Comments (13)
That would be a good idea. Right now I am working on random forests and I think I can upload the working code by end of today
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I created a bucket with autompg data. It can be retrieved using this gs://dsp_final/auto-mpg.csv
.
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I think we are left with unit tests
. Let's aim for 23rd April to release our first version of code into master branch
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Yes. the end of "23/04/2019" or "24/09/2019" afternoon sounds like a good deadline.
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@Anirudh-Kakarlapudi , @Jayant1234 : The code looks pretty stable, for now. I believe we can start working on the Unit Tests, atleast for a couple of models, so that we can work towards the "release" target.
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@Aaashishyadavally I agree. Lets start Unit Tests.
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@Anirudh-Kakarlapudi, @Jayant1234 : In the last project, I used pytest
module, which simulates unit testing. We could do the same this time around as well, or, here is the link for Python's official unit-testing (taking into consideration the self-imposed deadline for the first release):
https://docs.python.org/3.4/library/unittest.html?highlight=unittest
What do you people suggest?
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Infact, until this point, I was under the impression that we will use the same for testing this time around as well, as can be seen in the __main__.py
script, where I added the test module to be executed by pytest
, but, I thought, we should discuss it before we start working on it.
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I think using the pytest
rather than default unittest
will make the code more readable and reproducible.
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I mean, yes, pytest
is relatively simpler, and it is also easy for future contributors to pick it up, if and when.
Cool, pytest
it is.
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Finished test suite for 50% of the package - everything but the Model
API. Considering the Integration Test isn't giving any issues, I think we can proceed and integrate the current status of the project into the master
branch, once Tests
pull request is reviewed and accepted.
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@Anirudh-Kakarlapudi , @Jayant1234 : I am sorry, I think I mixed up the meanings of "CI -> Gitflow"
It is lot more than I assumed it would be, in terms of building a travis.yml
file and maintaining the build.
I guess, let's stick with maintaining the develop
branch, and merging into master
periodically, without using the term release
for now, considering the deadline for the project.
It's something I would love to explore in the future projects though! :)
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The good thing is - let's merge into master such that, each merge passes all the unit tests and integration test.
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Related Issues (15)
- Created a Base Class which can be used in all regression models. HOT 1
- need a parameter model to return a dictionary also HOT 2
- Dataset for models HOT 1
- Metrics to track model performance HOT 3
- Class/Variable names HOT 1
- GCP Initialization Action HOT 6
- defining pipelines HOT 6
- Whether `Model` class in base.py should remain abstract or not HOT 4
- Lock on 'develop' branch HOT 6
- Encryption of the csv file for data security HOT 3
- Error while testing HOT 9
- Unit tests for models HOT 2
- Adding a cross validation step HOT 2
- PVLib ForecastModel class HOT 2
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