Merge pull request #261 from arup-group/fixes-post-release

Post-release updates & fixes

.github/workflows/pre-release.yml

@@ -9,5 +9,11 @@ jobs:
   conda-build:
     uses: arup-group/actions-city-modelling-lab/.github/workflows/conda-build.yml@main
     secrets: inherit
+    with:
+      package_name: cml-pam
+
+  pip-build:
+    uses: arup-group/actions-city-modelling-lab/.github/workflows/pip-build.yml@main
+    secrets: inherit
     with:
       package_name: cml-pam

.github/workflows/release.yml

@@ -10,6 +10,14 @@ jobs:
     secrets: inherit
     with:
       package_name: cml-pam
+      build_workflow: pre-release.yml
+
+  pip-upload:
+    uses: arup-group/actions-city-modelling-lab/.github/workflows/pip-upload.yml@main
+    secrets: inherit
+    with:
+      package_name: cml-pam
+      build_workflow: pre-release.yml
 
   docs-stable:
     permissions:

CHANGELOG.md

@@ -16,6 +16,20 @@ All notable changes to this project will be documented in this file.
 The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.1.0/),
 and this project adheres to [Semantic Versioning](https://semver.org/spec/v2.0.0.html).
 
+## [Unreleased]
+
+### Fixed
+
+- **internal** conda upload CI script.
+
+### Added
+
+- **internal** PyPI build and upload CI scripts (triggered on tagging and releasing new versions).
+
+### Changed
+
+- User install instructions to prefer direct install from mamba (or PyPI if a user is willing to deal with installing non-python libs themselves).
+
 ## [v0.3.0] - 2023-09-27
 
 ### Fixed
@@ -95,6 +109,7 @@ This version is a pre-release
 
 This is the first version of PAM which follows semantic versioning and can be considered the first _official_ release of the package.
 
+[Unreleased]: https://github.com/arup-group/pam/compare/v0.3.0...main
 [v0.3.0]: https://github.com/arup-group/pam/compare/v0.2.4...v0.3.0
 [v0.2.4]: https://github.com/arup-group/pam/compare/v0.2.3...v0.2.4
 [v0.2.3]: https://github.com/arup-group/pam/compare/v0.2.2...v0.2.3

README.md

@@ -65,11 +65,8 @@ To install PAM, we recommend using the [mamba](https://mamba.readthedocs.io/en/l
 ### As a user
 <!--- --8<-- [start:docs-install-user] -->
 ``` shell
-git clone [email protected]:arup-group/pam.git
-cd pam
-mamba create -n pam -c conda-forge -c city-modelling-lab --file requirements/base.txt
+mamba create -n pam -c conda-forge -c city-modelling-lab cml-pam
 mamba activate pam
-pip install --no-deps .
 ```
 <!--- --8<-- [end:docs-install-user] -->
 ### As a developer
@@ -82,6 +79,11 @@ mamba activate pam
 pip install --no-deps -e .
 ```
 <!--- --8<-- [end:docs-install-dev] -->
+
+### Installing with pip
+
+Installing directly with pip as a user (`pip install cml-pam`) or as a developer (`pip install -e '.[dev]'`) is also possible, but you will need the `libgdal` & `libspatialindex` geospatial non-python libraries pre-installed.
+
 For more detailed instructions, see our [documentation](https://arup-group.github.io/pam/latest/installation/).
 
 ## Contributing
@@ -111,4 +113,4 @@ mike deploy 0.2
 mike serve
 ```
 
-Then you can view the documentation in a browser at http://localhost:8000/.
+Then you can view the documentation in a browser at <http://localhost:8000/>.

docs/installation.md

@@ -7,27 +7,29 @@ As a PAM user, it is easiest to install PAM using the [mamba](https://mamba.read
 
 1. Install mamba with the [Mambaforge](https://github.com/conda-forge/miniforge#mambaforge) executable for your operating system.
 2. Open the command line (or the "miniforge prompt" in Windows).
-3. Download (a.k.a., clone) the PAM repository: `git clone [email protected]:arup-group/pam.git`
-4. Change into the `pam` directory: `cd pam`
-5. Create the PAM mamba environment: `mamba create -n pam -c conda-forge -c city-modelling-lab --file requirements/base.txt`
-6. Activate the PAM mamba environment: `mamba activate pam`
-7. Install the PAM package into the environment, ignoring dependencies (we have dealt with those when creating the mamba environment): `pip install --no-deps .`
+3. Create the PAM mamba environment and install `cml-pam` into it: `mamba create -n pam -c conda-forge -c city-modelling-lab cml-pam`
+4. Activate the PAM mamba environment: `mamba activate pam`
 
 All together:
 
 --8<-- "README.md:docs-install-user"
 
 We do not recommend trying to install PAM directly with pip (e.g. in a virtual environment) as you need to first install underlying native geospatial libraries, the method for which differs by operating system.
-If you choose to install into a virtual environment, ensure you have `libgdal` and `libspatialindex` installed on your device before installing with pip. 
+If you choose to install into a virtual environment, ensure you have `libgdal` and `libspatialindex` installed on your device before installing with pip:
+
+``` bash
+pip install cml-pam
+```
 
 ### Running the example notebooks
+
 If you have followed the non-developer installation instructions above, you will need to install `jupyter` into your `pam` environment to run the [example notebooks](https://github.com/arup-group/pam/tree/main/examples):
 
 ``` shell
 mamba install -n pam jupyter
 ```
 
-With Jupyter installed, it's easiest to then add the environment as a jupyter kernel: 
+With Jupyter installed, it's easiest to then add the environment as a jupyter kernel:
 
 ``` shell
 mamba activate pam
@@ -36,10 +38,11 @@ jupyter notebook
 ```
 
 ### Choosing a different environment name
+
 If you would like to use a different name to `pam` for your mamba environment, the installation becomes (where `[my-env-name]` is your preferred name for the environment):
 
 ``` shell
-mamba create -n [my-env-name] -c conda-forge -c city-modelling-lab --file requirements/base.txt
+mamba create -n [my-env-name] -c conda-forge -c city-modelling-lab cml-pam
 mamba activate [my-env-name]
 ipython kernel install --user --name=[my-env-name]
 ```

pam/__init__.py

@@ -1,4 +1,4 @@
-__version__ = "0.3.0"
+__version__ = "0.3.1.dev"
 
 
 class PAMValidationError(Exception):

requirements/base.txt

@@ -1,6 +1,7 @@
 click < 9
 gdal < 3.6
 geopandas >= 0.13, < 0.14
+importlib_resources >= 6, < 7
 ipykernel < 7
 lxml < 5
 matplotlib >= 3, < 4