我正在运行以下python 3代码:
import os
import csv
import glob
import numpy as np
import collections
Prices = collections.namedtuple('Prices', field_names=['time', 'open', 'high', 'low', 'close', 'volume'])
def read_csv(file_name, sep=',', filter_data=True, fix_open_price=False):
print("Reading", file_name)
with open(file_name, 'rt', encoding='utf-8') as fd:
reader = csv.reader(fd, delimiter=sep)
x = next(reader)
if '<OPEN>' not in x and sep == ',':
return read_csv(file_name, ';')
indices = [x.index(s) for s in ('<TIME>', '<OPEN>', '<HIGH>', '<LOW>', '<CLOSE>', '<VOL>')]
t, o, h, l, c, v = [], [], [], [], [], []
count_out = 0
count_filter = 0
count_fixed = 0
prev_vals = None
for row in reader:
vals = list(map(float, [row[idx] for idx in indices]))
if filter_data and all(map(lambda v: abs(v-vals[0]) < 1e-8, vals[:-1])):
count_filter += 1
continue
to, po, ph, pl, pc, pv = vals
# fix open price for current bar to match close price for the previous bar
if fix_open_price and prev_vals is not None:
ppo, pph, ppl, ppc, ppv = prev_vals
if abs(po - ppc) > 1e-8:
count_fixed += 1
po = ppc
pl = min(pl, po)
ph = max(ph, po)
count_out += 1
t.append(to)
o.append(po)
c.append(pc)
h.append(ph)
l.append(pl)
v.append(pv)
prev_vals = vals
print("Read done, got %d rows, %d filtered, %d open prices adjusted" % (count_filter + count_out, count_filter, count_fixed))
return Prices(time=np.array(t, dtype=np.int),
open=np.array(o, dtype=np.float32),
high=np.array(h, dtype=np.float32),
low=np.array(l, dtype=np.float32),
close=np.array(c, dtype=np.float32),
volume=np.array(v, dtype=np.float32))
def prices_to_relative(prices):
"""
Convert prices to relative in respect to open price
:param ochl: tuple with open, close, high, low
:return: tuple with open, rel_close, rel_high, rel_low
"""
assert isinstance(prices, Prices)
rh = (prices.high - prices.open) / prices.open
rl = (prices.low - prices.open) / prices.open
rc = (prices.close - prices.open) / prices.open
tm = prices.time
return Prices(time=tm, open=prices.open, high=rh, low=rl, close=rc, volume=prices.volume)
def load_relative(csv_file):
return prices_to_relative(read_csv(csv_file))
def price_files(dir_name):
result = []
for path in glob.glob(os.path.join(dir_name, "*.csv")):
result.append(path)
return result
def load_year_data(year, basedir='data'):
y = str(year)[-2:]
result = {}
for path in glob.glob(os.path.join(basedir, "*_%s*.csv" % y)):
result[path] = load_relative(path)
return result
load_relative(read_csv('/home/darfeder/Downloads/9781838826994_Code/Chapter10/data/YNDX_150101_151231.csv'))
我得到一个错误:
TypeError: expected str, bytes or os.PathLike object, not Prices
加载的csv文件如下所示:
错误出现在“价格相对”函数中
堆栈跟踪:
--------------------------------------------------------------------------- TypeError Traceback (most recent call last) in 87 88 ---> 89 load_relative(read_csv('/home/darfeder/Downloads/9781838826994_Code/Chapter10/data/YNDX_150101_151231.csv'))
in load_relative(csv_file) 69 70 def load_relative(csv_file): ---> 71 return prices_to_relative(read_csv(csv_file)) 72 73
in read_csv(file_name, sep, filter_data, fix_open_price) 11 def read_csv(file_name, sep=',', filter_data=True, fix_open_price=False): 12 print("Reading", file_name) ---> 13 with open(file_name, 'rt', encoding='utf-8') as fd: 14 reader = csv.reader(fd, delimiter=sep) 15 x = next(reader)
TypeError: expected str, bytes or os.PathLike object, not Prices
您的代码似乎很奇怪-当我希望只看到一个调用时,有几个调用
read_csv
,例如:大体上:
在load_relative中:
在read_csv中,递归调用?(我想这可能还可以,适合使用;作为CSV分隔符):
我认为问题是第一个:传递文件名而不是读取文件的结果,因此将其更改为:
此外,您还应打开csv文件而不指定“rt”,并根据文档示例https://docs.python.org/3/library/csv.html指定换行符='',因此更改:
致:
由于您没有提供示例数据,我没有办法对此进行测试-希望这些建议能够解决问题
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