This is an automated email from the ASF dual-hosted git repository.
agrove pushed a commit to branch main
in repository https://gitbox.apache.org/repos/asf/arrow-datafusion-python.git
The following commit(s) were added to refs/heads/main by this push:
new 8ec98a8 Fix release instructions (#238)
8ec98a8 is described below
commit 8ec98a84ac9ac1be8629ecae056f1cfe0146cba5
Author: Andy Grove <[email protected]>
AuthorDate: Tue Feb 28 13:08:48 2023 -0700
Fix release instructions (#238)
---
dev/release/README.md | 48 ++++++++++++++++++++++++------------------------
1 file changed, 24 insertions(+), 24 deletions(-)
diff --git a/dev/release/README.md b/dev/release/README.md
index aed0e29..8894c2c 100644
--- a/dev/release/README.md
+++ b/dev/release/README.md
@@ -171,29 +171,6 @@ This will create a file named
`dist/datafusion-0.7.0.tar.gz`. Upload this to tes
python3 -m twine upload --repository testpypi dist/datafusion-0.7.0.tar.gz
```
-### Publish Python Artifacts to Anaconda
-
-Publishing artifacts to Anaconda is similar to PyPi. First, Download the
source tarball created in the previous step and untar it.
-
-```bash
-# Assuming you have an existing conda environment named `datafusion-dev` if
not see root README for instructions
-conda activate datafusion-dev
-conda build .
-```
-
-This will setup a virtual conda environment and build the artifacts inside of
that virtual env. This step can take a few minutes as the entire build, host,
and runtime environments are setup. Once complete a local filesystem path will
be emitted for the location of the resulting package. Observe that path and
copy to your clipboard.
-
-Ex: `/home/conda/envs/datafusion/conda-bld/linux-64/datafusion-0.7.0.tar.bz2`
-
-Now you are ready to publish this resulting package to anaconda.org. This can
be accomplished in a few simple steps.
-
-```bash
-# First login to Anaconda with the datafusion credentials
-anaconda login
-# Upload the package
-anaconda upload
/home/conda/envs/datafusion/conda-bld/linux-64/datafusion-0.7.0.tar.bz2
-```
-
### Send the Email
Send the email to start the vote.
@@ -221,7 +198,7 @@ Create the source release tarball:
./dev/release/release-tarball.sh 0.8.0 1
```
-### Publishing Python Artifacts
+### Publishing Python Artifacts to PyPi
Go to the Test PyPI page of Datafusion, and download
[all published artifacts](https://test.pypi.org/project/datafusion/#files)
under `dist-release/` directory. Then proceed
@@ -231,6 +208,29 @@ uploading them using `twine`:
twine upload --repository pypi dist-release/*
```
+### Publish Python Artifacts to Anaconda
+
+Publishing artifacts to Anaconda is similar to PyPi. First, Download the
source tarball created in the previous step and untar it.
+
+```bash
+# Assuming you have an existing conda environment named `datafusion-dev` if
not see root README for instructions
+conda activate datafusion-dev
+conda build .
+```
+
+This will setup a virtual conda environment and build the artifacts inside of
that virtual env. This step can take a few minutes as the entire build, host,
and runtime environments are setup. Once complete a local filesystem path will
be emitted for the location of the resulting package. Observe that path and
copy to your clipboard.
+
+Ex: `/home/conda/envs/datafusion/conda-bld/linux-64/datafusion-0.7.0.tar.bz2`
+
+Now you are ready to publish this resulting package to anaconda.org. This can
be accomplished in a few simple steps.
+
+```bash
+# First login to Anaconda with the datafusion credentials
+anaconda login
+# Upload the package
+anaconda upload
/home/conda/envs/datafusion/conda-bld/linux-64/datafusion-0.7.0.tar.bz2
+```
+
### Push the Release Tag
```bash
