merantix-momentum · winfried-ripken · Apr 5, 2022 · Apr 5, 2022 · Apr 5, 2022 · Apr 5, 2022
diff --git a/README.md b/README.md
@@ -1,6 +1,6 @@
 <div align="center">
 
-# <img src="docs/source/_static/logo.png" width="150px"> Squirrel Datasets Core
+# <img src="https://raw.githubusercontent.com/merantix-momentum/squirrel-datasets-core/main/docs/source/_static/logo.png" width="150px"> Squirrel Datasets Core
 
 [![Python](https://img.shields.io/pypi/pyversions/squirrel-datasets-core.svg?style=plastic)](https://badge.fury.io/py/squirrel-datasets-core)
 [![PyPI](https://badge.fury.io/py/squirrel-datasets-core.svg)](https://badge.fury.io/py/squirrel-datasets-core)
@@ -21,46 +21,21 @@ your own datasets with the tools we provide here.
 
 For preprocessing, we currently support Spark as the main tool to carry out the task.
 
-Please see our [documentation](https://squirrel-datasets-core.readthedocs.io) for further details.
-
-If you have any questions or would like to contribute, join our Slack community!
+If you have any questions or would like to contribute, join our [Slack community](https://join.slack.com/t/squirrel-core/shared_invite/zt-14k6sk6sw-zQPHfqAI8Xq5WYd~UqgNFw)!
 
 # Installation
-Currently, we have not released a functional version of `squirrel-core` and `squirrel-datasets-core` into the public 
-pypi registry. Therefore we ask you to use the following installation method, which uses the source code directly:
+Install `squirrel-core` and `squirrel-datasets-core` with pip:
 
-First, you need to clone the `squirrel-core` and `squirrel-datasets-core` repositories by:
-```shell
-git clone https://github.com/merantix-momentum/squirrel-core.git
-```
-and 
 ```shell
-git clone https://github.com/merantix-momentum/squirrel-datasets-core.git
+pip install squirrel-core[all]
+pip install squirrel-datasets-core[all]
 ```
-Then you can install both packages by
-```shell
-pip install -e "squirrel-core[all]"
-```
-and
-```shell
-pip install -e "squirrel-datasets-core[all]"
-```
-
-In the documentation, you may also see some requirements to install the two packages first, please follow the 
-instruction above, instead of installing from public pypi registry (e.g `pip install squirrel-core` or 
-`pip install squirrel-datasets-core`). We kindly ask for your patience.
-
 # Documentation
 
-To view the docs locally, please use the following command in root directory of `squirrel-datasets-core`:
-```
-sphinx-build ./docs/source ./docs/build
-```
-The command above will create all documentation pages under `./docs/build`.
-To view the start page, open `./docs/build/index.html` in your browser. 
+Visit our documentation on [Readthedocs](https://squirrel-datasets-core.readthedocs.io).
 
 # Contributing
-Squirrel is open source and community contributions are welcome!
+`squirrel-datasets-core` is open source and community contributions are welcome!
 
 # The humans behind Squirrel
 We are [Merantix Momentum](https://merantix-momentum.com/), a team of ~30 machine learning engineers, developing machine learning solutions for industry and research. Each project comes with its own challenges, data types and learnings, but one issue we always faced was scalable data loading, transforming and sharing. We were looking for a solution that would allow us to load the data in a fast and cost-efficient way, while keeping the flexibility to work with any possible dataset and integrate with any API. That's why we build Squirrel – and we hope you'll find it as useful as we do! By the way, [we are hiring](https://merantix-momentum.com/about#jobs)!

diff --git a/docs/source/conf.py b/docs/source/conf.py
@@ -4,8 +4,8 @@
 # -- Project information
 
 project = "Squirrel Datasets"
-copyright = f"{datetime.datetime.now().year}, Merantix Labs GmbH"
-author = "Merantix Labs GmbH"
+copyright = f"{datetime.datetime.now().year}, Merantix Momentum"
+author = "Merantix Momentum"
 # -- General configuration
 
 extensions = [

diff --git a/docs/source/index.rst b/docs/source/index.rst
@@ -2,6 +2,7 @@ Squirrel Datasets Documentation
 ===============================
 `Squirrel Datasets <https://github.com/merantix-momentum/squirrel-datasets-core>`_ is an extension of the Squirrel platform for data transform, access, and discovery.
 It includes common drivers for public datasets, which are ready to use along with data preprocessing logic.
+A good way to get started is with our `Tutorials <https://github.com/merantix-momentum/squirrel-datasets-core/tree/main/examples>`_. 
 Visit the official `Squirrel Documentation <https://squirrel.readthedocs.io>`_ on more information how to use Squirrel.
 
 Find out more about Merantix Momentum on our `Website <https://merantix-momentum.com/>`_.

diff --git a/requirements.in b/requirements.in
@@ -1,5 +1,5 @@
 datasets
-squirrel-core[gcp, zarr]>=0.12,<0.13
+squirrel-core[gcp, zarr]>=0.12.1
 numpy
 pillow
 torchvision

diff --git a/requirements.txt b/requirements.txt
@@ -3,7 +3,7 @@
 # To update, run:
 #
 #    pip-compile --generate-hashes --no-annotate --no-emit-index-url --output-file=requirements.txt --strip-extras requirements.dev.in requirements.hub.in requirements.in requirements.preprocessing.in requirements.torchvision.in
-
+#
 aiohttp==3.8.1 \
     --hash=sha256:11691cf4dc5b94236ccc609b70fec991234e7ef8d4c02dd0c9668d1e486f5abf
 aiosignal==1.2.0 \
@@ -12,9 +12,6 @@ alabaster==0.7.12 \
     --hash=sha256:446438bdcca0e05bd45ea2de1668c1d9b032e1a9154c2c259092d77031ddd359
 antlr4-python3-runtime==4.8 \
     --hash=sha256:15793f5d0512a372b4e7d2284058ad32ce7dd27126b105fb0b2245130445db33
-appnope==0.1.2 \
-    --hash=sha256:93aa393e9d6c54c5cd570ccadd8edad61ea0c4b9ea7a01409020c9aa019eb442 \
-    --hash=sha256:dd83cd4b5b460958838f6eb3000c660b1f9caf2a5b1de4264e941512f603258a
 argon2-cffi==21.3.0 \
     --hash=sha256:8c976986f2c5c0e5000919e6de187906cfd81fb1c72bf9d88c01177e77da7f80 \
     --hash=sha256:b746dba803a79238e925d9046a63aa26bf86ab2a2fe74ce6b009a1c3f5c8f2ae
@@ -56,6 +53,11 @@ colorclass==2.2.2 \
     --hash=sha256:6f10c273a0ef7a1150b1120b6095cbdd68e5cf36dfd5d0fc957a2500bbf99a55
 coverage==6.3.2 \
     --hash=sha256:8fbbdc8d55990eac1b0919ca69eb5a988a802b854488c34b8f37f3e2025fa90d
+cryptography==36.0.2 \
+    --hash=sha256:70f8f4f7bb2ac9f340655cbac89d68c527af5bb4387522a8413e841e3e6628c9 \
+    --hash=sha256:7b2d54e787a884ffc6e187262823b6feb06c338084bbe80d45166a1cb1c6c5bf \
+    --hash=sha256:c2c5250ff0d36fd58550252f54915776940e4e866f38f3a7866d92b32a654b86 \
+    --hash=sha256:ea634401ca02367c1567f012317502ef3437522e2fc44a3ea1844de028fa4b84
 datasets==1.18.4 \
     --hash=sha256:e13695ad7aeda2af4430ac1a0b62def9c4b60bb4cc14dbaa240e6683cac50c49
 debugpy==1.5.1 \
@@ -138,6 +140,9 @@ ipywidgets==7.6.5 \
     --hash=sha256:d258f582f915c62ea91023299603be095de19afb5ee271698f88327b9fe9bf43
 jedi==0.18.1 \
     --hash=sha256:637c9635fcf47945ceb91cd7f320234a7be540ded6f3e99a50cb6febdfd1ba8d
+jeepney==0.8.0 \
+    --hash=sha256:5efe48d255973902f6badc3ce55e2aa6c5c3b3bc642059ef3a91247bcfcc5806 \
+    --hash=sha256:c0a454ad016ca575060802ee4d590dd912e35c122fa04e70306de3d076cce755
 jinja2==3.0.3 \
     --hash=sha256:077ce6014f7b40d03b47d1f1ca4b0fc8328a692bd284016f806ed0eaca390ad8
 jmespath==0.10.0 \
@@ -352,6 +357,9 @@ s3transfer==0.5.2 \
     --hash=sha256:7a6f4c4d1fdb9a2b640244008e142cbc2cd3ae34b386584ef044dd0f27101971
 scipy==1.8.0 \
     --hash=sha256:ad5be4039147c808e64f99c0e8a9641eb5d2fa079ff5894dcd8240e94e347af4
+secretstorage==3.3.1 \
+    --hash=sha256:422d82c36172d88d6a0ed5afdec956514b189ddbfb72fefab0c8a1cee4eaf71f \
+    --hash=sha256:fd666c51a6bf200643495a04abb261f83229dcb6fd8472ec393df7ffc8b6f195
 send2trash==1.8.0 \
     --hash=sha256:f20eaadfdb517eaca5ce077640cb261c7d2698385a6a0f072a4a5447fd49fa08
 six==1.16.0 \
@@ -385,9 +393,9 @@ sphinxcontrib-qthelp==1.0.3 \
     --hash=sha256:bd9fc24bcb748a8d51fd4ecaade681350aa63009a347a8c14e637895444dfab6
 sphinxcontrib-serializinghtml==1.1.5 \
     --hash=sha256:352a9a00ae864471d3a7ead8d7d79f5fc0b57e8b3f95e9867eb9eb28999b92fd
-squirrel-core==0.12.0 \
-    --hash=sha256:9780240c15b5e84535285f01b3c4ccad2dc0bb21e379bb0f68b62f73cf283e83 \
-    --hash=sha256:eeed4feada50316e101cca5e5879eac6c1944c6c41a5615e62a3ea74f290aa14
+squirrel-core==0.12.1 \
+    --hash=sha256:3556d1d602b0bbca4f5362a4f659cb063aae691db0a4c0aa33f6a5674d809f8b \
+    --hash=sha256:ebc787a41b7e05806909626a815ac1765e5ee5d8af4d95de36943e77a78e35e6
 stack-data==0.2.0 \
     --hash=sha256:999762f9c3132308789affa03e9271bbbe947bf78311851f4d485d8402ed858e
 termcolor==1.1.0 \

diff --git a/setup.py b/setup.py
@@ -110,8 +110,7 @@ def parse_req(spec: str) -> str:
 
 # TODO remove after beta-testing phase
 classifiers = [
-    "Private :: Do Not Upload",
-    "Development Status :: 4 - Beta",
+    "Development Status :: 5 - Production/Stable",
     "License :: OSI Approved :: Apache Software License",
     "Programming Language :: Python :: 3.8",
     "Typing :: Typed",
@@ -126,7 +125,7 @@ def parse_req(spec: str) -> str:
         description="Squirrel public datasets collection",
         long_description=long_description,
         long_description_content_type="text/markdown",
-        author="Merantix Labs GmbH",
+        author="Merantix Momentum",
         license="Apache 2.0",
         # Needed to make jinja work and not get linting errors in the rendered file
         package_dir={"": "src"},