GitHub CI action

.github/workflows/ci.yml

@@ -0,0 +1,25 @@
+name: CI
+
+on:
+  push:
+    branches: ['**']
+  pull_request:
+
+jobs:
+  tests:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout
+        uses: actions/checkout@master
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.9'
+          cache: 'pip' # caching pip dependencies
+
+      - name: Run tests
+        run: |
+          pip install -r requirements.txt
+          python -m pytest

README.md

@@ -5,9 +5,7 @@ NoLiTSA (<b>No</b>n<b>Li</b>near <b>T</b>ime <b>S</b>eries
 <b>A</b>nalysis) is a Python module implementing several standard
 algorithms used in nonlinear time series analysis.
 
-[![Build Status](https://travis-ci.org/manu-mannattil/nolitsa.svg?branch=master)](https://travis-ci.org/manu-mannattil/nolitsa)
-[![Coverage Status](https://coveralls.io/repos/github/manu-mannattil/nolitsa/badge.svg)](https://coveralls.io/github/manu-mannattil/nolitsa)
-
+[![CI](https://github.com/manu-mannattil/nolitsa/actions/workflows/ci.yml/badge.svg)](https://github.com/manu-mannattil/nolitsa/actions/workflows/ci.yml)
 
 Features
 --------
@@ -30,22 +28,15 @@ Features
 Installation
 ------------
 
-NoLiTSA can be installed using pip by running
-
-    git clone https://github.com/manu-mannattil/nolitsa.git
-    pip install ./nolitsa
-
-or, with newer versions of pip:
+NoLiTSA can be installed via
 
     pip install git+https://github.com/manu-mannattil/nolitsa.git
 
 NoLiTSA requires NumPy, SciPy, and Numba.
 
 ### Tests
 
-NoLiTSA’s unit tests can be executed by running `nosetests`, or by using
-
-    python setup.py test
+NoLiTSA’s unit tests can be executed by running `pytest`.
 
 Publications
 ------------

setup.py

@@ -24,8 +24,7 @@
     license='BSD',
     packages=['nolitsa'],
     install_requires=['numpy>=1.11.0', 'scipy>=0.17.0'],
-    test_suite='nose.collector',
-    tests_require=['nose>=1.3.1'],
+    test_suite='pytest',
     include_package_data=True,
     zip_safe=False
 )