Update Featuretools Branch Name - #1038
Merged
Merged
Conversation
rwedge
reviewed
Jun 29, 2020
| ```bash | ||
| git remote add upstream https://github.com/conda-forge/featuretools-feedstock.git | ||
| ``` | ||
| 4. If you made the fork previously and its master branch is missing commits, update it with any changes from upstream |
Contributor
There was a problem hiding this comment.
Unsure if we will be able to rename this branch since it is part of conda-forge, worth looking into
Contributor
Author
There was a problem hiding this comment.
It seems that conda-forge defaults to master, and all the packages use master.
Codecov Report
@@ Coverage Diff @@
## main #1038 +/- ##
==========================================
- Coverage 98.35% 98.33% -0.02%
==========================================
Files 126 126
Lines 13052 13052
==========================================
- Hits 12837 12835 -2
- Misses 215 217 +2
Continue to review full report at Codecov.
|
gsheni
commented
Jun 30, 2020
| **Predict Next Purchase** | ||
|
|
||
| [Repository](https://github.com/Featuretools/predict_next_purchase/) | [Notebook](https://github.com/Featuretools/predict_next_purchase/blob/master/Tutorial.ipynb) | ||
| [Repository](https://github.com/Featuretools/predict_next_purchase/) | [Notebook](https://github.com/Featuretools/predict_next_purchase/blob/main/Tutorial.ipynb) |
Contributor
Author
There was a problem hiding this comment.
Main Branch Added:
https://github.com/Featuretools/predict-next-purchase/tree/main
gsheni
commented
Jun 30, 2020
| An example of this approach can be seen in the `Predict Next Purchase demo notebook <https://github.com/featuretools/predict_next_purchase>`_. In this example, we partition data by customer and only load a fixed number of customers into memory at any given time. We implement this easily using `Dask <https://dask.pydata.org/>`_, which could also be used to scale the computation to a cluster of computers. A framework like `Spark <https://spark.apache.org/>`_ could be used similarly. | ||
|
|
||
| An additional example of partitioning data to distribute on multiple cores or a cluster using Dask can be seen in the `Featuretools on Dask notebook <https://github.com/Featuretools/Automated-Manual-Comparison/blob/master/Loan%20Repayment/notebooks/Featuretools%20on%20Dask.ipynb>`_. This approach is detailed in the `Parallelizing Feature Engineering with Dask article <https://medium.com/feature-labs-engineering/scaling-featuretools-with-dask-ce46f9774c7d>`_ on the Feature Labs engineering blog. Dask allows for simple scaling to multiple cores on a single computer or multiple machines on a cluster. | ||
| An additional example of partitioning data to distribute on multiple cores or a cluster using Dask can be seen in the `Featuretools on Dask notebook <https://github.com/Featuretools/Automated-Manual-Comparison/blob/main/Loan%20Repayment/notebooks/Featuretools%20on%20Dask.ipynb>`_. This approach is detailed in the `Parallelizing Feature Engineering with Dask article <https://medium.com/feature-labs-engineering/scaling-featuretools-with-dask-ce46f9774c7d>`_ on the Feature Labs engineering blog. Dask allows for simple scaling to multiple cores on a single computer or multiple machines on a cluster. |
Contributor
Author
There was a problem hiding this comment.
Main Branch Added:
https://github.com/Featuretools/Automated-Manual-Comparison/tree/main
gsheni
commented
Jun 30, 2020
| An additional example of partitioning data to distribute on multiple cores or a cluster using Dask can be seen in the `Featuretools on Dask notebook <https://github.com/Featuretools/Automated-Manual-Comparison/blob/main/Loan%20Repayment/notebooks/Featuretools%20on%20Dask.ipynb>`_. This approach is detailed in the `Parallelizing Feature Engineering with Dask article <https://medium.com/feature-labs-engineering/scaling-featuretools-with-dask-ce46f9774c7d>`_ on the Feature Labs engineering blog. Dask allows for simple scaling to multiple cores on a single computer or multiple machines on a cluster. | ||
|
|
||
| For a similar partition and distribute implementation using Apache Spark with PySpark, refer to the `Feature Engineering on Spark notebook <https://github.com/Featuretools/predicting-customer-churn/blob/master/churn/4.%20Feature%20Engineering%20on%20Spark.ipynb>`_. This implementation shows how to carry out feature engineering on a cluster of EC2 instances using Spark as the distributed framework. A write-up of this approach is described in the `Featuretools on Spark article <https://blog.featurelabs.com/featuretools-on-spark-2/>`_ on the Feature Labs engineering blog. | ||
| For a similar partition and distribute implementation using Apache Spark with PySpark, refer to the `Feature Engineering on Spark notebook <https://github.com/Featuretools/predicting-customer-churn/blob/main/churn/4.%20Feature%20Engineering%20on%20Spark.ipynb>`_. This implementation shows how to carry out feature engineering on a cluster of EC2 instances using Spark as the distributed framework. A write-up of this approach is described in the `Featuretools on Spark article <https://blog.featurelabs.com/featuretools-on-spark-2/>`_ on the Feature Labs engineering blog. |
Contributor
Author
There was a problem hiding this comment.
Main Branch Added:
https://github.com/Featuretools/predict-customer-churn/tree/main/churn
gsheni
commented
Jun 30, 2020
| - uses: actions/checkout@v2 | ||
| - name: PyPI Upload | ||
| uses: FeatureLabs/gh-action-pypi-upload@master | ||
| uses: FeatureLabs/gh-action-pypi-upload@main |
Contributor
Author
There was a problem hiding this comment.
Main Branch added:
https://github.com/FeatureLabs/gh-action-pypi-upload/tree/main
Contributor
There was a problem hiding this comment.
Perhaps we should switch to using tagged releases of this action so that the branch name isn't even a factor
Merged
This file contains hidden or bidirectional Unicode text that may be interpreted or compiled differently than what appears below. To review, open the file in an editor that reveals hidden Unicode characters.
Learn more about bidirectional Unicode characters
Sign up for free
to join this conversation on GitHub.
Already have an account?
Sign in to comment
2 participants
Add this suggestion to a batch that can be applied as a single commit.This suggestion is invalid because no changes were made to the code.Suggestions cannot be applied while the pull request is closed.Suggestions cannot be applied while viewing a subset of changes.Only one suggestion per line can be applied in a batch.Add this suggestion to a batch that can be applied as a single commit.Applying suggestions on deleted lines is not supported.You must change the existing code in this line in order to create a valid suggestion.Outdated suggestions cannot be applied.This suggestion has been applied or marked resolved.Suggestions cannot be applied from pending reviews.Suggestions cannot be applied on multi-line comments.Suggestions cannot be applied while the pull request is queued to merge.Suggestion cannot be applied right now. Please check back later.
Pull Request Description
mastertomain