#!/usr/bin/env python
# coding: utf-8

# # df019_Cache
# Cache a processed RDataFrame in memory for further usage.
# 
# This tutorial shows how the content of a data frame can be cached in memory
# in form of a dataframe. The content of the columns is stored in memory in
# contiguous slabs of memory and is "ready to use", i.e. no ROOT IO operation
# is performed.
# 
# Creating a cached data frame storing all of its content deserialised and uncompressed
# in memory is particularly useful when dealing with datasets of a moderate size
# (small enough to fit the RAM) over which several explorative loops need to be
# performed as fast as possible. In addition, caching can be useful when no file
# on disk needs to be created as a side effect of checkpointing part of the analysis.
# 
# All steps in the caching are lazy, i.e. the cached data frame is actually filled
# only when the event loop is triggered on it.
# 
# 
# 
# 
# **Author:** Danilo Piparo (CERN)  
# <i><small>This notebook tutorial was automatically generated with <a href= "https://github.com/root-project/root/blob/master/documentation/doxygen/converttonotebook.py">ROOTBOOK-izer</a> from the macro found in the ROOT repository  on Wednesday, April 17, 2024 at 11:07 AM.</small></i>

# In[1]:


import ROOT
import os


# We create a data frame on top of the hsimple example.

# In[2]:


hsimplePath = os.path.join(str(ROOT.gROOT.GetTutorialDir().Data()), "hsimple.root")
df = ROOT.RDataFrame("ntuple", hsimplePath)


# We apply a simple cut and define a new column.

# In[3]:


df_cut = df.Filter("py > 0.f")\
           .Define("px_plus_py", "px + py")


# We cache the content of the dataset. Nothing has happened yet: the work to accomplish
# has been described.

# In[4]:


df_cached = df_cut.Cache()

h = df_cached.Histo1D("px_plus_py")


# Now the event loop on the cached dataset is triggered by accessing the histogram.
# This event triggers the loop on the `df` data frame lazily.

# In[5]:


c = ROOT.TCanvas()
h.Draw()
c.SaveAs("df019_Cache.png")

print("Saved figure to df019_Cache.png")


# Draw all canvases 

# In[6]:


from ROOT import gROOT 
gROOT.GetListOfCanvases().Draw()