GNAT GPS: Add a custom command - ada

I would like to know if it is possible to add a custom command to the GNAT Programming Studio (GPS)?
If the custom command is invoked (by a button in the menu bar or a keyboard shortcut) an external Python script should be called with the full/absolute path to the file that is opened and selected in the editor.

This is a quick-and-dirty script that might give some direction. I tested it on Linux, but it should also work on Windows. Change the action near the end to invoke the script you like. To actually use it, you must put it in the (hidden) .gps/plug-ins directory which can be found in your home directory. The actual action can be invoked from the context menu in the source code window.
run_my_script.py
"""Run Python Script
This plug-in executes a python script.
"""
###########################################################################
# No user customization below this line
###########################################################################
import os, sys
import GPS
from gps_utils import interactive
def __contextualMenuFilter(context):
# Check if the context is generated by the source editor
if not (context.module_name == "Source_Editor"):
return False
# If all OK, show the menu item in the context menu.
return True
def __contextualMenuLabel(context):
# Get current buffer
name = context.file().name()
basename = os.path.basename(name)
# Name of the menu item.
return "Run Python script for <b>{}</b>".format(basename)
#interactive(
name ="Run Python script",
contextual = __contextualMenuLabel,
filter = __contextualMenuFilter)
def on_activate():
# If modified, then save before proceeding.
eb = GPS.EditorBuffer.get()
if eb.is_modified:
eb.save()
# Run the action (defined below).
GPS.execute_action("my_script")
GPS.parse_xml ("""
<action name="my_script">
<external output="Output of my_script">python3 /home/deedee/my_script.py %F</external>
</action>""")
my_script.py (some test script)
import sys
print ("Running script {0} for {1}".format(sys.argv[0], sys.argv[1]));
output (shown in GPS on a new tab named "Output of my_script")
python3 /home/deedee/my_script.py /home/deedee/example/src/main.adb
Running script /home/deedee/my_script.py for /home/deedee/example/src/main.adb
Some relevant info from the GNAT Studio (formerly GPS) documentation:
15.5.2. Defining Actions
15.5.3. Macro arguments
15.8.7.3. Redirecting the output of spawned processes
17. Scripting API reference for GPS

Related

How to capture the log details on pytest-html as well as writing in to Console?

In my pytest script, I need to customize the pytest-HTML report for capturing the stdout at the same time writing into the console as I have user input in my automated test.
test_TripTick.py
import os
import sys
import pytest
from Process import RunProcess
from recordtype import recordtype
from pip._vendor.distlib.compat import raw_input
#pytest.fixture(scope="module")
def Process(request):
# print('\nProcess setup - module fixture')
fileDirectory = os.path.abspath(os.path.dirname(__file__))
configFilePath = os.path.join(fileDirectory, 'ATR220_Config.json')
process = RunProcess.RunProcess()
process.SetConfigVariables(configFilePath)
process.GetComPort(["list=PID_0180"])
def fin():
sys.exit()
request.addfinalizer(fin)
return process
def test_WipeOutReader(Process):
assert Process.WipeOutTheReader() == True
def test_LoadingKeysIntoMemoryMap(Process):
assert Process.LoadingKeysIntoMemoryMap() == True
def test_LoadingFW(Process): # only use bar
assert Process.LoadingFW() == True
def test_LoadingSBL(Process):
assert Process.LoadingSBL() == True
def test_CCIDReadForPaymentCards(Process):
assert Process.CCIDReadWrite('Payment Card') == True
Currently, if I run the following command from the windows command line, I get output on the console, but no captured output on the HTML report.
pytest C:\Projects\TripTickAT\test_TripTick.py -s --html=Report.html --verbose
Also, I would like to know the programmatic way of customizing the HTML report where I can update the file name, ordering test based on time of the execution and capturing the std-out.
I have tried additional flags to the pytest command. --capture sys and
-rP for Passed tests. --capture sys and -rF for failed tests
And I can see the console log as well in the html document after I click show All details button as shown in the output. I have captured only partial screen for the purpose of showing to you. But you can scroll down the output to see all the console logs. The grey area in the image below is the console output. I am not sure of the command line level flag that works regardless of failed or passed tests. But here is a temporary solution. This will print logs on command line console as well as html logs console
`

How do I determine whether a julia script is included as module or run as script?

I would like to know how in the Julia language, I can determine if a file.jl is run as script, such as in the call:
bash$ julia file.jl
It must only in this case start a function main, for example. Thus I could use include('file.jl'), without actually executing the function.
To be specific, I am looking for something similar answered already in a python question:
def main():
# does something
if __name__ == '__main__':
main()
Edit:
To be more specific, the method Base.isinteractive (see here) is not solving the problem, when using include('file.jl') from within a non-interactive (e.g. script) environment.
The global constant PROGRAM_FILE contains the script name passed to Julia from the command line (it does not change when include is called).
On the other hand #__FILE__ macro gives you a name of the file where it is present.
For instance if you have a files:
a.jl
println(PROGRAM_FILE)
println(#__FILE__)
include("b.jl")
b.jl
println(PROGRAM_FILE)
println(#__FILE__)
You have the following behavior:
$ julia a.jl
a.jl
D:\a.jl
a.jl
D:\b.jl
$ julia b.jl
b.jl
D:\b.jl
In summary:
PROGRAM_FILE tells you what is the file name that Julia was started with;
#__FILE__ tells you in what file actually the macro was called.
tl;dr version:
if !isdefined(:__init__) || Base.function_module(__init__) != MyModule
main()
end
Explanation:
There seems to be some confusion. Python and Julia work very differently in terms of their "modules" (even though the two use the same term, in principle they are different).
In python, a source file is either a module or a script, depending on how you chose to "load" / "run" it: the boilerplate exists to detect the environment in which the source code was run, by querying the __name__ of the embedding module at the time of execution. E.g. if you have a file called mymodule.py, it you import it normally, then within the module definition the variable __name__ automatically gets set to the value mymodule; but if you ran it as a standalone script (effectively "dumping" the code into the "main" module), the __name__ variable is that of the global scope, namely __main__. This difference gives you the ability to detect how a python file was ran, so you could act slightly differently in each case, and this is exactly what the boilerplate does.
In julia, however, a module is defined explicitly as code. Running a file that contains a module declaration will load that module regardless of whether you did using or include; however in the former case, the module will not be reloaded if it's already on the workspace, whereas in the latter case it's as if you "redefined" it.
Modules can have initialisation code via the special __init__() function, whose job is to only run the first time a module is loaded (e.g. when imported via a using statement). So one thing you could do is have a standalone script, which you could either include directly to run as a standalone script, or include it within the scope of a module definition, and have it detect the presence of module-specific variables such that it behaves differently in each case. But it would still have to be a standalone file, separate from the main module definition.
If you want the module to do stuff, that the standalone script shouldn't, this is easy: you just have something like this:
module MyModule
__init__() = # do module specific initialisation stuff here
include("MyModule_Implementation.jl")
end
If you want the reverse situation, you need a way to detect whether you're running inside the module or not. You could do this, e.g. by detecting the presence of a suitable __init__() function, belonging to that particular module. For example:
### in file "MyModule.jl"
module MyModule
export fun1, fun2;
__init__() = print("Initialising module ...");
include("MyModuleImplementation.jl");
end
### in file "MyModuleImplementation.jl"
fun1(a,b) = a + b;
fun2(a,b) = a * b;
main() = print("Demo of fun1 and fun2. \n" *
" fun1(1,2) = $(fun1(1,2)) \n" *
" fun2(1,2) = $(fun2(1,2)) \n");
if !isdefined(:__init__) || Base.function_module(__init__) != MyModule
main()
end
If MyModule is loaded as a module, the main function in MyModuleImplementation.jl will not run.
If you run MyModuleImplementation.jl as a standalone script, the main function will run.
So this is a way to achieve something close to the effect you want; but it's very different to saying running a module-defining file as either a module or a standalone script; I don't think you can simply "strip" the module instruction from the code and run the module's "contents" in such a manner in julia.
The answer is available at the official Julia docs FAQ. I am copy/pasting it here because this question comes up as the first hit on some search engines. It would be nice if people found the answer on the first-hit site.
How do I check if the current file is being run as the main script?
When a file is run as the main script using julia file.jl one might want to activate extra functionality like command line argument handling. A way to determine that a file is run in this fashion is to check if abspath(PROGRAM_FILE) == #__FILE__ is true.

Jupyter (Lab): Browsing the remote file system inside a notebook

I have several Jupyter notebooks which perform analysis on datasets. Right now, a dataset is specified by its filename. Every time the user wants to perform analysis on a new dataset, she/he has to edit the appropriate line in the notebook and modify dataset path string. The datasets can be located in different directories. The notebooks can also be located in different directories. In each notebook I would like to provide a widget that allows the user to browse the remote file system and pick the dataset he/she wants to analyse.
Are there any open source projects that support the above functionality? I am looking for something that is still active/supported and has some basic documentation. I did quick search on Google and surprisingly I didn't find anything.
Then I realised that JupyterLab, the evolution of Jupyter, has something very similar to what I want. It already has a very capable file browser but it is a bit "isolated" from everything else.
Is it possible somehow to get the relative (to the currently opened notebook) path of the selected file in the JupyterLab file browser?
Thank you.
Here's code for a server-side file browsing widget. Only tested in regular Jypter notebook - not Jupyter Lab. Also, must use a fairly recent version. Hope this helps.
import sys
import os
import ipywidgets as ui
from IPython.display import display
class PathSelector():
def __init__(self,start_dir,select_file=True):
self.file = None
self.select_file = select_file
self.cwd = start_dir
self.select = ui.SelectMultiple(options=['init'],value=(),rows=10,description='')
self.accord = ui.Accordion(children=[self.select])
self.accord.selected_index = None # Start closed (showing path only)
self.refresh(self.cwd)
self.select.observe(self.on_update,'value')
def on_update(self,change):
if len(change['new']) > 0:
self.refresh(change['new'][0])
def refresh(self,item):
path = os.path.abspath(os.path.join(self.cwd,item))
if os.path.isfile(path):
if self.select_file:
self.accord.set_title(0,path)
self.file = path
self.accord.selected_index = None
else:
self.select.value = ()
else: # os.path.isdir(path)
self.file = None
self.cwd = path
# Build list of files and dirs
keys = ['[..]'];
for item in os.listdir(path):
if item[0] == '.':
continue
elif os.path.isdir(os.path.join(path,item)):
keys.append('['+item+']');
else:
keys.append(item);
# Sort and create list of output values
keys.sort(key=str.lower)
vals = []
for k in keys:
if k[0] == '[':
vals.append(k[1:-1]) # strip off brackets
else:
vals.append(k)
# Update widget
self.accord.set_title(0,path)
self.select.options = list(zip(keys,vals))
with self.select.hold_trait_notifications():
self.select.value = ()
f = PathSelector('/some/data')
display(f.accord)

How can I set up default startup commands in iPython notebooks?

I want to put couple of cells with commands I need in almost every new notebook in every new notebook I create.
For example when I create a new notebook it should put a
%matplotlib inline
import matplotlib.pyplot as plt
in a cell by default but not execute it.
How could I set something like that up?
This will work for both terminal based IPython shell and Browser based Notebook:
Navigate to ~/.ipython/profile_default
Create a folder called startup if it’s not already there
Add a new Python file called start.py
Put your favorite imports (and custom functions may be) in this file
Launch IPython or a Jupyter Notebook and your favorite libraries will be automatically loaded every time!
Here is my sample for start.py:
Another Source
To define set of commands on default startup, you need to add the commands in the templete ipy_user_conf.py file in your ~/.ipython directory.
This module is imported during IPython startup. So you can easily do : import modules, configure extensions, change options, define magic commands, put variables and functions in the IPython namespace etc.
Here is the sample ipy_user_conf.py :
# Most of your config files and extensions will probably start
# with this import
import IPython.ipapi
ip = IPython.ipapi.get()
# You probably want to uncomment this if you did %upgrade -nolegacy
# import ipy_defaults
import os
def main():
#ip.dbg.debugmode = True
ip.dbg.debug_stack()
# uncomment if you want to get ipython -p sh behaviour
# without having to use command line switches
import ipy_profile_sh
import jobctrl
# Configure your favourite editor?
# Good idea e.g. for %edit os.path.isfile
#import ipy_editors
# Choose one of these:
#ipy_editors.scite()
#ipy_editors.scite('c:/opt/scite/scite.exe')
#ipy_editors.komodo()
#ipy_editors.idle()
# ... or many others, try 'ipy_editors??' after import to see them
# Or roll your own:
#ipy_editors.install_editor("c:/opt/jed +$line $file")
o = ip.options
# An example on how to set options
#o.autocall = 1
o.system_verbose = 0
#import_all("os sys")
#execf('~/_ipython/ns.py')
# -- prompt
# A different, more compact set of prompts from the default ones, that
# always show your current location in the filesystem:
#o.prompt_in1 = r'\C_LightBlue[\C_LightCyan\Y2\C_LightBlue]\C_Normal\n\C_Green|\#>'
#o.prompt_in2 = r'.\D: '
#o.prompt_out = r'[\#] '
# Try one of these color settings if you can't read the text easily
# autoexec is a list of IPython commands to execute on startup
#o.autoexec.append('%colors LightBG')
#o.autoexec.append('%colors NoColor')
o.autoexec.append('%colors Linux')
# some config helper functions you can use
def import_all(modules):
""" Usage: import_all("os sys") """
for m in modules.split():
ip.ex("from %s import *" % m)
def execf(fname):
""" Execute a file in user namespace """
ip.ex('execfile("%s")' % os.path.expanduser(fname))
main()
For more details, please refer the link : Customization of IPython.
I hope this is what you wanted to know.
JupyterLab
In a comment to one of the other answers, the OP pointed out the need to insert the actual code instead of having it load in the background. One way is to create a text keyboard shortcut by going to Settings -> Advanced settings editor -> JSON settings Editor and adding the following under User Preferences:
{
"shortcuts": [
{
"command": "apputils:run-first-enabled",
"selector": "body",
"keys": ["Alt I"],
"args": {
"commands": [
"console:replace-selection",
"fileeditor:replace-selection",
"notebook:replace-selection",
],
"args": {"text": "import pandas as pd\nimport altair as alt\n\n"}
}
}
]
}
This will insert the following snippet each time you press Alt + i in the notebook:
import pandas as pd
import altair as alt
# <-- Cursor placed here
More on text shortcuts in jupyterlab
IPython console
If you are interested in automatically importing commonly used libraries in the IPython console only so that they are there for interactive use, but not in the notebook to avoid issues with sharing notebooks lacking some imports, you can launch IPython like so (and set up an alias to not have to type this each time):
ipython -c "import pandas as pd; import numpy as np" -i
(This was what I was looking for when I originally found this question)

OptionParser in ipython notebook?

I am enjoying developing inside the ipython notebook, but I am having a problem when I want to write a main() function that reads the command line args (with OptionParser, for example). I want to be able to export the code to a .py file and run it from the command line, but I haven't found a way to have a main() that runs both in the notebook with predefined arguments or from the command line with python and command line args. What is the secret?
In case that is not clear, I would like to do something like this:
if __name__ == '__main__':
# if in the notebook
vals = {'debug':True, 'tag_file': 't.tags'}
options = Object()
for k,v in vals.items():
options.setattr(k,v)
args = 'fname1.txt'
# if running as a command line python script
from optparse import OptionParser
parser = OptionParser()
parser.add_option('-d','--debug',action='store_true',dest='debug')
parser.add_option('-t','--tags',action='store',dest='tag_file')
options,args = parser.parse_args()
You cannot determine that you are in an IPython notebook or a qtconsole, or a simple IPython shell, for the simple reason the 3 can be connected to the same kernel at the same time.
It would be like asking, what color is the current key the user is typing. You could get it by looking the plugged usb devices and look for images on the internet and guess the keyboard color, but nothing guarantees you it will be accurate, nor that it won't change, and user can have multiple keyboard plugged, or even painted keyboard.
It is really the same with the notebook, Even if you determine you are in ZMQKernel, are you speeking to qtconsole or webserver ? Again, you found that you were talking to the webserver, are you talking to JS or Emacs ? And so on and so forth.
The only thing you can do, you can ask the user.
What is reliable, is test wether you are in IPython or not.
If you really but reeaaalllyy want a way, as until now, the notebook is the only thing that can display Javascript. And javascript can execute code in pyton. So you might be able to create something that display JS that send back info to the kernel. And using thread and timer you can say that you were not in a notebook (but you will have a race condition).
Don't worry about the distinction. Just set default values, and unless they are overridden from the command line, use those.
if __name__ == '__main__':
parser = OptionParser()
parser.add_option('-d', '--debug', action='store_true', dest='debug',
default=True)
parser.add_option('-t','--tags',action='store',dest='tag_file',
default='t.tags')
options, args = parser.parse_args()
if not args:
args = ['fname1.txt']

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