afanlife/r-executor
R language execution environment that integrates the R runtime and a Python Flask service
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afanlife/r-executor repository overview
R-Executor
github：https://github.com/AFAN-LIFE/R-Executor
Author: AFAN (WeChat: afan-life)
R-Executor is a Docker-based R language execution environment that integrates the R runtime and a Python Flask service. Through HTTP requests, users can send R code to the r-executor container for execution and retrieve the results. This project aims to provide a cross-platform R language invocation solution, simplifying the remote execution of R code and result retrieval.
Features
- Flask Integration: Embeds a Flask service into the R Docker environment, creating a remotely callable R execution service.
- Data Type Conversion: Utilizes
rpy2to convert R data types into standard Python data types, enabling HTTP-based result parsing.
Directory Structure
- app.py # Flask service entry point
- config.py # Global configuration file
- Dockerfile # Docker image build file
- requirements.txt # Python dependency list for building the image
- r_packages.txt # R dependency list for building the image
- compose.yaml # Docker Compose configuration file
- test/ # Test cases
- test0_local.py # Test R code execution inside the container
- test1_basic.py # Test client requests to retrieve R data types
- test2_lrm.py # Test client requests to call the lrm function from the rms package for logistic regression
- test3_plot.py # Test client requests to generate and save a nomogram plot
- train.csv # Dataset used for test cases
- nom.png # Output of test3_plot.py (nomogram plot)
Usage
Get the Image
Pulling the Image from Docker Hub
The r-executor image is available on Docker Hub. You can pull it directly using the following command:
docker pull afanlife/r-executor
Image URL：https://hub.docker.com/r/afanlife/r-executor
The r-executor image comes pre-installed with Python 3.13.2 and R 4.4.2, along with the default Python and R dependencies listed in requirements.txt and r_packages.txt. If the current version meets your needs, you can directly pull the image from Docker Hub.
Note: The app.py in r-executor is executed within the container via volume mounting, allowing direct modifications without rebuilding the image.
Rebuilding the Image
If the default version does not meet your requirements, you can rebuild the image as needed:
- To change the Python or R version, modify the
Dockerfile. - To adjust Python or R dependencies, modify
requirements.txtandr_packages.txt.
docker build -t r-executor:1.0 .
Commands for exporting and loading the image:
docker save -o r-executor.tar r-executor
docker load -i r-executor.tar
Starting the Container
Map all files in the current directory to the /app directory inside the container and start the service.
Manual Start
docker run -it -p 5000:5000 -v .:/app afanlife/r-executor /bin/bash
python app.py
Using Docker Compose
docker compose up
Test Cases
Starting app.py
root@9f2585313bab:/app# Python app.py
3.5.17
* Serving Flask app 'app'
* Debug mode: on
WARNING: This is a development server. Do not use it in a production deployment. Use a production WSGI server instead.
* Running on all addresses (0.0.0.0)
* Running on http://127.0.0.1:5000
* Running on http://172.17.0.2:5000
Press CTRL+C to quit
* Restarting with stat
Running test1_basic.py (Testing Basic Data Types)
{
"data": {
"dataframe": {
"a": [
1.0,
2.0
],
"b": [
"x",
"y"
]
},
"matrix": [
1,
2,
3,
4
],
"vector": [
1.0,
2.0,
3.0
]
},
"message": "R code run success",
"status": "success"
}
Running test2_lrm.py (Testing Logistic Regression Model)
{
"data": {
"accuracy": [
0.991
],
"model_summary": [
"Logistic Regression Model",
"",
"lrm(formula = Heart_Disease ~ ., data = r_df)",
"",
" Model Likelihood Discrimination Rank Discrim. ",
" Ratio Test Indexes Indexes ",
"Obs 1000 LR chi2 238.07 R2 0.859 C 0.997 ",
" 0 968 d.f. 4 R2(4,1000)0.209 Dxy 0.994 ",
" 1 32 Pr(> chi2) <0.0001 R2(4,92.9)0.919 gamma 0.994 ",
"max |deriv| 2e-05 Brier 0.007 tau-a 0.062 ",
"",
" Coef S.E. Wald Z Pr(>|Z|)",
"Intercept -109.6707 24.8000 -4.42 <0.0001 ",
"Age 0.4953 0.1116 4.44 <0.0001 ",
"Blood_Sugar 0.5558 0.1228 4.52 <0.0001 ",
"Blood_Pressure 0.0135 0.0213 0.63 0.5270 ",
"Weight 0.0647 0.0307 2.11 0.0352 ",
""
]
},
"message": "R code run success",
"status": "success"
}
Running test3_plot.py (Testing Plot Generation and Saving)
References
Tag summary
Content type
Image
Digest
sha256:ae2357f78…
Size
527.5 MB
Last updated
over 1 year ago
docker pull afanlife/r-executor