def load_api_result_csv(filename: str) -> DataFrame:
csv_path = datasource.get_file_path(filename + ".csv")
df = pd.read_csv(csv_path,
header=0,
names=[_ticketcount, _url, _duration],
usecols=[_ticketcount, _url, _duration])
log.debug("Loaded data")
log.debug(df)
return df
def run_bulk_queries(inputfile="input-raw-calls.csv",
outputfile="results-timed-api"):
csv_path = datasource.get_file_path(inputfile)
urls_to_call = pd.read_csv(csv_path,
header=0,
names=[_ticketcount, _url],
usecols=[_ticketcount, _url])
results = []
for index, row in urls_to_call.iterrows():
ms = time_api(row, index)
results.append(ms)
log.info(f"{len(results)} results gathered")
urls_to_call[_duration] = pd.Series(results)
log.debug(urls_to_call)
outputhelper.save_to_input_directory(urls_to_call, outputfile)
def foo():
csv_path = datasource.get_input_file_path()
df = pd.read_csv(csv_path, header=1, names=["x", "y"], usecols=["x", "y"])
# print(df)
# print(df.iloc[:, 0])
# print(df.iloc[:, 1])
df2 = pd.read_csv(datasource.get_file_path("additional.csv"),
header=1,
names=["a", "b", "c"],
usecols=["b", "c"])
second_run = import_additional_results("input2", "csv")
run_3 = import_additional_results_from_csv("input3")
print(run_3)
# print(df.join(df2))
# print(df.join(df2.iloc[:,0]))
# df['b'] = df2.b
df = df.join(second_run.input2)
df = df.join(run_3.input3)
fig = px.scatter(df, x=df.x, y=df.y)
# fig.show()
df_melt = df.melt(id_vars="x", value_vars=["y", "input2"])
print(df_melt)
# fig = px.scatter(df, x=df_melt.x, y=df_melt.value, color=df_melt.variable)
trace2 = go.Scatter(x=df.x, y=df.input2, mode="lines+markers")
fig.add_trace(trace2)
fig.show()
def import_additional_results(filename: str, extension: str) -> DataFrame:
full_filename = filename + "." + extension
csv_path = datasource.get_file_path(full_filename)
df = pd.read_csv(csv_path, header=0, names=["x", filename], usecols=[0, 1])
return df
def raw_api_call_second():
df = pd.read_csv(datasource.get_file_path("raw-calls.csv"))
df.duration = df.duration.apply(lambda x: probably_speed_up(x))
df.to_csv(datasource.get_file_path("raw-calls-2.csv"), index=False)