --shell bash > ~/.bash_completion.d/myspellchecker
source ~/.bash_completion.d/myspellchecker

# Generate zsh completion
myspellchecker completion --shell zsh > ~/.zsh/completions/_myspellchecker

# Generate fish completion
myspellchecker completion --shell fish > ~/.config/fish/completions/myspellchecker.fish

# Database path (required - no bundled database included)
database: /path/to/your/custom.db

# Use a preset (default, fast, accurate, minimal, strict)
preset: default

# Core settings
max_edit_distance: 2
max_suggestions: 5

# Feature toggles
use_phonetic: true
use_context_checker: true

# Provider configuration
provider_config:
  pool_max_size: 5
  pool_timeout: 5.0