无论json.load和json.loads无法加载我jsonl文件

Question

我试图加载我jsonl文件中的巨蟒。我使用下面的代码，并收到错误如下。

with open("mli_train_v1.jsonl", 'r', encoding='utf-8') as f:
    data = json.loads(f)

它的示值误差为

TypeError: the JSON object must be str, bytes or bytearray, not 'TextIOWrapper'

所以，我想这

with open("mli_train_v1.jsonl", 'r') as f:
    data = json.load(f)

而我得到的错误

JSONDecodeError: Extra data: line 2 column 1 (char 835)

我jsonl文件格式是这样的

{"sentence1": "Labs were notable for Cr 1.7 (baseline 0.5 per old records) and lactate 2.4.", "pairID": "23eb94b8-66c7-11e7-a8dc-f45c89b91419", "sentence1_parse": "(ROOT (S (NP (NNPS Labs)) (VP (VBD were) (ADJP (JJ notable) (PP (IN for) (NP (NP (NP (NN Cr) (CD 1.7)) (PRN (-LRB- -LRB-) (NP (NP (NN baseline) (CD 0.5)) (PP (IN per) (NP (JJ old) (NNS records)))) (-RRB- -RRB-))) (CC and) (NP (NN lactate) (CD 2.4)))))) (. .)))", "sentence1_binary_parse": "( Labs ( ( were ( notable ( for ( ( ( ( Cr 1.7 ) ( -LRB- ( ( ( baseline 0.5 ) ( per ( old records ) ) ) -RRB- ) ) ) and ) ( lactate 2.4 ) ) ) ) ) . ) )", "sentence2": " Patient has elevated Cr", "sentence2_parse": "(ROOT (S (NP (NN Patient)) (VP (VBZ has) (NP (JJ elevated) (NN Cr)))))", "sentence2_binary_parse": "( Patient ( has ( elevated Cr ) ) )", "gold_label": "entailment"}
{"sentence1": "Labs were notable for Cr 1.7 (baseline 0.5 per old records) and lactate 2.4.", "pairID": "23eb979c-66c7-11e7-b76c-f45c89b91419", "sentence1_parse": "(ROOT (S (NP (NNPS Labs)) (VP (VBD were) (ADJP (JJ notable) (PP (IN for) (NP (NP (NP (NN Cr) (CD 1.7)) (PRN (-LRB- -LRB-) (NP (NP (NN baseline) (CD 0.5)) (PP (IN per) (NP (JJ old) (NNS records)))) (-RRB- -RRB-))) (CC and) (NP (NN lactate) (CD 2.4)))))) (. .)))", "sentence1_binary_parse": "( Labs ( ( were ( notable ( for ( ( ( ( Cr 1.7 ) ( -LRB- ( ( ( baseline 0.5 ) ( per ( old records ) ) ) -RRB- ) ) ) and ) ( lactate 2.4 ) ) ) ) ) . ) )", "sentence2": " Patient has normal Cr", "sentence2_parse": "(ROOT (S (NP (NN Patient)) (VP (VBZ has) (NP (JJ normal) (NN Cr)))))", "sentence2_binary_parse": "( Patient ( has ( normal Cr ) ) )", "gold_label": "contradiction"}
{"sentence1": "Labs were notable for Cr 1.7 (baseline 0.5 per old records) and lactate 2.4.", "pairID": "23eb9986-66c7-11e7-9ef9-f45c89b91419", "sentence1_parse": "(ROOT (S (NP (NNPS Labs)) (VP (VBD were) (ADJP (JJ notable) (PP (IN for) (NP (NP (NP (NN Cr) (CD 1.7)) (PRN (-LRB- -LRB-) (NP (NP (NN baseline) (CD 0.5)) (PP (IN per) (NP (JJ old) (NNS records)))) (-RRB- -RRB-))) (CC and) (NP (NN lactate) (CD 2.4)))))) (. .)))", "sentence1_binary_parse": "( Labs ( ( were ( notable ( for ( ( ( ( Cr 1.7 ) ( -LRB- ( ( ( baseline 0.5 ) ( per ( old records ) ) ) -RRB- ) ) ) and ) ( lactate 2.4 ) ) ) ) ) . ) )", "sentence2": " Patient has elevated BUN", "sentence2_parse": "(ROOT (S (NP (NN Patient)) (VP (VBZ has) (NP (JJ elevated) (NN BUN)))))", "sentence2_binary_parse": "( Patient ( has ( elevated BUN ) ) )", "gold_label": "neutral"}

Answer 1

要读取一个JSON文件一个具有读取行，然后解析。

data = []
with open("mli_train_v1.jsonl", 'r', encoding='utf-8') as f:
    for line in f:
       data.append(json.loads(line))

Answer 2

下面可能解决您的问题。

import re, json
path = 'path/to/your/file'
with open(path) as f:
    contents = f.read()
contents = re.sub('}', '},', contents)
contents = contents[:-1]
contents = '[' + contents + ']'
with open(path, 'w') as f:
    f.write(contents)
with open(path) as f:
    json_contents = json.load(f)