Merge pull request #3 from Tauffer-Consulting/alphavantage

Alphavantage

.domino/compiled_metadata.json

@@ -209,7 +209,7 @@
             "title": "SecretsModel",
             "type": "object"
         },
-        "source_url": "https://github.com/Tauffer-Consulting/news_domino_pieces/tree/main/pieces/NewsApiArticlesPiece"
+        "source_url": "https://github.com/Tauffer-Consulting/data_apis_domino_pieces/tree/main/pieces/NewsApiArticlesPiece"
     },
     "NewsApiHeadlinesPiece": {
         "name": "NewsApiHeadlinesPiece",
@@ -475,7 +475,7 @@
             "title": "SecretsModel",
             "type": "object"
         },
-        "source_url": "https://github.com/Tauffer-Consulting/news_domino_pieces/tree/main/pieces/NewsApiHeadlinesPiece"
+        "source_url": "https://github.com/Tauffer-Consulting/data_apis_domino_pieces/tree/main/pieces/NewsApiHeadlinesPiece"
     },
     "NasaEarthImagePiece": {
         "name": "NasaEarthImagePiece",
@@ -572,6 +572,6 @@
             "title": "SecretsModel",
             "type": "object"
         },
-        "source_url": "https://github.com/Tauffer-Consulting/news_domino_pieces/tree/main/pieces/NasaEarthImagePiece"
+        "source_url": "https://github.com/Tauffer-Consulting/data_apis_domino_pieces/tree/main/pieces/NasaEarthImagePiece"
     }
 }

.domino/dependencies_map.json

@@ -13,6 +13,6 @@
             "NASA_API_KEY",
             "NEWSAPI_API_KEY"
         ],
-        "source_image": "ghcr.io/tauffer-consulting/data_apis_domino_pieces:development-group0"
+        "source_image": "ghcr.io/tauffer-consulting/data_apis_domino_pieces:0.2.0-group0"
     }
 }

.github/workflows/validate-and-organize.yml

@@ -17,10 +17,10 @@ jobs:
           persist-credentials: false # otherwise, the token used is the GITHUB_TOKEN, instead of your personal access token.
           fetch-depth: 0 # otherwise, there would be errors pushing refs to the destination repository.
 
-      - name: Set up Python 3.8
+      - name: Set up Python 3.10
         uses: actions/setup-python@v3
         with:
-          python-version: "3.8"
+          python-version: "3.10"
 
       - name: Pip install packages
         run: |

README.md

@@ -2,6 +2,7 @@
 
 Domino Pieces for a variety of Data APIs:
 
-- **NewsApiArticlesPiece** - Retrieves articles using [News API](https://newsapi.org/)
+- **NewsApiArticlesPiece** - Retrieves articles using [News API](https://newsapi.org)
 - **NewsApiHeadlinesPiece** - Retrieves headlines using [News API](https://newsapi.org/)
 - **NasaEarthImagePiece** - Retrieves images of Earth using [NASA's EPIC API](https://epic.gsfc.nasa.gov/about/api)
+- **AlphaVantageDailyPiece** - Retrieves daily stock data using [Alpha Vantage API](https://www.alphavantage.co)

config.toml

@@ -4,4 +4,4 @@ REGISTRY_NAME = "tauffer-consulting"
 REPOSITORY_NAME = "data_apis_domino_pieces"
 REPOSITORY_LABEL = "Data APIs Domino Pieces"
 
-VERSION = "0.2.0"
+VERSION = "0.3.0"

dependencies/requirements.txt

@@ -1,2 +1,4 @@
 newsapi-python==0.2.7
-beautifulsoup4==4.12.2
+beautifulsoup4==4.12.2
+pandas==2.1.3
+plotly==5.18.0

pieces/AlphaVantageDailyPiece/metadata.json

@@ -0,0 +1,21 @@
+{
+    "name": "AlphaVantageDailyPiece",
+    "description": "This Piece uses the AlphaVantage API to get daily stock data.\n- https://www.alphavantage.co/",
+    "dependency": {
+        "requirements_file": "requirements.txt"
+    },
+    "container_resources": {
+        "requests": {
+            "cpu": "100m",
+            "memory": "128Mi"
+        },
+        "limits": {
+            "cpu": "500m",
+            "memory": "512Mi"
+        }
+    },
+    "style": {
+        "node_label": "AlphaVantage Daily",
+        "icon_class_name": "ant-design:stock-outlined"
+    }
+}

pieces/AlphaVantageDailyPiece/models.py

@@ -0,0 +1,35 @@
+from pydantic import BaseModel, Field
+from enum import Enum
+
+
+class OutputSizeTypes(str, Enum):
+    compact = "compact"
+    full = "full"
+
+
+class InputModel(BaseModel):
+    symbol: str = Field(
+        default="AAPL",
+        description="The stock symbol."
+    )
+    output_size: OutputSizeTypes = Field(
+        default=OutputSizeTypes.compact,
+        description="The size of the output data. Options are `compact` (100 data points) and full (full-length data). Default is `compact`."
+    )
+    max_data_points: int = Field(
+        default=-1,
+        description="The maximum number of data points to return. Default is -1, which returns all data points."
+    )
+
+
+class OutputModel(BaseModel):
+    data_file_path: str = Field(
+        default="",
+        description='Path to the data file.'
+    )
+
+
+class SecretsModel(BaseModel):
+    ALPHA_VANTAGE_API_KEY: str = Field(
+        description="API key for Alpha Vantage data API."
+    )

pieces/AlphaVantageDailyPiece/piece.py

@@ -0,0 +1,97 @@
+from domino.base_piece import BasePiece
+from .models import InputModel, OutputModel, SecretsModel
+import pandas as pd
+import requests
+import json
+import plotly
+import plotly.graph_objects as go
+
+
+def make_plotly_fig(df: pd.DataFrame, symbol: str):
+    fig = go.Figure()
+    trace_candlestick = go.Candlestick(
+        x=df['Date'],
+        open=df['Open'],
+        high=df['High'],
+        low=df['Low'],
+        close=df['Close'],
+        name='Candlestick'
+    )
+    fig.add_trace(trace_candlestick)
+    fig.update_layout(
+        xaxis=dict(
+            rangeslider=dict(visible=True),
+            showgrid=True,  # Show gridlines for the x-axis
+            gridcolor='lightgray'  # Set the grid color to gray
+        ),
+        yaxis=dict(
+            showgrid=True,
+            gridcolor='lightgray',
+            fixedrange=False
+        ),
+        title=f'{symbol} Daily Stock Data',
+        xaxis_title='Date',
+        yaxis_title='Price',
+        height=600,
+        width=800,
+        plot_bgcolor='white',
+    )
+    return fig
+
+
+class AlphaVantageDailyPiece(BasePiece):
+    """
+    This Piece uses the AlphaVantage API to get daily stock data.
+    - https://www.alphavantage.co/
+    """
+    def piece_function(self, input_data: InputModel, secrets_data: SecretsModel):
+
+        api_key = secrets_data.ALPHA_VANTAGE_API_KEY
+        if not api_key:
+            raise Exception("Alpha Vantage API key is required.")
+
+        symbol = input_data.symbol
+        output_size = input_data.output_size.value
+        number_of_points = input_data.max_data_points
+
+        endpoint = 'https://www.alphavantage.co/query'
+        params = {
+            'function': 'TIME_SERIES_DAILY',
+            'symbol': symbol,
+            'outputsize': output_size,
+            'apikey': api_key
+        }
+
+        data_file_path = f"{self.results_path}/results_daily_data.csv"
+
+        try:
+            response = requests.get(endpoint, params=params)
+            if response.status_code == 200:
+                data = response.json()
+                daily_data = data['Time Series (Daily)']
+                df = pd.DataFrame(daily_data).T
+                if number_of_points > 0 and number_of_points < len(df):
+                    df = df[:number_of_points]
+                df.columns = ['Open', 'High', 'Low', 'Close', 'Volume']
+                df.index = pd.to_datetime(df.index)
+                df.reset_index(inplace=True)
+                df.rename(columns={'index': 'Date'}, inplace=True)
+                df.to_csv(data_file_path, index=False)
+            else:
+                raise Exception(f'Error: {response.status_code} - {response.text}')
+        except Exception as e:
+            raise Exception(f'Error: {e}')
+
+        # Save image to results
+        fig = make_plotly_fig(df, symbol)
+        fig_json = json.dumps(fig, cls=plotly.utils.PlotlyJSONEncoder)
+        with open(f"{self.results_path}/results_plotly.json", "w") as f:
+            f.write(fig_json)
+        self.display_result = {
+            "file_type": "plotly-json",
+            "file_path": f"{self.results_path}/results_plotly.json",
+        }
+
+        return OutputModel(
+            data_file_path=data_file_path
+        )

pieces/AlphaVantageDailyPiece/test_alphavantage.py

@@ -0,0 +1,22 @@
+from domino.testing import piece_dry_run
+from pathlib import Path
+import os
+
+
+def test_alphavantage():
+    ALPHA_VANTAGE_API_KEY = os.environ.get("ALPHA_VANTAGE_API_KEY", None)
+    if not ALPHA_VANTAGE_API_KEY:
+        raise Exception("ALPHA_VANTAGE_API_KEY environment variable is required.")
+    input_data = dict(
+        symbol="AAPL",
+        output_size="compact",
+        max_data_points=-1
+    )
+    piece_output = piece_dry_run(
+        piece_name="AlphaVantageDailyPiece",
+        input_data=input_data,
+        secrets_data=dict(
+            ALPHA_VANTAGE_API_KEY=ALPHA_VANTAGE_API_KEY
+        ),
+    )
+    assert Path(piece_output["data_file_path"]).exists()