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Using python ijson to read a large json file with multiple json objects

I'm trying to parse a large (~100MB) json file using ijson package which allows me to interact with the file in an efficient way. However, after writing some code like this,
with open(filename, 'r') as f:
parser = ijson.parse(f)
for prefix, event, value in parser:
if prefix == "name":
print(value)
I found that the code parses only the first line and not the rest of the lines from the file!!
Here is how a portion of my json file looks like:
{"name":"accelerator_pedal_position","value":0,"timestamp":1364323939.012000}
{"name":"engine_speed","value":772,"timestamp":1364323939.027000}
{"name":"vehicle_speed","value":0,"timestamp":1364323939.029000}
{"name":"accelerator_pedal_position","value":0,"timestamp":1364323939.035000}
In my opinion, I think ijson parses only one json object.
Can someone please suggest how to work around this?

Since the provided chunk looks more like a set of lines each composing an independent JSON, it should be parsed accordingly:
# each JSON is small, there's no need in iterative processing
import json
with open(filename, 'r') as f:
for line in f:
data = json.loads(line)
# data[u'name'], data[u'engine_speed'], data[u'timestamp'] now
# contain correspoding values

Unfortunately the ijson library (v2.3 as of March 2018) does not handle parsing multiple JSON objects. It can only handle 1 overall object, and if you attempt to parse a second object, you will get an error: "ijson.common.JSONError: Additional data". See bug reports here:
https://github.com/isagalaev/ijson/issues/40
https://github.com/isagalaev/ijson/issues/42
https://github.com/isagalaev/ijson/issues/67
python: how do I parse a stream of json arrays with ijson library
It's a big limitation. However, as long as you have line breaks (new line character) after each JSON object, you can parse each one line-by-line independently, like this:
import io
import ijson
with open(filename, encoding="UTF-8") as json_file:
cursor = 0
for line_number, line in enumerate(json_file):
print ("Processing line", line_number + 1,"at cursor index:", cursor)
line_as_file = io.StringIO(line)
# Use a new parser for each line
json_parser = ijson.parse(line_as_file)
for prefix, type, value in json_parser:
print ("prefix=",prefix, "type=",type, "value=",value)
cursor += len(line)
You are still streaming the file, and not loading it entirely in memory, so it can work on large JSON files. It also uses the line streaming technique from: How to jump to a particular line in a huge text file? and uses enumerate() from: Accessing the index in 'for' loops?

How to read line-delimited JSON from large file (line by line)

I'm trying to load a large file (2GB in size) filled with JSON strings, delimited by newlines. Ex:
{
"key11": value11,
"key12": value12,
}
{
"key21": value21,
"key22": value22,
}
…
The way I'm importing it now is:
content = open(file_path, "r").read()
j_content = json.loads("[" + content.replace("}\n{", "},\n{") + "]")
Which seems like a hack (adding commas between each JSON string and also a beginning and ending square bracket to make it a proper list).
Is there a better way to specify the JSON delimiter (newline \n instead of comma ,)?
Also, Python can't seem to properly allocate memory for an object built from 2GB of data, is there a way to construct each JSON object as I'm reading the file line by line? Thanks!

Just read each line and construct a json object at this time:
with open(file_path) as f:
for line in f:
j_content = json.loads(line)
This way, you load proper complete json object (provided there is no \n in a json value somewhere or in the middle of your json object) and you avoid memory issue as each object is created when needed.
There is also this answer.:
https://stackoverflow.com/a/7795029/671543

contents = open(file_path, "r").read()
data = [json.loads(str(item)) for item in contents.strip().split('\n')]

This will work for the specific file format that you gave. If your format changes, then you'll need to change the way the lines are parsed.
{
"key11": 11,
"key12": 12
}
{
"key21": 21,
"key22": 22
}
Just read line-by-line, and build the JSON blocks as you go:
with open(args.infile, 'r') as infile:
# Variable for building our JSON block
json_block = []
for line in infile:
# Add the line to our JSON block
json_block.append(line)
# Check whether we closed our JSON block
if line.startswith('}'):
# Do something with the JSON dictionary
json_dict = json.loads(''.join(json_block))
print(json_dict)
# Start a new block
json_block = []
If you are interested in parsing one very large JSON file without saving everything to memory, you should look at using the object_hook or object_pairs_hook callback methods in the json.load API.

This expands Cohen's answer:
content_object = s3_resource.Object(BucketName, KeyFileName)
file_buffer = io.StringIO()
file_buffer = content_object.get()['Body'].read().decode('utf-8')
json_lines = []
for line in file_buffer.splitlines():
j_content = json.loads(line)
json_lines.append(j_content)
df_readback = pd.DataFrame(json_lines)
This assumes that the entire file will fit in memory. If it is too big then this will have to be modified to read in chunks or use Dask.

Had to read some data from AWS S3 and parse a newline delimited jsonl file. My solution was this using splitlines
The code:
for line in json_input.splitlines():
one_json = json.loads(line)

The line by line reading approach is good, as mentioned in some of the above answers.
However across multiple JSON tree structures I would recommend decomposition into 2 functions to have more robust error handling.
For example,
def load_cases(file_name):
with open(file_name) as file:
cases = (parse_case_line(json.loads(line)) for line in file)
cases = filter(None, cases)
return list(cases)
parse_case_line can encapsulate the key parsing logic required in your above example, for example with regex matching, or application-specific requirements. It also means that you can select which json key-values you want to parse out.
Another advantage of this approach is filter handles multiple \n in the middle of your json object, and parses the whole file :-).

Just read it line by line and parse e through a stream
while ur hacking trick (adding commas between each JSON string and also a beginning and ending square bracket to make it a proper list) isn't memory-friendly if the file is too more than 1GB as the whole content will land on the RAM.

How to store something other than a string in a file

I'm trying to write some code to create a file that will write data about a "character". I've been able to write strings using:
f = open('player.txt','w')
f.write("Karatepig")
f.close()
f = open('player.txt','r')
f.read()
The issue is, how do I store something other than a string to a file? Can I convert it from a string to a value?

Files can only store strings, so you have to convert other values to strings when writing, and converting them back to original values when reading.
The Python standard library has a whole section dedicated to data persistence that can help make this task easier.
However, for simple types, it is perhaps easiest to use the json module to serialize data to a file and read it back again with ease:
import json
def write_data(data, filename):
with open(filename, 'w') as outfh:
json.dump(data, outfh)
def read_data(filename):
with open(filename, 'r') as infh:
json.load(infh)

Adding brackets and commas to multiple JSON objects

I've created a very simple piece of code to read in tweets in JSON format in text files, determine if they contain an id and coordinates and if so, write these attributes to a csv file. This is the code:
f = csv.writer(open('GeotaggedTweets/ListOfTweets.csv', 'wb+'))
all_files = glob.glob('SampleTweets/*.txt')
for filename in all_files:
with open(filename, 'r') as file:
data = simplejson.load(file)
if 'text' and 'coordinates' in data:
f.writerow([data['id'], data['geo']['coordinates']])
I've been having some difficulties but with the help of the excellent JSON Lint website have realised my mistake. I have multiple JSON objects and from what I read these need to be separated by commas and have square brackets added to the start and end of the file.
How can I achieve this? I've seen some examples online where each individual line is read and it's added to the first and last line, but as I load the whole file I'm not entirely sure how to do this.

You have a file that either contains too many newlines (in the JSON values themselves) or too few (no newlines between the tweets at all).
You can still repair this by using some creative re-stitching. The following generator function should do it:
import json
def read_objects(filename):
decoder = json.JSONDecoder()
with open(filename, 'r') as inputfile:
line = next(inputfile).strip()
while line:
try:
obj, index = decoder.raw_decode(line)
yield obj
line = line[index:]
except ValueError:
# Assume we didn't have a complete object yet
line += next(inputfile).strip()
if not line:
line += next(inputfile).strip()
This should be able to read all your JSON objects in sequence:
for filename in all_files:
for data in read_objects(filename):
if 'text' and 'coordinates' in data:
f.writerow([data['id'], data['geo']['coordinates']])
It is otherwise fine to have multiple JSON strings written to one file, but you need to make sure that the entries are clearly separated somehow. Writing JSON entries that do not use newlines, then using newlines in between them, for example, makes sure you can later on read them one by one again and process them sequentially without this much hassle.

Update json file

I have json file with some data, and would like to occasionally update this file.
I read the file:
with open('index.json', 'rb') as f:
idx = json.load(f)
then check for presence of a key from potentially new data, and if key is not present update the file:
with open('index.json', mode='a+') as f:
json.dump(new_data, f, indent=4)
However this procedure just creates new json object (python dict) and appends it as new object in output json file, making the file not valid json file.
Is there any simple way to append new data to json file without overwriting whole file, by updating the initial dict?

One way to do what you're after is to write one JSON object per line in the file. I'm using that approach and it works quite well.
A nice benefit is that you can read the file more efficiently (memory-wise) because you can read one line at a time. If you need all of them, there's no problem with assembling a list in Python, but if you don't you're operating much faster and you can also append.
So to initially write all your objects, you'd do something like this:
with open(json_file_path, "w") as json_file:
for data in data_iterable:
json_file.write("{}\n".format(json.dumps(data)))
Then to read efficiently (will consume little memory, no matter the file size):
with open(json_file_path, "r") as json_file:
for line in json_file:
data = json.loads(line)
process_data(data)
To update/append:
with open(json_file_path, "a") as json_file:
json_file.write("{}\n".format(json.dumps(new_data)))
Hope this helps :)