Panda python textfile processing into xlsx

If the suggestion in my comment is fine, then this is your solution.

If it is not, please point out how you would prefer it and I will try to help you do that.

Either way, this can get you on the right path for a vectorized solution.

def extract(gits):
    # get repo names in a colum
    gits = gits.assign(repoName= gits[0][gits[0].str.startswith("<Location /git")])

    # use ffill to match the reponame to the following rows of information
    gits["repoName"] = gits.repoName.str.split("<Location /git").str[-1].str[1:-1].ffill()
    
    # keep only rows with the group information
    gits = gits[gits[0].str.startswith("Require group")].copy()

    # set root repo to "/"
    gits.loc[gits.repoName.eq(""), "repoName"] = "/"
    
    # keep only the group name
    gits["groupName"] = gits[0].str.split(" ").str[-1]

    return gits[["groupName", "repoName"]].reset_index(drop= True)

In order for this function to work, you need a dataframe that has a row for every row in the text file, and only one column with name 0, which contains all the rows of the text file.

I saved your sample text in a file called "gits.txt". I assumed that there are no commas, which is why pd.read_csv works. You might have to use a different way to read it into the dataframe-format that I described.

From the console:

# pandas should not consider the first row a header
gits = pd.read_csv("gits.txt", header= None)

gits
>>>
         0
0                                            <Location /git>
1                                             AuthType Basic
2    AuthName "Please enter your CVC username and password."
3   AuthBasicProvider LOCAL_authfile LDAP_CVCLAB LDAP_CVC007
4                         AuthGroupFile /data/conf/git_group
5                                        #Require valid-user
6                                       Require group admins
7                                      Require group m4rtcdd
8                                                </Location>
9                                                     # TEST
10                                                   # SPACE
11                               <Location /git/industry2go>
12                                            AuthType Basic
13   AuthName "Please enter your CVC username and password."
14  AuthBasicProvider LOCAL_authfile LDAP_CVCLAB LDAP_CVC007
15                        AuthGroupFile /data/conf/git_group
16                                       #Require valid-user
17                                      Require group admins
18                            Require group space_mobile_app
19                                               </Location>
20                             <Location /git/sales2go-core>
21                                            AuthType Basic
22   AuthName "Please enter your CVC username and password."
23  AuthBasicProvider LOCAL_authfile LDAP_CVCLAB LDAP_CVC007
24                        AuthGroupFile /data/conf/git_group
25                                       #Require valid-user
26                                      Require group admins
27                            Require group space_mobile_app
28                                               </Location>

done = extract(gits)
done
>>> 
          groupName       repoName
0            admins              /
1           m4rtcdd              /
2            admins    industry2go
3  space_mobile_app    industry2go
4            admins  sales2go-core
5  space_mobile_app  sales2go-core

The output is just a dataframe, save it however you like.

The following code might give you what you need. I use regex to find all markup <Location></Location> tags, manipulate each line in each markup tag then save them to a dataframe.

Edit: I added a condition statement to filter group name admins to appear only once.

import re
import pandas as pd

with open("data.txt") as f:
    data = f.read()

locations = re.findall(r"<Location \S+>[\s\S]*?(?:\n.*?<\/Location>)", data, flags=re.MULTILINE)
df = pd.DataFrame(columns=["groupName", "repoName"])

for location in locations:
    lines = [line.strip() for line in location.split("\n") if line.startswith("<Location") or line.strip().startswith("Require group")]

    repo_name = lines[0].split(" ")[-1][:-1] # get repository name
    repo_name = "/" if repo_name == "/git" else repo_name.replace("/git/", "")
    
    for line in lines[1:]: # start with 2nd lines to get each group name
        if line.startswith("Require group"):
            group_name = line.split(" ")[-1]
            if repo_name != "/" and group_name == "admins":
                continue
            df = df.append({"groupName": group_name, "repoName": repo_name}, ignore_index=True)

Output:

Reference

• Demo of regex at regex101