Develop Reference

How to add document for search in marqo

i recently started using the marqo library and i am trying to add document so that marqo can search and return the relevant part of the document but i keep getting error when i run the the code.
i used the
add_document()
method and i pass the document as a string for search but it returns an error. Here is what my code look like;
import marqo
DOCUMENT = 'the document'
mq = marqo.Client(url='http://localhost:8882')
mq.index("my-first-index").add_documents(DOCUMENT)
and when i run it i get a
MarqoWebError

you are getting the error because the add_document() method takes a list of python dictionaries as an argument not a string, so you are to pass the document as a value to any key you assign to it. But it is advisable to add a title and also an id for later referencing. Here is what i mean;
mq.index("my-first-index").add_documents([
{
"Title": the_title_of_your_document,
"Description": your_document,
"_id": your_id,
}]
)
the id can be any string of your choice. You can add as many dictionaries as you want to the list, each dictionary represents a document.

I think the documents need to be a list of dicts. See here https://marqo.pages.dev/API-Reference/documents/

using variable (f)-string stored in json

I have a json config file where I store my path to data there
The data is bucketed in month and days, so without the json I would use an f-string like:
spark.read.parquet(f"home/data/month={MONTH}/day={DAY}")
Now I want to extract that from json. However, I run into problems with the Month and day variable. I do not want to split the path in the json.
But writing it like this:
{
"path":"home/data/month={MONTH}/day={DAY}"
}
and loading with:
DAY="1"
MONTH="12"
conf_path=pandas.read_json("...")
path=conf_path["path"]
data=spark.read_parquet(f"{path}")
does not really work.
Could you hint me a solution to retrieving a path with variable elements and filling them after reading? How would you store the path or retrieve it without splitting the path? Thanks
------- EDIT: SOLUTION --------
Thanks to Deepak Tripathi answer below, the answer is to use string format.
with the code like this:
day="1"
month="12"
conf_path=pandas.read_json("...")
path=conf_path["path"]
data=spark.read_parquet(path.format(MONTH=month, DAY=day))

you should use string.format() instead of f-strings
Still if you want to use f-strings then you should use eval like this, its unsafe
DAY="1"
MONTH="12"
df = pd.DataFrame(
[{
"path":"home/data/month={MONTH}/day={DAY}"
},
{
"path":"home/data/month={MONTH}/day={DAY}"
}
]
)
a = df['path'][0]
print(eval(f"f'{a}'"))
#home/data/month=12/day=1

How to iterate through this nested json array with python

So I made an API call to JIRA to get the list of all the issues. It returns something like this:
{
issues: [
{
fields: {
description:
summary:
creator:
reporter:
priority:
}
}
]
and I'm trying to get to what's inside fields.
Here's what I have:
response = requests.get(url + '/search?jql=resolution%20=%20Unresolved%20order%20by%20priority%20DESC,updated%20DESC', auth=auth).json()
and then :
response['issues'] works. But I can't find a way to access fields and then the elements inside it. I thought about iterating through but not sure if there's a simpler solution.
My understanding is that response[issues] is a list and I know how to access each element of it response[issues][0] but how to access the object nested inside the list? (still researching on it -- might find an answer)

if you look at your json it's an array to a hash or list to dict. To get fields you'd just call the first array element and the key.
response[issues][0][fields]

MongoDB PyMongo Listing all keys in a document

I have a question about how to manipulate a document in PyMongo to have it list all of its current keys, and I'm not quite sure how to do it. For example, if I had a document that looked like this:
{
"_id" : ObjectID("...")
"name": ABCD,
"info": {
"description" : "XYZ",
"type" : "QPR"
}
}
and I had a variable "document" that had this current document as its value, how could I write code to print the three keys:
"_id"
"name"
"info"
I don't want it to list the values, simply the names. The motivation for this is that the user would type one of the names and my program would do additional things after that.

As mentioned in the documentation:
In PyMongo we use dictionaries to represent documents.
So you can get all keys using .keys():
print(document.keys())

Using Python we can do the following which is to fetch all the documents in a variable as mydoc
mydoc = collections.find()
for x in mydoc:
l=list(x.keys())
print(l)
Using this we can get all the keys as a list and then we can use them for further user's need

the document is a python dictionary so you can just print its keys
e.g.
document = db.collection_name.find_one()
for k in document:
print(k)

Altering JSON array using python

This is the way reading from a .json file on ubuntu terminal:
python -c "import json;print json.loads(open('json_file.json', 'r').read())['foo']['bar']"
What I'd like to do is altering the JSON file, adding new objects and arrays. So how to do this in python?
json_file.json:
{
"data1" :
[
{
"unit" : "Unit_1",
"value" : "20"
},
{
"unit" : "Unit_2",
"value" : "10"
}
]
}

First of all, create a new python file.
import json
data = json.loads(open('json_file.json', 'r').read())
The data is then just a bunch of nested dictionaries and lists.
You can modify it the same way you would modify any python dictionary and list; it shouldn't be hard to find a resource on this as it is one of the most basic python functionalities. You can find a complete reference at the official python documentation, and if you are familiar with arrays/lists and associative arrays/hashes in any language, this should be enough to get you going. If it's not, you can probably find a tutorial and if that doesn't help, if you are able to create a well-formed specific question then you could ask it here.
once you are done, you can put everything back into json:
print json.dumps(data)
For more information on how to customize the output, and about the json module overall, see the documentation.