If your data is using ExperimentHub,  it should already be caching the 
downloaded data.  Once it is downloaded once, it should be using the cached 
download for subsequent calls to the hub.  We will investigate to ensure that 
the caching mechanism is functioning properly on all of our Bioconductor 
builders.



Lori Shepherd

Bioconductor Core Team

Roswell Park Comprehensive Cancer Center

Department of Biostatistics & Bioinformatics

Elm & Carlton Streets

Buffalo, New York 14263

________________________________
From: Bioc-devel <bioc-devel-boun...@r-project.org> on behalf of Murphy, Alan E 
<a.mur...@imperial.ac.uk>
Sent: Monday, March 22, 2021 5:38 AM
To: bioc-devel@r-project.org <bioc-devel@r-project.org>
Subject: [Bioc-devel] Methods to speed up R CMD Check

Hi all,

I am working on the development of 
[EWCE](https://secure-web.cisco.com/1uG0LGgCjdg85VowwaeRHk2fMjXFkOtQWsgL8p2MQD2j2PZFh_tqvJWaCHJfArA8O4B2WLG1JOwn31NISgSrPW3syUdiPlWNi7cHAMCWKZUQ8d9RrlR-d81LDXXx0xtfCI5ZjjTyFS2xxM2tDea27Y51bWk4Y7jpSnC8Bx768AHBeaJAg3YAK_HTxR6hMzFW99X6Pg8bETgPYi92ccneqdgAJcDBIdfwZnd9OMaM4JS0kY9kYT3F58ho2jM_k0n6EqMzhuXl3HEM7uneL7twMxTTxSZ-vFC1U1eFSkAr0sp38AyD3g6gTbf-vUbghaGV-JBKoybZto3ZDmHhs8OE6cQ/https%3A%2F%2Fgithub.com%2FNathanSkene%2FEWCE)
 but have hit an issue with R CMD check's runtime. I have been informed this 
test needs to be completed in 15 minutes but mine is currently running in ~24 
minutes and I am looking for methods to speed this up. The main culprits for 
the runtime issue are:

checking examples (5m 49.8s)
Running �testthat.R� [308s/469s] (7m 49.1s)
checking for unstated dependencies in vignettes (7m 49.4s)
checking re-building of vignette outputs (5m 12s)

With the exception of using smaller datasets which I will consider myself, is 
there known ways of speeding these up? EWCE derives data from an Experimenthub 
package 
[ewceData](https://secure-web.cisco.com/1r4B8NJkUGCpdQsdBW8RWLwGvwEA9TlvXY7VUYgAKS-TBmT7s-6a3zMLfS6rXRVUUxG4x8SCYzXUXZKYMtZ_ysyEzk56tVxfvju-9mo6l11KLQ7CzEpFMikVqdyT25f0G3SQK5u9b0_5JK2gNhR4l0j_5_b_B-uPxzyFF0jtLCZFHKW2-pD7e2P4RVOfbgRALwBXM-hQvhcoaxxrR8tWz3JLjKxWqNIhTrsJdATsAnUO0EnQ5U8JNXClmS9LvWwyTf-0ZqokYXTkjdfYDUAm6KiAGNJo4oX99GUBQZllyiIDprF07KeqjsMNMg4dbmMh0t6jl-UEiUaV3j1xRG8UyyA/https%3A%2F%2Fgithub.com%2Fneurogenomics%2FewceData)
 for its examples, tests and vignette. This is run repeatedly and I have noted 
this takes a significant amount of time to load a dataset. Is there anyway of 
caching the datasets for all the checks or more generally of speeding this up?

I have heard of the use of [long 
tests](http://secure-web.cisco.com/1yfwFXFFfUKBuFTwUeuS8XGYbh53YduG9ZGKMVmVU9Yrgxg4DbKA0_prEIOCNcgc8uANWYzUw115x_8njawa33mjqM5ZBEvTPTJhmXRzttl1eaRVu3Pa0FTA-d-wPRK3Xxa4miiXob79k_exN0isifYlHPTK7WRxh9_LbFye17PwVVOGsfxjEFKi8WF27D6LWJynf8k-L7iEqB2MSDkf_1zWmfA2qJByna147_Jkaa-nLx9FFl4VhsosBoNDE_qnC939XrCLLCT7RgV0jPukrVdahccxXfT6bgtGBR8ZKfj25BoCeE1_hTJXFgGP0CGmegMYqqmsbd3pGTbo63vTW-A/http%3A%2F%2Fbioconductor.org%2Fdevelopers%2Fhow-to%2Flong-tests%2F)
 which aren't run daily by Bioconductor but are these still checked in R CMD 
Check? Is there any other way to exclude my tests from the R CMD Check given 
they aren't a necessity from Bioconductor?

Does checking for unstated dependencies in vignettes have a long runtime based 
on the number of package dependencies? If I just export specific functions from 
packages will this check time reduce?

Lastly, is there any way to get an exception of the 15 minute maximum? I may be 
ill-informed but is the max time for packages on Bioconductor's daily check 40 
minutes which my code in its current state would complete by.

Kind regards,
Alan.


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