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Description:

dfdiskcache 0.0.2

df-diskcache

Summary
Installation
Features
Usage

Set TTL for cache entries

Dependencies

Summary
df-diskcache is a Python library for caching pandas.DataFrame objects to local disk.

Installation
pip install df-diskcache

Features
Supports the following methods:

get: Get a cache entry (pandas.DataFrame) for the key. Returns None if the key is not found.
set: Create a cache entry with an optional time-to-live (TTL) for the key-value pair.
update
touch: Update the last accessed time of a cache entry to extend the TTL.
delete
prune: Delete expired cache entries.

Dictionary-like operations:

__getitem__
__setitem__
__contains__
__delitem__

Usage

Sample Code:
import pandas as pd
from dfdiskcache import DataFrameDiskCache

cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"

df = cache.get(url)
if df is None:
print("cache miss")
df = pd.read_csv(url)
cache.set(url, df)
else:
print("cache hit")

print(df)

You can also use operations like a dictionary:

Sample Code:
import pandas as pd
from dfdiskcache import DataFrameDiskCache

cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"

df = cache[url]
if df is None:
print("cache miss")
df = pd.read_csv(url)
cache[url] = df
else:
print("cache hit")

print(df)

Set TTL for cache entries

Sample Code:
import pandas as pd
from dfdiskcache import DataFrameDiskCache

DataFrameDiskCache.DEFAULT_TTL = 10 # you can override the default TTL (default: 3600 seconds)

cache = DataFrameDiskCache()
url = "https://raw.githubusercontent.com/pandas-dev/pandas/v2.1.3/pandas/tests/io/data/csv/iris.csv"

df = cache.get(url)
if df is None:
df = pd.read_csv(url)
cache.set(url, df, ttl=60) # you can set a TTL for the key-value pair

print(df)

Dependencies

Python 3.7+
Python package dependencies (automatically installed)