v1.0.0-rc1 preparation

.github/workflows/test_and_deploy.yml

@@ -5,7 +5,7 @@ on:
     branches: [main]
   pull_request:
   release:
-    types: [released]
+    types: [prereleased, released]
 jobs:
   test_repo:
     name: Test on ${{ matrix.os }} w/ Py${{ matrix.python-version }}
@@ -114,6 +114,7 @@ jobs:
           path: dist/
   build_wheels:
     name: Build wheels on Ubuntu
+    needs: test_repo
     runs-on: ubuntu-20.04 # Can be also run for macOS
     steps:
       - uses: actions/checkout@v3
@@ -125,17 +126,17 @@ jobs:
         with:
           platforms: all
       - name: Build wheels
-        if: github.event_name != 'release' && github.event.action != 'released'
-        uses: pypa/cibuildwheel@v2.15.0 # The main configuration is in pyproject.toml
+        if: github.event_name != 'release'
+        uses: pypa/cibuildwheel@v2.19.2 # The main configuration is in pyproject.toml
         env:
           CIBW_BUILD: "cp311-manylinux*" # Build only python 3.11 wheels for testing
           # Increase verbosity to see what's going on in the build in case of failure
           CIBW_BUILD_VERBOSITY: 3
           CIBW_REPAIR_WHEEL_COMMAND_LINUX: >
             auditwheel show {wheel} && auditwheel repair -w {dest_dir} {wheel}
       - name: Build release wheels
-        if: github.event_name == 'release' && github.event.action == 'released'
-        uses: pypa/cibuildwheel@v2.15.0 # The main configuration is in pyproject.toml
+        if: github.event_name == 'release' && (github.event.action == 'released' || github.event.action == 'prereleased')
+        uses: pypa/cibuildwheel@v2.19.2 # The main configuration is in pyproject.toml
         env:
           # Set NLE_RELEASE_BUILD to 1 to build release wheels
           CIBW_ENVIRONMENT: "NLE_RELEASE_BUILD=1"
@@ -175,6 +176,46 @@ jobs:
           python -m pytest --import-mode=append -svx $REPONAME/nle/tests
           popd
 
+  # Use prereleases to test publish the artefacts to testpypi
+  test_deploy:
+    name: Deploy artefacts to testpypi
+    needs: [test_sdist_3_11, test_manylinux_3_11]
+    if: github.event_name == 'release' && github.event.action == 'prereleased'
+    runs-on: ubuntu-latest
+    environment:
+      name: prerelease
+      url: https://testpypi.org/p/nle
+    permissions:
+      id-token: write
+    steps:
+      - uses: actions/checkout@v4
+      - name: Check version matches release tag
+        run: |
+          echo "v$(cat version.txt)"
+          echo "${{ github.event.release.tag_name }}"
+          [[ "${{ github.event.release.tag_name }}" == "v$(cat version.txt)" ]]
+      - name: Get sdist artifact # Get sdist artifact from the test_sdist job
+        uses: actions/download-artifact@v3
+        with:
+          name: python-sdist
+          path: dist
+      - name: Get wheels artifacts # Get wheels artifacts from the build_wheels job
+        uses: actions/download-artifact@v3
+        with:
+          name: python-wheels
+          path: dist
+      - name: Report dist contents
+        run: |
+          pwd
+          ls -R
+          ls -al .
+          ls -R dist/
+          ls -al dist/
+      - name: Publish package to TestPyPI
+        uses: pypa/gh-action-pypi-publish@release/v1
+        with:
+          repository-url: https://test.pypi.org/legacy/
+
   # TODO move this to separate workflow whenever github decides to provide basic
   #      functionalities like workflow dependencies :|
   deploy_sdist:

CMakeLists.txt

@@ -1,6 +1,8 @@
 cmake_minimum_required(VERSION 3.15)
 file(STRINGS "version.txt" NLE_VERSION)
-project(nle VERSION ${NLE_VERSION})
+# Remove any rcXX suffix from the version number as CMake doesn't like it
+string(REGEX REPLACE "rc[0-9+]$" "" CMAKE_NLE_VERSION ${NLE_VERSION})
+project(nle VERSION ${CMAKE_NLE_VERSION})
 
 if(CMAKE_BUILD_TYPE MATCHES Debug)
   message("Debug build.")
@@ -30,7 +32,7 @@ else()
   message("Some other build type.")
 endif()
 
-message(STATUS "Building nle backend version: ${NLE_VERSION}")
+message(STATUS "Building nle backend version: ${CMAKE_NLE_VERSION}")
 
 set(CMAKE_POSITION_INDEPENDENT_CODE ON)
 

README.md

@@ -28,41 +28,6 @@ README](./README.nh), at [nethack.org](https://nethack.org/), and on the
 
 This version of NLE uses the [Farama Organisation Gymnasium Environment](https://gymnasium.farama.org) APIs.
 
-### NLE Language Wrapper
-
-We thank [ngoodger](https://github.com/ngoodger) for implementing the [NLE Language Wrapper](https://github.com/ngoodger/nle-language-wrapper) that translates the non-language observations from NetHack tasks into similar language representations. Actions can also be optionally provided in text form which are converted to the Discrete actions of the NLE.
-
-### NetHack Learning Dataset
-
-The NetHack Learning Dataset (NLD) code now ships with `NLE`, allowing users to the load large-scale datasets featured in [Dungeons and Data: A Large-Scale NetHack Dataset](), while also generating and loading their own datasets.
-
-```python
-import nle.dataset as nld
-
-if not nld.db.exists():
-    nld.db.create()
-    # NB: Different methods are used for data based on NLE and data from NAO.
-    nld.add_nledata_directory("/path/to/nld-aa", "nld-aa-v0")
-    nld.add_altorg_directory("/path/to/nld-nao", "nld-nao-v0")
-
-dataset = nld.TtyrecDataset("nld-aa-v0", batch_size=128, ...)
-for i, mb in enumerate(dataset):
-    foo(mb) # etc...
-```
-
-For information on how to download NLD-AA and NLD-NAO, see the dataset doc [here](./DATASET.md).
-
-Otherwise checkout the tutorial Colab notebook [here](https://colab.research.google.com/drive/1GRP15SbOEDjbyhJGMDDb2rXAptRQztUD?usp=sharing).
-
-# Papers using the NetHack Learning Environment
-- Izumiya and Simo-Serra [Inventory Management with Attention-Based Meta Actions](https://esslab.jp/~ess/publications/IzumiyaCOG2021.pdf) (Waseda University, CoG 2021).
-- Samvelyan et al. [MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research](https://arxiv.org/abs/2109.13202) (FAIR, UCL, Oxford, NeurIPS 2021).
-- Zhang et al. [BeBold: Exploration Beyond the Boundary of Explored Regions](https://arxiv.org/abs/2012.08621) (Berkley, FAIR, Dec 2020).
-- Küttler et al. [The NetHack Learning Environment](https://arxiv.org/abs/2006.13760) (FAIR, Oxford, NYU, Imperial, UCL, NeurIPS 2020).
-
-Open a [pull
-request](https://github.com/heiner/nle/edit/main/README.md)
-to add papers.
 
 # Getting started
 
@@ -200,6 +165,42 @@ $ python -m nle.scripts.plot
                                        steps
 ```
 
+### NLE Language Wrapper
+
+We thank [ngoodger](https://github.com/ngoodger) for implementing the [NLE Language Wrapper](https://github.com/ngoodger/nle-language-wrapper) that translates the non-language observations from NetHack tasks into similar language representations. Actions can also be optionally provided in text form which are converted to the Discrete actions of the NLE.
+
+### NetHack Learning Dataset
+
+The NetHack Learning Dataset (NLD) code now ships with `NLE`, allowing users to the load large-scale datasets featured in [Dungeons and Data: A Large-Scale NetHack Dataset](), while also generating and loading their own datasets.
+
+```python
+import nle.dataset as nld
+
+if not nld.db.exists():
+    nld.db.create()
+    # NB: Different methods are used for data based on NLE and data from NAO.
+    nld.add_nledata_directory("/path/to/nld-aa", "nld-aa-v0")
+    nld.add_altorg_directory("/path/to/nld-nao", "nld-nao-v0")
+
+dataset = nld.TtyrecDataset("nld-aa-v0", batch_size=128, ...)
+for i, mb in enumerate(dataset):
+    foo(mb) # etc...
+```
+
+For information on how to download NLD-AA and NLD-NAO, see the dataset doc [here](./DATASET.md).
+
+Otherwise checkout the tutorial Colab notebook [here](https://colab.research.google.com/drive/1GRP15SbOEDjbyhJGMDDb2rXAptRQztUD?usp=sharing).
+
+# Papers using the NetHack Learning Environment
+- Izumiya and Simo-Serra [Inventory Management with Attention-Based Meta Actions](https://esslab.jp/~ess/publications/IzumiyaCOG2021.pdf) (Waseda University, CoG 2021).
+- Samvelyan et al. [MiniHack the Planet: A Sandbox for Open-Ended Reinforcement Learning Research](https://arxiv.org/abs/2109.13202) (FAIR, UCL, Oxford, NeurIPS 2021).
+- Zhang et al. [BeBold: Exploration Beyond the Boundary of Explored Regions](https://arxiv.org/abs/2012.08621) (Berkley, FAIR, Dec 2020).
+- Küttler et al. [The NetHack Learning Environment](https://arxiv.org/abs/2006.13760) (FAIR, Oxford, NYU, Imperial, UCL, NeurIPS 2020).
+
+Open a [pull
+request](https://github.com/heiner/nle/edit/main/README.md)
+to add papers.
+
 
 
 # Contributing

version.txt

@@ -1 +1 @@
-1.0.0
+1.0.0rc1