### Install PyKoSpacing via PyPI

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Standard installation using pip for Python 3. Ensure TensorFlow and Keras are installed first.

```bash
pip install tensorflow
pip install keras
```

--------------------------------

### Install TensorFlow on M1 Mac with Miniforge3

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Instructions for installing TensorFlow on M1 Macs using Miniforge3. This involves installing Miniforge, activating its environment, and then installing specific TensorFlow packages for macOS.

```bash
# Install Miniforge3 for mac
curl -O https://github.com/conda-forge/miniforge/releases/latest/download/Miniforge3-MacOSX-arm64.sh
chmod +x Miniforge3-MacOSX-arm64.sh
sh Miniforge3-MacOSX-arm64.sh
# Activate Miniforge3 virtualenv
# You should use Python version 3.10 or less.
source ~/miniforge3/bin/activate
# Install the Tensorflow dependencies 
conda install -c apple tensorflow-deps 
# Install base tensorflow 
python -m pip install tensorflow-macos 
# Install metal plugin 
python -m pip install tensorflow-metal
```

--------------------------------

### Install PyKoSpacing from GitHub

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Install the package directly from the GitHub repository using pip. This is useful for obtaining the latest development version.

```bash
pip install git+https://github.com/haven-jeon/PyKoSpacing.git
```

--------------------------------

### Initialize and Use Spacing Model

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Initialize the Spacing model and use it for basic Korean word spacing. Handles ambiguous text by predicting correct spaces.

```python
from pykospacing import Spacing

# Initialize the spacing model
spacing = Spacing()

# Basic usage - add spaces to unspaced Korean text
text = "김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다."
result = spacing(text)
print(result)
# Output: "김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."

# Simple example demonstrating disambiguation
ambiguous = "아버지가방에들어가신다."
print(spacing(ambiguous))
# Output: "아버지가 방에 들어가신다."  (My father enters the room)
```

--------------------------------

### Use Command Line Interface for Batch Processing

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Process text files or standard input directly from the terminal using the pykospacing module.

```bash
# Basic usage - read from file, output to stdout
python -m pykospacing.pykos input.txt

# Output to a specific file
python -m pykospacing.pykos input.txt output.txt

# Overwrite the input file with spaced result
python -m pykospacing.pykos -o input.txt

# Read from stdin
echo "아버지가방에들어가신다." | python -m pykospacing.pykos /dev/stdin
```

--------------------------------

### Setting Spacing Rules from CSV

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Configure custom spacing rules by loading them from a CSV file using the `set_rules_by_csv` method. Specify the column containing the words to be used as rules.

```bash
$ cat test.csv
인덱스,단어
1,네이버영화
2,언급된단어
```

```python
>>> from pykospacing import Spacing
>>> spacing = Spacing(rules=[''])
>>> spacing.set_rules_by_csv('./test.csv', '단어')
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.")
"김형호 영화시장 분석가는 '1987'의 네이버영화 정보 네티즌 10점 평에서 언급된단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."
```

--------------------------------

### Troubleshoot libstdc++ error on Ubuntu

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

If you encounter a GLIBCXX_3.4.22 not found error on Ubuntu, these commands can help resolve the issue by upgrading the C++ standard library.

```bash
sudo apt-get install libstdc++6
   sudo apt-get install ppa:ubuntu-toolchain-r/test
   sudo apt-get update
   sudo apt-get upgrade
   sudo apt-get dist-upgrade (This takes long time.)
```

--------------------------------

### Handling English Characters with `ignore='none'`

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Demonstrates the default behavior of the `ignore` parameter, where no special pre- or post-processing is applied for English characters. Spacing may occur within English words.

```python
>>> from pykospacing import Spacing
>>> spacing = Spacing()
>>> spacing("친구와함께bmw썬바이저를썼다.", ignore='none')
"친구와 함께 bm w 썬바이저를 썼다."
>>> spacing("chicken박스를열고닭다리를꺼내입에문다.crispy한튀김옷덕에내입주변은glossy해진다.", ignore='none')
"chicken박스를 열고 닭다리를 꺼내 입에 문다. crispy 한튀김 옷 덕에 내 입 주변은 glossy해진다."
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.", ignore='none')
"김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."
```

--------------------------------

### Command Line Spacing

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Utilize PyKoSpacing directly from the command line to process text files. This is convenient for batch processing.

```bash
$ cat test_in.txt
김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.
아버지가방에들어가신다.
$ python -m pykospacing.pykos test_in.txt
김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다.
아버지가 방에 들어가신다.
```

--------------------------------

### Load Rules from CSV File

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Load custom compound word rules from a CSV file using `set_rules_by_csv()`. Specify the column containing the words to preserve.

```python
from pykospacing import Spacing

# CSV file format (test.csv):
# 인덱스,단어
# 1,네이버영화
# 2,언급된단어

# Initialize and load rules from CSV
spacing = Spacing(rules=[''])  # Initialize with empty rules
spacing.set_rules_by_csv('./test.csv', '단어')  # Load rules from '단어' column

text = "김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다."
result = spacing(text)
print(result)
# Output: "김형호 영화시장 분석가는 '1987'의 네이버영화 정보 네티즌 10점 평에서 언급된단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."

# Without specifying key - reads all columns
spacing2 = Spacing(rules=[''])
spacing2.set_rules_by_csv('./words.csv')  # Uses all words in CSV
```

--------------------------------

### Basic Korean Text Spacing

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Instantiate the Spacing class and use it to correct spacing in Korean text. This is the default behavior without custom rules.

```python
>>> from pykospacing import Spacing
>>> spacing = Spacing()
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.")
"김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."
```

--------------------------------

### Handling English Characters with `ignore='pre2'`

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Uses pre-processing to remove characters matching `ignore_pattern` and then predicts spacing on both the pre-processed and original text. This allows for more accurate spacing around ignored characters but doubles computation time.

```python
>>> spacing("친구와함께bmw썬바이저를썼다.", ignore='pre2')
"친구와 함께 bmw 썬바이저를 썼다."
>>> spacing("chicken박스를열고닭다리를꺼내입에문다.crispy한튀김옷덕에내입주변은glossy해진다.", ignore='pre2')
"chicken박스를 열고 닭다리를 꺼내 입에 문다. crispy 한 튀김옷 덕에 내 입 주변은 glossy해진다."
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.", ignore='pre2')

```

--------------------------------

### Process Multi-line Text in Python

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Iterate through lines of text to apply spacing individually, which is effective for handling longer documents.

```python
from pykospacing import Spacing

spacing = Spacing()

# Multi-line text processing
korean_text = """아즈사쨩이살인자가되는건싫어요...
그런어둡고우울한이야기,전싫어요
그게진실이라고,이세계의본질이라고해도,전싫어요!
저는좋아하는게있어요!
평범하고,별다른개성도없는저이지만....자신이좋아하는것에한해선절대로양보못해요!"""

# Process each line separately
result_lines = []
for line in korean_text.split('\n'):
    spaced_line = spacing(line)
    result_lines.append(spaced_line)
    print(spaced_line)

# Join results
final_text = '\n'.join(result_lines)
```

--------------------------------

### Applying Non-Spacing Rules

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Use the Spacing class with a list of words that should not be spaced. This is useful for specific terms or names.

```python
>>> # Apply a list of words that must be non-spacing
>>> spacing('귀밑에서턱까지잇따라난수염을구레나룻이라고한다.')
'귀 밑에서 턱까지 잇따라 난 수염을 구레나 룻이라고 한다.'
>>> spacing = Spacing(rules=['구레나룻'])
>>> spacing('귀밑에서턱까지잇따라난수염을구레나룻이라고한다.')
'귀 밑에서 턱까지 잇따라 난 수염을 구레나룻이라고 한다.'
```

--------------------------------

### Handling English Characters with `ignore='pre'`

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Applies pre-processing to remove characters matching `ignore_pattern` before spacing. Deleted characters are merged back after prediction, potentially causing incorrect spacing after them.

```python
>>> spacing("친구와함께bmw썬바이저를썼다.", ignore='pre')
"친구와 함께bmw 썬바이저를 썼다."
>>> spacing("chicken박스를열고닭다리를꺼내입에문다.crispy한튀김옷덕에내입주변은glossy해진다.", ignore='pre')
"chicken박스를 열고 닭다리를 꺼내 입에 문다.crispy 한 튀김옷 덕에 내 입 주변은glossy 해진다."
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.", ignore='pre')
"김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램R과KoNLP 패키지로 텍스트마이닝하여 분석했다."
```

--------------------------------

### set_rules_by_csv

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Configures non-spacing rules from a CSV file.

```APIDOC
## POST /spacing/rules/csv

### Description
Loads a list of words that should not be spaced from a CSV file.

### Method
POST

### Endpoint
/spacing/rules/csv

### Parameters
#### Request Body
- **file_path** (string) - Required - Path to the CSV file.
- **column_name** (string) - Required - The column name containing the words to protect from spacing.
```

--------------------------------

### Apply Custom Ignore Patterns in Python

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Use custom regex patterns to prevent specific characters or sequences from being affected by the spacing algorithm.

```python
# Custom pattern - only ignore uppercase English letters
text = "BMW자동차를타고SEOUL에서BUSAN까지달렸다."
custom_pattern = r'[A-Z]+'
print(spacing(text, ignore='pre2', ignore_pattern=custom_pattern))
# Output: "BMW 자동차를 타고 SEOUL에서 BUSAN까지 달렸다."

# Pattern to ignore numbers only
number_text = "2024년1월1일에시작한다."
number_pattern = r'[0-9]+'
print(spacing(number_text, ignore='pre2', ignore_pattern=number_pattern))
```

--------------------------------

### Handling English Characters with `ignore='post'`

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

Applies post-processing to ignore model outputs on characters matching `ignore_pattern`. This can lead to English characters affecting spacing of nearby non-English characters.

```python
>>> spacing("친구와함께bmw썬바이저를썼다.", ignore='post')
"친구와 함께 bm w 썬바이저를 썼다."
>>> spacing("chicken박스를열고닭다리를꺼내입에문다.crispy한튀김옷덕에내입주변은glossy해진다.", ignore='post')
"chicken박스를 열고 닭다리를 꺼내 입에 문다. crispy 한튀김 옷 덕에 내 입 주변은 glossy해진다."
>>> spacing("김형호영화시장분석가는'1987'의네이버영화정보네티즌10점평에서언급된단어들을지난해12월27일부터올해1월10일까지통계프로그램R과KoNLP패키지로텍스트마이닝하여분석했다.", ignore='post')
"김형호 영화시장 분석가는 '1987'의 네이버 영화 정보 네티즌 10점 평에서 언급된 단어들을 지난해 12월 27일부터 올해 1월 10일까지 통계 프로그램 R과 KoNLP 패키지로 텍스트마이닝하여 분석했다."
```

--------------------------------

### Handling English Characters with Ignore Parameter

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Control how non-Korean characters, especially English, are handled during spacing using the `ignore` parameter. Options include 'none', 'pre', 'post', and 'pre2'.

```python
from pykospacing import Spacing

spacing = Spacing()
text = "친구와함께bmw썬바이저를썼다."

# ignore='none' - No preprocessing, model output as-is (may split English words)
print(spacing(text, ignore='none'))
# Output: "친구와 함께 bm w 썬바이저를 썼다."

# ignore='pre' - Remove non-Korean before prediction, merge after (space after English)
print(spacing(text, ignore='pre'))
# Output: "친구와 함께bmw 썬바이저를 썼다."

# ignore='post' - Ignore model output on non-Korean characters
print(spacing(text, ignore='post'))
# Output: "친구와 함께 bm w 썬바이저를 썼다."

# ignore='pre2' - Double prediction for accurate spacing around English (slower but best)
print(spacing(text, ignore='pre2'))
# Output: "친구와 함께 bmw 썬바이저를 썼다."

# Complex example with multiple English words
mixed_text = "chicken박스를열고닭다리를꺼내입에문다.crispy한튀김옷덕에내입주변은glossy해진다."
print(spacing(mixed_text, ignore='pre2'))
# Output: "chicken박스를 열고 닭다리를 꺼내 입에 문다. crispy 한 튀김옷 덕에 내 입 주변은 glossy해진다."
```

--------------------------------

### Spacing Correction API

Source: https://github.com/haven-jeon/pykospacing/blob/master/README.md

The primary interface for correcting spacing in Korean text strings.

```APIDOC
## POST /spacing

### Description
Corrects the spacing of a provided Korean text string using the Spacing model.

### Method
POST

### Endpoint
/spacing

### Parameters
#### Request Body
- **text** (string) - Required - The Korean text to be corrected.
- **rules** (list) - Optional - A list of words that must not be separated by spaces.
- **ignore** (string) - Optional - Strategy for handling non-Korean characters ('none', 'pre', 'post', 'pre2'). Default is 'none'.
- **ignore_pattern** (string) - Optional - Regex pattern for characters to ignore.

### Response
#### Success Response (200)
- **result** (string) - The spacing-corrected text.
```

--------------------------------

### Custom Ignore Pattern for Character Handling

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Use the `ignore_pattern` parameter with a regex to define custom character sets to be handled by the `ignore` modes. This offers fine-grained control over character processing.

```python
from pykospacing import Spacing

spacing = Spacing()

# Default pattern matches non-Korean, non-ASCII symbol sequences

```

--------------------------------

### Custom Rules for Compound Words

Source: https://context7.com/haven-jeon/pykospacing/llms.txt

Specify custom rules to preserve compound words that should not be split by the spacing model. Useful for proper nouns or technical terms.

```python
from pykospacing import Spacing

# Without rules - model incorrectly splits "구레나룻" (sideburns)
spacing = Spacing()
text = "귀밑에서턱까지잇따라난수염을구레나룻이라고한다."
print(spacing(text))
# Output: "귀 밑에서 턱까지 잇따라 난 수염을 구레나 룻이라고 한다."

# With rules - preserve "구레나룻" as one word
spacing_with_rules = Spacing(rules=['구레나룻'])
print(spacing_with_rules(text))
# Output: "귀 밑에서 턱까지 잇따라 난 수염을 구레나룻이라고 한다."

# Multiple rules can be specified
spacing_multi = Spacing(rules=['네이버영화', '텍스트마이닝', '구레나룻'])
text2 = "네이버영화에서텍스트마이닝을한다."
print(spacing_multi(text2))
# Output: "네이버영화에서 텍스트마이닝을 한다."
```

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