df-diskcache
df-diskcache is a Python library for caching pandas.DataFrame objects to local disk.
pip install df-diskcache
Supports the following methods:
get: Get a cache entry (pandas.DataFrame) for the key. ReturnsNoneif the key is not found.set: Create a cache entry with an optional time-to-live (TTL) for the key-value pair.updatetouch: Update the last accessed time of a cache entry to extend the TTL.deleteprune: Delete expired cache entries.- Dictionary-like operations:
__getitem____setitem____contains____delitem__
| 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) |
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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) |
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| 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) |
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