Tree structure created by retrieving data from ElasticSearch using Flask App You need to create tree search API with Python (Flask) and Elasticsearch. Let’s assume that we have following tree stored in Elasticsearch:
● folder1
❍ folder2
■ folder3
● aBc.txt
● ABb.txt
● xyz.txt
■ folder4
● Folder10
❍ oaxbco.pdf
❍ ddAb.doc
❍ folder111
■ file.pdf
■ fileab.zip
■ somefile.doc
■ fo.txt
■ Kkk.zip
■ Folder19
● Dd.doc
● Oacb.pdf
● Folder32
❍ Kab.pdf
❍ ygabe.docx
❍ kabcd.xls
❍ folder5
■ folder6
●folder88
❍ test.doc
● fo.docs
● xaby.txt
● lkAB.docx
■ qqa.docx
Now when we search for term "ab" API should return following tree:
●folder1
❍ folder2
■ folder3
● aBc.txt
● ABb.txt
■ folder4
● Folder10
❍ ddAb.doc
❍ folder111
■ Folder19
● Folder32
❍ Kab.pdf
❍ ygabe.docx
❍ kabcd.xls
❍ folder5
■ folder6
● xaby.txt
● lkAB.docx
This is an example of Elastic mapping you should use to store files and dirs:
PUT documents
{
"mappings": {
"document": {
"properties": {
"DS_Name": {
"type": "text"
},
"DS_Type": {
"type": "keyword",
"index": "not_analyzed"
},
"DS_Parent": {
"type": "keyword",
"index": "not_analyzed"
}
}
}
}
}
Where DS_Name represent file/dir name, DS_Type represent a "file" or "dir" and DS_Parent is _id of parent dir where this file/dir is located (if DS_Parent is equal to null then it is root of the tree).
But you are not limited to this structure only rule is that you have parent field which represent _id of parent directory of current file/dir. If you want to put some analyzer, change structure, addadditional fields, ... you can do that.
API should contain one POST route called /search which expect following parameters:
{
"query": "ab"
}
There are two modes for the search: - One will only search for files (MODE=files) - Other will search both for files and folders (MODE=files_and_folders)
Which mode is active should be specified by providing environment variable MODE with one of following values:
● files
● files_and_folders
if you search for "fo" in the above tree and if the MODE is equal to files result should be:
● folder1
❍ folder2
■ folder4
● Folder10
❍ folder111
■ fo.txt
❍ folder5
■ folder6
● fo.docs
on the other hand if the MODE is equal to files_and_folders result should be:
● folder1
❍ folder2
■ folder3
■ folder4
● Folder10
❍ folder111
■ fo.txt
■ Folder19
● Folder32
❍ folder5
■ folder6
● folder88
● fo.docs
If following tree is result of search:
● folder1
❍ folder2
■ folder4
● a.txt
● b.txt
■ Folder19
■ c.txt
❍ folder5
■ d.docs
then API should return following JSON:
[
{
"_id": "1"
"DS_Name": "folder1",
"DS_Type": "dir",
"DS_Parent": "null",
"children": [
{
"_id": "2",
"DS_Name": "folder2",
"DS_Type": "dir",
"DS_Parent": "1",
"children": [
{
"_id": "4",
"DS_Name": "folder4",
"DS_Type": "dir",
"DS_Parent": "2",
"children": [
{
"_id": "6",
"DS_Name": "a.txt",
"DS_Type": "file",
"DS_Parent": "4",
"children": []
},
{
"_id": "7",
"DS_Name": "b.txt",
"DS_Type": "file",
"DS_Parent": "4",
"children": []
},
]
},
{
"_id": "5",
"DS_Name": "Folder19",
"DS_Type": "dir",
"DS_Parent": "2",
"children": []
},
{
"_id": "8",
"DS_Name": "c.txt",
"DS_Type": "file",
"DS_Parent": "2",
"children": []
}
]
},
{
"_id": "3",
"DS_Name": "folder5",
"DS_Type": "dir",
"DS_Parent": "1",
"children": [
{
"_id": "9",
"DS_Name": "d.docs",
"DS_Type": "file",
"DS_Parent": "3",
"children": []
}
]
}
]
}
]
You must provide docker-compose.yml file which will start two containers: ● One for Elasticsearch ● One for Flask API
so app will be tested by running:
docker-compose -f docker-compose.yml up -d --build
and then hitting API endpoint from the Postman tool. Keep in mind that your app will be run under some VM so you must expose proper ports (You can use docker-machine in order to test your app).
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