Related
This is the code i have so far:
import json
import requests
import time
endpoint = "https://www.deadstock.ca/collections/new-arrivals/products/nike-
air-max-1-cool-grey.json"
req = requests.get(endpoint)
reqJson = json.loads(req.text)
for id in reqJson['product']:
name = (id['title'])
print (name)
Feel free to visit the link, I'm trying to grab all the "id" value and print them out. They will be used later to send to my discord.
I tried with my above code but i have no idea how to actually get those values. I don't know which variable to use in the for in reqjson statement
If anyone could help me out and guide me to get all of the ids to print that would be awesome.
for product in reqJson['product']['title']:
ProductTitle = product['title']
print (title)
I see from the link you provided that the only ids that are in a list are actually part of the variants list under product. All the other ids are not part of a list and have therefore no need to iterate over. Here's an excerpt of the data for clarity:
{
"product":{
"id":232418213909,
"title":"Nike Air Max 1 \/ Cool Grey",
...
"variants":[
{
"id":3136193822741,
"product_id":232418213909,
"title":"8",
...
},
{
"id":3136193855509,
"product_id":232418213909,
"title":"8.5",
...
},
{
"id":3136193789973,
"product_id":232418213909,
"title":"9",
...
},
...
],
"image":{
"id":3773678190677,
"product_id":232418213909,
"position":1,
...
}
}
}
So what you need to do should be to iterate over the list of variants under product instead:
import json
import requests
endpoint = "https://www.deadstock.ca/collections/new-arrivals/products/nike-air-max-1-cool-grey.json"
req = requests.get(endpoint)
reqJson = json.loads(req.text)
for product in reqJson['product']['variants']:
print(product['id'], product['title'])
This outputs:
3136193822741 8
3136193855509 8.5
3136193789973 9
3136193757205 9.5
3136193724437 10
3136193691669 10.5
3136193658901 11
3136193626133 12
3136193593365 13
And if you simply want the product id and product name, they would be reqJson['product']['id'] and reqJson['product']['title'], respectively.
I am following the DynamoDB python tutorial. This step shows how to query the table based on a specific key: http://docs.aws.amazon.com/amazondynamodb/latest/gettingstartedguide/GettingStarted.Python.04.html.
Here is the code for this query:
from __future__ import print_function # Python 2/3 compatibility
import boto3
import json
import decimal
from boto3.dynamodb.conditions import Key, Attr
# Helper class to convert a DynamoDB item to JSON.
class DecimalEncoder(json.JSONEncoder):
def default(self, o):
if isinstance(o, decimal.Decimal):
return str(o)
return super(DecimalEncoder, self).default(o)
dynamodb = boto3.resource('dynamodb', region_name='us-west-2', endpoint_url="http://localhost:8000")
table = dynamodb.Table('Movies')
print("Movies from 1992 - titles A-L, with genres and lead actor")
response = table.query(
ProjectionExpression="#yr, title, info.genres, info.actors[0]",
ExpressionAttributeNames={ "#yr": "year" }, # Expression Attribute Names for Projection Expression only.
KeyConditionExpression=Key('year').eq(1992) & Key('title').between('A', 'L')
)
for i in response[u'Items']:
print(json.dumps(i, cls=DecimalEncoder))
An example response item is
{
"title": "Juice",
"year": "1992",
"info": {
"actors": [
"Omar Epps"
],
"genres": [
"Crime",
"Drama",
"Thriller"
]
}
}
The table has the two key attributes 'title' and 'year' as well as the nested attribute 'info'. What I am trying to do is query the database and filter the movies by genre, for example get all Drama movies. I am not sure how to do this since the genre key is nested inside info.
I tried to get all the Drama movies from 1992 like this but it came up blank.
response = table.query(
KeyConditionExpression=Key('year').eq(1992),
FilterExpression=Attr('info.genres').eq('Drama')
)
How do I properly filter this query with the nested info attribute?
You can use contains to filter the data from List data type.
genres -attribute stored as List inside info attribute which is a Map data type
FilterExpression=Attr('info.genres').contains('Drama')
Unlike in the accepted answer, to be able to filter all the items with the attribute, you need to use scan() instead of query(). query() requires KeyCondition which is unnecessary in your case and forces you to create condition containing f.e. year.
Therefore
table.scan(FilterExpression=Attr('info.genres').contains('Drama'))
should do the job
I have a .json.gz file that I wish to load into elastic search.
My first attempt involved using the json module to convert the JSON to a list of dicts.
import gzip
import json
from pprint import pprint
from elasticsearch import Elasticsearch
nodes_f = gzip.open("nodes.json.gz")
nodes = json.load(nodes_f)
Dict example:
pprint(nodes[0])
{u'index': 1,
u'point': [508163.122, 195316.627],
u'tax': u'fehwj39099'}
Using Elasticsearch:
es = Elasticsearch()
data = es.bulk(index="index",body=nodes)
However, this returns:
elasticsearch.exceptions.RequestError: TransportError(400, u'illegal_argument_exception', u'Malformed action/metadata line [1], expected START_OBJECT or END_OBJECT but found [VALUE_STRING]')
Beyond this, I wish to be able to find the tax for given point query, in case this has an impact on how I should be indexing the data with elasticsearch.
Alfe pointed me in the right direction, but I couldn't get his code to work.
I found two solutions:
Line by line with a for loop:
es = elasticsearch.Elasticsearch()
for node in nodes:
_id = node['index']
es.index(index='nodes',doc_type='external',id=_id,body=node)
In bulk, using helper:
actions = [
{
"_index" : "nodes_bulk",
"_type" : "external",
"_id" : str(node['index']),
"_source" : node
}
for node in nodes
]
helpers.bulk(es,actions)
Bulk was around 22 times faster for a list of 343724 dicts.
Here is my working code using bulk api:
Define a list of dicts:
from elasticsearch import Elasticsearch, helpers
es = Elasticsearch([{'host':'localhost', 'port': 9200}])
doc = [{'_id': 1,'price': 10, 'productID' : 'XHDK-A-1293-#fJ3'},
{'_id':2, "price" : 20, "productID" : "KDKE-B-9947-#kL5"},
{'_id':3, "price" : 30, "productID" : "JODL-X-1937-#pV7"},
{'_id':4, "price" : 30, "productID" : "QQPX-R-3956-#aD8"}]
helpers.bulk(es, doc, index='products',doc_type='_doc', request_timeout=200)
The ES bulk library showed several problems, including performance trouble, not being able to set specific _ids etc. But since the bulk API of ES is not very complicated, we did it ourselves:
import requests
headers = { 'Content-type': 'application/json',
'Accept': 'text/plain'}
jsons = []
for d in docs:
_id = d.pop('_id') # take _id out of dict
jsons.append('{"index":{"_id":"%s"}}\n%s\n' % (_id, json.dumps(d)))
data = ''.join(jsons)
response = requests.post(url, data=data, headers=headers)
We needed to set a specific _id but I guess you can skip this part in case you want a random _id set by ES automatically.
Hope that helps.
Following the documentation, I'm trying to create an update statement that will update or add if not exists only one attribute in a dynamodb table.
I'm trying this
response = table.update_item(
Key={'ReleaseNumber': '1.0.179'},
UpdateExpression='SET',
ConditionExpression='Attr(\'ReleaseNumber\').eq(\'1.0.179\')',
ExpressionAttributeNames={'attr1': 'val1'},
ExpressionAttributeValues={'val1': 'false'}
)
The error I'm getting is:
botocore.exceptions.ClientError: An error occurred (ValidationException) when calling the UpdateItem operation: ExpressionAttributeNames contains invalid key: Syntax error; key: "attr1"
If anyone has done anything similar to what I'm trying to achieve please share example.
Found working example here, very important to list as Keys all the indexes of the table, this will require additional query before update, but it works.
response = table.update_item(
Key={
'ReleaseNumber': releaseNumber,
'Timestamp': result[0]['Timestamp']
},
UpdateExpression="set Sanity = :r",
ExpressionAttributeValues={
':r': 'false',
},
ReturnValues="UPDATED_NEW"
)
Details on dynamodb updates using boto3 seem incredibly sparse online, so I'm hoping these alternative solutions are useful.
get / put
import boto3
table = boto3.resource('dynamodb').Table('my_table')
# get item
response = table.get_item(Key={'pkey': 'asdf12345'})
item = response['Item']
# update
item['status'] = 'complete'
# put (idempotent)
table.put_item(Item=item)
actual update
import boto3
table = boto3.resource('dynamodb').Table('my_table')
table.update_item(
Key={'pkey': 'asdf12345'},
AttributeUpdates={
'status': 'complete',
},
)
If you don't want to check parameter by parameter for the update I wrote a cool function that would return the needed parameters to perform a update_item method using boto3.
def get_update_params(body):
"""Given a dictionary we generate an update expression and a dict of values
to update a dynamodb table.
Params:
body (dict): Parameters to use for formatting.
Returns:
update expression, dict of values.
"""
update_expression = ["set "]
update_values = dict()
for key, val in body.items():
update_expression.append(f" {key} = :{key},")
update_values[f":{key}"] = val
return "".join(update_expression)[:-1], update_values
Here is a quick example:
def update(body):
a, v = get_update_params(body)
response = table.update_item(
Key={'uuid':str(uuid)},
UpdateExpression=a,
ExpressionAttributeValues=dict(v)
)
return response
The original code example:
response = table.update_item(
Key={'ReleaseNumber': '1.0.179'},
UpdateExpression='SET',
ConditionExpression='Attr(\'ReleaseNumber\').eq(\'1.0.179\')',
ExpressionAttributeNames={'attr1': 'val1'},
ExpressionAttributeValues={'val1': 'false'}
)
Fixed:
response = table.update_item(
Key={'ReleaseNumber': '1.0.179'},
UpdateExpression='SET #attr1 = :val1',
ConditionExpression=Attr('ReleaseNumber').eq('1.0.179'),
ExpressionAttributeNames={'#attr1': 'val1'},
ExpressionAttributeValues={':val1': 'false'}
)
In the marked answer it was also revealed that there is a Range Key so that should also be included in the Key. The update_item method must seek to the exact record to be updated, there's no batch updates, and you can't update a range of values filtered to a condition to get to a single record. The ConditionExpression is there to be useful to make updates idempotent; i.e. don't update the value if it is already that value. It's not like a sql where clause.
Regarding the specific error seen.
ExpressionAttributeNames is a list of key placeholders for use in the UpdateExpression, useful if the key is a reserved word.
From the docs, "An expression attribute name must begin with a #, and be followed by one or more alphanumeric characters". The error is because the code hasn't used an ExpressionAttributeName that starts with a # and also not used it in the UpdateExpression.
ExpressionAttributeValues are placeholders for the values you want to update to, and they must start with :
Based on the official example, here's a simple and complete solution which could be used to manually update (not something I would recommend) a table used by a terraform S3 backend.
Let's say this is the table data as shown by the AWS CLI:
$ aws dynamodb scan --table-name terraform_lock --region us-east-1
{
"Items": [
{
"Digest": {
"S": "2f58b12ae16dfb5b037560a217ebd752"
},
"LockID": {
"S": "tf-aws.tfstate-md5"
}
}
],
"Count": 1,
"ScannedCount": 1,
"ConsumedCapacity": null
}
You could update it to a new digest (say you rolled back the state) as follows:
import boto3
dynamodb = boto3.resource('dynamodb', 'us-east-1')
try:
table = dynamodb.Table('terraform_lock')
response = table.update_item(
Key={
"LockID": "tf-aws.tfstate-md5"
},
UpdateExpression="set Digest=:newDigest",
ExpressionAttributeValues={
":newDigest": "50a488ee9bac09a50340c02b33beb24b"
},
ReturnValues="UPDATED_NEW"
)
except Exception as msg:
print(f"Oops, could not update: {msg}")
Note the : at the start of ":newDigest": "50a488ee9bac09a50340c02b33beb24b" they're easy to miss or forget.
Small update of Jam M. Hernandez Quiceno's answer, which includes ExpressionAttributeNames to prevent encoutering errors such as:
"errorMessage": "An error occurred (ValidationException) when calling the UpdateItem operation:
Invalid UpdateExpression: Attribute name is a reserved keyword; reserved keyword: timestamp",
def get_update_params(body):
"""
Given a dictionary of key-value pairs to update an item with in DynamoDB,
generate three objects to be passed to UpdateExpression, ExpressionAttributeValues,
and ExpressionAttributeNames respectively.
"""
update_expression = []
attribute_values = dict()
attribute_names = dict()
for key, val in body.items():
update_expression.append(f" #{key.lower()} = :{key.lower()}")
attribute_values[f":{key.lower()}"] = val
attribute_names[f"#{key.lower()}"] = key
return "set " + ", ".join(update_expression), attribute_values, attribute_names
Example use:
update_expression, attribute_values, attribute_names = get_update_params(
{"Status": "declined", "DeclinedBy": "username"}
)
response = table.update_item(
Key={"uuid": "12345"},
UpdateExpression=update_expression,
ExpressionAttributeValues=attribute_values,
ExpressionAttributeNames=attribute_names,
ReturnValues="UPDATED_NEW"
)
print(response)
An example to update any number of attributes given as a dict, and keep track of the number of updates. Works with reserved words (i.e name).
The following attribute names shouldn't be used as we will overwrite the value: _inc, _start.
from typing import Dict
from boto3 import Session
def getDynamoDBSession(region: str = "eu-west-1"):
"""Connect to DynamoDB resource from boto3."""
return Session().resource("dynamodb", region_name=region)
DYNAMODB = getDynamoDBSession()
def updateItemAndCounter(db_table: str, item_key: Dict, attributes: Dict) -> Dict:
"""
Update item or create new. If the item already exists, return the previous value and
increase the counter: update_counter.
"""
table = DYNAMODB.Table(db_table)
# Init update-expression
update_expression = "SET"
# Build expression-attribute-names, expression-attribute-values, and the update-expression
expression_attribute_names = {}
expression_attribute_values = {}
for key, value in attributes.items():
update_expression += f' #{key} = :{key},' # Notice the "#" to solve issue with reserved keywords
expression_attribute_names[f'#{key}'] = key
expression_attribute_values[f':{key}'] = value
# Add counter start and increment attributes
expression_attribute_values[':_start'] = 0
expression_attribute_values[':_inc'] = 1
# Finish update-expression with our counter
update_expression += " update_counter = if_not_exists(update_counter, :_start) + :_inc"
return table.update_item(
Key=item_key,
UpdateExpression=update_expression,
ExpressionAttributeNames=expression_attribute_names,
ExpressionAttributeValues=expression_attribute_values,
ReturnValues="ALL_OLD"
)
Hope it might be useful to someone!
In a simple way you can use below code to update item value with new one:
response = table.update_item(
Key={"my_id_name": "my_id_value"}, # to get record
UpdateExpression="set item_key_name=:item_key_value", # Operation action (set)
ExpressionAttributeValues={":value": "new_value"}, # item that you need to update
ReturnValues="UPDATED_NEW" # optional for declarative message
)
Simple example with multiple fields:
import boto3
dynamodb_client = boto3.client('dynamodb')
dynamodb_client.update_item(
TableName=table_name,
Key={
'PK1': {'S': 'PRIMARY_KEY_VALUE'},
'SK1': {'S': 'SECONDARY_KEY_VALUE'}
}
UpdateExpression='SET #field1 = :field1, #field2 = :field2',
ExpressionAttributeNames={
'#field1': 'FIELD_1_NAME',
'#field2': 'FIELD_2_NAME',
},
ExpressionAttributeValues={
':field1': {'S': 'FIELD_1_VALUE'},
':field2': {'S': 'FIELD_2_VALUE'},
}
)
using previous answer from eltbus , it worked for me , except for minor bug,
You have to delete the extra comma using update_expression[:-1]
I am trying to parse a JSON data set that looks something like this:
{"data":[
{
"Rest":0,
"Status":"The campaign is moved to the archive",
"IsActive":"No",
"StatusArchive":"Yes",
"Login":"some_login",
"ContextStrategyName":"Default",
"CampaignID":1111111,
"StatusShow":"No",
"StartDate":"2013-01-20",
"Sum":0,
"StatusModerate":"Yes",
"Clicks":0,
"Shows":0,
"ManagerName":"XYZ",
"StatusActivating":"Yes",
"StrategyName":"HighestPosition",
"SumAvailableForTransfer":0,
"AgencyName":null,
"Name":"Campaign_01"
},
{
"Rest":82.6200000000008,
"Status":"Impressions will begin tomorrow at 10:00",
"IsActive":"Yes",
"StatusArchive":"No",
"Login":"some_login",
"ContextStrategyName":"Default",
"CampaignID":2222222,
"StatusShow":"Yes",
"StartDate":"2013-01-28",
"Sum":15998,"StatusModerate":"Yes",
"Clicks":7571,
"Shows":5535646,
"ManagerName":"XYZ",
"StatusActivating":"Yes",
"StrategyName":"HighestPosition",
"SumAvailableForTransfer":0,
"AgencyName":null,
"Name":"Campaign_02"
}
]
}
Lets assume that there can be many of these data sets.
I would like to iterate through each one of them and grab the "Name" and the "Campaign ID" parameter.
So far my code looks something like this:
decoded_response = response.read().decode("UTF-8")
data = json.loads(decoded.response)
for item in data[0]:
for x in data[0][item] ...
-> need a get name procedure
-> need a get campaign_id procedure
Probably quite straight forward! I am not good with lists/dictionaries :(
Access dictionaries with d[dict_key] or d.get(dict_key, default) (to provide default value):
jsonResponse=json.loads(decoded_response)
jsonData = jsonResponse["data"]
for item in jsonData:
name = item.get("Name")
campaignID = item.get("CampaignID")
I suggest you read something about dictionaries.