answer:You can iterate over the items in your dictionary and look for the substring in each value. If the substring is found, you can return the key. Here is an example of how you can accomplish this: ```python myDict = {'age': '12', 'address': '34 Main Street, 212 First Avenue', 'firstName': 'Alan', 'Mary-Ann', 'lastName': 'Stone', 'Lee'} # Function to search for substring in dictionary values def find_key(myDict, value): for key, val in myDict.items(): for v in val: if value in v: return key return None # Using the function print(find_key(myDict, 'Mary')) ``` In this code, the function `find_key` iterates over the items (key-value pairs) of the given dictionary. For each value (which is a list of strings), it checks if the desired string (or substring) is found within it. If it is found, it returns the corresponding key. If the string is not found in any of the values after iterating through the whole dictionary, it returns `None`. Note that this function only returns the first key where the string is found, even if there might be other keys with values containing the string. The last line of the code uses the function `find_key` to find and print the key for which one of its values contains the string 'Mary'.,You can solve this problem by using list comprehensions in Python. Here is the detailed solution: First, we create a function that for each dictionary value, checks whether the 'Mary' string is found as a substring. ```python def search_in_values(my_string, my_dict): return k for k in my_dict if my_string in my_dictk ``` Then you can use this function to search for 'Mary' in your dictionary values: ```python #Just an example how the dictionary may look like myDict = {'age': '12', 'address': '34 Main Street, 212 First Avenue', 'firstName': 'Alan', 'Mary-Ann', 'lastName': 'Stone', 'Lee'} #Checking if string 'Mary' exists in dictionary value search_results = search_in_values('Mary', myDict) for result in search_results: print(result) ``` This code will print the keys for which your desired search string ('Mary' in your example) is found as a substring., To search for a specific string that exists in the values of a dictionary and return the corresponding key, you can use a loop to iterate through the dictionary items and check if the string is in the value of each item. Here's an example of how you can do this: ```python # Just an example of how the dictionary may look like myDict = {'age': '12', 'address': '34 Main Street, 212 First Avenue', 'firstName': 'Alan', 'Mary-Ann', 'lastName': 'Stone', 'Lee'} def find_key(dictionary, value): for key, val in dictionary.items(): if value in str(val): return key return None # Checking if string 'Mary' exists in dictionary value print(find_key(myDict, 'Mary')) ``` In the above example, I have created a helper function `find_key` that takes a dictionary and a value as input, it will iterate through the items of the dictionary, and check if the value is in the string representation of the value, if yes then it will return the key. Also, I have used the `str()` function to convert the values to string, so that it can handle both list and string values in the dictionary. It's important to note that, this will return the first key it finds with the value containing the string, if you want to get all the keys that contain the string, you need to modify the function accordingly.

answer:One way to manage this situation more effectively in Python is by using inheritance. You can define a base class in the separate file and then have your main class inherit from this base class. This way you can call the methods defined in the separate file directly on the object of the main class without needing to call the function from the separate module. Here's how you can do this: First, define the base class in the separate file: ```python # separate.py class BaseClass(object): def long_func_1(self, a, b): if self.global_var_1: ... self.func_2(z) ... return ... # define other methods here ``` Then, in your main file, inherit from this base class: ```python # main.py from separate import BaseClass class MainClass(BaseClass): self.global_var_1 = ... self.global_var_2 = ... def func_1(self, x, y): ... def func_2(self, z): ... # tons of similar functions ``` Now, you can create an object of MainClass and call the method directly on the object: ```python obj_1 = MainClass() obj_1.long_func_1(a, b) ``` This way, you are able to separate the functions into multiple files and also avoid the repetitiveness of your previous approach., Yes, there is a better solution to this. You can use inheritance to make the `MainClass` inherit from a new class where you put the shared functions. This way, the functions will be accessible directly from the `MainClass` object and you won't need to change arguments. Here's how you can restructure your code: File: base.py ```python class BaseClass(object): def __init__(self): self.global_var_1 = ... self.global_var_2 = ... def func_2(self, z): ... # Other shared functions ``` File: main.py ```python import base class MainClass(base.BaseClass): def func_1(self, x, y): ... def long_func_1(self, a, b): # Calling the function directly without passing the instance if self.global_var_1: ... self.func_2(z) ... return ... ``` Now, you don't need the `separate.py` file anymore. The functions from `BaseClass` will be accessible from the `MainClass` object and you can maintain the desired function calling syntax: `obj_1.long_func_1(a, b)`. You can move all the common functionality to the `BaseClass` and make your code better organized and more manageable.,Yes, there is a more Pythonic and elegant way to solve your problem. You should use Python's method wrapping/inheritance feature. First, define your 'long_func_1' as a static method in your MainClass. This method will be defined in its own file, but it will still be part of the MainClass. This way, you can call it through an instance of your MainClass. Here is your modified MainClass: ```python class MainClass(object): self.global_var_1 = ... self.global_var_2 = ... @staticmethod def long_func_1(a, b): ... ``` Then, in your separate.py file, override this method, adding any necessary code. ```python def long_func_1(a, b): if obj.global_var_1: ... obj.func_2(z) ... return ... ``` You can now create an instance of MainClass and call the function: ```python import MainClass obj_1 = MainClass() obj_1.long_func_1(a, b) ``` This way, you define your extensive methods in a separate file while keeping them easily accessible to instances of your MainClass.

answer:To change the default working directory for Jupyter notebooks, you will need to modify your Jupyter notebook configuration file. If you haven't created this file yet, you can do so by running the following command in your terminal: ```python jupyter notebook --generate-config ``` This command will create a `jupyter_notebook_config.py` file in your Jupyter directory, which is usually in your home directory under `.jupyter`. Now, you need to modify this configuration file to change your default directory. Open the `jupyter_notebook_config.py` file in a text editor. Look for the following line: ```python #c.NotebookApp.notebook_dir = '' ``` Uncomment it (remove the `#`) and set its value to your desired directory. For example, if you want your default directory to be `D:my_notebooks`, change the line to: ```python c.NotebookApp.notebook_dir = 'D:/my_notebooks' ``` Save and close the file. Now, when you start your Jupyter notebook server, it should default to opening in your specified directory., To change the default working directory of a Jupyter Notebook, you can follow these steps: 1. Open a new or existing Jupyter Notebook. 2. In a new code cell, enter the following command: ```python import os os.chdir('/path/to/new/directory') ``` Replace `/path/to/new/directory` with the actual path to the directory where you want to set the default working directory. 3. Run the cell by clicking on the "Run" button or pressing Shift+Enter. This will change the current working directory to the one you specified. 4. To make this change permanent, you need to modify the Jupyter Notebook configuration file. You can do this by running the following command in your terminal or command prompt: ```bash jupyter notebook --generate-config ``` This will generate a default configuration file named `jupyter_notebook_config.py` in your home directory (e.g., `C:UsersUSERNAME`). 5. Open the configuration file in a text editor and search for the following line: ```python c.NotebookApp.notebook_dir = '' ``` 6. Change the value of `notebook_dir` to the path of the directory where you want to set the default working directory. For example: ```python c.NotebookApp.notebook_dir = '/path/to/new/directory' ``` 7. Save the configuration file and restart the Jupyter Notebook server. The default working directory should now be set to the directory you specified in the configuration file.,To change the default working directory of a Jupyter notebook, follow these steps: 1. Open Jupyter notebook. 2. In the command palette, type `Kernel: Change kernel` and press `Enter`. This will open the Kernel menu. 3. Choose the kernel (usually named 'Python 3') and click on the gear icon to open the Kernel settings. 4. In the 'Kernel' menu, select 'Change kernel...' and choose the kernel you want to edit. 5. Once a kernel is selected, go to the 'Edit' tab and locate the 'Resource roots' section. Here, you can add, edit, or delete directories that will be automatically added to your File Browser. Note: You cannot remove the root directory. 6. Click on the '+'(plus) button to add a directory. In the 'Directory' textbox, paste your desired directory path. 7. Once added, click the ORB button (the horizontal bars) to change the order (to move it to first position) or click the cross button to remove it from the list of root directories. 8. Click 'Save' when you're done. 9. Finally, restart the kernel for the changes to take effect. Remember, the settings are specific to the kernel, so if you use different kernels, you may have to change the directory for each one separately. Remember to replace 'C:UsersUSERNAME' with your desired location. Remember, the path should be correct and accessible for the Jupyter notebook to function properly.

answer:It seems like the issue you're facing is related to the transition from IPython to Jupyter Notebook. The extension loading mechanism has changed, and the `load_ipython_extension` function may not be called automatically. A possible solution is to use a Jupyter Notebook config file to customize the behavior and load your extension. You can create or modify the config file using the following command: ```bash jupyter notebook --generate-config ``` This command will create a config file at `~/.jupyter/jupyter_notebook_config.py`. Open this file and add the following lines at the end: ```python c.InteractiveShellApp.extensions = 'django_jupyter' # This is the location of your custom django_jupyter extension c.InteractiveShellApp.extra_extension_defaults'django_jupyter': { ' settings_module': 'settings', # Replace this with your Django settings module } ``` Now, create a new Python file named `django_jupyter.py` in a directory which is in your PYTHONPATH. You can place it in your Django project directory: ```python # django_jupyter.py import os import django def load_jupyter_extension(): try: os.environ.setdefault("DJANGO_SETTINGS_MODULE", "settings_module") django.setup() except ImportError: pass # This allows the settings to be accessed as jupyter_notebook_config.settings settings_module = 'django_jupyter.settings' # This tells IPython to run `load_jupyter_extension` when it starts def find_extension_modules(): return os.path.abspath('.') ``` Replace "settings_module" with the actual settings module for your Django project. Now, when starting Jupyter Notebook, it should load your extension and set up Django automatically. Alternatively, you can programmatically set up Django in the first cell of your Jupyter notebook as you've already described. However, configuring Jupyter Notebook using the `jupyter_notebook_config.py` file makes the setup more reusable and consistent across different notebooks.,To get Django and Jupyter to work together, you need to create a startup file for Jupyter/IPython to execute each time it starts. The following steps will guide you through the process: 1. First, you need to find out where the IPython startup directory is located. You can do this by running the following command in your Jupyter notebook: ``` import IPython print(IPython.paths.get_ipython_dir()) ``` This will print the path to your IPython directory. 2. In this directory, there should be a subdirectory named `profile_default/startup`. If this directory does not exist, you need to create it. 3. Now, create a new Python file in this directory. You can name it anything, but it has to end with `.py`. 4. Paste the following code into the newly created file: ``` import os os.environ.setdefault("DJANGO_SETTINGS_MODULE", "settings") import django django.setup() ``` 5. Save and close the file. Now, every time you start a new Jupyter notebook, Django will be automatically set up. Remember to replace `"settings"` with the actual name of your Django settings module. You may also need to add the path to your Django project to `sys.path` if it's not already there. Here's an example of how you can do it: ``` import os, sys sys.path.insert(0, '/path/to/your/django/project') os.environ.setdefault("DJANGO_SETTINGS_MODULE", "your_project.settings") import django django.setup() ``` This should resolve the issue and allow you to run Django code in your Jupyter notebooks without having to manually set up Django each time.,The issue you are currently facing might be because Jupyter is not recognizing your extension after the upgrade. You can check this by running ``jupyter nbextension list`` in your terminal. If your extension is not appearing it means that the extension is not loading. However, you can manually edit the startup scripts that jupyter notebook uses and include your code. Please follow these steps: 1. Find your startup scripts directory. This is usually located at ``~/.ipython/profile_default/startup``. If the directory doesn't exist, you can create it. 2. Create a new python script (say, 00-django-setup.py) in the ``~/.ipython/profile_default/startup`` directory and edit the script to include your extension: ```python def load_ipython_extension(ipython): # The `ipython` argument is the currently active `InteractiveShell` # instance, which can be used in any way. This allows you to register # new magics or aliases, for example. try: import os os.environ.setdefault("DJANGO_SETTINGS_MODULE", "settings") import django django.setup() except ImportError: pass ``` 3. Start jupyter notebook and your code should be ready to use. This way, jupyter notebook will automatically load your extension when it starts. Remember to replace "settingsfile" and "/path/to/project" in your code with the actual path to your settings file and the path to your Django project respectively.