Add GH action, update README

Author: stuartquin

.github/workflows/build.yml

@@ -0,0 +1,42 @@
+name: Build
+
+on:
+  release:
+    types: [published]
+  push:
+    branches: main
+  pull_request:
+    branches: "*"
+
+jobs:
+  build:
+    runs-on: ubuntu-latest
+    strategy:
+      matrix:
+        python-version: [3.9]
+        poetry-version: [1.1.10]
+
+    steps:
+      - uses: actions/checkout@v2
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v2
+        with:
+          python-version: ${{ matrix.python-version }}
+      - name: Run image
+        uses: abatilo/actions-poetry@v2.0.0
+        with:
+          poetry-version: ${{ matrix.poetry-version }}
+      - name: Install dependencies
+        working-directory: ./ossso_app
+        run: |
+          poetry install
+      - name: Test
+        working-directory: ./ossso_app
+        run: |
+          poetry run pytest
+
+      - name: Build and publish to pypi
+        if: github.event_name == 'release'
+        uses: JRubics/poetry-publish@v1.13
+        with:
+          pypi_token: ${{ secrets.PYPI_TOKEN }}

README.md

@@ -1,6 +1,6 @@
 # DataQA
 
-TODO: Add logo here
+![alt text](https://dataqa.ai/static/images/logo-violet.png "DataQA")
 
 DataQA is a tool to perform AI model quality assessment (QA) using an interactive app that can be shared with technical and non-technical members of your team.
 
@@ -16,7 +16,7 @@ The official documentation page is at: [docs.dataqa.ai]().
 
 ## Step 1: create an account
 
-Go to (https://app.dataqa.ai/)[https://app.dataqa.ai/login] and follow the steps to create your first project. Once your account and your first project have been created, you will see a screen such as this one:
+Go to [https://app.dataqa.ai/](https://app.dataqa.ai/login) and follow the steps to create your first project. Once your account and your first project have been created, you will see a screen such as this one:
 
 TODO: Add screenshot of the screen with the publish string
 
@@ -28,7 +28,7 @@ Creating your first shareable QA app is as simple as this:
 
 ```python
 import pandas as pd
-from lib.publish import DataQA 
+from dataqa.publish import DataQA
 dataqa = DataQA()
 dataqa.login()
 # Prompt username and password