eshangj/stackoverflow_q_and_a_sample huggingface dataset:
Question: My project has an executable called powerscript.exe, which is a Python interpreter that does and knows some extra things. This is out of my control, I can not change this. From the command line I can use this as a drop-in replacement for the Python interpreter. In PyCharm I cannot. Adding this thing as a Python interpreter yields the error message:  Select Python Interpreter An invalid Python interpreter name 'powerscript.exe'!  Which I guess is just a sanity-check on the filename that I want to deactivate or work around. I have read How to resolve "Invalid Python interpreter name 'python.exe'!" error in PyCharm, they have the same error message but in their case it is a false positive, in my case I really do have an invalid name.

Answer: Since it's apparent that PyCharm validates only the name of the executable, you can make a copy of the wrapper executable powerscript.exe and rename the copy to python.exe as an interpreter for PyCharm.
Question: I'm trying to solve a cubic with a parameter r, for x. The cubic is the awful expression poly = b*(-(10 + x)*b - 10*b) - ((8/3) + x)*((10+x)*(1+x) - 10)  where b = sp.sqrt((8/3)*(1 - a))  which factors out to x^3 + (41/3)x^2 + (8/3)(a + 10)x + (160/3)(a - 1). SymPy's solveset() gives a solution, but it is really long mostly due to the large mass of repeated fractions in the answer. I'd like to do something like Rational(solution) to make the solution nicer, but it doesn't work. Here's my code and the error: import sympy as sp from sympy import Eq, solveset, Rational from sympy.abc import x, a, b poly = b*(-(10 + x)*b - 10*b) - ((8/3) + x)*((10+x)*(1+x) - 10) polysub = poly.subs(b,sp.sqrt((8/3)*(1 - a))) polyeq = Eq(polysub,0) solutionset = solveset(polyeq,x) Rational(solutionset)  TypeError: invalid input: {ridiculously long solution} 

Answer: If you import S and use S(8)/3 instead of 8/3 you will get fractions instead of floats...but it will still be complicated. You can also use cse to give a symbolically simpler substituted expression: ...your code >>> from sympy import cse >>> cse(solve(polyeq,x)) [(x0, 8*a + 817/9), (x1, (-556*a + sqrt(-4*x0**3 + (70450/27 - 1112*a)**2)/2 + 35225/27)**(1/3)), (x2, x1/3), (x3, x0/(3*x1)), (x4, sqrt(3)*I/2), (x5, -x4 - 1/2), (x6, x4 - 1/2)], [-x2 - x3 - 41/9, -x2*x5 - x3/x5 - 41/9, -x2*x6 - x3/x6 - 41/9]) >>> _[-1] [-x2 - x3 - 41/9, -x2*x5 - x3/x5 - 41/9, -x2*x6 - x3/x6 - 41/9]
Question: I've created a module in odoo18 and in that I created a xml called product_views. It has a list in it. I added a button in the header of the list but I can't see it. Here is my xml file: <?xml version="1.0" encoding="utf-8"?> <odoo> <record id="view_product_list" model="ir.ui.view"> <field name='name'>"electronic.product.list"</field> <field name='model'>product.product</field> <field name="priority" eval="99"/> <field name="arch" type="xml"> <list> <header> <button name="import_action" string="import" type='object'/> </header> <field name="name" string="product name" /> <field name="volume" string="quantity" /> <field name="x_link" string="quantity" /> </list> </field> </record> <record id="action_electronic_products" model="ir.actions.act_window"> <field name="name">Electronic Products</field> <field name="res_model">product.product</field> <field name="view_mode">list</field> <field name="view_id" ref="view_product_list"/> </record> <menuitem id="menu_electronic_product_root" name="Electronic Products" action="action_electronic_products" sequence="10" groups="base.group_user"/>  This is my model: from odoo import models, fields, api class ProductProduct(models.Model): _inherit = 'product.product' # Correct inheritance x_link = fields.Char( string='Product Link', help='URL of the product', default='', tracking=True # Shows changes in chatter ) def import_action(self): return { 'name': 'Import Products', 'type': 'ir.actions.act_window', 'res_model': 'product.import.wizard', 'view_mode': 'form', 'target': 'new', 'context': {'default_product_id': self.id}, }  Can you help me please?

Answer: Actually, your code works, the button does appear.  I assume that, you didn't know that in Odoo, for general, buttons that used in the tree/list view don't always show, they only appear when any data is selected. So, if I don't select any data, you can see on the picture below, the "import" button of yours will disappear.  Therefore, if what you want is for the button to always be shown, then you need to make further customization by utilizing the Owl JS component (but it needs more advanced knowledge) You can see a topic discussed in Odoo forum similar with that here: How to add a button next to Create in List View in Odoo 16
Question: I would like to create a class that looks something like ConfigAndPath: import pathlib from typing import TypeVar, Generic from dataclasses import dataclass, astuple class ConfigBase: pass T = TypeVar("T", bound=ConfigBase) @dataclass class ConfigAndPath(Generic[T]): path: pathlib.Path config: T  I often have a list of these ConfigAndPath, and so would want to destructure it in list comprehensions like this: l: list[ConfigAndPath[MyConfig]] = ... filenames = [_path.name for _path, _my_config in l]  So I added an __iter__ method to my class: # In ConfigAndPath def __iter__(self): return iter(astuple(self))  However, I'm not sure how to make it so that my typechecker (Pyright) realizes that _path is a pathlib.Path and _my_config is a MyConfig. This works with NamedTuple, however I can't appear to use generics with NamedTuple due to it not allowing multiple inheritance. Is this possible to specify what I want? I tried writing an as_tuple method: # In ConfigAndPath def as_tuple(self) -> Tuple[pathlib.Path, T]: return self.path, self.config  Which then allows me to write filenames2 = [_path.name for _path, _my_config in [i.as_tuple() for i in l]]  Which gives me a type hint but is quite verbose and walks the list twice.

Answer: You can destructure a dataclass using a match block (requires python ≥ 3.10). It is more verbose, but type checkers understand it. For example, using mypy: @dataclass class Foo(Generic[T]): x: int y: T foo = Foo[float](1, 2.0) match foo: # NB. this case means must be an object, and have an attribute x and attribute y, # which will be stored in the current scope as x and y respectively. case object(x=x, y=y): reveal_type(x) # note: Revealed type is "builtins.int" reveal_type(y) # note: Revealed type is "builtins.float" assert x + y == 3 case _: raise RuntimeException('unreachable')  However, a match block is a statement and not an expression. As such it cannot be used within a list comprehension.
Question: I'm trying to use the wx.FileDialog class to select the name of a file. I don't want to open it. This is a minimal example of what I'm trying to do: import wx if __name__ == '__main__': app = wx.App(redirect=False) frame = wx.Frame(None) frame.Show() dlg = wx.FileDialog(parent=frame, style=wx.FD_OPEN|wx.FD_FILE_MUST_EXIST, wildcard="Project (*.ap*)|*.ap*|All files (*.*)|*.*") dlg.ShowModal() app.MainLoop()   The text is in Swedish and says "File in use. Select a different name of close the file in use in another program". I'm trying to select the filename of a TIA Portal project file (Siemens PLC programming tool). Unfortunately it seems that TIA Portal locks the file. NOTE: I don't want to open the file. I just need the name.

Answer: Unfortunately it looks like this is currently impossible because wxWidgets doesn't set FOS_SHAREAWARE flag and so doesn't customize the default handling of locked files — which is to do what you see. It should be relatively straightforward to implement support for this in wxWidgets itself and, as it's an open source library which is open to contributions, anybody could do it. But somebody would have to do it first, before this functionality becomes accessible in wxPython.
Question: My environment: OS: Windows 11 Python version: 3.13.2 NumPy version: 2.1.3  According to NumPy Fundementals guide describing how to use numpy.genfromtxt function:  The optional argument comments is used to define a character string that marks the beginning of a comment. By default, genfromtxt assumes comments='#'. The comment marker may occur anywhere on the line. Any character present after the comment marker(s) is simply ignored. Note: There is one notable exception to this behavior: if the optional argument names=True, the first commented line will be examined for names.  To do a test about the above-mentioned note (indicated in bold), I created the following data file and I put the header line, as a commented line: C:\tmp\data.txt #firstName|LastName Anthony|Quinn Harry|POTTER George|WASHINGTON  And the following program to read and print the content of the file: with open("C:/tmp/data.txt", "r", encoding="UTF-8") as fd: result = np.genfromtxt(fd, comments="#", delimiter="|", dtype=str, names=True, skip_header=0) print(f"result = {result}")  But the result is not what I expected: result = [('', '') ('', '') ('', '')]  I cannot figure out where is the error in my code and I don't understand why the content of my data file, and in particular, its header line after the comment indicator #, is not interpreted correctly. I'd appriciate if you could kindly make some clarification.

Answer: Thanks to what @mehdi-sahraei suggested, I changed the dtype to None and this permitted to parse other rows (any row after the header line) correctly. Finally, it seems that there is no bug about how the header line is treated but rather a lack of clarity in the documentation. As indicated in my original post, the documentation says:  ... if the optional argument names=True, the first commented line will be examined for names ...  But what the documentation doesn't tell you, is that in that case, the detected header is stored in dtype.names and not beside other rows that come after the header in the file. So the header line is actually there but it is not directly accessible like other rows in the file. Here is a working test case for those who might be interested to check how this works in preactice: C:\tmp\data.txt #firstName|LastName Anthony|Quinn Harry|POTTER George|WASHINGTON  And the program: with open("C:/tmp/data.txt", "r", encoding="UTF-8") as fd: result = np.genfromtxt( fd, delimiter="|", comments="#", dtype=None, names=True, skip_header=0, autostrip=True, ) print(f"result = {result}\n\n") print("".join([ "After parsing the file entirely, the detected ", "header line is: ", f"{result.dtype.names}" ]))  Which gives the expected result: result = [('Anthony', 'Quinn') ('Harry', 'POTTER') ('George', 'WASHINGTON')] After parsing the file entirely, the detected header line is: ('firstName', 'LastName')  Thanks everyone for your time and your help and I hope this might clarify the issue for those who have encountered the same problem.
Question: I have a dataframe, I need to select a range of data based on a month value, but the result expected is always showing six rows where the month selected appears in the filtered data , here's the code : import pandas as pd data = { "function": ["test1","test2","test3","test4","test5","test6","test7","test8","test9","test10","test11","test12"], "service": ["A", "B", "AO", "M" ,"A", "PO", "MP", "YU", "Z", "R", "E", "YU"], "month": ["January","February", "March", "April", "May", "June", "July", "August", "September", "October", "November", "December"] } df = pd.DataFrame(data) selected_month = "January" selected_month_idx = df[df["month"] == selected_month].index[0] six_months_indices = [i % len(df) for i in range(selected_month_idx - 2, selected_month_idx + 4)] six_months_df = df.loc[six_months_indices] # add .reset_index(drop=True) if needed print(six_months_df)  output :  function service month 10 test11 E November 11 test12 YU December 0 test1 A January 1 test2 B February 2 test3 AO March 3 test4 M April  the issue with this code is when I select January for example, the order of the months is not good, what I expet is somthing like that :  function service month 0 test1 A January 1 test2 B February 2 test3 AO March 3 test4 M April 3 test5 A May 3 test6 PO June  when I select December for example the output should be :  function service month 6 test7 MP July 7 test8 YU August 8 test9 Z September 9 test10 R October 10 test11 E November 11 test12 YU December  when I select Octobre the output should be for example :  function service month 6 test7 MP July 7 test8 YU August 8 test9 Z September 9 test10 R October 10 test11 E November 11 test12 YU December  the order of the month displated matters, always min(month) => max(month) output like this is not expected : output :  function service month 10 test11 E November 11 test12 YU December 0 test1 A January 1 test2 B February 2 test3 AO March 3 test4 M April  anyone please could to adjust the code above, thanks

Answer: If there is default index is possible select by DataFrame.loc: selected_month_idx = df[df["month"] == selected_month].index[0] start = np.clip(selected_month_idx, 0, len(df) - 6) six_month_window = df.loc[start : start + 5] print(six_month_window)  If always match value in condition, get position of first True by np.argmax, count start of first value by np.clip and select by position in DataFrame.iloc: selected_month_idx = np.argmax(df["month"] == selected_month) start = np.clip(selected_month_idx, 0, len(df) - 6) six_month_window = df.iloc[start : start + 6]
Question: I have come across multiple ways to describe a websocket connection object while using the websockets library in python but can't seem to understand which way to go. In the documentation, the code to start a server is very simple. import asyncio from websockets.asyncio.server import serve async def hello(websocket): name = await websocket.recv() print(f"<<< {name}") greeting = f"Hello {name}!" await websocket.send(greeting) print(f">>> {greeting}") async def main(): async with serve(hello, "localhost", 8765) as server: await server.serve_forever() if __name__ == "__main__": asyncio.run(main())  But when I simply copy and paste the code, the IDE cannot recognize the .recv() and the .send() methods. So I started to look around what is the type of the websocket object to get some idea about it and what other methods are available for that object. So I found that all these can be used: - websockets.ServerConnection - websockets.server.ServerConnection - websockets.asyncio.server.ServerConnection  I think the methods they provide are the same. If these are significantly different, then an explanation? Can I use any of the three and it won't make much difference? In the documentation, the asyncio implementation of the server creates a websockets.asyncio.server.ServerConnection instance upon client connection. So then what are the other classes? I'm sorry if this is too basic.

Answer: No need to apologize — your question is valid, and it’s clear you’re trying to understand how the websockets library works. That’s awesome! So, here’s what’s going on: When you define async def hello(websocket), the websocket parameter is the connection object to the client. Specifically, if you’re using websockets.asyncio.server.serve, that websocket is an instance of websockets.asyncio.server.ServerConnection. The .recv() and .send() methods you’re using are part of that class — they’re the standard methods to receive and send messages. If your IDE doesn’t recognize them, it’s probably just not sure what type websocket is, or it’s missing some type hints. Now about those different class names:  websockets.ServerConnection — this is basically a shortcut to one of the actual implementations.  websockets.server.ServerConnection — this might be from an older version or an intermediate module path.  websockets.asyncio.server.ServerConnection — this is the one you want to use when working with asyncio. It’s what the serve() function actually creates behind the scenes.
Question: I am trying to implement simple gradient descent to find the root of a quadratic equation using PyTorch. I'm doing this to get a better sense of how the autograd function works but it's not going very well. Let's say that I want to find the roots of y = 3x^2 + 4x + 9 as a random example. Below was my first attempt to run one step of gradient descent and re-calculate the gradient: import torch # Step size alpha = 0.1 # Random starting point x = torch.tensor([42.0], requires_grad=True) # Function y = 3 * x^2 + 4 * x + 9 # Find the minimum of this with gradient descent y = 3 * x ** 2 + 4 * x + 9 y.backward() print(x.grad) with torch.no_grad(): x -= alpha * x.grad y.backward() print(x.grad)  This didn't like calling .backward() multiple times, so I updated it to this: import torch # Step size alpha = 0.1 # Random starting point x = torch.tensor([42.0], requires_grad=True) # Function y = 3 * x^2 + 4 * x + 9 # Find the minimum of this with gradient descent y = 3 * x ** 2 + 4 * x + 9 y.backward(retain_graph=True) # <--- Change here print(x.grad) with torch.no_grad(): x -= alpha * x.grad y.backward(retain_graph=True) # <--- And here print(x.grad)  and I get the error: RuntimeError: one of the variables needed for gradient computation has been modified by an inplace operation: [torch.FloatTensor [1]] is at version 1; expected version 0 instead. Hint: enable anomaly detection to find the operation that failed to compute its gradient, with torch.autograd.set_detect_anomaly(True).  I get the sense that I am fundamentally misunderstanding something about PyTorch here. How would I do this correctly?

Answer: In-place operations like x -= ... can break the computation graph if the tensor is a leaf tensor that requires gradients, and the operation is not inside a torch.no_grad() context. This causes a version mismatch error during .backward() if you try to reuse the computation graph or modify variables that are part of it.  Gradients in PyTorch accumulate by default for efficiency (useful during mini-batch training). So you must call x.grad.zero_() (or reinitialize x with .detach()) before the next .backward() pass if you're doing manual gradient descent.  Updating model parameters (or any tensor that requires gradients) must happen inside torch.no_grad() to prevent PyTorch from tracking the update operation itself. If you don't, the update becomes part of the graph and causes unwanted memory usage and errors.  retain_graph=True is only needed if you plan to reuse the same computation graph across multiple backward passes (e.g., higher-order derivatives). In simple gradient descent (with one .backward() per step), there's no need for retain_graph=True.   Here is the code with correction: import torch alpha = 0.1 x = torch.tensor([42.0], requires_grad=True) for i in range(10): y = 3 * x ** 2 + 4 * x + 9 y.backward() print(f"Step {i+1}: x = {x.item():.4f}, y = {y.item():.4f}, grad = {x.grad.item():.4f}") with torch.no_grad(): x -= alpha * x.grad x.grad.zero_() # you may replace x.grad.zero_() with x = x.detach().clone().requires_grad_(True) for advanced control.
Question: I work in WSL Ubuntu. After instalation python3.13 dependencies from my previous projects stopped working. Venv with python 3.12 stopped activate in vscode interface. ErrorMessage:  An Invalid Python interpreter is selected, please try changing it to enable features such as IntelliSense, linting, and debugging. See output for more details regarding why the interpreter is invalid.  command "source venv/bin/activate" works but all libraries "could not be resolvedPylance". When I try reinstal I see error:  ModuleNotFoundError: No module named 'pip'  But pip installed in this venv. I can see it folders. init and main files etc. I have pip for python3.12 and I have -m venv for python 3.12. I can recreate this venv but why I can`t turn it on properly? Tried reinstall venv and pip for python3.12. python3 -m ensurepip is ok:  Requirement already satisfied: pip in /usr/lib/python3/dist-packages (24.0)  But python3.12 -m ensurepip  ensurepip is disabled in Debian/Ubuntu for the system python.  python3.12 -m pip --version is working also as python3.12 -m pip install and python3.12 -m pip --upgrade pip

Answer: I ran into the exact same problem after installing Python 3.13 on WSL. Suddenly, all my existing virtual environments (created with Python 3.12) broke in VSCode. I was getting the "Invalid Python interpreter" error, Pylance couldn't resolve any imports, and pip appeared to be missing—even though I could see it in the venv/bin folder. Here’s what fixed it for me: First, check what your system python3 now points to: python3 --version which python3  In my case, it was now Python 3.13, which explains why stuff started breaking. Your virtual environment still points to the Python 3.12 binary internally, but VSCode (and maybe even pip) is trying to use 3.13 instead. You can confirm that by looking at the pyvenv.cfg file inside your venv: cat venv/pyvenv.cfg  You should see something like: home = /usr/bin/python3.12  If that's the case, then you just need to tell VSCode to use that exact interpreter. Open the command palette (Ctrl+Shift+P) in VSCode, choose “Python: Select Interpreter”, and manually select the path to your virtualenv’s Python binary: /path/to/your/venv/bin/python  Also, double-check the shebang in your pip script: head -n 1 venv/bin/pip  If it says #!/usr/bin/python3, that might now point to Python 3.13, which breaks the venv. You can fix this by rebuilding the venv with the correct Python version: python3.12 -m venv --upgrade-deps venv  Or, if that doesn’t work cleanly: rm -rf venv python3.12 -m venv venv source venv/bin/activate pip install -r requirements.txt  And yeah, ensurepip being disabled for system Python is normal on Ubuntu. Just make sure you have the necessary packages installed: sudo apt install python3.12-venv python3.12-distutils  Once I manually selected the right interpreter in VSCode and fixed the pip shebang, everything worked again—IntelliSense, linting, imports, etc. Hope that helps.