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Below code demonstrates the difference between assignment, shallow copy using the copy method, shallow copy using the (slice) [:] and the deepcopy If you need to copy the elements of the list as well, use generic copy.deepcopy() Below example uses nested lists there by making the differences more evident.

A shallow copy constructs a new compound object and then (to the extent possible) inserts references into it to the objects found in the original Import copy new_list = copy.copy(old_list) this is a little slower than list() because it has to find out the datatype of old_list first A deep copy constructs a new compound object and then, recursively, inserts copies into it of the objects found in the original.

If you want a copy, the fastest way of doing this would be to save the project

Then make a copy of the entire thing on the file system Go back into visual studio and open the copy (by right clicking on solution => add existing project => open the copied project) To get a fully independent copy of an object you can use the copy.deepcopy() function For more details about shallow and deep copying please refer to the other answers to this question and the nice explanation in this answer to a related question.

How do i copy a file in python?copy2(src,dst) is often more useful than copyfile(src,dst) because It allows dst to be a directory (instead of the complete target filename), in which case the basename of src is used for creating the new file It preserves the original modification and access info (mtime and atime) in the file metadata (however, this comes with a slight overhead) You should check the add and copy documentation for a more detailed description of their behaviors, but in a nutshell, the major difference is that add can do more than copy

Add allows <src> to be a url referring to comments below, the add documentation states that

If is a local tar archive in a recognized compression format (identity, gzip, bzip2 or xz) then it is unpacked as a directory. When selecting a sub dataframe from a parent dataframe, i noticed that some programmers make a copy of the data frame using the.copy() method For example, x = my_dataframe[features_list].copy(). Clone is designed for arbitrary duplications

A clone implementation for a type t can do arbitrarily complicated operations required to create a new t It is a normal trait (other than being in the prelude), and so requires being used like a normal trait, with method calls, etc The copy trait represents values that can be safely duplicated via memcpy Things like reassignments and passing an.

I am trying to create a script on windows which when run on an admin pc

Copies a folder from the admin pc into a group of network pcs by specifying the ip address / range for each destination pc,

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