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https://github.com/shalinir8/mathspell
https://github.com/shalinir8/mathspell
contextual num2word package python spacy spacy-nlp
Last synced: 6 days ago
JSON representation
- Host: GitHub
- URL: https://github.com/shalinir8/mathspell
- Owner: ShaliniR8
- License: mit
- Created: 2025-01-03T20:42:41.000Z (23 days ago)
- Default Branch: main
- Last Pushed: 2025-01-12T21:19:34.000Z (14 days ago)
- Last Synced: 2025-01-18T19:37:02.791Z (8 days ago)
- Topics: contextual, num2word, package, python, spacy, spacy-nlp
- Language: Python
- Homepage: https://pypi.org/project/mathspell/
- Size: 21.5 KB
- Stars: 4
- Watchers: 1
- Forks: 1
- Open Issues: 2
-
Metadata Files:
- Readme: README.md
- License: LICENSE
Awesome Lists containing this project
README
# MathSpell
MathSpell is a Python package for converting numbers into contextually appropriate words, such as "twenty-first century" for years or "two thousand and twenty-three" for general numbers.
## Installation
1. Install the package:
```bash
pip install mathspell
```
2. Download the required spaCy language model:
```bash
python -m spacy download en_core_web_sm
```
3. Upgrade Pint to it's latest version if it is incompatible with the current version of numpy.
```bash
pip install --upgrade pint
```
## Usage
After installation, you can use MathSpell to process text containing numbers. For example:
```python
from mathspell import analyze_text
text = "This is the 21st century. I was born in 1995."
converted_text = analyze_text(text)
print(converted_text)
# Output: "This is the twenty-first century. I was born in nineteen ninety-five."
```
## **Further Examples**
### **1. Year Conversion**
```python
from mathspell import analyze_text
input_text = "Something happened in 2021."
output = analyze_text(input_text)
print(output)
# Output: "Something happened in twenty twenty-one."
```
---
### **2. Ordinal Numbers**
```python
from mathspell import analyze_text
input_text = "This is my 3rd attempt to fix the bug."
output = analyze_text(input_text)
print(output)
# Output: "This is my third attempt to fix the bug."
```
---
### **3. Dates and Years**
```python
from mathspell import analyze_text
input_text = "My birthday is on 4th April, 1993."
output = analyze_text(input_text)
print(output)
# Output: "My birthday is on fourth April, nineteen ninety-three."
```
---
### **4. Quantities**
```python
from mathspell import analyze_text
input_text = "This contains 15 boxes."
output = analyze_text(input_text)
print(output)
# Output: "This contains fifteen boxes."
```
### **5. Handling Ordinal and Non-Ordinal Context**
```python
from mathspell import analyze_text
input_text = "This is the 1st floor, and the elevator can hold 5 people."
output = analyze_text(input_text)
print(output)
# Output: "This is the first floor, and the elevator can hold five people."
```
---
### **6. Temperature Conversion**
```python
from mathspell import analyze_text
input_text = "The temperature is expected to be 25 degrees tomorrow."
output = analyze_text(input_text)
print(output)
# Output: "The temperature is expected to be twenty-five degrees tomorrow."
```
---
### **7. Complex Sentence**
```python
from mathspell import analyze_text
input_text = "The 2nd prize was awarded in 2022 for the 10th time."
output = analyze_text(input_text)
print(output)
# Output: "The second prize was awarded in twenty twenty-two for the tenth time."
```