From 1053a6e9ce935ff29c8f69f56d0a6b3c3397520e Mon Sep 17 00:00:00 2001
From: Dani <46004242+otivedani@users.noreply.github.com>
Date: Thu, 30 Jul 2020 07:02:37 +0700
Subject: [PATCH] Update PyPi package metadata and resolve Travis CI failing
 build (#1602)

* Update PyPi package metadata setup.py 'long_description'

* Add V8 package to Travis CI config & caching pip
---
 .travis.yml     | 5 +++++
 python/setup.py | 7 ++++---
 2 files changed, 9 insertions(+), 3 deletions(-)

diff --git a/.travis.yml b/.travis.yml
index 528a9a1..b9cbae9 100644
--- a/.travis.yml
+++ b/.travis.yml
@@ -1,4 +1,8 @@
 dist: xenial
+addons:
+  apt:
+    packages:
+      - libv8-dev
 language: python
 
 jobs:
@@ -6,6 +10,7 @@ jobs:
     - language: python
       python:
         - "3.7"
+      cache: pip
       install:
         - pip install --upgrade pip
         - pip install -U -r python/requirements.txt dask[dataframe] distributed
diff --git a/python/setup.py b/python/setup.py
index edba5bd..db70d8b 100644
--- a/python/setup.py
+++ b/python/setup.py
@@ -113,6 +113,8 @@ class TestCommand(test_command):
             sys.modules.update(old_modules)
             working_set.__init__()
 
+with open('README.md', 'r', encoding='utf-8') as f:
+    long_description = f.read()
 
 with open('requirements.txt', 'r') as f:
     install_requires = f.read().splitlines()
@@ -143,7 +145,6 @@ setup(
         'Programming Language :: Python :: 3',
         'Programming Language :: Python :: 3.7',
     ],
-    long_description="""
-Implements a procedure for forecasting time series data based on an additive model where non-linear trends are fit with yearly, weekly, and daily seasonality, plus holiday effects. It works best with time series that have strong seasonal effects and several seasons of historical data. Prophet is robust to missing data and shifts in the trend, and typically handles outliers well.
-"""
+    long_description=long_description,
+    long_description_content_type='text/markdown',
 )