Like many github users, I would benefit from being able to ignore a specific file from the language statistics. I'm generating/bundling a javascript file from react files and I want to exclude it from the statistics. Here's my .gitattributes file.
BlueSlide/static/js/homepage_compiled.js linguist-generated=true
I'm having trouble finding many examples on this, but the few that I do find look like this (https://help.github.com/en/articles/customizing-how-changed-files-appear-on-github) so I'm not sure why it's not working. Maybe it just takes time to update the statistics?
apparently the =true part breaks it, despite it being on there documentation... As soon as I got rid of it, it worked
BlueSlide/static/js/homepage_compiled.js linguist-generated
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I am working on data factory and was wondering if there are any activities to just "move files" without actually reading them rather than "copy data" (which seems like does a read operation)?
I am trying to move files if any exist from one folder to another and if there are many files, since copy data reads each file, it makes the process slow.
Any suggestion. This is how my current data source looks like and all I want to do is, if there is any csv file exists at the location move it without reading it per say.
So here is a MSFT link I followed to move files.
https://learn.microsoft.com/en-us/azure/data-factory/solution-template-move-files
This tutorial was not very detailed when it comes to explaining everything. Like it assumes that the user needs parameters. I did as it said but my datasets were pointing to exactly where files need to be picked up and land, so I left the parameters empty. Debugging or running the trigger didn't move a file.. solution didn't work.
I had to remove the parameters created in the template to make this work. In case its helpful to some. File move started happening after that.
So lesson learned, empty parameters wont work. If you don't need them remove them.
Also, I watched this tutorial in case its helpful to some one.
https://www.youtube.com/watch?v=u_X_f4z8zoQ
I have implemented a backup per workspace functionality in my extension using workspaceState. Since the data can be sensitive - I'd like to clear all workspaceStates on extension deactivation/uninstall.
The ExtensionContext provides no ability to clear all extension related data across different workspaces with their workspaceStates.
So I've considered saving data on the ExtensionContext globalState, tagging each entry with a workspace id. Problem is that the workspace namespace doesn't provide a way to uniquely identify the current workspace. I thought about hashing workspace name and path but both of these things are changeable and any change will destroy the pointer to the data. This is exactly why I cant just write files to internal folders. The only other solution I have is to write the backup data directly to the workspace and I'd like to avoid that.
How does VSCode maintain the knowledge of which workspaceState belongs to which workspace? How can I tie data to the workspace but have access from anywhere else in VSCode?
Side note: You should avoid saving sensitive data in general. And if necessary, try to encrypt it.
Anyway:
I don't have the full answers but i was researching something similar (An extension I use crashes due to now invalid settings in the WorkspaceState).
I found the Storage for the Workspace state in this folder (windows):
%appdata%\Code\User\workspaceStorage\
In there, you find a lot of folders with hex-based names. Inside those folders, I always found 2 Files named state.vscdb and state.vscdb.backup.
There usually is a 3rd file called workspace.json which helps you figure out if you are in the correct workspace. (but you'd have to iterate through all the folders - maybe there is a way to figure out the folder name coming from the extension API?)
If you open the state.vscdb-file you find something that looks quite like a serialized object set in my eyes. It does have some Seperator chars of unknown function. But you also find full paths or names in there that clearly origin from different modules of VSC - Including the extensions.
I don't need to worry about the other cached stuff i'm just gonna delete the whole folder to fix my current issue. But I'm pretty sure, one can figure out the way the file is built and edit out your sensitive data if one has to.
The state.vscdb.backup-file looks pretty much like what the name is telling you: they probably just make a copy of the other file every few minutes so you have a fallback position.
To add to the conversation, there are two SQLite state databases:
<user-data-dir>\User\globalStorage\state.vscdb
<user-data-dir>\User\workspaceStorage\<workspace.id>\state.vscdb
Depending on how VS Code was launched you could have a Single Folder Workspace or a Multi-Folder Workspace that is global or local. Globally, the data lives here:
Linux: $HOME/.config/Code/
OS X: $HOME/Library/Application Support/Code/
Windows: %APPDATA%\Code\
Locally, the data will be in the .vscode folder of the current workspace.
In my situation:
I open a new workspace.
Set it up as I want it to start every time.
Makes copies of the two SQLite databases.
Copy over the databases before launching VS Code.
This leads to a clean VS Code state.
To see how workspace.id is generated check this link.
I'm developing a Modelica library and need to produce a document with source code listings. I'd like to be able to include the source of the Modelica models without annotations.
I could manually edit them out, but I'm looking for a more automated strategy. I'm guessing the most convenient and straightforward approach is to use some tool to save .mo files with no annotations and include those in my document (I'm using \lstinputlisting in LaTeX).
Is it possible to do this? I have access to Dymola, OpenModelica and JModelica. Dymola is obviously capable of producing such a listing, as it's able to include it in the automatically generated documentation (File > Export > HTML...). I've been looking into scripting with Dymola and OpenModelica, but haven't found a way to do this either.
JModelica seems like it could be a good option, but I don't have experience working with Python. If this is possible and someone gives me some pointers, I'm willing to look into it myself. I found a mention to a prettyprint function that might do the job, but I'm not sure where to start. I can't even find reference to that function in the latest documentation.
It would also be more convenient for me to find a way of doing it with Dymola/OpenModelica (whether through the UI or by using a script). Have I missed something?
I think you could use saveTotalModel("total.mo", MyModelName) in OpenModelica. This will strip most annotations (not ones used for code generation if I remember correctly) and pretty-print the source code including all dependencies. Then you just copy-paste the models/packages that you want to include in the listing. Or if you prefer, you can do something like the following to only include code for a particular model:
loadModel(Modelica);
loadFile("MyModel.mo");
saveTotalModel("total.mo", MyModel.A.B);
clear();
loadFile(MyModel);
str := list(MyModel.A.B);
writeFile("MyModel.A.B.listing", str);
In my Protractor conf.js file, I'd like to re-use the same spec files multiple times; however, it's seems to not be possible.
Some background:
We are reading test cases from a JSON file, launching reports, then testing grid results and various DOM elements.
All reports have the same format. The primary differences lie in the report titles, data columns, actual data results, etc.
So in my conf.js file, ideally I'd like to re-use the same spec files multiple times - but my understanding is that I cannot do this.
For example, my spec array:
specs: [
'spec/report1-spec.js',
'spec/report-grid-details-spec.js',
'spec/report2-spec.js',
'spec/report-grid-details-spec.js',
'spec/report3-spec.js',
'spec/report-grid-details-spec.js',
]
I've read this post (http://ramt.in/how-to-run-identical-jasmine-specs-multiple-times-with-protractor/ ) where you can move your spec files into a node module, but 1) I don't want to move all specs files there, and 2) it doesn't work anyway when I move even one spec file into a module export file.
If I can't do it, then I'll just move my report-grid-details-spec.js code into a common page object file and call it whenever it's needed.
Just wondering if anyone out there has found a solution to this need to re-use spec files multiple times in one conf.js configuration.
Thank you,
Bob
If I can't do it, then I'll just move my report-grid-details-spec.js code into a common page object file and call it whenever it's needed.
This would probably be the easiest way to approach the problem. Though, I like the idea of putting specs into modules - it is a plus to reusability overall.
The thing is, jasmine does not allow executing the same test in a single test run. And, from what I understand, there is no easy way to change the behavior.
One of the possible workarounds is to completely restart protractor and, hence, recreate the jasmine testing environment so that the next report-grid-details-spec.js would run in a new jasmine environment - this is something that protractor-flake project uses to retry the failing tests (it basically restarts protractor through command-line passing the failing specs as a comma-separated list to the specs argument, source).
Can anyone share his experience on workflow for R peject development under ESS? I tried several times to learn emacs but I have not get it yet. I can understand ESS as an editor, but is there a project view in ESS? what's the efficient ways to set up/view R project directory, coding, and testing, and how's ESS has an edge to facilitate the whole process?
Do you use ESS as a good R editor only or tend to emulate a R IDE environment within ESS?
Thanks for any advices.
It sounds like you're asking two separate questions.
One question concerns workflow and the other concerns using ESS.
As I use StatET and Eclipse, I'll just share my experience regarding the workflow aspect of your question.
As with Vincent I also follow something like the workflow set out by Josh Reich here (also see Hadley's useful comments):
Workflow for statistical analysis and report writing
Although it can vary between projects, I tend to have a couple of main R files
import.R: this imports data files and does any necessary cleaning and manipulation
analyse.R: This generates the output that I need for any final report
main.R: This calls import.R and analyse.R
The aim is for import.R and analyse.R to represent the complete and final workflow for producing the final results of any analyses.
In terms of a directory structure for an analysis project, I'll often also have the following folders
data: for storing any raw data files
meta: for storing meta data, such as variable labels, scoring systems for tests, recoding information, etc.
output: for storing any graphics, tables, or text generated by my analyses that I might want to incorporate into an external program
temp: When exploring the data and brainstorming analyses, I like to type code into files instead of using the console. I tend to label these temp1.R, temp2.R, temp3.R. I store these in a temp folder. That way I have a permanent record that's easily accessible. If the analyses become final they get incorporated into one of the main R files (i.e., import.R or analysis.R)
functions: If I think that a function will be needed across a couple of projects, I often place it one function per file or a set of related functions in a file in a folder called functions. This makes it relatively easy to reuse functions across projects, when the formal requirements of package development are more than needed.
library: If I want to create some general functions that I think will be project specific, I'll place them in this folder
save: A folder to store any saved R objects
StatET and Eclipse make it easy to interact with such a file system.
Of course, given all the R gurus that use ESS and Emacs, I'm sure it also handles interactions with the file system well.
I'm not exactly sure what you expect as an answer on this one. I, for one, have stolen (and adapted) a system that was suggested here a little while ago (by Josh Reich):
Create a folder for every project, and split up your work in a bunch of different .R files:
Load.R for getting your raw data into R;
Prep.R for cleaning the data, recoding variables, etc.;
Func.R for coding any custom functions you will need for evaluation; and
Eval.R for running your final stuff.
If that doesn't fit your style, just change it.
Then, you can either have a master file to call each of the parts one after each other (good for reproducibility), or save at different stages and have the individual scripts load the appropriate data (good if some of the prep work is very computationally/time intensive).
**
On a different note, the trick that is posted at the link really helped me get into ESS. It turns Shift-Enter into a one-stop-ESS-shop: http://www.kieranhealy.org/blog/archives/2009/10/12/make-shift-enter-do-a-lot-in-ess/
Others have given you some good ideas about how to setup your directory/file structure for a project.
You also asked about "project views," in which case you might want to look into the Emacs Code Browser (ECB).
You can find some screen shots of it in action on its site, here:
http://ecb.sourceforge.net/screenshots/index.html