I must predicate this by saying that I am still quite new to RStudio/R so I hope this is not user error. However when debugging I am getting some strange results whilst in debug mode.
1) The code jumps to another part of the code without apparently being called.
2) When this happens the highlighter only partially highlights the code it jumps to but the arrow in the margin points to this partially highlighted line
3) The code then returns to place it jumped away from originally
I get the warning "Debug location is approximate because source source code is not available". Is this related to the problem?
You can replicate the results by installing the package dlm:
https://cran.r-project.org/web/packages/dlm/dlm.pdf
p<-3
G=diag(c(0.9963,0.9478,0.7740))
W=diag(c(0.0026^2,0.0027^2,0.0035^2))
C0_est=solve(diag(p)-G%*%t(G))*W
mod2<-dlm(m0=c(0.0501,-0.0251,-0.0116),C0=C0_est,FF=X,V=0.000000001*diag(m),GG=diag(c(0.9963,0.9478,0.7740)),W=diag(c(0.0026^2,0.0027^2,0.0035^2)))
debugonce(dlmForecast)
dlmForecast(mod2, nAhead=5, sampleNew=2)
When you step through using F10 you will find that the code jumps to L7 from Lines 28,32, 54 and 57 and to L4 from line 47.
Q1.) Why does this partial highlighting of the line being debugged mean?
Q2.) What causeses the code to jump backward and forwards like this with no apparent function call?
Kind Regards
Baz
Most R packages don't include copies of the package's source code (the keep.source option controls this behavior; you can read more about it here). When you debug code from this kind of package, RStudio has to guess at both what the code looked like originally and where the current execution point is in that code. This process includes some heuristics and does occasionally misinterpret the execution point. So what you're seeing is not the actual execution point jumping around, but RStudio making the wrong guess about where it is in the deparsed code.
Code from your own R scripts (and from packages with keep.source) have source references (see R journal article) which allow RStudio to line up the code and execution point precisely.
I wasn't able to reproduce this with your example (it appears to reference a variable m that it doesn't declare); if you can resolve that and send it to me (jonathan at rstudio dot com) I'll see if we can improve the heuristics so this case works better.
Related
I am using pycodestyle_magic as a linter in Jupyter. I am following the instructions at
https://github.com/mattijn/pycodestyle_magic
But I get error with 1-cell checking be it '%%pycodestyle' or '%%flake8'.
1st ERROR
# 1st CELL
%load_ext pycodestyle_magic
# 2nd CELL
%%pycodestyle
a=1
print(a)
2nd ERROR
# 1st CELL
%load_ext pycodestyle_magic
# 2nd CELL
%%flake8
a=1
print(a)
1st ERROR
I'm basing this on your image you posted for '1st error' and not the inaccurate code you posted:
Note that the error in your first error was saying line magic and not cell magic because it was not looking for cell magic anymore. You can see it will look for cell magic on the first line of a cell by putting in %%fake_magic as a first line and then 2 + 2 as a second line of cell. Running that you'll see UsageError: Cell magic %%fake_magic not found.
Hence, your first 'error' is that you are missing that the first line of the cell where you want to use cell magic becomes special. You cannot have something else on the first line where you want to use cell magic, even if it is commented out. In the image, you have #%%flake8 above %%pycodestyle. If you remove that line, it should work.
2nd ERROR
I'm basing this on your image you posted for '2nd ERROR' and not the inaccurate code you posted:
You've stumbled upon a bug currently involving flake8. (Maybe same or more bugs seem to prevent the %%flake8 magic from working at all for now, see comments.)
The solution/workaround is very similar to the '1st ERROR'. Remove the line you were trying to comment out because it being there is causing an issue.
The reasoning appears to be complex about the way the %%flake8 cell magic appears to work behind the scenes so that you cannot have comments in the code content at this time or it won't work. (And the second time it sees that comment symbol, it throws the error you see.) This bug has been reported here.
But the solution/work-around for now is straightforward. Remove the complexity you added, and see if it works.
In case of the %%flake8 magic, running the demo notebook as shown there doesn't work as shown, and so there is indeed a bug in the current version that was introduced by actually a bug in flake8 that the extension uses, see the specific comment here and the link to the underlying issue over at the flake8 repo. (In fact the extent that it doesn't work may be greater than the notebook reflects because as discussed in the comments, even cells without commented lines fail to report any formatting issues. The demo actually doesn't have any without and so I got distracted noting it only didn't show the buffer error for the first one in the demo notebook but since it had a commented line I thought it was still related.)The other way to workaround it at present is to install an older version of flake8 as pointed out here. The solution was merged though and should be available soon, and so just avoiding the triggering code in simple cases like yours is probably easier.
Note about the inaccurate code:
Post code for what gave you the issue, not what you think gave you the issue. Part of why you are asked to provide code as text the way you ran it, it is so those looking into it can run it the same way. Plus they don't have to type and can easily run it as you did. Beyond that, there's more reason behind it: you can try to see if what you observed originally matches what you are seeing now.
If you had run what you posted under the heading '1st ERROR' as the code block text, you would have seen it without the error you showed in your image. Usually you'd then discern the error/difference yourself. In other words, starball's comment was trying to point you to why you should be doing that, and sorted that 1st error out yourself. That would ultimately make your point about the fragile nature of %%flake8 magic have more impact because it isn't diluted by report of an error that isn't really an error. Plus, you may have realized what was necessary to avoid '2nd ERROR' because that code block works without error no matter how many times you run it.
Technical notes:
Anyone wishing to try out pycodestyle_magic with some of this code and the demo notebooks can click here to launch such a session served via the mybinder.org. service with most things necessary already set up. Once the session starts up in the classic Jupyter notebook interface, you need to do some further preparation to use pycodestyle_magic. As detailed here, you can install it with pip install flake8 pycodestyle_magic. So open a new notebook with the Python kernel backing it using New drop down on the upper right side and then choose the Python3 kernel. When it opens, make a cell that has %pip install flake8 pycodestyle_magic and run it. Then put %load_ext pycodestyle_magic as a cell and run that. You can now try the magic with code or pull the demo notebooks over and run those.
When working in RStudio (version 0.99.482 and 1.0.136), if I source a file and an error occur I just get the error message without any context. If the file is longer than a few lines of code, that informaiton is largely useless. What I want to know when an error occurs is the following:
What function threw the error? Preferably what function I called from my script, not something burried deep inside a package.
On what line of my file did the error occur?
This seems like a very basic thing for a scripting language to do, but yet I am unable to find an easy solution. Yes, I am aware of the traceback() function, but (a) it is a hassle to call it every time there is an error, and (b) the output is massive and not that helpful.
I have a script with self-written functions (no plots). When I copy-paste that script into the R-Studio console, it takes ages to execute, but when I use source("Helperfunctions.R") it doesn't take more than a second.
Question: Where does the difference in speed come from?
I am aware of two differences between running code via the source() function vs. entering code at the R-Studio console:
From ?source:
Since expressions are not executed at the top level, auto-printing is not done.
The way I understand this: source() will not plot graphs (unless made specific with e.g. print(plot)), while the R Studio console codes will always plot graphs. I'm sure this will affect the speed of execution to a certain degree, but this seems irrelevant in my case, because there are barely any plot calls.
And:
(...) the complete file is parsed before any of it is run
I have been working with R for a while now, but I'm not sure whether this relevant for the speed-issue I'm having. Is it possible that completely parsing all code "before any of it is run" speeds up the execution of my helper functions script by a factor of a hundred?
Edit: I'm using R version 3.2.3.
The issue is not source() vs. console line code. Instead, it is an issue of how RStudio sends code from the source pane to the console.
When I copy the content of Helperfunctions.R and run it in RGui (instead of RStudio), the code is executed with nearly the same speed as when I use source("Helperfunctions.R") in RStudio.
Apparently, lines of code always (?) require more execution time in RStudio than in RGui. Even though you may usually not notice the time-difference when executing a couple of lines in the console, it seems to make a huge difference when, say, 3.000 lines of code are being executed in the R Studio console at once.
My understanding is that upon using source("Helperfunctions.R") in the RStudio source pane, the code is not actually sent to the RStudio console (which would have been slow), but is actually executed directly in the R language.
The problem is that when I run the code, there's no return in the console; I mean it does run the code, but does not return any output.
For example, if I write
v <- c(1, 2, 3, 4, 5)
v
I would expect in return
[1] 1 2 3 4 5
But it's not working.
I have version RStudio Version 0.98.1079 and R Version 3.1.1
Possibility 1 (until the + sign was mentioned): I was wondering if you had been doing a tutorial where they were demonstrating the sink function and you hadn't gotten to the point where it was reversed.
> sink('out.txt') # diverts all output to a disk file
> v <- c(1,2)
> v # output went to file
> sink() # sets the output back to the console
> v
[1] 1 2
Another way would be to call closeAllConnections:
> sink('out.txt')
> v
> v
> closeAllConnections()
> v
[1] 1 2
Possibility 2: To address the lack of response with a "+" showing at the Rstudio console ... that is a sign that the R parser "thinks" the entered text has not completed a full R command. It may indicate that you haven't typed a closing bracket or parenthesis. If typing one or two of those is unsuccessful and you keep getting mor +'s then you may be successful with typing the [esc]-key. If it is showing up immediately after a restart then you should check your code for correctness and make sure that the .Rdata file is deleted from your working directory. If you don't know what that means then you may need to search for the methods appropriate to your operating system. You could also have an error in the code of one of your .rprofile files.
In any case these two possibilities have nothing to do with Rstudio per se and everything to to with the typical behavior of an R console session in pretty much any IDE.
Do the lines still start with a "+"? It is also possible you forgot to close the brackets of a function. Try "}".
I had the same issue and none of the tips mentioned here were working.
Session > Restart R did the trick for me, possibly suggesting that I had a similar problem as andrewH but was not patient enough to wait for R to behave again.
This is a very old question, but I just had the same problem with a different cause, so I thought I would describe it here case it should be useful to someone else. I was getting the regular command prompt, with nothing more, no matter what I typed at the command line. I tried multiple returns, escape, sink, traceback, closeAllConnections (which did give me a response, "error: unexpected ) in (), but then went back to the command prompt and ignored a second traceback).
Anyway after half an hour or so of pulling my hair out, up pops "View(Mid2)". Mid2 is a tibble with 8.5 million observations of 88 numeric variables. I must have tapped it in the environment pane accidentally. I suppose it just took that long for the viewer to render it. I assume that all the other things I did hit at once, because RStudio crashed immediately thereafter.
The interesting thing about this particular version of the problem is what didn't happen. The red stop sign in the upper right of the console window, that lights when R is busy, didn't light. That is unfortunate -- but understandable, if the RStudio viewer is a different process. But also, when my computer is working hard on a really big computation or IO task, the fan usually starts, but it didn't. Don't know why. . I took its absence, incorrectly, to mean no such computation was underway.
If the lines in console are starting with "+".
Save your work and close the 'RStudio' or other tool which you are using and Start it again, it worked for me.
If you are using R Studio Cloud, refresh or re-opening won't work.
Only clue from the above posts or answers is your console will always start with '+'
In my case I tried all possibilities of closing braces.
And ")" worked for me when I typed that into the console and press enter.
sink() function did nothing in R Studio Cloud
A simple mistake might have also caused this problem:
A rather lengthy command left abandoned in the console is blocking the appearance of the result line.
Thus, the console only shows that line, but the result from any code run from the source, will not appear.
To solve this, just switch to the console, remove any remaining command and try again.
Experiencing something like that explained here as an unresponsive console to the R-Code running was just devastating for me when I experienced it. But luckly although I tried every trick explained in this page, it did not work for me. At last I clicked on the "To console" option available just below the Environment, History, Connections, Tutorial Tab on the R Studio. It solved the puzzle for me just now.
The best solution I've found is closeAllConnections and/or sink which almost always work
But as a stop gap measure, View()'ing always works. It's sort of a pain but whatever you wanted to print out, surround by View and you can see it
I have a longer, complex code (>7000 lines) with many nested functions, each of them enclosed in a separate tryCatch. The code works perfectly except for a "pseudo-error":
Error in doWithOneRestart(return(expr), restart): no function to return from, jumping to top level
doWithOneRestart() is internal in R as an element of the tryCatch function. I call it "pseudo-error", because the tryCatch should lead to stop() if an error ocurrs and write the error message in a log file. Instead, this "error" is not stopping the program (actually not influencing it at all) and it is shown only on the console and not written into the log file. Usual debugging procedures did not help, because the error is not reproducible (!): it may ocurr at different processing stages of the program. Changing the warning options to 0 or -1 will not help.
Since the program does the job, this error is not critical. But I would like to understand what is happening. Maybe someone has already experienced the same problem, or could come up with an original debugging strategy ...
Update (28.10.2013):
I found out where the problem came from. It's linked to a problem with java heap overflow (I was using the xlsx package to read Excel files). Among many other problems: although the connection to the Excel file is closed (definitely!), the system considers it as an unused connection (shown in traceback()), tries to close it, but finds out it is already closed: you get the "pseudo-error" described above, and never exactly at the same moment (not reproducible). Using the garbage collector gc() at the right place solved the problem. The script is now running stable for several days.
Advice from Peter Dalgaard on R-help.
The easiest way to get that message is to execute return() from the
top level:
return(1)
You might be trying to return() from source()d file. Or maybe
source()ing something that was intended to be inside a function body
(extraneous '}' characters can do that).
The usual debugging strategies should work: calling traceback() after the error, or setting options(error = recover).