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* Pin Squirrel V0.12.1

* Update reference to squirrel image

* Update Documentation and Readme

* Update company name and development status

* Install [all] and allow greater squirrel version
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Winfried Lötzsch committed Apr 5, 2022
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39 changes: 7 additions & 32 deletions README.md
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<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)
Expand All @@ -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)!
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4 changes: 2 additions & 2 deletions docs/source/conf.py
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Expand Up @@ -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 = [
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1 change: 1 addition & 0 deletions docs/source/index.rst
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Expand Up @@ -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/>`_.
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2 changes: 1 addition & 1 deletion requirements.in
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datasets
squirrel-core[gcp, zarr]>=0.12,<0.13
squirrel-core[gcp, zarr]>=0.12.1
numpy
pillow
torchvision
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22 changes: 15 additions & 7 deletions requirements.txt
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Expand Up @@ -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 \
Expand All @@ -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
Expand Down Expand Up @@ -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 \
Expand Down Expand Up @@ -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 \
Expand Down Expand Up @@ -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 \
Expand Down Expand Up @@ -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 \
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5 changes: 2 additions & 3 deletions setup.py
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Expand Up @@ -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",
Expand All @@ -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"},
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