HiDRA-assets / cache /ProTrek /utils /file_reader.py
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import os
import copy
import numpy as np
from utils.mpr import MultipleProcessRunnerSimplifier
# efficiently read large file by using a pointer
class FileReader:
@classmethod
# build a pointer for file
def build_pointer(cls, file_path, save_path):
with open(file_path, 'r') as r:
loc = r.tell()
line = r.readline()
# record the index of the beginning position for each line
cnt = 0
loc_array = []
while line:
loc_array.append(loc)
loc = r.tell()
line = r.readline()
cnt += 1
if cnt % 100000 == 0:
print(f"\rAlready loaded {cnt} rows", end='', flush=True)
loc_array = np.array(loc_array)
np.save(save_path, loc_array)
def __init__(self, file_path):
# If the pointer doesn't exist, build it
pointer_path = f"{file_path}.pointer.npy"
if not os.path.exists(pointer_path):
FileReader.build_pointer(file_path, pointer_path)
self.file = open(file_path, 'r')
# self.pointer = []
# with open(pointer_path, 'r') as r:
# for line in r:
# self.pointer.append(int(line))
self.pointer = np.load(pointer_path)
# return specific line given index
def get(self, index):
loc = self.pointer[index]
self.file.seek(loc)
return self.file.readline()[:-1]
def __len__(self):
return len(self.pointer)
def get_file_readers(file_path: str, n_readers: int) -> list:
"""
This function is used to read large file by using multiple readers
Args:
file_path: path to file
n_readers: number of readers
Returns: a list of file readers
"""
reader = FileReader(file_path)
reader.file.close()
reader_list = []
for i in range(n_readers):
tmp = copy.copy(reader)
tmp.file = open(file_path, "r")
reader_list.append(tmp)
return reader_list