IO¶
This module offers some methods for data load/dump and file operations.
Data load/dump¶
cvbase
provides a universal api for loading and dumping data, currently
supported formats are json, yaml and pickle.
import cvbase as cvb
# load data from a file
data = cvb.load('test.json')
data = cvb.load('test.yaml')
data = cvb.load('test.pickle')
# load data from a file-like object
with open('test.json', 'r') as f:
data = cvb.load(f)
# dump data to a string
json_str = cvb.dump(data, format='json')
# dump data to a file with a filename (infer format from file extension)
cvb.dump(data, 'out.pickle')
# dump data to a file with a file-like object
with open('test.yaml', 'w') as f:
data = cvb.dump(data, f, format='yaml')
Load list from a text file¶
For example a.txt is a text file with 5 lines.
a
b
c
d
e
Then use list_from_file
to load the list from a.txt.
import cvbase as cvb
cvb.list_from_file('a.txt')
# output ['a', 'b', 'c', 'd', 'e']
cvb.list_from_file('a.txt', offset=2)
# output ['c', 'd', 'e']
cvb.list_from_file('a.txt', max_num=2)
# output ['a', 'b']
cvb.list_from_file('a.txt', prefix='/mnt/')
# output ['/mnt/a', '/mnt/b', '/mnt/c', '/mnt/d', '/mnt/e']
Load dict from a text file¶
For example a.txt is a text file with 5 lines.
1 cat
2 dog cow
3 panda
Then use dict_from_file
to load the list from a.txt.
import cvbase as cvb
cvb.dict_from_file('a.txt')
# output {'1': 'cat', '2': ['dog', 'cow'], '3': 'panda'}
cvb.dict_from_file('a.txt', key_type=int)
# output {1: 'cat', 2: ['dog', 'cow'], 3: 'panda'}
File/Directory operations¶
Use check_file_exist
to check if a file exists, if not, a FileNotFoundError
or IOError
will be thrown out.
Use mkdir_or_exist
to check if a directory exists, the directory will be created if not exists.
Use scandir
to scan a directory for all files or files will certain suffix.
import cvbase as cvb
# scan the folder "test" for all files
for filename in cvb.scandir('test'):
print(filename)
# scan the folder "test" for all jpg files
for filename in cvb.scandir('test', '.jpg'):
print(filename)