如何在Dockerfile中跨多个CMD语句持久化R工作区？

我正在创建一个docker容器来接受来自客户端的输入数据，然后生成一个R脚本，该脚本对给定数据运行分析，并将三个绘图作为PDF输出到工作目录。我遇到了Docker引擎不允许在Docker文件中使用两条CMD语句的问题。我需要在运行时读取用户的数据，以便可以根据用户更改数据集。然后，在用户的数据作为R工作区中的表对象读入后，需要获取R脚本的源代码。发生的情况是，数据读取正常，但一条错误消息表明，作为R脚本源的第二行CMD无法找到刚刚读入的数据。我理解这是因为Dockerfile的每一行都是在构建时单独执行的，但我不知道如何解决这个问题。我已经研究了体积、supervisor的使用以及使用多个容器的可能性。我也可以制作一个Python脚本来动态编程我的R脚本，但这可能仍然需要两行CMD。我还没有找到一个适合我的情况的例子。你们中有谁会解决这个问题

以下是我的R脚本，用于从数据框“x”创建3个绘图：

library(iq)
norm_data <- iq::preprocess(x, median_normalization = FALSE, pdf_out = NULL)
protein_list <- iq::create_protein_list(norm_data)

# basic protein plot
pdf(file = "Protein P00366.pdf")
iq::plot_protein(protein_list$P00366, main = "Protein P00366", split = NULL)
dev.off()

protein_table <- iq::create_protein_table(protein_list)

#MaxLFQ plot
pdf(file = "MaxLFQ quantification of P00366.pdf")
iq::plot_protein(rbind(protein_list$P00366, 
                       MaxLFQ = iq::maxLFQ(protein_list$P00366)$estimate), 
                 main = "MaxLFQ quantification of P00366", 
                 col = c(rep("gray", nrow(protein_list$P00366)), "green"), 
                 split = NULL)  
dev.off()

# ground truth
MaxLFQ_estimate <- iq::maxLFQ(protein_list$P12799)$estimate

ground_truth <-  log2(rep(c(200, 125.99, 79.37, 50, 4, 2.52, 1.59, 1), each = 3))
ground_truth <- ground_truth - mean(ground_truth) + mean(MaxLFQ_estimate)

#ground truth plot
pdf(file = "P12799 MaxLFQ versus groundtruth.pdf")
iq::plot_protein(rbind(MaxLFQ = MaxLFQ_estimate,
                       Groundtruth = ground_truth), 
                 main = "P12799 - MaxLFQ versus groundtruth",  
                 split = 0.75, 
                 col = c("green", "gold"))  
dev.off()

尝试运行后，我从R工作区收到以下错误消息：

> source('iqTest.R')
Error in iq::preprocess(x, median_normalization = FALSE, pdf_out = NULL) : 
  object 'x' not found
Calls: source -> withVisible -> eval -> eval -> <Anonymous>

---

如果您希望通过环境变量配置数据路径，那么我建议您使用访问脚本中的该变量。这还允许您使用

Rscript

而不是

R-e“source…

以下是对我有效的方法：

script.R

cat(Sys.getenv('SCRIPT'), '\n');
cat(Sys.getenv('DATA'), '\n')

Dockerfile

FROM r-base:latest

ENV SCRIPT="script.R"
ENV DATA="data.csv"

WORKDIR /workspace

CMD R -q -e "source('$SCRIPT')"
# alternative: CMD Rscript $SCRIPT

daniel@nuest /tmp/stackoverflow []$ docker build --tag stackoverflow .
Sending build context to Docker daemon  4.608kB
Step 1/5 : FROM r-base:latest
 ---> 46edce0e80af
Step 2/5 : ENV SCRIPT="script.R"
 ---> Using cache
 ---> 8f26d34d9c0a
Step 3/5 : ENV DATA="data.csv"
 ---> Using cache
 ---> 16c83c16a4c8
Step 4/5 : WORKDIR /workspace
 ---> Running in fce8619af30b
Removing intermediate container fce8619af30b
 ---> a8278f609d9a
Step 5/5 : CMD R -q -e "source('$SCRIPT')"
 ---> Running in 765bafeb8681
Removing intermediate container 765bafeb8681
 ---> ff7d7b09dffb
Successfully built ff7d7b09dffb
Successfully tagged stackoverflow:latest
daniel@nuest /tmp/stackoverflow []$ docker run --rm -it -v $(pwd):/workspace stackoverflow
> source('script.R')
script.R 
data.csv 
> 
> 

用法

FROM r-base:latest

ENV SCRIPT="script.R"
ENV DATA="data.csv"

WORKDIR /workspace

CMD R -q -e "source('$SCRIPT')"
# alternative: CMD Rscript $SCRIPT

daniel@nuest /tmp/stackoverflow []$ docker build --tag stackoverflow .
Sending build context to Docker daemon  4.608kB
Step 1/5 : FROM r-base:latest
 ---> 46edce0e80af
Step 2/5 : ENV SCRIPT="script.R"
 ---> Using cache
 ---> 8f26d34d9c0a
Step 3/5 : ENV DATA="data.csv"
 ---> Using cache
 ---> 16c83c16a4c8
Step 4/5 : WORKDIR /workspace
 ---> Running in fce8619af30b
Removing intermediate container fce8619af30b
 ---> a8278f609d9a
Step 5/5 : CMD R -q -e "source('$SCRIPT')"
 ---> Running in 765bafeb8681
Removing intermediate container 765bafeb8681
 ---> ff7d7b09dffb
Successfully built ff7d7b09dffb
Successfully tagged stackoverflow:latest
daniel@nuest /tmp/stackoverflow []$ docker run --rm -it -v $(pwd):/workspace stackoverflow
> source('script.R')
script.R 
data.csv 
> 
> 

---

或者，您可以尝试将数据路径作为参数传递给脚本文件，请参见

---

顺便说一句：为了再现性，最好固定一个特定的R版本，而不是使用

：latest

。

如果您想通过环境变量配置数据路径，那么我建议您使用访问脚本中的该变量。这也允许您使用

Rscript

，而不是

R-e“来源…

以下是对我有效的方法：

script.R

cat(Sys.getenv('SCRIPT'), '\n');
cat(Sys.getenv('DATA'), '\n')

Dockerfile

FROM r-base:latest

ENV SCRIPT="script.R"
ENV DATA="data.csv"

WORKDIR /workspace

CMD R -q -e "source('$SCRIPT')"
# alternative: CMD Rscript $SCRIPT

daniel@nuest /tmp/stackoverflow []$ docker build --tag stackoverflow .
Sending build context to Docker daemon  4.608kB
Step 1/5 : FROM r-base:latest
 ---> 46edce0e80af
Step 2/5 : ENV SCRIPT="script.R"
 ---> Using cache
 ---> 8f26d34d9c0a
Step 3/5 : ENV DATA="data.csv"
 ---> Using cache
 ---> 16c83c16a4c8
Step 4/5 : WORKDIR /workspace
 ---> Running in fce8619af30b
Removing intermediate container fce8619af30b
 ---> a8278f609d9a
Step 5/5 : CMD R -q -e "source('$SCRIPT')"
 ---> Running in 765bafeb8681
Removing intermediate container 765bafeb8681
 ---> ff7d7b09dffb
Successfully built ff7d7b09dffb
Successfully tagged stackoverflow:latest
daniel@nuest /tmp/stackoverflow []$ docker run --rm -it -v $(pwd):/workspace stackoverflow
> source('script.R')
script.R 
data.csv 
> 
> 

用法

FROM r-base:latest

ENV SCRIPT="script.R"
ENV DATA="data.csv"

WORKDIR /workspace

CMD R -q -e "source('$SCRIPT')"
# alternative: CMD Rscript $SCRIPT

daniel@nuest /tmp/stackoverflow []$ docker build --tag stackoverflow .
Sending build context to Docker daemon  4.608kB
Step 1/5 : FROM r-base:latest
 ---> 46edce0e80af
Step 2/5 : ENV SCRIPT="script.R"
 ---> Using cache
 ---> 8f26d34d9c0a
Step 3/5 : ENV DATA="data.csv"
 ---> Using cache
 ---> 16c83c16a4c8
Step 4/5 : WORKDIR /workspace
 ---> Running in fce8619af30b
Removing intermediate container fce8619af30b
 ---> a8278f609d9a
Step 5/5 : CMD R -q -e "source('$SCRIPT')"
 ---> Running in 765bafeb8681
Removing intermediate container 765bafeb8681
 ---> ff7d7b09dffb
Successfully built ff7d7b09dffb
Successfully tagged stackoverflow:latest
daniel@nuest /tmp/stackoverflow []$ docker run --rm -it -v $(pwd):/workspace stackoverflow
> source('script.R')
script.R 
data.csv 
> 
> 

---

或者，您可以尝试将数据路径作为参数传递给脚本文件，请参见

顺便说一句：为了再现性，最好固定一个特定的R版本，而不是使用

：latest