To my knowledge, there seems to be a conflict between these two packages due to their shared module name, “tensorflow-datasets”.
During the pip installation process, both of these packages are installed simultaneously. However, pip does not isolate these two packages, but rather installs them both in the site-packages folder. This results in the same module (list below) from the latter installed package overwriting the one installed by the previous package. This overriding behavior, as one can imagine, may result in some functional errors.
# Note that these modules have different content in the two package
'tensorflow_datasets/core/as_dataframe.py'
'tensorflow_datasets/scripts/cli/build.py'
'tensorflow_datasets/core/dataset_builder_test.py'
'tensorflow_datasets/core/splits.py'
'tensorflow_datasets/core/file_adapters_test.py'
'tensorflow_datasets/core/file_adapters.py'
'tensorflow_datasets/core/dataset_builder.py'
'tensorflow_datasets/core/dataset_builders/huggingface_dataset_builder.py'
'tensorflow_datasets/version.py'
Steps to Reproduce
pip install xxx
Desired Change
Indeed, it is not an ideal behavior for modules to be overwritten, even if they are not actively used or if the overwritten module is the one being called. It introduces uncertainty and can cause issues in the long run, especially if there are changes or updates to the overwritten modules in future development. It is generally recommended to avoid such conflicts and ensure that only the necessary and compatible dependencies are declared in the requirements to maintain a stable and predictable environment for the project.
We believe that although this project can only modify direct dependencies and indirect dependencies are a black box, it is possible to add additional explanations rather than directly declaring both conflicting packages in the requirements.txt file. Or maybe you can check the dependencies and remove the redundant dependencies from the requirements.txt.
Adding extra explanations or documentation about the potential conflicts and the need to choose only one of the conflicting packages can help developers understand the issue and make informed decisions. Including a clear instruction or warning in the project’s documentation can guide users to choose the appropriate package based on their specific requirements.
Background
Dependencies in
setup.pyhave module conflicts.Description
There are multiple dependencies mentioned in the
setup.pyfile(the -> means the indirect dependencies):To my knowledge, there seems to be a conflict between these two packages due to their shared module name, “tensorflow-datasets”.
During the pip installation process, both of these packages are installed simultaneously. However, pip does not isolate these two packages, but rather installs them both in the
site-packagesfolder. This results in the same module (list below) from the latter installed package overwriting the one installed by the previous package. This overriding behavior, as one can imagine, may result in some functional errors.Steps to Reproduce
pip install xxxDesired Change
Indeed, it is not an ideal behavior for modules to be overwritten, even if they are not actively used or if the overwritten module is the one being called. It introduces uncertainty and can cause issues in the long run, especially if there are changes or updates to the overwritten modules in future development. It is generally recommended to avoid such conflicts and ensure that only the necessary and compatible dependencies are declared in the requirements to maintain a stable and predictable environment for the project.
We believe that although this project can only modify direct dependencies and indirect dependencies are a black box, it is possible to add additional explanations rather than directly declaring both conflicting packages in the requirements.txt file. Or maybe you can check the dependencies and remove the redundant dependencies from the requirements.txt.
Adding extra explanations or documentation about the potential conflicts and the need to choose only one of the conflicting packages can help developers understand the issue and make informed decisions. Including a clear instruction or warning in the project’s documentation can guide users to choose the appropriate package based on their specific requirements.