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Created May 23, 2023 17:23
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ChatGPT-inspired classes representing business metric formulas
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metric_ontology_classes_by_chatgpt.ipynb
{
"cells": [
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Hacky metrics classes based on ChatGPT output\n",
"\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"Sampling of prompts given to ChatGPT:\n",
"\n",
"```\n",
" given the following formulas for common financial metrics:\n",
"\n",
" operating profit = revenue - operating expenses\n",
" operating margin = operating profit / revenue\n",
" net profit = operating profit - interest - taxes\n",
" free cash flow = net profit + non-cash expenses - increase in working capital - capital expenditures\n",
"\n",
" Write python classes to represent each metric as a \"node\" in a DAG.\n",
" \n",
" for the metrics that are calculated from other metrics, write classes to represent those mathematical operations via an abstract syntax tree (AST).\n",
"\n",
" Ensure the code can handle metrics calculated from more than two parent metrics. also be sure to convert the names of metrics to lower-case when storing them as instance variables.\n",
"\n",
" Also satisfy the following requirements:\n",
" (a) given a set of available metrics, such as {\"operating expenses\", \"revenue\"} or {\"operating expenses\", \"revenue\", \"interest\", \"taxes\"} which downstream metrics can be calculated directly from those available metrics?\n",
" (b) given a set of desired metrics, such as {\"operating margin\", \"free cash flow\"}, which upstream metrics are required to calculate the requested metrics?\n",
"\n",
" the code should have the following behavior.\n",
"\n",
" if i run this code block:\n",
"\n",
" ```python\n",
" requested_metrics = {\"operating margin\", \"free cash flow\"}\n",
" upstream_metrics = graph.calculate_upstream_metrics(requested_metrics)\n",
" print(upstream_metrics)\n",
" ```\n",
"\n",
" I should get this output:\n",
"\n",
" ```\n",
" ['revenue', 'operating expenses', 'interest', 'taxes', 'non cash expenses', 'increase in working_capital', 'capital expenditures']\n",
" ```\n",
"\n",
" if i run this code block: \n",
"\n",
" ```python\n",
" available_metrics = {\"operating expenses\", \"revenue\", \"interest\", \"taxes\"}\n",
" downstream_metrics = graph.calculate_downstream_metrics(available_metrics)\n",
" print(downstream_metrics)\n",
" ```\n",
"\n",
" i should get this output:\n",
"\n",
" ```\n",
" ['operating profit', 'operating margin', 'net profit']\n",
"```"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"ChatGPT output did not produce the desired output, but after a bunch of hacky changes, the following code appears to produce the expected output.\n",
"\n",
"However it will likely fail any battery of comprehensive unit tests."
]
},
{
"cell_type": "code",
"execution_count": 87,
"metadata": {},
"outputs": [],
"source": [
"import inspect\n",
"\n",
"class BaseMetric:\n",
" \"\"\"\n",
" Metrics not derived from upstream metrics. This is sort of arbitrary as any metric\n",
" can be further broken down into smaller conponents.\n",
" \"\"\"\n",
"\n",
" def __init__(self, name):\n",
" self.name = name.lower()\n",
" self.root_parents = [] # upstream root metrics used to calculate this metric\n",
" self.parents = [] # upstream derived metrics used to calculate this metric\n",
" self.children = [] # downstream metrics calculated from this metric\n",
" self.value = None # a concrete value for this metric\n",
"\n",
" def add_parent(self, parent):\n",
" self.parents.append(parent)\n",
" parent.children.append(self)\n",
"\n",
" def remove_parent(self, parent):\n",
" self.parents.remove(parent)\n",
" parent.children.remove(self)\n",
"\n",
" def add_child(self, child):\n",
" self.children.append(child)\n",
" child.parent.append(self)\n",
" \n",
" def remove_child(self, child):\n",
" self.children.remove(child)\n",
" child.parent.remove(self)\n",
"\n",
" def calculate(self):\n",
" return self.value\n",
"\n",
" def get_downstream_metrics(self, downstream_metrics):\n",
" downstream_metrics.add(self)\n",
" for child in self.children:\n",
" child.get_downstream_metrics(downstream_metrics)\n",
"\n",
" def get_upstream_metrics(self, upstream_metrics):\n",
" if not self.parents:\n",
" upstream_metrics.add(self)\n",
" for parent in self.parents:\n",
" parent.get_upstream_metrics(upstream_metrics)\n",
"\n",
" def __repr__(self):\n",
" return self.name\n",
"\n",
" def get_formula(self):\n",
" return self.name\n",
"\n",
"class DerivedMetric(BaseMetric):\n",
" \"\"\"\n",
" Metrics calculated from upstream 'parent' metrics. The upstream metrics can be\n",
" derived metrics themselves or root/base metrics.\n",
" \"\"\"\n",
"\n",
" def __init__(self, name, operation, *parents):\n",
" super().__init__(name)\n",
" self.operation = operation\n",
"\n",
" # add operands to list of current metric's parents\n",
" self.parents = list(parents)\n",
"\n",
" # add current metric as child of each operand\n",
" for parent in self.parents:\n",
" parent.children.append(self)\n",
" \n",
" # add base or root metrics to list of current metric's root metrics\n",
" root_parent_set = set()\n",
" for parent in self.parents:\n",
" parent.get_upstream_metrics(root_parent_set)\n",
" \n",
" self.root_parents = list(root_parent_set)\n",
"\n",
" def calculate(self):\n",
" # if a derived metric's value is already available, just return it\n",
" if self.value:\n",
" return self.value\n",
" # otherwise calculate it from its upstream parent metrics\n",
" values = [parent.calculate() for parent in self.parents]\n",
" return self.operation(*values)\n",
"\n",
" def get_formula(self):\n",
" return inspect.getsource(self.operation).strip().rstrip(',')\n",
"\n",
"class MetricGraph:\n",
" \"\"\"\n",
" Represents the known universe of available metrics.\n",
" \"\"\"\n",
"\n",
" def __init__(self):\n",
" self.nodes = {}\n",
"\n",
" def add_metric(self, metric):\n",
" self.nodes[metric.name] = metric\n",
"\n",
" def calculate_metric(self, metric_name):\n",
" metric = self.nodes.get(metric_name.lower())\n",
" if metric:\n",
" return metric.calculate()\n",
" return None\n",
"\n",
" def list_extended_downstream_metrics(self, available_metrics, debug=False):\n",
"\n",
" available_metrics = set(metric.lower() for metric in set(available_metrics))\n",
" downstream_metrics = set()\n",
"\n",
" for metric_name in available_metrics:\n",
" metric = self.nodes.get(metric_name.lower())\n",
"\n",
" if metric:\n",
" metric.get_downstream_metrics(downstream_metrics)\n",
" \n",
" if debug:\n",
" print(\n",
" f'current metric: {metric.name}',\n",
" f'downstream metrics so far: {downstream_metrics}',\n",
" sep='\\n'\n",
" )\n",
"\n",
" # lists all downstream metrics calculated from the available metrics,\n",
" # possibly together with other metrics not listed as available \n",
" return [metric.name for metric in downstream_metrics\n",
" if metric.name not in available_metrics]\n",
"\n",
" def list_direct_downstream_metrics(self, available_metrics, debug=False):\n",
"\n",
" available_metrics = set(metric.lower() for metric in set(available_metrics))\n",
" downstream_metrics = self.list_extended_downstream_metrics(available_metrics)\n",
" direct_downstream_metrics = set()\n",
"\n",
" for metric_name in downstream_metrics:\n",
" metric = self.nodes.get(metric_name.lower())\n",
"\n",
" # directly downstream if it can be calculated from just the available metrics\n",
" if metric:\n",
" # check if its derived parents are subset of available metrics\n",
" derived_parent_names = set([parent_metric.name for parent_metric in metric.parents])\n",
" # check if its root parents are subset of available metrics\n",
" root_parent_names = set([parent_metric.name for parent_metric in metric.root_parents])\n",
"\n",
" if debug:\n",
" print(\n",
" f'current metric: {metric.name}',\n",
" f'derived parents: {derived_parent_names}',\n",
" f'root parents: {root_parent_names}',\n",
" f'available metrics: {available_metrics}',\n",
" sep='\\n'\n",
" )\n",
"\n",
" if derived_parent_names.issubset(available_metrics) or \\\n",
" root_parent_names.issubset(available_metrics):\n",
" direct_downstream_metrics.add(metric)\n",
"\n",
" return [metric.name for metric in direct_downstream_metrics]\n",
"\n",
" def list_upstream_metrics(self, requested_metrics):\n",
" \n",
" requested_metrics = set(metric.lower() for metric in set(requested_metrics))\n",
" upstream_metrics = set()\n",
"\n",
" for metric_name in requested_metrics:\n",
" metric = self.nodes.get(metric_name.lower())\n",
" if metric:\n",
" metric.get_upstream_metrics(upstream_metrics)\n",
"\n",
" return [metric.name for metric in upstream_metrics]\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Define metrics and known universe of available metrics"
]
},
{
"cell_type": "code",
"execution_count": null,
"metadata": {},
"outputs": [],
"source": [
"# define base or root metrics (arbitrary since these can be further decomposed)\n",
"revenue = BaseMetric(\"revenue\")\n",
"operating_expenses = BaseMetric(\"operating expenses\")\n",
"interest = BaseMetric(\"interest\")\n",
"taxes = BaseMetric(\"taxes\")\n",
"non_cash_expenses = BaseMetric(\"non cash expenses\")\n",
"increase_in_working_capital = BaseMetric(\"increase in working capital\")\n",
"capital_expenditures = BaseMetric(\"capital expenditures\")\n",
"\n",
"# define derived or calculated metrics: calculated from root metrics or upstream derived ones\n",
"operating_profit = DerivedMetric(\"operating profit\", \n",
" lambda rev, opex: rev - opex, \n",
" revenue, operating_expenses)\n",
"\n",
"operating_margin = DerivedMetric(\"operating margin\", \n",
" lambda op_profit, rev: op_profit / rev, \n",
" operating_profit, revenue)\n",
"net_profit = DerivedMetric(\"net profit\", \n",
" lambda op_profit, interest, taxes: op_profit - interest - taxes, \n",
" operating_profit, interest, taxes)\n",
"\n",
"operating_cash_flow = DerivedMetric(\"operating cash flow\", \n",
" lambda net_profit, noncash_exp, change_wc: net_profit + noncash_exp - change_wc,\n",
" net_profit, non_cash_expenses, increase_in_working_capital)\n",
"\n",
"free_cash_flow = DerivedMetric(\"free cash flow\", \n",
" lambda op_cash, capex: op_cash - capex, \n",
" operating_cash_flow, capital_expenditures)\n",
"\n",
"# metric graph represents universe of known metrics\n",
"graph = MetricGraph()\n",
"graph.add_metric(revenue)\n",
"graph.add_metric(operating_expenses)\n",
"graph.add_metric(interest)\n",
"graph.add_metric(taxes)\n",
"graph.add_metric(non_cash_expenses)\n",
"graph.add_metric(increase_in_working_capital)\n",
"graph.add_metric(capital_expenditures)\n",
"graph.add_metric(operating_profit)\n",
"graph.add_metric(operating_margin)\n",
"graph.add_metric(net_profit)\n",
"graph.add_metric(operating_cash_flow)\n",
"graph.add_metric(free_cash_flow)\n"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### List upstream metrics required to calculate given set of requested metrics"
]
},
{
"cell_type": "code",
"execution_count": 50,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"To calculate:\n",
"\t{'operating profit'}\n",
"... the following metrics are required:\n",
"\t['revenue', 'operating expenses']\n",
"\n",
"To calculate:\n",
"\t{'operating margin'}\n",
"... the following metrics are required:\n",
"\t['revenue', 'operating expenses']\n",
"\n",
"To calculate:\n",
"\t{'operating margin', 'net profit'}\n",
"... the following metrics are required:\n",
"\t['revenue', 'taxes', 'operating expenses', 'interest']\n",
"\n",
"To calculate:\n",
"\t{'operating cash flow'}\n",
"... the following metrics are required:\n",
"\t['non cash expenses', 'taxes', 'increase in working capital', 'revenue', 'operating expenses', 'interest']\n",
"\n",
"To calculate:\n",
"\t{'free cash flow', 'operating margin', 'net profit'}\n",
"... the following metrics are required:\n",
"\t['non cash expenses', 'taxes', 'increase in working capital', 'capital expenditures', 'revenue', 'operating expenses', 'interest']\n"
]
}
],
"source": [
"# Calculate upstream metrics required to calculate a set of metrics\n",
"print(\n",
" \"\\nTo calculate:\",\n",
" \"\\t\" + str(requested_metrics := {\n",
" \"operating profit\"\n",
" }),\n",
" \"... the following metrics are required:\",\n",
" f\"\\t{graph.list_upstream_metrics(requested_metrics)}\",\n",
"\n",
" \"\\nTo calculate:\",\n",
" \"\\t\" + str(requested_metrics := {\n",
" \"operating margin\"\n",
" }),\n",
" \"... the following metrics are required:\",\n",
" f\"\\t{graph.list_upstream_metrics(requested_metrics)}\",\n",
"\n",
" \"\\nTo calculate:\",\n",
" \"\\t\" + str(requested_metrics := {\n",
" \"operating margin\", \"net profit\"\n",
" }),\n",
" \"... the following metrics are required:\",\n",
" f\"\\t{graph.list_upstream_metrics(requested_metrics)}\",\n",
"\n",
" \"\\nTo calculate:\",\n",
" \"\\t\" + str(requested_metrics := {\n",
" \"operating cash flow\"\n",
" }),\n",
" \"... the following metrics are required:\",\n",
" f\"\\t{graph.list_upstream_metrics(requested_metrics)}\",\n",
"\n",
" \"\\nTo calculate:\",\n",
" \"\\t\" + str(requested_metrics := {\n",
" \"net profit\", \"operating margin\", \"free cash flow\"\n",
" }),\n",
" \"... the following metrics are required:\",\n",
" f\"\\t{graph.list_upstream_metrics(requested_metrics)}\",\n",
" \n",
" sep='\\n'\n",
")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### List metrics with formulas involving terms in a given set of metrics"
]
},
{
"cell_type": "code",
"execution_count": 94,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"The following metrics:\n",
"\t{'operating expenses'}\n",
"... are referenced in the formulas for these metrics:\n",
"\t['net profit', 'operating profit', 'operating cash flow', 'free cash flow', 'operating margin']\n",
"\n",
"The following metrics:\n",
"\t{'revenue', 'operating expenses'}\n",
"... are referenced in the formulas for these metrics:\n",
"\t['net profit', 'operating profit', 'operating cash flow', 'free cash flow', 'operating margin']\n",
"\n",
"The following metrics:\n",
"\t{'taxes'}\n",
"... are referenced in the formulas for these metrics:\n",
"\t['free cash flow', 'operating cash flow', 'net profit']\n",
"\n",
"The following metrics:\n",
"\t{'capital expenditures'}\n",
"... are referenced in the formulas for these metrics:\n",
"\t['free cash flow']\n",
"\n",
"The following metrics:\n",
"\t{'revenue', 'taxes', 'operating expenses', 'interest'}\n",
"... are referenced in the formulas for these metrics:\n",
"\t['net profit', 'operating profit', 'operating cash flow', 'free cash flow', 'operating margin']\n"
]
}
],
"source": [
"# get all downstream metrics that can be derived from a list of available metrics,\n",
"# including those requiring supplementary metrics not listed as available\n",
"\n",
"print(\n",
" \"\\nThe following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\"\n",
" }),\n",
" \"... are referenced in the formulas for these metrics:\",\n",
" f\"\\t{graph.list_extended_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nThe following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\"\n",
" }),\n",
" \"... are referenced in the formulas for these metrics:\",\n",
" f\"\\t{graph.list_extended_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nThe following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"taxes\"\n",
" }),\n",
" \"... are referenced in the formulas for these metrics:\",\n",
" f\"\\t{graph.list_extended_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nThe following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"capital expenditures\"\n",
" }),\n",
" \"... are referenced in the formulas for these metrics:\",\n",
" f\"\\t{graph.list_extended_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nThe following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\", \"interest\", \"taxes\"\n",
" }),\n",
" \"... are referenced in the formulas for these metrics:\",\n",
" f\"\\t{graph.list_extended_downstream_metrics(available_metrics)}\",\n",
"\n",
" sep='\\n'\n",
")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### List downstream metrics calculated from just the given set of metrics"
]
},
{
"cell_type": "code",
"execution_count": 96,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"\n",
"Given only the following metrics:\n",
"\t{'taxes'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t[]\n",
"\n",
"Given only the following metrics:\n",
"\t{'capital expenditures'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t[]\n",
"\n",
"Given only the following metrics:\n",
"\t{'operating expenses'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t[]\n",
"\n",
"Given only the following metrics:\n",
"\t{'revenue', 'operating expenses'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t['operating profit', 'operating margin']\n",
"\n",
"Given only the following metrics:\n",
"\t{'revenue', 'taxes', 'operating expenses', 'interest'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t['operating profit', 'operating margin', 'net profit']\n",
"\n",
"Given only the following metrics:\n",
"\t{'taxes', 'net profit', 'interest'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t[]\n",
"\n",
"Given only the following metrics:\n",
"\t{'increase in working capital', 'net profit', 'non cash expenses'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t['operating cash flow']\n",
"\n",
"Given only the following metrics:\n",
"\t{'increase in working capital', 'interest', 'taxes', 'operating expenses', 'non cash expenses', 'revenue'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t['operating margin', 'operating profit', 'operating cash flow', 'net profit']\n",
"\n",
"Given only the following metrics:\n",
"\t{'increase in working capital', 'interest', 'taxes', 'operating expenses', 'non cash expenses', 'revenue', 'capital expenditures'}\n",
"... we can directly calculate these downstream metrics:\n",
"\t['net profit', 'operating profit', 'free cash flow', 'operating cash flow', 'operating margin']\n"
]
}
],
"source": [
"# get the list of downstream metrics that can be calculated directly from a given\n",
"# set of input metrics, without requiring any other metrics\n",
"\n",
"print(\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"taxes\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"capital expenditures\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\", \"interest\", \"taxes\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"net profit\", \"interest\", \"taxes\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"net profit\", \"non cash expenses\", \"increase in working capital\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\", \"interest\", \"taxes\", \"non cash expenses\", \"increase in working capital\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" \"\\nGiven only the following metrics:\",\n",
" \"\\t\" + str(available_metrics := {\n",
" \"operating expenses\", \"revenue\", \"interest\", \"taxes\", \"non cash expenses\", \"increase in working capital\", \"capital expenditures\"\n",
" }),\n",
" \"... we can directly calculate these downstream metrics:\",\n",
" f\"\\t{graph.list_direct_downstream_metrics(available_metrics)}\",\n",
"\n",
" sep='\\n'\n",
")"
]
},
{
"attachments": {},
"cell_type": "markdown",
"metadata": {},
"source": [
"#### Calculations involving concrete values of metrics"
]
},
{
"cell_type": "code",
"execution_count": 93,
"metadata": {},
"outputs": [
{
"name": "stdout",
"output_type": "stream",
"text": [
"operating cash flow when values of upstream derived metrics are set:\n",
"operating cash flow = lambda net_profit, noncash_exp, change_wc: net_profit + noncash_exp - change_wc --> 78\n",
"operating cash flow when values of upstream root metrics are set:\n",
"operating cash flow = lambda net_profit, noncash_exp, change_wc: net_profit + noncash_exp - change_wc --> 54\n"
]
}
],
"source": [
"net_profit.value, non_cash_expenses.value, increase_in_working_capital.value = 90, 24, 36\n",
"\n",
"print(\n",
" 'operating cash flow when values of upstream derived metrics are set:',\n",
" operating_cash_flow.name + ' = ' + operating_cash_flow.get_formula() + ' --> ' + str(operating_cash_flow.calculate()),\n",
" sep='\\n'\n",
")\n",
"\n",
"revenue.value, operating_expenses.value, interest.value, taxes.value = 150, 40, 18, 26\n",
"net_profit.value, non_cash_expenses.value, increase_in_working_capital.value = None, 24, 36\n",
"\n",
"print(\n",
" 'operating cash flow when values of upstream root metrics are set:',\n",
" operating_cash_flow.name + ' = ' + operating_cash_flow.get_formula() + ' --> ' + str(operating_cash_flow.calculate()),\n",
" sep='\\n'\n",
")"
]
}
],
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}
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