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我正在對CSV文件進行一些計算。任何人都可以幫我解釋爲什麼方法1比方法2快3倍嗎?我想讓自己的代碼更加通用和可持續,所以我不想像方法1那樣進行硬編碼,但是一旦我切換到方法2,性能就大幅下降,我無法弄清楚原因。爲什麼我的字典訪問速度很慢?
方法1:
for row in itertools.islice(csv_f, 0, period):
voltage_rail1 = float(row[rail1_index])
voltage_rail1_q.append(voltage_rail1)
current_rail1 = float(row[current_index])
current_rail1_q.append(current_rail1)
power_rail1_q.append(voltage_rail1*current_rail1)
voltage_rail2 = float(row[rail2_index])
voltage_rail2_q.append(voltage_rail2)
current_rail2 = float(row[current_index])
current_rail2_q.append(current_rail2)
power_rail2_q.append(voltage_rail2*current_rail2)
方法2:
rails_d = OrderedDict()
rails_d['rail1'] = 0
rails_d['rail2'] = 1
for row in itertools.islice(csv_f, 0, period):
for rail in rails_d:
voltage_d[rail] = float(row[voltage_column_index_d[rail]])
voltage_dq[rail].append(voltage_d[rail])
current_d[rail] = float(row[current_column_index_d[rail]])
current_dq[rail].append(current_d[rail])
power_dq[rail].append(voltage_d[rail]*current_d[rail])
感謝您的建議。我已經實現了兩個,但性能看起來差不多。 rail_l = ['rail1','rail2'] for rail,itertools.product(rails_l,itertools.islice(csv_f,0,period))中的行: voltage_d [rail] = float(row [voltage_column_index_d [導軌] current_dq [rail] .append(current_d [導軌]) power_dq [rail]] power_dq [rail] .append(voltage_d [rail]) current_d [rail] = float(row [current_column_index_d [ ] .append(voltage_d [軌] * current_d [軌])' – Colin