flowR is a sophisticated, static dataflow analyzer for the R programming language. It offers a wide variety of features, for example:

🍕 program slicing
Given a point of interest like the visualization of a plot, flowR reduces the program to just the parts which are relevant for the computation of the point of interest.
Example: Slicing with flowR

The simplest way to retrieve slices is with flowR's Visual Studio Code extension. However, you can slice using the REPL as well. This can help you if you want to reuse specific parts of an existing analysis within another context or if you want to understand what is happening in the code.

For this, let's have a look at the example file, located at test/testfiles/example.R:
```
sum <- 0
product <- 1
w <- 7
N <- 10

for (i in 1:(N-1)) {
  sum <- sum + i + w
  product <- product * i
}

cat("Sum:", sum, "\n")
cat("Product:", product, "\n")
```
Let's suppose we are interested only in the sum which is printed in line 11. To get a slice for this, you can use the following command:
```
$ docker run -it --rm eagleoutice/flowr # or npm run flowr 
flowR repl using flowR v2.2.5, R v4.4.0 (r-shell engine)
R> :slicer test/testfiles/example.R --criterion "11@sum"
```
Output
```
sum <- 0
w <- 7
N <- 10
for(i in 1:(N-1)) sum <- sum + i + w
sum
```
📚 dependency analysis
Given your analysis project, flowR offers a plethora of so-called queries to get more information about your code. An important query is the dependencies query, which shows you the library your project needs, the data files it reads, the scripts it sources, and the data it outputs.

Example: Dependency Analysis with flowR

The following showcases the dependency view of the Visual Studio Code extension:

🚀 fast data- and control-flow graphs
Within just 117.7 ms (as of Feb 17, 2025), flowR can analyze the data- and control-flow of the average real-world R script. See the benchmarks for more information, and consult the wiki pages for more details on the dataflow graph.

Example: Generating a dataflow graph with flowR

You can investigate flowR's analyses using the REPL. Commands like :dataflow* allow you to view a dataflow graph for a given R script.

Let's have a look at the following example:

sum <- 0
product <- 1
w <- 7
N <- 10

for (i in 1:(N-1)) {
  sum <- sum + i + w
  product <- product * i
}

cat("Sum:", sum, "\n")
cat("Product:", product, "\n")

To get the dataflow graph for this script, you can use the following command:

$ docker run -it --rm eagleoutice/flowr # or npm run flowr 
flowR repl using flowR v2.2.5, R v4.4.0 (r-shell engine)
R> :dataflow* test/testfiles/example.R

Output

https://mermaid.live/view#base64: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

Following the link output should show the following:

flowchart LR
    1{{"`#91;RNumber#93; 0
      (1)
      *1.8*`"}}
    0["`#91;RSymbol#93; sum
      (0)
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    2[["`#91;RBinaryOp#93; #60;#45;
      (2)
      *1.1-8*
    (0, 1)`"]]
    4{{"`#91;RNumber#93; 1
      (4)
      *2.12*`"}}
    3["`#91;RSymbol#93; product
      (3)
      *2.1-7*`"]
    5[["`#91;RBinaryOp#93; #60;#45;
      (5)
      *2.1-12*
    (3, 4)`"]]
    7{{"`#91;RNumber#93; 7
      (7)
      *3.6*`"}}
    6["`#91;RSymbol#93; w
      (6)
      *3.1*`"]
    8[["`#91;RBinaryOp#93; #60;#45;
      (8)
      *3.1-6*
    (6, 7)`"]]
    10{{"`#91;RNumber#93; 10
      (10)
      *4.6-7*`"}}
    9["`#91;RSymbol#93; N
      (9)
      *4.1*`"]
    11[["`#91;RBinaryOp#93; #60;#45;
      (11)
      *4.1-7*
    (9, 10)`"]]
    12["`#91;RSymbol#93; i
      (12)
      *6.6*`"]
    13{{"`#91;RNumber#93; 1
      (13)
      *6.11*`"}}
    16(["`#91;RSymbol#93; N
      (16)
      *6.14*`"])
    17{{"`#91;RNumber#93; 1
      (17)
      *6.16*`"}}
    18[["`#91;RBinaryOp#93; #45;
      (18)
      *6.14-16*
    (16, 17)`"]]
    19[["`#91;RExpressionList#93; (
      (19)
      *6.13*
    (18)`"]]
    20[["`#91;RBinaryOp#93; #58;
      (20)
      *6.11-17*
    (13, 19)`"]]
    24(["`#91;RSymbol#93; sum
      (24, :may:36+)
      *7.10-12*`"])
    25(["`#91;RSymbol#93; i
      (25, :may:36+)
      *7.16*`"])
    26[["`#91;RBinaryOp#93; #43;
      (26, :may:36+)
      *7.10-16*
    (24, 25)`"]]
    27(["`#91;RSymbol#93; w
      (27, :may:36+)
      *7.20*`"])
    28[["`#91;RBinaryOp#93; #43;
      (28, :may:36+)
      *7.10-20*
    (26, 27)`"]]
    23["`#91;RSymbol#93; sum
      (23, :may:)
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    29[["`#91;RBinaryOp#93; #60;#45;
      (29, :may:36+)
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    (23, 28)`"]]
    31(["`#91;RSymbol#93; product
      (31, :may:36+)
      *8.14-20*`"])
    32(["`#91;RSymbol#93; i
      (32, :may:36+)
      *8.24*`"])
    33[["`#91;RBinaryOp#93; #42;
      (33, :may:36+)
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    (31, 32)`"]]
    30["`#91;RSymbol#93; product
      (30, :may:)
      *8.3-9*`"]
    34[["`#91;RBinaryOp#93; #60;#45;
      (34, :may:36+)
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    (30, 33)`"]]
    35[["`#91;RExpressionList#93; #123;
      (35, :may:36+)
      *6.20*
    (29, 34)`"]]
    36[["`#91;RForLoop#93; for
      (36)
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    (12, 20, 35)`"]]
    38{{"`#91;RString#93; #34;Sum#58;#34;
      (38)
      *11.5-10*`"}}
    40(["`#91;RSymbol#93; sum
      (40)
      *11.13-15*`"])
    42{{"`#91;RString#93; #34;
#34;
      (42)
      *11.18-21*`"}}
    44[["`#91;RFunctionCall#93; cat
      (44)
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    (38, 40, 42)`"]]
    46{{"`#91;RString#93; #34;Product#58;#34;
      (46)
      *12.5-14*`"}}
    48(["`#91;RSymbol#93; product
      (48)
      *12.17-23*`"])
    50{{"`#91;RString#93; #34;
#34;
      (50)
      *12.26-29*`"}}
    52[["`#91;RFunctionCall#93; cat
      (52)
      *12.1-30*
    (46, 48, 50)`"]]
    0 -->|"defined-by"| 1
    0 -->|"defined-by"| 2
    2 -->|"argument"| 1
    2 -->|"returns, argument"| 0
    3 -->|"defined-by"| 4
    3 -->|"defined-by"| 5
    5 -->|"argument"| 4
    5 -->|"returns, argument"| 3
    6 -->|"defined-by"| 7
    6 -->|"defined-by"| 8
    8 -->|"argument"| 7
    8 -->|"returns, argument"| 6
    9 -->|"defined-by"| 10
    9 -->|"defined-by"| 11
    11 -->|"argument"| 10
    11 -->|"returns, argument"| 9
    12 -->|"defined-by"| 20
    16 -->|"reads"| 9
    18 -->|"reads, argument"| 16
    18 -->|"reads, argument"| 17
    19 -->|"returns, argument"| 18
    20 -->|"reads, argument"| 13
    20 -->|"reads, argument"| 19
    24 -->|"reads"| 0
    24 -->|"reads"| 23
    24 -->|"CD-True"| 36
    linkStyle 25 stroke:gray,color:gray;
    25 -->|"reads"| 12
    25 -->|"CD-True"| 36
    linkStyle 27 stroke:gray,color:gray;
    26 -->|"reads, argument"| 24
    26 -->|"reads, argument"| 25
    26 -->|"CD-True"| 36
    linkStyle 30 stroke:gray,color:gray;
    27 -->|"reads"| 6
    27 -->|"CD-True"| 36
    linkStyle 32 stroke:gray,color:gray;
    28 -->|"reads, argument"| 26
    28 -->|"reads, argument"| 27
    28 -->|"CD-True"| 36
    linkStyle 35 stroke:gray,color:gray;
    23 -->|"defined-by"| 28
    23 -->|"defined-by"| 29
    29 -->|"argument"| 28
    29 -->|"returns, argument"| 23
    29 -->|"CD-True"| 36
    linkStyle 40 stroke:gray,color:gray;
    31 -->|"reads"| 3
    31 -->|"reads"| 30
    31 -->|"CD-True"| 36
    linkStyle 43 stroke:gray,color:gray;
    32 -->|"reads"| 12
    32 -->|"CD-True"| 36
    linkStyle 45 stroke:gray,color:gray;
    33 -->|"reads, argument"| 31
    33 -->|"reads, argument"| 32
    33 -->|"CD-True"| 36
    linkStyle 48 stroke:gray,color:gray;
    30 -->|"defined-by"| 33
    30 -->|"defined-by"| 34
    34 -->|"argument"| 33
    34 -->|"returns, argument"| 30
    34 -->|"CD-True"| 36
    linkStyle 53 stroke:gray,color:gray;
    35 -->|"argument"| 29
    35 -->|"returns, argument"| 34
    35 -->|"CD-True"| 36
    linkStyle 56 stroke:gray,color:gray;
    36 -->|"reads, argument"| 12
    36 -->|"reads, argument"| 20
    36 -->|"argument, non-standard-evaluation"| 35
    40 -->|"reads"| 0
    40 -->|"reads"| 23
    44 -->|"argument"| 38
    44 -->|"reads, argument"| 40
    44 -->|"argument"| 42
    48 -->|"reads"| 3
    48 -->|"reads"| 30
    52 -->|"argument"| 46
    52 -->|"reads, argument"| 48
    52 -->|"argument"| 50

Loading

(The analysis required 24.34 ms (including parse and normalize, using the r-shell engine) within the generation environment.)

If you want to use flowR and the features it provides, feel free to check out the:

Visual Studio Code extension: provides access to flowR directly in VS Code (or vscode.dev)
RStudio Addin: integrates flowR into RStudio
R package: use flowR in your R scripts
Docker image: run flowR in a container, this also includes flowR's server
NPM package: include flowR in your TypeScript and JavaScript projects

⭐ Getting Started

To get started with flowR and its features, please check out the Overview wiki page. The Setup wiki page explains how you can download and setup flowR on your system. With docker 🐳️, the following line should be enough (and drop you directly into the read-eval-print loop):

docker run -it --rm eagleoutice/flowr

You can enter :help to gain more information on its capabilities.

Example REPL session

📜 More Information

For more details on how to use flowR please refer to the wiki pages, as well as the deployed code documentation.

🚀 Contributing

We welcome every contribution! Please check out the contributing guidelines for more information.

Contributors

flowr is actively developed by Florian Sihler under the GPLv3 License.
It is partially supported by the German Research Foundation (DFG) under the grant 504226141 ("CodeInspector").

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If you want to make changes please edit the source file (the CI will take care of the rest). In fact, many files in the wiki are generated, so make sure to check for the source file if you want to make changes.

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