Test your AI Agents with the all-new Agent to Agent Testing Platform.Learn More
How to use get_metric_data method in localstack
Best Python code snippet using localstack_python
yahoo_finance_scraper.py
Source:yahoo_finance_scraper.py 
...78 r = requests.get(f"https://finance.yahoo.com/quote/{symbol}/key-statistics?p={symbol}", headers=headers)79 soup = bs(r.content, "html.parser")80 soup_tracker[symbol] = soup81 for m in self.df.columns:82 self.df.loc[symbol, m] = self.get_metric_data(soup, m, statistics_page_element)83 except Exception:84 print(f"-- {symbol.upper()} was not found")85 # Since the data86 self.df = self.df.drop(symbol)87 # Ranges for each field88 profitability_range = detailed_metric_list[0:2]89 management_effectiveness_range = detailed_metric_list[2:4]90 income_statement_range = detailed_metric_list[4:12]91 balance_sheet_range = detailed_metric_list[12:18]92 cash_flow_statement_range = detailed_metric_list[18:20]93 stock_price_history_range = detailed_metric_list[20:25]94 share_statistics_range = detailed_metric_list[25:32]95 dividend_and_splits_range = detailed_metric_list[32:42]96 self.profitability = pd.DataFrame(index=self.ticker_list, columns=profitability_range)97 self.management_effectiveness = pd.DataFrame(index=self.ticker_list, columns=management_effectiveness_range)98 self.income_statement = pd.DataFrame(index=self.ticker_list, columns=income_statement_range)99 self.balance_sheet = pd.DataFrame(index=self.ticker_list, columns=balance_sheet_range)100 self.cash_flow_statement = pd.DataFrame(index=self.ticker_list, columns=cash_flow_statement_range)101 self.stock_price_history = pd.DataFrame(index=self.ticker_list, columns=stock_price_history_range)102 self.share_statistics = pd.DataFrame(index=self.ticker_list, columns=share_statistics_range)103 self.dividends_and_split = pd.DataFrame(index=self.ticker_list, columns=dividend_and_splits_range)104 self.statistics_table = pd.DataFrame(index=self.ticker_list, columns=table_metric_list)105 # Fill each dataframe106 # Financials Table107 for symbol in self.profitability.index:108 for m in table_metric_list:109 self.statistics_table.loc[symbol, m] = self.get_metric_data(soup_tracker[symbol], m, statistics_table_element)110 # Profitability section111 for symbol in self.profitability.index:112 for m in detailed_metric_list[0:2]:113 self.profitability.loc[symbol,m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)114 # Management Effectiveness section115 for symbol in self.management_effectiveness.index:116 for m in detailed_metric_list[2:4]:117 self.management_effectiveness.loc[symbol,m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)118 # Income Statement119 for symbol in self.income_statement.index:120 for m in detailed_metric_list[4:12]:121 self.income_statement.loc[symbol,m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)122 # Balance Sheet123 for symbol in self.balance_sheet.index:124 for m in detailed_metric_list[12:18]:125 self.balance_sheet.loc[symbol,m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)126 # Cash flow statement127 for symbol in self.cash_flow_statement.index:128 for m in detailed_metric_list[18:20]:129 self.cash_flow_statement.loc[symbol, m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)130 # Stock price history131 for symbol in self.stock_price_history.index:132 for m in detailed_metric_list[20:25]:133 self.stock_price_history[symbol,m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)134 # Share Statistics135 for symbol in self.share_statistics.index:136 for m in detailed_metric_list[25:32]:137 self.share_statistics.loc[symbol, m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)138 # Dividends & Splits139 for symbol in self.share_statistics.index:140 for m in detailed_metric_list[32:42]:141 self.dividends_and_split.loc[symbol, m] = self.get_metric_data(soup_tracker[symbol], m, statistics_page_element)142 '''143 Function: set_income_statement()144 Description: 145 Returns: DataFrame146 '''147 def set_income_statement(self):148 # All the metrics that will be collected149 table_metric_list = ["Total Revenue", "Cost of Revenue", "Gross Profit",150 "Operating Expense", "Operating Income", "Net Non Operating Interest Income Expense",151 "Other Income Expense","Pretax Income", "Tax Provision",152 "Net Income Common Stockholders", "Diluted NI Available to Com Stockholders", "Basic EPS",153 "Diluted EPS", "Basic Average Shares", "Diluted Average Shares",154 "Total Operating Income as Reported", "Total Expenses", "Net Income from Continuing & Discontinued Operation",155 "Normalized Income", "Interest Income", "Interest Expense",156 "Net Interest Income", "EBIT", "EBITDA",157 "Reconciled Cost of Revenue", "Reconciled Depreciation", "Net Income from Continuing Operation Net Minority Interest",158 "Normalized EBITDA"]159 # Class element for the table160 table_element = "Ta(c) Py(6px) Bxz(bb) BdB Bdc($seperatorColor) Miw(120px) Miw(100px)--pnclg Bgc($lv1BgColor) fi-row:h_Bgc($hoverBgColor) D(tbc)"161 # Assigning the dataframe162 self.income_statement_dataframe = pd.DataFrame(index=self.ticker_list, columns=table_metric_list)163 for symbol in self.income_statement_dataframe.index:164 try:165 r = requests.get(f"https://finance.yahoo.com/quote/{symbol}/financials?p={symbol}", headers=headers)166 soup = bs(r.content, "html.parser")167 for m in self.income_statement_dataframe.columns:168 self.income_statement_dataframe.loc[symbol, m] = self.get_metric_data(soup, m, table_element)169 except Exception:170 print(f"-- {symbol.upper()} was not found")171 # Since the data172 self.income_statement_dataframe = self.income_statement_dataframe.drop(symbol)173 '''174 Function: set_balance_sheet()175 Description: Scrapes the balance sheet and stores the values in a dataframe.176 Returns: None177 '''178 def set_balance_sheet(self):179 balance_sheet_metrics = ["Total Assets", "Total Liabilities Net Minority Interest", "Total Equity Gross Minority Interest",180 "Total Capitalization", "Common Stock Equity", "Net Tangible Assets",181 "Working Capital", "Invested Capital", "Tangible Book Value",182 "Total Debt", "Net Debt", "Share Issued", "Ordinary Shares Number"]183 # Class element for the table184 table_element = "Ta(c) Py(6px) Bxz(bb) BdB Bdc($seperatorColor) Miw(120px) Miw(100px)--pnclg D(tbc)"185 # Assigning the dataframe186 self.balance_sheet_dataframe= pd.DataFrame(index=self.ticker_list, columns=balance_sheet_metrics)187 for symbol in self.balance_sheet_dataframe.index:188 try:189 r = requests.get(f"https://finance.yahoo.com/quote/{symbol}/balance-sheet?p={symbol}", headers=headers)190 soup = bs(r.content, "html.parser")191 for m in self.balance_sheet_dataframe.columns:192 self.balance_sheet_dataframe.loc[symbol, m] = self.get_metric_data(soup, m, table_element)193 except Exception:194 print(f"-- {symbol.upper()} was not found")195 # Since the data196 self.balance_sheet_dataframe = self.balance_sheet_dataframe.drop(symbol)197 '''198 Function: set_cash_flow_statement()199 Description: Scrapes the cash flow statement from yahoo.200 Returns: None201 '''202 def set_cash_flow_statement(self):203 cash_flow_metrics = ["Operating Cash Flow", "Investing Cash Flow", "Financing Cash Flow",204 "End Cash Position", "Income Tax Paid Supplemental Data", "Interest Paid Supplemental Data",205 "Capital Expenditure", "Issuance of Capital Stock", "Issuance of Debt",206 "Repayment of Debt", "Repurchase of Capital Stock", "Free Cash Flow"]207 # Class element for the table208 table_element = "Ta(c) Py(6px) Bxz(bb) BdB Bdc($seperatorColor) Miw(120px) Miw(100px)--pnclg D(tbc)"209 # Assigning the dataframe210 self.cash_flow_dataframe = pd.DataFrame(index=self.ticker_list, columns=cash_flow_metrics)211 212 # Fill the dataframe213 for symbol in self.cash_flow_dataframe.index:214 try:215 r = requests.get(f"https://finance.yahoo.com/quote/{symbol}/balance-sheet?p={symbol}", headers=headers)216 soup = bs(r.content, "html.parser")217 for m in self.cash_flow_dataframe.columns:218 self.cash_flow_dataframe.loc[symbol, m] = self.get_metric_data(soup, m, table_element)219 except Exception:220 print(f"-- {symbol.upper()} was not found")221 # Since the data222 self.cash_flow_dataframe = self.cash_flow_dataframe.drop(symbol)223 '''224 Function: set_price_data()225 Description:226 Returns: 227 '''228 def set_price_data(self):229 230 # Assigning the dataframe231 # self.price_dataframe = pd.DataFrame(index=self.ticker_list)232 dud = self.subtract_dates(4)233 print(f"DUD: {dud}")234 # Fill the dataframe235 for symbol in self.ticker_list:236 r = f"https://query1.finance.yahoo.com/v7/finance/download/{symbol}?period1={self.subtract_dates(5)}&period2={dt.datetime.now().timestamp()}&interval=1d&events=history&includeAdjustedClose=true"237 df = pd.read_csv(r)238 print(f"DF: {df}")239 240 241 '''242 Function: subtract_dates(int)243 Description: Subtracts a specified amount of years by the current date244 Returns: str245 '''246 def subtract_dates(self, years_to_subtract: int):247 new_time = dt.datetime.now() - relativedelta(years=years_to_subtract)248 print(f"New: {int(new_time.timestamp())}")249 return int(new_time.timestamp())250 '''251 Function:252 Description:253 Returns: 254 '''255 '''256 Function:257 Description:258 Returns: 259 '''260 '''261 Function: get_metric_data(BeautifulSoup, str)262 Description: Gets the data for the specific metric passed.263 Returns: Any264 '''265 @staticmethod266 def get_metric_data(soup, metric: str, class_of_element: str):267 data = soup.find(text=metric).find_next(class_=class_of_element).text268 return data269def main():270 ticker = "AAPL"271 yf = YahooFinanceScraper(ticker)272 yf.set_price_data()...
draw_plot.py
Source:draw_plot.py
...158 previous = result[len(result) - 1]159 if metric[2] > previous[2]:160 result.append(metric)161 return result162def get_metric_data(data_dir, baseline_file, name):163 result_files = []164 files = os.listdir(data_dir)165 for file in files:166 if not os.path.isdir(file):167 result_files.append(os.path.join(data_dir, file))168 metric_datas = []169 for result_file in result_files:170 recall, qps = calc_recall(result_file, baseline_file)171 metric_datas.append(("useless", name, recall, qps))172 metric_datas = remove_useless_point(metric_datas)173 print(name, metric_datas)174 return metric_datas175def draw_ip_recipe(image_name):176 linestyle = create_linestyles([ivf_name, hnsw_name,177 nra_ivf_name, nra_hnsw_name,178 nra_ivf_omp_name, nra_hnsw_omp_name])179 baseline_file = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/baseline.txt"180 ivf_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/ivf"181 hnsw_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/hnsw"182 nra_ivf_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/nra-ivf"183 nra_hnsw_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/nra-hnsw"184 nra_ivf_omp_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/nra-ivf2"185 nra_hnsw_omp_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-recipe/nra-hnsw2"186 ivf_data = get_metric_data(ivf_dir, baseline_file, ivf_name)187 hnsw_data = get_metric_data(hnsw_dir, baseline_file, hnsw_name)188 nra_ivf_data = get_metric_data(nra_ivf_dir, baseline_file, nra_ivf_name)189 nra_hnsw_data = get_metric_data(nra_hnsw_dir, baseline_file, nra_hnsw_name)190 nra_omp_ivf_data = get_metric_data(nra_ivf_omp_dir, baseline_file, nra_ivf_omp_name)191 nra_omp_hnsw_data = get_metric_data(nra_hnsw_omp_dir, baseline_file, nra_hnsw_name)192 data = {ivf_name: ivf_data, hnsw_name: hnsw_data,193 nra_ivf_name: nra_ivf_data, nra_hnsw_name: nra_hnsw_data,194 nra_ivf_omp_name: nra_omp_ivf_data,195 nra_hnsw_omp_name: nra_omp_hnsw_data}196 create_plot(all_data=data, raw=False, x_log=False, y_log=True,197 xn='k-nn', yn='qps', fn_out=image_name,198 linestyles=linestyle, batch=False)199def draw_ip_glove(image_name):200 linestyle = create_linestyles([ivf_name, hnsw_name,201 nra_ivf_name, nra_hnsw_name,202 nra_ivf_omp_name, nra_hnsw_omp_name])203 baseline_file = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/baseline.txt"204 ivf_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/ivf"205 hnsw_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/hnsw"206 nra_ivf_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/nra-ivf1"207 nra_hnsw_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/nra-hnsw1"208 nra_ivf_omp_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/nra-ivf"209 nra_hnsw_omp_dir = "/home/abner/workspace/MultiVector/cmake-build-debug/test/ip-glove/nra-hnsw"210 ivf_data = get_metric_data(ivf_dir, baseline_file, ivf_name)211 hnsw_data = get_metric_data(hnsw_dir, baseline_file, hnsw_name)212 nra_ivf_data = get_metric_data(nra_ivf_dir, baseline_file, nra_ivf_name)213 nra_hnsw_data = get_metric_data(nra_hnsw_dir, baseline_file, nra_hnsw_name)214 nra_omp_ivf_data = get_metric_data(nra_ivf_omp_dir, baseline_file, nra_ivf_omp_name)215 nra_omp_hnsw_data = get_metric_data(nra_hnsw_omp_dir, baseline_file, nra_hnsw_name)216 data = {ivf_name: ivf_data, hnsw_name: hnsw_data,217 nra_ivf_name: nra_ivf_data, nra_hnsw_name: nra_hnsw_data,218 nra_ivf_omp_name: nra_omp_ivf_data,219 nra_hnsw_omp_name: nra_omp_hnsw_data}220 create_plot(all_data=data, raw=False, x_log=False, y_log=True,221 xn='k-nn', yn='qps', fn_out=image_name,222 linestyles=linestyle, batch=False)223def draw_l2(image_name):224 linestyle = create_linestyles([225 "NRA4096_4096 IVFFLAT", "NRA4096_4096 HNSW",226 "NRA8192_8192 IVFFLAT", "NRA8192_8192 HNSW",227 "NRA16384_16384 IVFFLAT", "NRA16384_16384 HNSW"228 ])229 # "NRA4096_4096 IVFFLAT-BATCH", "NRA4096_4096 HNSW-BATCH"])230 baseline_file = "/root/results/l2/baseline.txt"231 ivf_dir1 = "/root/results/l2/ivfflat/test1"232 hnsw_dir1 = "/root/results/l2/hnsw/test1"233 ivf_dir2 = "/root/results/l2/ivfflat/test2"234 hnsw_dir2 = "/root/results/l2/hnsw/test2"235 ivf_dir3 = "/root/results/l2/ivfflat/test3"236 hnsw_dir3 = "/root/results/l2/hnsw/test3"237 ivf_metric_data1 = get_metric_data(ivf_dir1 , baseline_file, "NRA8192_8192 IVFFLAT")238 hnsw_metric_data1 = get_metric_data(hnsw_dir1 , baseline_file, "NRA8192_8192 HNSW")239 ivf_metric_data2 = get_metric_data(ivf_dir2 , baseline_file, "NRA4096_4096 IVFFLAT")240 hnsw_metric_data2 = get_metric_data(hnsw_dir2 , baseline_file, "NRA4096_4096 HNSW")241 ivf_metric_data3 = get_metric_data(ivf_dir3 , baseline_file, "NRA16384_16384 IVFFLAT")242 hnsw_metric_data3 = get_metric_data(hnsw_dir3 , baseline_file, "NRA16384_16384 HNSW")243 # data = {"L2 NRA IVF-Flat": ivf_metric_data, "L2 NRA HNSW": hnsw_metric_data}244 data = {245 "NRA8192_8192 IVFFLAT": ivf_metric_data1, "NRA8192_8192 HNSW": hnsw_metric_data1,246 "NRA4096_4096 IVFFLAT": ivf_metric_data2, "NRA4096_4096 HNSW": hnsw_metric_data2,247 "NRA16384_16384 IVFFLAT": ivf_metric_data3, "NRA16384_16384 HNSW": hnsw_metric_data3248 }249 create_plot(all_data=data, raw=False, x_log=False, y_log=True,250 xn='k-nn', yn='qps', fn_out=image_name,251 linestyles=linestyle, batch=False)252if __name__ == "__main__":253 ivf_name = "IVF-Flat"254 hnsw_name = "HNSW"255 nra_ivf_name = "NRA IVF-Flat"256 nra_hnsw_name = "NRA HNSW"...
server.py
Source:server.py
...13def set_zero_metrics():14 metrics = [OPEN_CONNECTIONS, REQUESTS_PER_SECOND, CONNECTIONS_PER_SECOND, BANDWIDTH_IN, BANDWIDTH_OUT]15 for metric in metrics:16 metric.set(0)17def get_metric_data(data_list):18 sum = 0.019 for data in data_list:20 try:21 sum = sum + float(data[1])22 except:23 pass24 return sum25def get_metrics():26 # Get start and end time 15 secs interval27 end = datetime.utcnow()28 start = end - timedelta(seconds=15)29 iso_end = end.strftime("%Y-%m-%dT%H%M%S")30 iso_start = start.strftime("%Y-%m-%dT%H%M%S")31 # Build request32 payload['start'] = iso_start33 payload['end'] = iso_end34 r = requests.get(url, headers=headers, params=payload)35 data = r.json().get('metrics').get('time_series')36 if not data:37 set_zero_metrics()38 # Set gauges39 OPEN_CONNECTIONS.set(get_metric_data(data.get('connections_per_second').get('values')))40 REQUESTS_PER_SECOND.set(get_metric_data(data.get('requests_per_second').get('values')))41 CONNECTIONS_PER_SECOND.set(get_metric_data(data.get('connections_per_second').get('values')))42 BANDWIDTH_IN.set(get_metric_data(data.get('bandwidth.in').get('values')))43 BANDWIDTH_OUT.set(get_metric_data(data.get('bandwidth.out').get('values')))44if __name__ == '__main__':45 start_http_server(9110)46 while True:47 time.sleep(5)...
Automation Testing Tutorials
Learn to execute automation testing from scratch with LambdaTest Learning Hub. Right from setting up the prerequisites to run your first automation test, to following best practices and diving deeper into advanced test scenarios. LambdaTest Learning Hubs compile a list of step-by-step guides to help you be proficient with different test automation frameworks i.e. Selenium, Cypress, TestNG etc.
LambdaTest Learning Hubs:
- JUnit Tutorial
- TestNG Tutorial
- Webdriver Tutorial
- WebDriverIO Tutorial
- Protractor Tutorial
- Selenium 4 Tutorial
- Jenkins Tutorial
- NUnit Tutorial
- Jest Tutorial
- Playwright Tutorial
- Cypress Tutorial
- PyTest Tutorial
YouTube
You could also refer to video tutorials over LambdaTest YouTube channel to get step by step demonstration from industry experts.
Run localstack automation tests on LambdaTest cloud grid
Perform automation testing on 3000+ real desktop and mobile devices online.
Try LambdaTest Now !!
Get 100 minutes of automation test minutes FREE!!
Was this article helpful?
