From 71ea6164f952320edb493f80343eb44aaf9c654e Mon Sep 17 00:00:00 2001 From: Illya Barziy Date: Mon, 15 Nov 2021 17:50:43 +0100 Subject: [PATCH] =?UTF-8?q?Bump=20version:=200.5.0=20=E2=86=92=200.6.0?= MIME-Version: 1.0 Content-Type: text/plain; charset=UTF-8 Content-Transfer-Encoding: 8bit --- .bumpversion.cfg | 2 +- docs/source/conf.py | 2 +- docs/source/getting_started/installation.rst | 6 +++--- setup.cfg | 2 +- setup.py | 3 +-- 5 files changed, 7 insertions(+), 8 deletions(-) diff --git a/.bumpversion.cfg b/.bumpversion.cfg index 64d639f8..4dcf5460 100644 --- a/.bumpversion.cfg +++ b/.bumpversion.cfg @@ -1,5 +1,5 @@ [bumpversion] -current_version = 0.5.0 +current_version = 0.6.0 commit = True tag = True tag_name = {new_version} diff --git a/docs/source/conf.py b/docs/source/conf.py index b489c78c..08bc37ce 100644 --- a/docs/source/conf.py +++ b/docs/source/conf.py @@ -22,7 +22,7 @@ author = 'Hudson & Thames Quantitative Research' # The full version, including alpha/beta/rc tags -release = '0.5.0' +release = '0.6.0' # -- General configuration --------------------------------------------------- diff --git a/docs/source/getting_started/installation.rst b/docs/source/getting_started/installation.rst index f3ed15ff..9702d2ba 100644 --- a/docs/source/getting_started/installation.rst +++ b/docs/source/getting_started/installation.rst @@ -81,7 +81,7 @@ Ubuntu Linux .. code-block:: - pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.5.0-py3-none-any.whl + pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.6.0-py3-none-any.whl 8. Install CVXPY (this library is used for convex optimization problems). @@ -185,7 +185,7 @@ Mac OS X .. code-block:: - pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.5.0-py3-none-any.whl + pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.6.0-py3-none-any.whl 8. Install CVXPY (this library is used for convex optimization problems). @@ -303,7 +303,7 @@ Windows .. code-block:: - pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.5.0-py3-none-any.whl + pip install https://1fed2947109cfffdd6aaf615ea84a82be897c4b9@raw.githubusercontent.com/hudson-and-thames-clients/arbitragelab/master/arbitragelab-0.6.0-py3-none-any.whl 9. (Optional) **Only if you want to use the ML Approach Module**, install the TensorFlow, Keras packages, and update the NumPy version. Note that you should have pip version "pip==20.1.1" to do this. Supported TensorFlow and Keras versions diff --git a/setup.cfg b/setup.cfg index 474d68e0..02db9d60 100644 --- a/setup.cfg +++ b/setup.cfg @@ -1,6 +1,6 @@ [metadata] name = arbitragelab -version = 0.5.0 +version = 0.6.0 author = Hudson and Thames Quantitative Research author_email = research@hudsonthames.org licence = All Rights Reserved diff --git a/setup.py b/setup.py index 6362f651..1b71025d 100644 --- a/setup.py +++ b/setup.py @@ -25,8 +25,7 @@ # 1. Create package: python setup.py bdist_wheel # 2. Unzip the dist.whl file # 2.2 cd into the unzipped dir -# 3. Obfuscate: pyarmor obfuscate --platform windows.x86_64 --platform linux.x86_64 --platform darwin.x86_64 --obf-code=0 --recursive --output dist/mlfinlab mlfinlab/__init__.py -# 4. Add back datasets in mlfinlab +# 3. Obfuscate: pyarmor obfuscate --platform windows.x86_64 --platform linux.x86_64 --platform darwin.x86_64 --obf-code=0 --recursive --output dist/arbitragelab arbitragelab/__init__.py # 4. Repackage # 5. install # 6. test