If you face module not found in a Jupyter environment, you had to install it on a Jupyter environment instead of installing it on the command prompt. I have confirmed the working directory of the notebook is WorkingDirectory. Neither PyCharm nor VSCode can no longer resolve the import from tensorflow.keras import ….

Short prefix version (but repeated prefix)

There is no way to „incrementally“ build up a module’s path by importing the packages that lead to it. You always have to refer to the entire module name when importing. Only use it when you’d otherwise be tempted to declare local copies of constants, or to abuse inheritance (the Constant Interface Antipattern). In other words, use it when you require frequent access to static members from one or two classes. If you overuse the static import feature, it can make your program unreadable and unmaintainable, polluting its namespace with all the static members you import. Readers of your code (including you, a few months after you wrote it) will not know which class a static member comes from.

Full prefix version

By clicking “Post Your Answer”, you agree to our terms of service and acknowledge you have read our privacy policy. Find centralized, trusted content and collaborate around the technologies you use most. It depends on how you want to access the import when you refer to it. That’s the bad and unsafe way of importing things (import all in a bulk), but it works. I’ve found this exception to be raised even if import MyPackage is ran from the usual Python console. Once JupyterLab restarts and compiles your code, the __pycache__ folders will be regenerated.

from X import *

One area in which I use import static is for retrieving constants from a class.We can also apply import static on static methods. Make sure to type import static because static import is wrong. The reason is that your MyPackage/__init__.py is run from the current working directory.

Best way to include CSS? Why use @import?

Importing all of the static members from a class can be particularly harmful to readability; if you need only one or two members, import them individually. Used appropriately, static import can make your program more readable, by removing the boilerplate of repetition of class names. You can now use sys.path.append to append the path you pass into the function to the folders Python looks for the modules (Please note that thats not permanent). If the path of your modules should be static, you should consider putting these in the Lib folder.

• Although the OP mentions having no success with using imports in the __init__.py files, it is actually the solution here.
• My problem was that my Visual Studio Code kernel was set to the wrong environment.
• Doesn’t mean „from the module called someModule that I imported earlier…“ it means „from the module named someModule that you find on sys.path…“.
• It is useful if you are often used a constant from another class in your code and if the static import is not ambiguous.

As Agilix correctly stated, you must have an __init__.py file in your „functionfolder“ (see directory illustration above). The same function object gets pointed at, except in the current scope the identifier pointing at it is bidFarewell whereas in module a the identifier pointing at it is sayBye. Form and then use name and age directly (without the a. prefix). The from module import identifiers form is more future proof because you can easily see when one import will be overriding another.

`from … import` vs `import .` duplicate

The second line looks for a package called package.subpackage and imports module from that package. The third line just looks for a module called module and doesn’t find one. It doesn’t „re-use“ the object called module that you got from the line above. What is static import in Java – JavaRevisited – A very good resource to know more about import static. The static import feature allows to access the static members of a class without the class qualification. The basic idea of static import is that whenever you are using a static class,a static variable or an enum,you can import them and save yourself from some typing.

In many, if not a majority of cases, it’s more important to make the developer more efficient, and only then make the code more performant. Then the download of the second stylesheet may not start until the first stylesheet has been downloaded. If, on the other hand, both stylesheets are referenced in elements in the main HTML page, both can be downloaded at the same time. If both stylesheets are always loaded together, it can also be helpful to simply combine them into a single file.

Adding that directory won’t actually fix the real issue outlined above. Once you’re at the minified stage, is faster, as people have pointed out, so at most link to a few stylesheets and don’t @import any if at all possible. There are two variables you’re optimizing for at any given time – the performance of your code, and the performance of the developer.

Then, with that kernel defined, all you have to do is to update this kernel’s environment variables to look at your project folder where your modules are located. But the second one need tensorflow.__path__ contains keras module statically during type checking. If the module in question (project.model in your case) has defined a list of stings named __all__, then every named variable in that list is imported. It import (into the current namespace) whatever names the module (or package) lists in its __all__ attribute — missing such an attribute, all names that don’t start with _. If you only want to import the particular object attribute1, just do from package.subpackage.module import attribute1 and be done with it.

• Form and then use name and age directly (without the a. prefix).
• You didn’t say this directly, but I’m assuming you’re having trouble with manipulating these global variables.
• There are two variables you’re optimizing for at any given time – the performance of your code, and the performance of the developer.
• Unless I was totally wrong somewhere, this will leave me with a feeling something is really broken in Python’s model of package and sub‑packages.
• The second line looks for a package called package.subpackage and imports module from that package.

Python: importing a sub‑package or sub‑module

Additionally, in __init__.py files, it’s best practice to use the relative import from . Import package instead of the absolute import import package to avoid any errors by accidentally importing a different package. And then, after all a package initialization actions like import module1 are done, restore „caller’s“ working directory with os.chdir(cwd). The best solution by far (for me) is to have a kernel for each environment you are working in.

It means, that interpreter cannot find the module named module1 since it is not located in either current or global packages directory. Multiple CSS requests of any import kind – whether through links or through @imports – are bad practice for high performance web sites. Once you’re at the point where optimization matters, all your CSS should be flowing through a minifier.

Connect and share knowledge within a single location that is structured and easy to search. This makes all names from the module available in the local namespace. First of all, let me explain exactly what the basic import statements do. Now if your venv has the package installed, JupyterLab can also see the package and will not have any problem importing the package. At first, I thought „yet another destructive and poorly documented refactoring decision“, but checking actually it seems lint has problem to access it with the directory structure of latest releases.

You didn’t say this directly, but I’m assuming you’re having trouble with manipulating these global variables. The name a in module.py and the name a in mod2.py will still point to the object 1.

This is a bug in the current version of tensorflow, as discussed in this issue. I tried to check the versions through the PyCharm interpreter tab and this is what I saw. For some reason PyCharm isn’t aware that there are versions after 2.0 (I have the latest version of pip installed in that environment). I’m guessing this is related, but not sure what to do with that. You can verify whether this is the case via import _tkinter; print(_tkinter.file) in the 3.2 shell. Alternatively, _tkinter may live in a different directory entirely.