I have a large json-file (too large to fit in memory) with the following structure:
{
"commonVal": "foo",
"entries": [
{ "bar": "baz1" },
{ "bar": "baz2" },
...,
]
}
I would like to process this json file as…
The ijson module has a documented option allow_comments=True, but when I include it,
an error message is produced:
ValueError: Comments are not supported by the python backend
Below is a transcript using the file test.py:
import ijson
for o in…
I am trying to parse a large JSON file (16GB) using ijson but I always get the following error :
Exception has occurred: IncompleteJSONError
lexical error: invalid char in json text.
venue" : { "type" : NumberInt(0) }, …
I am having json file which around 600MB. The structure of the json file is,
[
{
"metadata":{
"batchSize":100,
"totalRecords":"1000",
"batchIndex":1
},
"notificationData":[
{
…
I am aware how IJSON is solving, the bulky JSON reading and processing challenges. However i am not able to find any article which specifies how to speed up this:
I have seen few things to achieve that
1. Use YAZL backend
2. Play with buff_size…
This is the code that I have been trying:
import ijson
import urllib.request
with urllib.request.urlopen(some_link) as read_file:
path_array = ijson.items(read_file, object_in_json)
but I get this error:
(b'lexical error: invalid char in…
I am using python 3.9 and trying :
with open(file, 'r') as fl:
val = ijson.items(fl, '.item', use_float=True)
for i in val:
print(i)
After some time print statement is not printing anything on jupyter console, but that…
I have to handle a big JSON file (approx. 47GB) and it seems as if I found the solution in ijson.
However, when I want to go through the objects I get the following error:
byggesag = (o for o in objects if o["h�ndelse"] == 'Byggesag')
…
I'm trying to read a big json file (>1,5Gb), using ijson package and deal with the results.
response = requests.get("https://api.scryfall.com/bulk-data/all-cards")
with urlopen(response.json()["download_uri"]) as all_cards:
for…
I have thousands of very large JSON files that I need to process on specific elements. To avoid memory overload I am using a python library called ijson which works fine when I am processing only a single element from the json file but when I try to…
I have come across an error while parsing json with ijson.
Background:
I have a series(approx - 1000) of large files of twitter data that are compressed in a '.bz2' format. I need to get elements from the file into a pd.DataFrame for further…
I have to read a large json file of size 3 Gb using python.There is a garbage value '][' between the data in the json files.For files with small volume,I used the below script to trim the garbage…
I'm using ijson.kvitems to iterate over all of the keys in a JSON file that I have.
the JSON file looks like this:
{"filename":{"file_data":
{"name":"samplefile",
"filetype":"Miscellaneous",
"id":123,
"timestamp":"2020-10-08 00:20:00"}}}
based on…
I am parsing an extremely large JSON file using IJSON and then writing the contents to a temp file. Afterwards, I overwrite the original file with the contents of the temp file.
FILE_NAME = 'file-name'
DIR_PATH = 'path'
#Generator function that…