# Cache Pandas Dataframes to Disk
Easily cache Pandas Dataframes to disk using a simple interface.
## Sample usage
```python
from cache_df import CacheDF
import pandas as pd
cache = CacheDF(cache_dir='./caches')
# Caching a dataframe
df = pd.DataFrame({'a': [1, 2, 3], 'b': [4, 5, 6]})
cache.cache(df, 'my_df')
# Checking if a dataframe is cached
df_is_cached = cache.is_cached('my_df')
# Reading a dataframe from cache
try:
df = cache.read('my_df')
df_selective_cols = cache.read('my_df', cols=['a']) # Read only a subset of columns
except FileNotFoundError:
print('Dataframe not cached')
# Deleting a dataframe from cache if it exists
cache.uncache('my_df')
# Clearing all cached dataframes
cache.clear()
```
## Where it can be used
1) It can be used when you are using a shared file system across multiple machines such as AWS EFS, GCP Filestore, Azure Files, etc.
cache_df-1.0.tar.gz （11个子文件） 
cache_df-1.0 
setup.py 1KB cache_df.egg-info 
top_level.txt 9B SOURCES.txt 229B PKG-INFO 2KB dependency_links.txt 1B requires.txt 7B setup.cfg 131B cache_df __init__.py 38B cache_df.py 3KB README.md 895B PKG-INFO 2KB资源评论
