Here we merge all API Refactor related branches

.github/workflows/test.yml

@@ -200,7 +200,7 @@ jobs:
         uses: actions/cache@v2
         with:
           path: ~/conda_pkgs_dir
-          key: conda-${{ runner.os }}-v1-${{ matrix.python }}-${{ hashFiles('build/conda/conda-3-9-env.yaml') }}
+          key: conda-${{ runner.os }}-v1-${{ matrix.python }}-${{ hashFiles('build/conda/conda-3-9-env-full.yaml') }}
 
       - name: Setup Miniconda
         uses: conda-incubator/setup-miniconda@v2
@@ -232,7 +232,7 @@ jobs:
         uses: actions/cache@v2
         with:
           path: ${{ steps.pip-cache.outputs.dir }}
-          key: ${{ runner.os }}-v1-3-9-pip-${{ hashFiles('requirements.txt') }}
+          key: ${{ runner.os }}-v1-3-9-pip-${{ hashFiles('requirements-full.txt') }}
           restore-keys: |
             ${{ runner.os }}-v1-pip-
 

openbb_terminal/alternative/covid/covid_view.py

@@ -20,6 +20,7 @@
 )
 from openbb_terminal.rich_config import console
 
+
 logger = logging.getLogger(__name__)
 
 

openbb_terminal/api.py

@@ -12,4 +12,5 @@
 from .portfolio import portfolio_api as portfolio
 from .reports import widget_helpers as widgets
 
+
 from .config_terminal import theme

openbb_terminal/common/behavioural_analysis/finbrain_model.py

@@ -12,20 +12,20 @@
 
 
 @log_start_end(log=logger)
-def get_sentiment(ticker: str) -> pd.DataFrame:
+def get_sentiment(symbol: str) -> pd.DataFrame:
     """Gets Sentiment analysis provided by FinBrain's API [Source: finbrain]
 
     Parameters
     ----------
-    ticker : str
-        Ticker to get the sentiment analysis from
+    symbol : str
+        Ticker symbol to get the sentiment analysis from
 
     Returns
     -------
     DataFrame()
         Empty if there was an issue with data retrieval
     """
-    result = requests.get(f"https://api.finbrain.tech/v0/sentiments/{ticker}")
+    result = requests.get(f"https://api.finbrain.tech/v0/sentiments/{symbol}")
     sentiment = pd.DataFrame()
     if result.status_code == 200:
         result_json = result.json()

openbb_terminal/common/behavioural_analysis/finbrain_view.py

@@ -34,7 +34,7 @@ def lambda_sentiment_coloring(val: float, last_val: float) -> str:
 
 @log_start_end(log=logger)
 def display_sentiment_analysis(
-    ticker: str,
+    symbol: str,
     raw: bool = False,
     export: str = "",
     external_axes: Optional[List[plt.Axes]] = None,
@@ -43,16 +43,16 @@ def display_sentiment_analysis(
 
     Parameters
     ----------
-    ticker : str
-        Ticker to get the sentiment analysis from
-    raw : False
+    symbol: str
+        Ticker symbol to get the sentiment analysis from
+    raw: False
         Display raw table data
-    export : str
+    export: str
         Format to export data
-    external_axes : Optional[List[plt.Axes]], optional
+    external_axes: Optional[List[plt.Axes]], optional
         External axes (1 axis is expected in the list), by default None
     """
-    sentiment = finbrain_model.get_sentiment(ticker)
+    sentiment = finbrain_model.get_sentiment(symbol)
     if sentiment.empty:
         console.print("No sentiment data found.\n")
         return
@@ -83,7 +83,7 @@ def display_sentiment_analysis(
         ax.set_ylabel("Sentiment")
         start_date = sentiment.index[-1].strftime("%Y/%m/%d")
         ax.set_title(
-            f"FinBrain's Sentiment Analysis for {ticker.upper()} since {start_date}"
+            f"FinBrain's Sentiment Analysis for {symbol.upper()} since {start_date}"
         )
         ax.set_ylim([-1.1, 1.1])
         senValues = np.array(pd.to_numeric(sentiment["Sentiment Analysis"].values))

openbb_terminal/common/behavioural_analysis/google_model.py

@@ -12,77 +12,77 @@
 
 
 @log_start_end(log=logger)
-def get_mentions(ticker: str) -> pd.DataFrame:
+def get_mentions(symbol: str) -> pd.DataFrame:
     """Get interest over time from google api [Source: google]
 
     Parameters
     ----------
-    ticker : str
-        Stock ticker
+    symbol: str
+        Stock ticker symbol
 
     Returns
     -------
     pd.DataFrame
         Dataframe of interest over time
     """
     pytrend = TrendReq()
-    pytrend.build_payload(kw_list=[ticker])
+    pytrend.build_payload(kw_list=[symbol])
     return pytrend.interest_over_time()
 
 
 @log_start_end(log=logger)
-def get_regions(ticker: str) -> pd.DataFrame:
+def get_regions(symbol: str) -> pd.DataFrame:
     """Get interest by region from google api [Source: google]
 
     Parameters
     ----------
-    ticker : str
-        Ticker to look at
+    symbol: str
+        Ticker symbol to look at
 
     Returns
     -------
     pd.DataFrame
         Dataframe of interest by region
     """
     pytrend = TrendReq()
-    pytrend.build_payload(kw_list=[ticker])
-    return pytrend.interest_by_region()
+    pytrend.build_payload(kw_list=[symbol])
+    return pytrend.interest_by_region().sort_values([symbol], ascending=False)
 
 
 @log_start_end(log=logger)
-def get_queries(ticker: str) -> pd.DataFrame:
+def get_queries(symbol: str) -> pd.DataFrame:
     """Get related queries from google api [Source: google]
 
     Parameters
     ----------
-    ticker : str
-        Stock ticker to compare
+    symbol: str
+        Stock ticker symbol to compare
 
     Returns
     -------
     pd.DataFrame
         Dataframe of related queries
     """
     pytrend = TrendReq()
-    pytrend.build_payload(kw_list=[ticker])
+    pytrend.build_payload(kw_list=[symbol])
     return pytrend.related_queries()
 
 
 @log_start_end(log=logger)
-def get_rise(ticker: str) -> pd.DataFrame:
+def get_rise(symbol: str) -> pd.DataFrame:
     """Get top rising related queries with this stock's query [Source: google]
 
     Parameters
     ----------
-    ticker : str
-        Stock ticker
+    symbol: str
+        Stock ticker symbol
 
     Returns
     -------
     pd.DataFrame
         Dataframe containing rising related queries
     """
     pytrend = TrendReq()
-    pytrend.build_payload(kw_list=[ticker])
+    pytrend.build_payload(kw_list=[symbol])
     df_related_queries = pytrend.related_queries()
-    return df_related_queries[ticker]["rising"]
+    return df_related_queries[symbol]["rising"]