I”m having a bit of trouble with my code. I’m trying to get the IDs from the list and compare it to an int input. If the int is the same as the ID, it’ll print(“Yes”). If it doesn’t match an ID, it’ll print(“no”). Problem is, it’s printing no for even the numbers that should return yes to.. I’m toying
Tag: python-dataclasses
dataclasses: how to ignore default values using asdict()?
I would like to ignore the default values after calling asdict() so if I call Answer The dataclasses module doesn’t appear to have support for detecting default values in asdict(), however the dataclass-wizard library does — via skip_defaults argument. Example: Further, results show it is close to 2x faster than an approach with dataclasses.adict(). I’ve added benchmark code I used
dataclass hash() of field with type annotation and default value = None is always nondeterministic
I am running into some unexpected behavior when trying to hash a dataclass and I’m wondering if anyone can explain it. The below script reproduces the problem. First, we need to run export PYTHONHASHSEED=’0′ to disable hash randomization so we can compare the hash across runs. Here’s the result of running the script twice: Note that the hash for the
Python dataclass, one attribute referencing other
Can a dataclass attribute access to the other one? In the above example, one can create a Stock by providing a symbol and the price. If price is not provided, it defaults to a price which we get from some function get_price. Is there a way to reference symbol? This example generates error NameError: name ‘symbol’ is not defined. Answer
Converting arguments to custom objects using dataclasses package
I recently discovered the dataclasses Python package. I’m running into an issue when using custom classes in my type annotation. I’ve got a simple example below. When the Entry class gets passed the location argument, the value of that argument should be used to construct a Location object. Similarly, when the Entry class gets passed a string for the creationDate
Validate dataclass field with custom defined method?
While working with dataclasses, type hints are good but what I’m looking also for is a Validation of passed values (such as string of max length 50, int with upper limit of 100 etc) Is there anyway to validate passed value ? For example, Pydantic has these Validators. I’m looking for something native without adding external libraries. My only solution
How to persist and load all attributes of a dataclass
I want to persist all attributes of an object which is an instance of a dataclass. Then I want to load back that object from the files that I persisted. Here it is an example that fullfills the task: As you can see I need to repeat the same code for every attribute, what is a better way to do
Filtering dataclass instances by unique attribute value
I have a list of dataclass instances in the form of: Now I would like to filter that list and get only unique instances by a certain key (company in this case). The desired list: The original idea was to use a function in the fashion of python’s set() or filter() functions, but both is not possible here. My working
Adding dataclass fields dynamically with dacite.from_dict
I am using dacite to transform a Python dictionary into a dataclass. Is there a way to dynamically add fields to a dataclass? Like in the example below, where the dataclass “Parameters” has defined only one timeseries “timeseriesA”, but there might be additional ones (provided through the dictionary) that cannot be declared. In this example, “timeseriesB” will be ignored by
Annotate dataclass class variable with type value
We have a number of dataclasses representing various results with common ancestor Result. Each result then provides its data using its own subclass of ResultData. But we have trouble to annotate the case properly. We came up with following solution: but it stopped working lately with mypy error ClassVar cannot contain type variables [misc]. It is also against PEP 526,