Upgrade to 0.7.3 (#402)

* Update table joins to conditional join * Update real-time risk on Bitnami kafka repo url, quantlib calendar for USA and Atoti's mapping to condition * Update customer 360 use case from Atoti mapping to condition * Update SA-CCR to switch join mapping to conditions * Update XVA to switch join mapping to conditions * Update join mapping to condition for CCF * Fixed tsfresh and protobuf conflict issue for collateral shortfall forecast notebook. Update mapping to condition * Update mapping to condition for collateral shortfall monitoring * Update mapping to condition for intraday liquidity * Update mappings to condition for airline industry use case * Update mappings to conditions for baseball notebook * Update mapping to conditions for ca-solar * Update mapping to conditions for digital marketing * remove mapping for drug efficacy * Update mapping to conditions for food processing notebook * Update mapping to conditions for F1 * update mapping to condition for election nb * Update mapping to condition for global covid nb * Update object detection to download data and model, mapping to conditions. * Update mappings to conditions for pokemon nb * Update mapping to conditions for pricing simulation nb * Update mapping from mapping to conditions for sales-commission nb * Update mapping to conditions for twitter nb * Update mapping to condition for conditional-function nb * Update mapping to conditions for curr-cov-weighted-avg nb * Update mapping to condition for curr-coversion nb * Update mappings to conditions for introductory-tutorial nb * Update mappings to conditions for rollup-hierarchies nb * Reorg pandas chart * Update `user.roles` to user_service_client.individual_roles instead * Formatting and update cell metadata for notebooks * Upgrade Atoti CE to v0.7.3 * Workaround for atoti/atoti#758 * Format notebook
atoti · Feb 24, 2023 · bb7840b · bb7840b
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diff --git a/notebooks/01-use-cases/finance/front-office/pnl-explained/main.ipynb b/notebooks/01-use-cases/finance/front-office/pnl-explained/main.ipynb
diff --git a/notebooks/01-use-cases/finance/front-office/real-time-risk/docker-compose.yml b/notebooks/01-use-cases/finance/front-office/real-time-risk/docker-compose.yml
@@ -0,0 +1,29 @@
+version: "2"
+
+services:
+  zookeeper:
+    image: docker.io/bitnami/zookeeper:3.8
+    ports:
+      - "2181:2181"
+    volumes:
+      - "zookeeper_data:/bitnami"
+    environment:
+      - ALLOW_ANONYMOUS_LOGIN=yes
+  kafka:
+    image: docker.io/bitnami/kafka:3.4
+    ports:
+      - "9092:9092"
+    volumes:
+      - "kafka_data:/bitnami"
+    environment:
+      - KAFKA_CFG_ZOOKEEPER_CONNECT=zookeeper:2181
+      - ALLOW_PLAINTEXT_LISTENER=yes
+      - KAFKA_CFG_ADVERTISED_LISTENERS=PLAINTEXT://127.0.0.1:9092
+    depends_on:
+      - zookeeper
+
+volumes:
+  zookeeper_data:
+    driver: local
+  kafka_data:
+    driver: local
diff --git a/notebooks/01-use-cases/finance/front-office/real-time-risk/img/docker-config.png b/notebooks/01-use-cases/finance/front-office/real-time-risk/img/docker-config.png
diff --git a/notebooks/01-use-cases/finance/front-office/real-time-risk/main.ipynb b/notebooks/01-use-cases/finance/front-office/real-time-risk/main.ipynb
diff --git a/notebooks/01-use-cases/finance/front-office/real-time-risk/pricing_engine_emulator.py b/notebooks/01-use-cases/finance/front-office/real-time-risk/pricing_engine_emulator.py
@@ -12,7 +12,7 @@ def reprice_trade(spot_price, trade, calc_date):
 
     # conventions
     day_count = ql.Actual365Fixed()
-    calendar = ql.UnitedStates()
+    calendar = ql.UnitedStates(ql.UnitedStates.NYSE)
     volatility = 0.3
     dividend_rate = 0.0163
     risk_free_rate = 0.001

diff --git a/notebooks/01-use-cases/finance/insurance/customer360/02-main-vertica-db.ipynb b/notebooks/01-use-cases/finance/insurance/customer360/02-main-vertica-db.ipynb
@@ -2935,7 +2935,7 @@
    "id": "0b772b49",
    "metadata": {},
    "source": [
-    "We can explicitly define the mapping between the tables."
+    "We can explicitly define the join between the tables."
    ]
   },
   {
@@ -2945,7 +2945,11 @@
    "metadata": {},
    "outputs": [],
    "source": [
-    "policy_tbl.join(ncd_tbl, mapping={\"PLAN_TYPE\": \"PLAN\", \"POLICY_TYPE\": \"POLICY_TYPE\"})"
+    "policy_tbl.join(\n",
+    "    ncd_tbl,\n",
+    "    (policy_tbl[\"PLAN_TYPE\"] == ncd_tbl[\"PLAN\"])\n",
+    "    & (policy_tbl[\"POLICY_TYPE\"] == ncd_tbl[\"POLICY_TYPE\"]),\n",
+    ")"
    ]
   },
   {

diff --git a/notebooks/01-use-cases/finance/insurance/customer360/03-main-csv.ipynb b/notebooks/01-use-cases/finance/insurance/customer360/03-main-csv.ipynb
diff --git a/notebooks/01-use-cases/finance/insurance/price-elasticity/main.ipynb b/notebooks/01-use-cases/finance/insurance/price-elasticity/main.ipynb
@@ -698,7 +698,6 @@
     "recall = []\n",
     "\n",
     "for estimator in model_list:\n",
-    "\n",
     "    estimator.fit(X_train, Y_train.values.ravel())\n",
     "    result = estimator.predict(X_val)\n",
     "\n",

diff --git a/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/main.ipynb b/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/main.ipynb
@@ -314,7 +314,7 @@
     "### 1.3 Join tables\n",
     "\n",
     "We enrich the data from the _Portfolios Allocation_ table by joining to some reference table.  \n",
-    "atoti assume a join based on the common columns between the two table. Otherwise, we could explicitly perform the join by declaring the column mappings. Refer to [atoti documentation](https://docs.atoti.io/latest/index.html) for more examples on [join](https://docs.atoti.io/latest/getting_started/tutorial/tutorial.html#Join)."
+    "atoti assume a join based on the common columns between the two table. Otherwise, we could explicitly define the conditions for the join. Refer to [atoti documentation](https://docs.atoti.io/latest/index.html) for more examples on [join](https://docs.atoti.io/latest/getting_started/tutorial/tutorial.html#Join)."
    ]
   },
   {
@@ -2734,7 +2734,6 @@
    "source": [
     "@session.endpoint(\"getIteration/{portfolio}\", method=\"GET\")\n",
     "def get_iteration(request, user, session):\n",
-    "\n",
     "    portfolio = request.path_parameters[\"portfolio\"]\n",
     "\n",
     "    helper_util = helper.Helper(session)\n",
@@ -2771,7 +2770,6 @@
    "source": [
     "@session.endpoint(\"upload/portfolio\", method=\"POST\")\n",
     "def upload_portfolio(request, user, session):\n",
-    "\n",
     "    helper_util = helper.Helper(session)\n",
     "    data = request.body\n",
     "    portfolio = data[\"portfolio\"]\n",

diff --git a/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/helper.py b/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/helper.py
@@ -7,7 +7,6 @@ def __init__(self, session):
         self.cube = session.cubes["Portfolio optimization"]
 
     def query_and_optimize(self, selected_port, selected_method, selected_iteration):
-
         l, m = self.cube.levels, self.cube.measures
         portfolio_tbl = self.session.tables["Portfolios Allocation"]
 

diff --git a/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/optimizer.py b/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/optimizer.py
@@ -1,19 +1,18 @@
 # https://bjerring.github.io/equity/2019/11/04/Portfolio-Optimization-using-CVaR.html
-#%% packages
+# %% packages
 
 import pulp
 import pandas as pd
 import numpy as np
 from pandas_datareader import data
 
 
-#%% functions
+# %% functions
 
 
 def PortfolioRiskTarget(
     mu, scen, CVaR_target=1, lamb=1, max_weight=1, min_weight=None, cvar_alpha=0.05
 ):
-
     """This function finds the optimal enhanced index portfolio according to some benchmark. The portfolio corresponds to the tangency portfolio where risk is evaluated according to the CVaR of the tracking error. The model is formulated using fractional programming.
 
     Parameters
@@ -87,7 +86,6 @@ def PortfolioRiskTarget(
 
     ### Add minimum weight constraint, either zero or atleast minimum weight
     if min_weight is not None:
-
         for i in i_idx:
             model += x[i] >= min_weight * b_z[i]
             model += x[i] <= b_z[i]
@@ -104,7 +102,6 @@ def PortfolioRiskTarget(
 
     # Get positions
     if pulp.LpStatus[model.status] == "Optimal":
-
         # print variables
         var_model = dict()
         for variable in model.variables():
@@ -136,7 +133,6 @@ def PortfolioRiskTarget(
 def PortfolioLambda(
     mu, mu_b, scen, scen_b, max_weight=1, min_weight=None, cvar_alpha=0.05, ft_points=15
 ):
-
     # asset names
     assets = mu.index
 

diff --git a/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/pyPortfoliOpt.py b/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/pyPortfoliOpt.py
@@ -13,6 +13,7 @@
 import numpy as np
 from pypfopt import HRPOpt
 
+
 # https://github.com/robertmartin8/PyPortfolioOpt/blob/master/cookbook/3-Advanced-Mean-Variance-Optimisation.ipynb
 # https://github.com/robertmartin8/PyPortfolioOpt/blob/master/examples.py
 # Deviation Risk Parity objective from Kolm et al (2014)

diff --git a/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/tickers.py b/notebooks/01-use-cases/finance/portfolio-management/cvar-optimizer/utils/tickers.py
@@ -29,7 +29,6 @@ def download_tickers(symbols, duration):
 
 
 def get_historical_vector(data):
-
     df_close = data["Adj Close"].copy()
     # drop those stocks where there are nan values
     df_close.dropna(axis="columns", inplace=True)

diff --git a/notebooks/01-use-cases/finance/portfolio-management/optimize-with-constraints/main.ipynb b/notebooks/01-use-cases/finance/portfolio-management/optimize-with-constraints/main.ipynb
@@ -308,7 +308,7 @@
     "### 1.3 Join tables\n",
     "\n",
     "We enrich the data from the _Portfolios Allocation_ table by joining to some reference table.  \n",
-    "atoti assume a join based on the common columns between the two table. Otherwise, we could explicitly perform the join by declaring the column mappings. Refer to [atoti documentation](https://docs.atoti.io/latest/index.html) for more examples on [join](https://docs.atoti.io/latest/getting_started/tutorial/tutorial.html#Join)."
+    "atoti assume a join based on the common columns between the two table. Otherwise, we could explicitly define the conditions for the join. Refer to [atoti documentation](https://docs.atoti.io/latest/index.html) for more examples on [join](https://docs.atoti.io/latest/getting_started/tutorial/tutorial.html#Join)."
    ]
   },
   {

diff --git a/...use-cases/finance/portfolio-management/optimize-with-constraints/utils/optimizer_utils.py b/...use-cases/finance/portfolio-management/optimize-with-constraints/utils/optimizer_utils.py
@@ -58,7 +58,6 @@ def exec_optimization(
         ticker_lower,
         target_return=None,
     ):
-
         print("=====================================================")
         print(f"sector_mapper: {sector_mapper}")
         print(f"sector_upper: {sector_upper}")

diff --git a/.../01-use-cases/finance/portfolio-management/optimize-with-constraints/utils/query_utils.py b/.../01-use-cases/finance/portfolio-management/optimize-with-constraints/utils/query_utils.py
@@ -121,7 +121,6 @@ def load_limits(
         target_returns,
         # limit_type="Ticker",
     ):
-
         lb_ticker_max_weight = "Max ticker weight"
         lb_ticker_min_weight = "Min ticker weight"
         lb_sector_max_weight = "Max sector weight"

diff --git a/...01-use-cases/finance/portfolio-management/optimize-with-constraints/utils/widget_utils.py b/...01-use-cases/finance/portfolio-management/optimize-with-constraints/utils/widget_utils.py
@@ -8,7 +8,6 @@
 
 class Widgets:
     def __init__(self, query):
-
         self.optimizer = opt_utils.Optimizer()
         self.query = query
         portfolio = query.get_portfolio()
@@ -133,7 +132,6 @@ def get_final_weights(self, obj):
         return weights_lower, weights_upper  # , max_optional
 
     def load_basic_results(self, _portfolio, _iteration, _opt_mtd, weights_df):
-
         weights_df["Portfolio"] = _portfolio
         weights_df["Iteration"] = _iteration
         weights_df["Opt Method"] = _opt_mtd
@@ -386,7 +384,6 @@ def update_sector_total(self, weight_type, change):
             )
 
     def update_ticker_total(self, weight_type, change):
-
         difference = change["new"] - change["old"]
 
         if weight_type == "min":