使用Python或Python / Pandas將具有.fmt文件的固定寬度的.dat文件以編程方式轉換為.csv文件

Question

我正在嘗試學習Python，但是我被困在這里，不勝感激。

我有2個檔案。

1是沒有固定寬度包含多行數據的列標題的.dat文件1是是包含列標題，列長和數據類型的.fmt文件

.dat示例：

10IFKDHGHS34
12IFKDHGHH35
53IFHDHGDF33

.fmt示例：

ID,2,n
NAME,8,c
CODE,2,n

所需的輸出為.csv：

ID,NAME,CODE
10,IFKDHGHS,34
12,IFKDHGHH,35
53,IFHDHGDF,33

Answer 1

首先，我將分析格式文件。

with open("format_file.fmt") as f:
    # csv.reader parses away the commas for us 
    # and we get rows as nice lists
    reader = csv.reader(f) 
    # this will give us a list of lists that looks like
    # [["ID", "2", "n"], ...]
    row_definitions = list(reader)

# iterate and just unpack the headers
# this gives us ["ID", "NAME", "CODE"]
header = [name for name, length, dtype in row_definitions]
# [2, 8, 2]
lengths = [int(length) for name, length, dtype in row_definitions]

# define a generator (possibly as a closure) that simply slices 
# into the string bit by bit -- this yields, for example, first 
# characters 0 - 2, then characters 2 - 10, then 8 - 12
def parse_line(line):
    start = 0
    for length in lengths:
        yield line[start: start+length]
        start = start + length

with open(data_file) as f:
     # iterating over a file pointer gives us each line separately
     # we call list on each use of parse_line to force the generator to a list
     parsed_lines = [list(parse_line(line)) for line in data_file]

# prepend the header
table = [header] + parsed_lines

# use the csv module again to easily output to csv
with open("my_output_file.csv", 'w') as f:
    writer = csv.writer(f)
    writer.writerows(table)