0.3.3 release

Author: ChernovAndrey

.github/workflows/lint.yml

@@ -0,0 +1,81 @@
+name: Lint
+
+on:
+  push:
+    branches: [main, develop, feat/**]
+  pull_request:
+    branches: [main, develop]
+
+jobs:
+  ruff:
+    name: Ruff (Linter & Formatter)
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install Ruff
+        run: pip install ruff
+
+      - name: Run Ruff linter
+        run: ruff check faim_sdk/ faim_client/ tests/
+
+      - name: Run Ruff formatter check
+        run: ruff format --check faim_sdk/ faim_client/ tests/
+
+  type-check:
+    name: Type Checking (mypy)
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
+      - name: Install dependencies
+        run: |
+          uv pip install --system -e .
+          uv pip install --system mypy types-requests
+
+      - name: Run mypy
+        run: mypy faim_sdk/ --ignore-missing-imports --no-strict-optional
+        continue-on-error: true
+
+  package-check:
+    name: Package Build Check
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install build dependencies
+        run: pip install poetry build twine
+
+      - name: Build package
+        run: poetry build
+
+      - name: Check package with twine
+        run: twine check dist/*
+
+      - name: Verify package contents
+        run: |
+          tar -tzf dist/*.tar.gz | grep -E "faim_sdk|faim_client"
+          unzip -l dist/*.whl | grep -E "faim_sdk|faim_client"

.github/workflows/test.yml

@@ -0,0 +1,78 @@
+name: Test
+
+on:
+  push:
+    branches: [main, develop, feat/**]
+  pull_request:
+    branches: [main, develop]
+
+jobs:
+  test:
+    name: Test Python ${{ matrix.python-version }}
+    runs-on: ubuntu-latest
+    strategy:
+      fail-fast: false
+      matrix:
+        python-version: ["3.11", "3.12"]
+
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python ${{ matrix.python-version }}
+        uses: actions/setup-python@v5
+        with:
+          python-version: ${{ matrix.python-version }}
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
+      - name: Install dependencies
+        run: |
+          uv pip install --system -e .
+          uv pip install --system pytest pytest-cov pytest-asyncio
+
+      - name: Run unit tests
+        run: |
+          pytest tests/unit/ -v --cov=faim_sdk --cov=faim_client --cov-report=xml --cov-report=term
+
+      - name: Upload coverage to Codecov
+        uses: codecov/codecov-action@v4
+        if: matrix.python-version == '3.11'
+        with:
+          file: ./coverage.xml
+          fail_ci_if_error: false
+          token: ${{ secrets.CODECOV_TOKEN }}
+
+  test-examples:
+    name: Test Examples
+    runs-on: ubuntu-latest
+    steps:
+      - name: Checkout code
+        uses: actions/checkout@v4
+
+      - name: Set up Python 3.11
+        uses: actions/setup-python@v5
+        with:
+          python-version: "3.11"
+
+      - name: Install uv
+        uses: astral-sh/setup-uv@v3
+        with:
+          version: "latest"
+
+      - name: Install dependencies with viz extras
+        run: |
+          uv pip install --system -e ".[viz]"
+          uv pip install --system jupyterlab pandas statsmodels
+
+      - name: Check example notebooks can be read
+        run: |
+          python -c "import nbformat; nbformat.read('examples/flowstate_simple_example.ipynb', as_version=4)"
+          python -c "import nbformat; nbformat.read('examples/model_comparison_example.ipynb', as_version=4)"
+
+      - name: Verify eval package imports
+        run: |
+          python -c "from faim_sdk.eval import mse, mase, crps_from_quantiles, plot_forecast; print('Eval imports successful')"

.gitignore

@@ -24,4 +24,5 @@ dmypy.json
 
 openapi.json
 pyproject.toml
-CLAUDE.md
+CLAUDE.md
+/poetry.lock

README.md

@@ -28,7 +28,6 @@ pip install faim-sdk
 ```python
 import numpy as np
 from faim_sdk import ForecastClient, Chronos2ForecastRequest
-from faim_client.models import ModelName
 
 # Initialize client with your API endpoint
 client = ForecastClient(
@@ -49,8 +48,8 @@ request = Chronos2ForecastRequest(
     quantiles=[0.1, 0.5, 0.9]  # 10th, 50th (median), 90th percentiles
 )
 
-# Generate forecast
-response = client.forecast(ModelName.CHRONOS2, request)
+# Generate forecast - model inferred automatically from request type
+response = client.forecast(request)
 
 # Access predictions
 print(response.quantiles.shape)  # (32, 24, 3)
@@ -75,7 +74,7 @@ request = FlowStateForecastRequest(
     prediction_type="mean"  # Options: "mean", "median"
 )
 
-response = client.forecast(ModelName.FLOWSTATE, request)
+response = client.forecast(request)
 print(response.point.shape)  # (batch_size, 24, features)
 ```
 
@@ -94,7 +93,7 @@ request = Chronos2ForecastRequest(
     quantiles=[0.05, 0.25, 0.5, 0.75, 0.95]  # Full distribution
 )
 
-response = client.forecast(ModelName.CHRONOS2, request)
+response = client.forecast(request)
 print(response.quantiles.shape)  # (batch_size, 24, 5)
 ```
 
@@ -111,7 +110,7 @@ request = TiRexForecastRequest(
     output_type="point"
 )
 
-response = client.forecast(ModelName.TIREX, request)
+response = client.forecast(request)
 print(response.point.shape)  # (batch_size, 24, features)
 ```
 
@@ -120,7 +119,7 @@ print(response.point.shape)  # (batch_size, 24, features)
 All forecasts return a `ForecastResponse` object with predictions and metadata:
 
 ```python
-response = client.forecast(ModelName.CHRONOS2, request)
+response = client.forecast(request)
 
 # Access predictions based on output_type
 if response.point is not None:
@@ -252,7 +251,6 @@ fig, axes = plot_forecast(
 import numpy as np
 from faim_sdk import ForecastClient, Chronos2ForecastRequest
 from faim_sdk.eval import mse, mase, crps_from_quantiles, plot_forecast
-from faim_client.models import ModelName
 
 # Initialize client
 client = ForecastClient(base_url="https://api.faim.example.com")
@@ -268,7 +266,7 @@ request = Chronos2ForecastRequest(
     output_type="quantiles",
     quantiles=[0.1, 0.5, 0.9]
 )
-response = client.forecast(ModelName.CHRONOS2, request)
+response = client.forecast(request)
 
 # Evaluate point forecast (use median)
 point_pred = response.quantiles[:, :, 1:2]  # Extract median, keep 3D shape
@@ -315,6 +313,7 @@ The SDK provides **machine-readable error codes** for robust error handling:
 ```python
 from faim_sdk import (
     ForecastClient,
+    Chronos2ForecastRequest,
     ValidationError,
     AuthenticationError,
     RateLimitError,
@@ -323,7 +322,8 @@ from faim_sdk import (
 )
 
 try:
-    response = client.forecast(ModelName.CHRONOS2, request)
+    request = Chronos2ForecastRequest(x=data, horizon=24, quantiles=[0.1, 0.5, 0.9])
+    response = client.forecast(request)
 
 except AuthenticationError as e:
     # Handle authentication failures (401, 403)
@@ -375,7 +375,6 @@ The SDK supports async operations for concurrent requests:
 ```python
 import asyncio
 from faim_sdk import ForecastClient, Chronos2ForecastRequest
-from faim_client.models import ModelName
 
 async def forecast_multiple_series():
     client = ForecastClient(
@@ -393,7 +392,7 @@ async def forecast_multiple_series():
     # Execute concurrently
     async with client:
         tasks = [
-            client.forecast_async(ModelName.CHRONOS2, req)
+            client.forecast_async(req)
             for req in requests
         ]
         responses = await asyncio.gather(*tasks)
@@ -462,13 +461,15 @@ Use context managers for automatic resource cleanup:
 ```python
 # Sync context manager
 with ForecastClient(base_url="https://api.faim.example.com") as client:
-    response = client.forecast(ModelName.CHRONOS2, request)
+    request = Chronos2ForecastRequest(x=data, horizon=24, quantiles=[0.1, 0.5, 0.9])
+    response = client.forecast(request)
     print(response.quantiles)
 # Client automatically closed
 
 # Async context manager
 async with ForecastClient(base_url="https://api.faim.example.com") as client:
-    response = await client.forecast_async(ModelName.CHRONOS2, request)
+    request = Chronos2ForecastRequest(x=data, horizon=24, quantiles=[0.1, 0.9])
+    response = await client.forecast_async(request)
     print(response.quantiles)
 # Client automatically closed
 ```