For reference, let's see what the original JSON would look like, with pretty formatting:

>>> print(json.dumps(my_json, indent=4))
{
    "name": "ns1:timeSeriesResponseType",
    "declaredType": "org.cuahsi.waterml.TimeSeriesResponseType",
    "scope": "javax.xml.bind.JAXBElement$GlobalScope",
    "value": {
        "queryInfo": {
            "creationTime": 1349724919000,
            "queryURL": "http://waterservices.usgs.gov/nwis/iv/",
            "criteria": {
                "locationParam": "[ALL:103232434]",
                "variableParam": "[00060, 00065]"
            },
            "note": [
                {
                    "value": "[ALL:103232434]",
                    "title": "filter:sites"
                },
                {
                    "value": "[mode=LATEST, modifiedSince=null]",
                    "title": "filter:timeRange"
                },
                {
                    "value": "sdas01",
                    "title": "server"
                }
            ]
        }
    },
    "nil": false,
    "globalScope": true,
    "typeSubstituted": false
}

That lets us see the structure of the data more clearly.

In the specific case, first we want to look at the corresponding value under the 'value' key in our parsed data. That is another dict; we can access the value of its 'queryInfo' key in the same way, and similarly the 'creationTime' from there.

To get the desired value, we simply put those accesses one after another:

my_json['value']['queryInfo']['creationTime'] # 1349724919000

Just do:

products = jsonObject[list(jsonObject.keys())[1]]["products"]["items"]

Json.loads will also decode that dictionary. So to access cpu_count for example it would be json_data["Hosts"]["cpu_count"].

The json library will turn everything into a standard python data type (dict, list, int, str) or from those data type into a json readable format. You can also define a parser to parse from a class into json.

if the result is in a text format you need to convert it into a dict first:

result = json.loads(resp.text)

And after that you get from the dict the info you need:

with open("result.txt", "w") as f_o:
    for row in result["routes"]:
        f_o.write("distance:" + str(row["summary"]["distance"])) # depending on how do you want the result

It is deeply nested, txs is the outer key, the value for txs is a list which has a dict with the inputs whose values is also a list that contains a dict, inside that dict prev_out has a dict as a value that has the addr_tagkey:

print(obj1["txs"][0]["inputs"][0]["prev_out"]["addr_tag"])

There are actually 2 addr_tags in the json the second is under:

print(obj1["txs"][0]["out"][1]["addr_tag"])

Satoshi Dice Change Address

If the keys are not always there you can use dict.get:

inter = js["txs"][0]
k1 = next((d["prev_out"].get("addr_tag") for d in inter["inputs"] if "prev_out" in d), None)
k2 = next((d.get("addr_tag") for d in inter["out"] if "addr_tag" in d), None)

If any key is not in your json, the value will be None so you can just check with an if:

 if k1 is not None:
     .......
 if k2 is not None:
      ................

Looking at the link the data and format keeps changing from run to run, this function will recursively check all the dicts and pull any "addr_tag" values:

def rec_get(d, k):
    if isinstance(d, dict):
        if k in d:
            yield d[k]
        else:
            for v in d.values():
                yield from rec_get(v, k)
    elif isinstance(d, list):
        for v in d:
            yield from rec_get(v, k)


print(list(rec_get(js, "addr_tag")))

using the link json, you get which repeats some keys but you can call set(.. instead of list:

['Satoshi Dice Change Address', 'Satoshi Dice Change Address', 'SatoshiDICE 50%', 'Satoshi Dice Change Address']

If you want to iterate over both keys and values of the dictionary, do this:

for key, value in data.items():
    print(key, value)

because your x variable is dict key name

for x in parsed:
    print(parsed[x]['web'])