publish

Author: tuttlepower

.github/workflows/publish.yml

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+name: Publish Python Package
+
+on:
+  push:
+    branches:
+      - main
+
+jobs:
+  test:
+    runs-on: ubuntu-latest
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install -r requirements.txt
+          pip install pytest
+
+      - name: Run tests
+        run: pytest tests/
+
+  publish:
+    runs-on: ubuntu-latest
+    needs: test  # Run only if tests succeed
+
+    steps:
+      - name: Checkout repository
+        uses: actions/checkout@v3
+
+      - name: Set up Python
+        uses: actions/setup-python@v4
+        with:
+          python-version: '3.x'
+
+      - name: Install dependencies
+        run: |
+          python -m pip install --upgrade pip
+          pip install setuptools wheel twine
+
+      - name: Build package
+        run: python setup.py sdist bdist_wheel
+
+      - name: Publish package to PyPI
+        env:
+          TWINE_USERNAME: ${{ secrets.PYPI_USERNAME }}
+          TWINE_PASSWORD: ${{ secrets.PYPI_PASSWORD }}
+        run: |
+          twine upload dist/*

predictit_markets.py

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+# __init__.py
+
+# You can import your main module here if needed
+from .predictit_markets import *

predictit_markets/__init__.py

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+# predictit_markets.py
+
+import pandas as pd
+import requests
+
+def market_data(market, time=90, maxContracts=6):
+    """
+    Fetch market data from PredictIt's API and return as a DataFrame.
+
+    Parameters:
+    - market (int): The market ID to fetch data for.
+    - time: The timespan for which data is fetched. Options: '24h', 7, 30, 90 (in days).
+    - maxContracts (int): The maximum number of contracts to fetch.
+
+    Returns:
+    - pd.DataFrame: DataFrame containing the market data or None if an error occurred.
+    """
+    url = f'https://www.predictit.org/api/Public/GetMarketChartData/{market}'
+    params = {
+        'timespan': time,
+        'maxContracts': maxContracts,
+        'isTimespanInHours': 'false'
+    }
+    try:
+        response = requests.get(url, params=params)
+        response.raise_for_status()  # Raises an HTTPError for bad responses
+
+        data = response.json()
+        df = pd.DataFrame(data)
+        return df
+
+    except requests.exceptions.HTTPError as e:
+        print(f"HTTP Error: {e}")
+    except requests.exceptions.RequestException as e:
+        print(f"Request Error: {e}")
+    except ValueError as e:
+        print(f"Error decoding JSON: {e}")
+    except Exception as e:
+        print(f"Unexpected error: {e}")
+
+    return None
+
+def market_name(market):
+    # this may not be the best way to do it, but it worked pretty well for me 
+    df = pd.read_json('https://www.predictit.org/api/marketdata/markets/'+str(market))
+    # sets the market to a string and returns it. 
+    text = str(df['name'][0])
+    return text

predictit_markets/__pycache__/__init__.cpython-311.pyc

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+from setuptools import setup, find_packages
+
+setup(
+    name="predictit_markets",  # Package name
+    version="0.1.0",  # Initial version
+    author="Your Name",
+    author_email="your.email@example.com",
+    description="A package for interacting with PredictIt markets",
+    long_description=open('README.md').read(),
+    long_description_content_type='text/markdown',
+    url="https://github.com/tuttlepower/predictit_markets",
+    packages=find_packages(),
+    package_data={
+        'predictit_markets': ['images/*.png']  # Include image files in the package
+    },
+    classifiers=[
+        "Programming Language :: Python :: 3",
+        "License :: OSI Approved :: MIT License",
+        "Operating System :: OS Independent",
+    ],
+    python_requires='>=3.6',
+    install_requires=[
+        'requests',
+          'pandas',  # Add any dependencies your package needs
+    ],
+)

predictit_markets/__pycache__/predictit_markets.cpython-311.pyc

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+# tests/__init__.py

images/output_example.PNG renamed to predictit_markets/images/output_example.PNG

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+# test_integration_predictit_markets.py
+
+import unittest
+from predictit_markets import predictit_markets
+
+class TestPredictItMarketsIntegration(unittest.TestCase):
+
+    def test_real_api_call(self):
+        # This test will hit the real API
+        df = predictit_markets.market_data(8089)
+        self.assertTrue(len(df) > 0)
+
+if __name__ == '__main__':
+    unittest.main()

predictit_markets/predictit_markets.py

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+# tests/test_predictit_markets.py
+
+import unittest
+from unittest.mock import patch, Mock
+import requests
+from predictit_markets.predictit_markets import market_data
+
+class TestPredictItMarkets(unittest.TestCase):
+
+    @patch('predictit_markets.predictit_markets.requests.get')
+    def test_market_data_success(self, mock_get):
+        # Simulate a successful API response
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.return_value = [
+            {'marketId': 8089, 'contractId': 31414, 'contractName': 'Shapiro', 'date': '2024-07-26T00:00:00', 'dateString': '2024-07-26', 'openSharePrice': 0.26, 'highSharePrice': 0.34, 'lowSharePrice': 0.25, 'closeSharePrice': 0.31, 'tradeVolume': 160257, 'lineColor': '#0D8ECF'}
+            # Add more sample data here if needed
+        ]
+        mock_get.return_value = mock_response
+
+        # Test the market_data function
+        df = market_data(8089)
+
+        # Assert the DataFrame is not None and contains the expected data
+        self.assertIsNotNone(df)
+        self.assertEqual(len(df), 1)
+        self.assertEqual(df.iloc[0]['contractName'], 'Shapiro')
+
+    @patch('predictit_markets.predictit_markets.requests.get')
+    def test_market_data_http_error(self, mock_get):
+        # Simulate an HTTP error response
+        mock_response = Mock()
+        mock_response.raise_for_status.side_effect = requests.exceptions.HTTPError("404 Client Error: Not Found")
+        mock_get.return_value = mock_response
+
+        # Test the market_data function
+        df = market_data(9999)  # Assuming 9999 is a non-existent market ID
+
+        # Assert the DataFrame is None due to the error
+        self.assertIsNone(df)
+
+    @patch('predictit_markets.predictit_markets.requests.get')
+    def test_market_data_request_exception(self, mock_get):
+        # Simulate a request exception
+        mock_get.side_effect = requests.exceptions.RequestException("Network error")
+
+        # Test the market_data function
+        df = market_data(8089)
+
+        # Assert the DataFrame is None due to the exception
+        self.assertIsNone(df)
+
+    @patch('predictit_markets.predictit_markets.requests.get')
+    def test_market_data_json_error(self, mock_get):
+        # Simulate a JSON decoding error
+        mock_response = Mock()
+        mock_response.status_code = 200
+        mock_response.json.side_effect = ValueError("No JSON object could be decoded")
+        mock_get.return_value = mock_response
+
+        # Test the market_data function
+        df = market_data(8089)
+
+        # Assert the DataFrame is None due to JSON error
+        self.assertIsNone(df)
+
+if __name__ == '__main__':
+    unittest.main()