I am trying to remove an item ("logs") from my dictionary using the del method.
this is my code:
del response.json() ["logs"]
print(response.json())
this is my JSON dictionary:
{'count': 19804,
'next': {'limit': 1, 'offset': 1},
'previous': None,
'results':
[{'id': '334455',
'custom_id': '112',
'company': 28,
'company_name': 'Sunshine and Flowers',
'delivery_address': '34 olive beach house, #01-22, 612345',
'delivery_timeslot': {'lower': '2019-12-06T10:00:00Z', 'upper': '2019-12-06T13:00:00Z', 'bounds': '[)'},
'sender_name': 'Edward Shine',
'sender_email': '',
'sender_contact': '91234567',
'removed': None,
'recipient_name': 'Mint Shine',
'recipient_contact': '91234567',
'notes': '',
'items': [{'id': 21668, 'name': 'Loose hair flowers', 'quantity': 1, 'metadata': {}, 'removed': None}, {'id': 21667, 'name': "Groom's Boutonniere", 'quantity': 1, 'metadata': {}, 'removed': None}, {'id': 21666, 'name': 'Bridal Bouquet', 'quantity': 1, 'metadata': {}, 'removed': None}],
'latitude': '1.28283838383642000000',
'longitude': '103.2828037266201000000',
'created': '2019-08-15T05:40:30.385467Z',
'updated': '2019-08-15T05:41:27.930110Z',
'status': 'pending',
'verbose_status': 'Pending',
'**logs**': [{'id': 334455, 'order': '50c402d8-7c76-45b5-b883-e2fb887a507e', 'order_custom_id': '112', 'order_delivery_address': '34 olive beach house, #01-22, 6123458', 'order_delivery_timeslot': {'lower': '2019-12-06T10:00:00Z', 'upper': '2019-12-06T13:00:00Z', 'bounds': '[)'}, 'message': 'Order was created.', 'failure_reason': None, 'success_code': None, 'success_description': None, 'created': '2019-08-15T05:40:30.431790Z', 'removed': None}, {'id': 334455, 'order': '50c402d8-7c76-45b5-b883-e2fb887a507e', 'order_custom_id': '112', 'order_delivery_address': '34 olive beach house, #01-22, 612345', 'order_delivery_timeslot': {'lower': '2019-12-06T10:00:00Z', 'upper': '2019-12-06T13:00:00Z', 'bounds': '[)'}, 'message': 'Order is pending.', 'failure_reason': None, 'success_code': None, 'success_description': None, 'created': '2019-08-15T05:40:30.433139Z', 'removed': None}],
'reschedule_requests': [],
'signature': None}]
but it is saying this error
KeyError: 'logs'
what am i doing wrong? please assist
Every time you call response.json(), it returns a new dict, so the key you delete from response.json() won't be reflected in the next call to response.json().
You should instead save the returning value of response.json() to a variable before deleting the desired key:
data = response.json()
del data['results'][0]['logs']
print(data)
Related
I'm trying to grab transaction data from plaid and input it into a data frame with clean columns. The "before" format is a list as excerpted below.
My goal is that the "after" format is a data frame where there is a column for each name in the list (e.g., "account_id" or "amount") such that I can then parse the list and insert values in each column.
I'm new to python--I'm fluent in r/dplyr but the syntax is confusing me.
Thanks in advance!
{'account_id': 'nKllGzvJQeIpZwvxlv1Mhw98Zdo57Ec6ZNEm5',
'account_owner': None,
'amount': 4.33,
'authorized_date': datetime.date(2020, 12, 8),
'authorized_datetime': None,
'category': ['Food and Drink', 'Restaurants', 'Coffee Shop'],
'category_id': '13005043',
'check_number': None,
'date': datetime.date(2020, 12, 8),
'datetime': None,
'iso_currency_code': 'USD',
'location': {'address': None,
'city': None,
'country': None,
'lat': None,
'lon': None,
'postal_code': None,
'region': None,
'store_number': None},
'merchant_name': 'Starbucks',
'name': 'Starbucks',
'payment_channel': 'in store',
'payment_meta': {'by_order_of': None,
'payee': None,
'payer': None,
'payment_method': None,
'payment_processor': None,
'ppd_id': None,
'reason': None,
'reference_number': None},
'pending': False,
'pending_transaction_id': None,
'personal_finance_category': None,
'transaction_code': None,
'transaction_id': 'llvvGK61QjH1eX8yP8qZC8BxB3WegMFZrXRjr',
'transaction_type': 'place',
'unofficial_currency_code': None}
enter code here
In this case, I would use the DataFrame constructor, in the list-of-records format.
Example:
import datetime
import pandas as pd
transaction = {'account_id': 'nKllGzvJQeIpZwvxlv1Mhw98Zdo57Ec6ZNEm5',
'account_owner': None,
'amount': 4.33,
'authorized_date': datetime.date(2020, 12, 8),
'authorized_datetime': None,
'category': ['Food and Drink', 'Restaurants', 'Coffee Shop'],
'category_id': '13005043',
'check_number': None,
'date': datetime.date(2020, 12, 8),
'datetime': None,
'iso_currency_code': 'USD',
'location': {'address': None,
'city': None,
'country': None,
'lat': None,
'lon': None,
'postal_code': None,
'region': None,
'store_number': None},
'merchant_name': 'Starbucks',
'name': 'Starbucks',
'payment_channel': 'in store',
'payment_meta': {'by_order_of': None,
'payee': None,
'payer': None,
'payment_method': None,
'payment_processor': None,
'ppd_id': None,
'reason': None,
'reference_number': None},
'pending': False,
'pending_transaction_id': None,
'personal_finance_category': None,
'transaction_code': None,
'transaction_id': 'llvvGK61QjH1eX8yP8qZC8BxB3WegMFZrXRjr',
'transaction_type': 'place',
'unofficial_currency_code': None}
transactions = [transaction]
df = pd.DataFrame(transactions)
Note that some columns are themselves objects, like the payment category column or payment_meta column. You didn't specify if you thought those should be handled specially or broken out into multiple columns, but it's something you should consider doing.
Also note that transactions is a list, and you can put multiple transactions in the same format into it, and construct the dataframe all at once. (This is preferable to creating multiple dataframes and appending them together, for the same reason as in dplyr.)
I need your help.
I have this code:
import ipaddress
from ipaddress import IPv4Network
prefixes = []
ip_addresses_all = [{'address': '10.0.0.1/24', 'vrf': {'id': 31,'name': 'god_inet'},
{'address': '10.0.0.10/24', 'vrf': {'id': 33, 'name': 'for_test'},
{'address': '10.1.1.1/30', 'vrf': {'id': 8, 'name': 'ott_private_net'},
{'address': '10.1.1.2/30', 'vrf': {'id': 11,'name': 'ott_public_net'},
{'address': '10.10.0.129/30', 'vrf': None,},
{'address': '10.10.0.130/30', 'vrf': None,},
{'address': '10.10.0.137/30', 'vrf': None,},
{'address': '10.10.0.138/30', 'vrf': None,}]
for ip in ip_addresses_all:
prefix = str(ipaddress.ip_network(ip.address, False))
mask_length = int(IPv4Network(prefix).prefixlen)
description_interface = ip.address
if ip.vrf:
ip_vrf_name = ip.vrf.name
ip_vrf_id = ip.vrf.id
ip_vrf = ip.vrf
else:
ip_vrf_name = 'null'
ip_vrf_id = 'null'
ip_vrf = 'null'
prefix_dict = {'prefix': prefix,
'vrf': {'name': ip_vrf_name,
'id': ip_vrf_id},
'prefix_description': [description_interface]}
if prefixes:
for i in prefixes:
if prefix != i['prefix']:
prefixes.append(prefix_dict)
elif i['prefix'] == prefix and i['vrf']['name'] == ip_vrf_name and description_interface not in i['prefix_description']:
i['prefix_description'].append(description_interface)
else:
prefixes.append(prefix_dict)
pprint(prefixes)
So, I wanna append the 'prefixes' list with dicts according to this logic : if prefix not in prefixes = [] - create new dict , if prefix with the same vrf already exists, then append a description string to a description key and update existing dict.
I struggle with this for 8 hours and it doesnt work, Ive got infinite loops=)
Intended output, something like that:
{'10.0.0.0/24': {'prefix_description': ['10.0.0.10/24'],'vrf': {'id': 31, 'name': 'god_inet'}},
'10.0.0.0/24': {'prefix_description': ['10.0.0.10/24'],'vrf': {'id': 33, 'name': 'for_test'}},
'10.1.1.0/30': {'prefix_description': ['10.1.1.2/30'],'vrf': {'id': 8, 'name': 'ott_private_net'}},
'10.1.1.0/30': {'prefix_description': ['10.1.1.2/30'],'vrf': {'id': 11, 'name': 'ott_public_net'}},
'10.10.0.128/30': {'prefix_description': ['10.10.0.129/30',
'10.10.0.130/30'],'vrf': {'id': 'null', 'name': 'null'}},
'10.10.0.136/30': {'prefix_description': ['10.10.0.137/30',
'10.10.0.138/30'],'vrf': {'id': 'null', 'name': 'null'}}}
Or better in a list like that:
[{'prefix': '10.0.0.0/24',
'prefix_description': ['77-GOD-VPN-2 ---- Vlan40'],
'vrf': {'id': 31, 'name': 'god_inet'}},
{'prefix': '10.0.0.0/24',
'prefix_description': ['78-ELS-CORE ---- Vlan142'],
'vrf': {'id': 33, 'name': 'for_test'}}]
make prefixes a dict and handle that code in the for loop
import ipaddress
from ipaddress import IPv4Network
prefixes = {}
ip_addresses_all = [{'address': '10.0.0.1/24', 'vrf': {'id': 31,'name': 'god_inet'}},
{'address': '10.0.0.10/24', 'vrf': {'id': 33, 'name': 'for_test'}},
{'address': '10.1.1.1/30', 'vrf': {'id': 8, 'name': 'ott_private_net'}},
{'address': '10.1.1.2/30', 'vrf': {'id': 11,'name': 'ott_public_net'}},
{'address': '10.10.0.129/30', 'vrf': None,},
{'address': '10.10.0.130/30', 'vrf': None,},
{'address': '10.10.0.137/30', 'vrf': None,},
{'address': '10.10.0.138/30', 'vrf': None,}]
for ip in ip_addresses_all:
prefix = str(ipaddress.ip_network(ip['address'], False))
mask_length = int(IPv4Network(prefix).prefixlen)
description_interface = ip['address']
if ip['vrf']:
ip_vrf_name = ip['vrf']['name']
ip_vrf_id = ip['vrf']['id']
ip_vrf = ip['vrf']
else:
ip_vrf_name = 'null'
ip_vrf_id = 'null'
ip_vrf = 'null'
prefix_dict = {
'vrf': {'name': ip_vrf_name,
'id': ip_vrf_id},
'prefix_description': [description_interface]}
if prefix in prefixes and \
prefixes[prefix]['vrf']['name'] == ip_vrf_name and \
description_interface not in prefixes[prefix]['prefix_description']:
prefixes[prefix]['prefix_description'].append(description_interface)
else:
prefixes[prefix] = prefix_dict
from pprint import pprint
pprint(prefixes)
output
{'10.0.0.0/24': {'prefix_description': ['10.0.0.10/24'],
'vrf': {'id': 33, 'name': 'for_test'}},
'10.1.1.0/30': {'prefix_description': ['10.1.1.2/30'],
'vrf': {'id': 11, 'name': 'ott_public_net'}},
'10.10.0.128/30': {'prefix_description': ['10.10.0.129/30', '10.10.0.130/30'],
'vrf': {'id': 'null', 'name': 'null'}},
'10.10.0.136/30': {'prefix_description': ['10.10.0.137/30', '10.10.0.138/30'],
'vrf': {'id': 'null', 'name': 'null'}}}
I want to get the price precision of any futures asset.
What I tried:
client.get_symbol_info(symbol='My Symbol')
But this returns the precision of the Spot and I need the precision of the futures.
So theres this Command:
client.futures_exchange_info()
Which return this:
{'timezone': 'UTC', 'serverTime': 1630437033153, 'futuresType': 'U_MARGINED', 'rateLimits': [{'rateLimitType': 'REQUEST_WEIGHT', 'interval': 'MINUTE', 'intervalNum': 1, 'limit': 2400},
{'rateLimitType': 'ORDERS', 'interval': 'MINUTE', 'intervalNum': 1, 'limit': 1200},
{'rateLimitType': 'ORDERS', 'interval': 'SECOND', 'intervalNum': 10, 'limit': 300}],
'exchangeFilters': [],
'assets': [{'asset': 'USDT', 'marginAvailable': True, 'autoAssetExchange': '-10000'},
{'asset': 'BTC', 'marginAvailable': True, 'autoAssetExchange': '-0.00100000'},
{'asset': 'BNB', 'marginAvailable': True, 'autoAssetExchange': '-10'},
{'asset': 'ETH', 'marginAvailable': True, 'autoAssetExchange': '-5'},
{'asset': 'BUSD', 'marginAvailable': True, 'autoAssetExchange': '-10000'}],
'symbols': [{'symbol': 'BTCUSDT', 'pair': 'BTCUSDT', 'contractType': 'PERPETUAL', 'deliveryDate': 4133404800000, 'onboardDate': 1569398400000, 'status': 'TRADING', 'maintMarginPercent': '2.5000', 'requiredMarginPercent': '5.0000', 'baseAsset': 'BTC', 'quoteAsset': 'USDT', 'marginAsset': 'USDT', 'pricePrecision': 2, 'quantityPrecision': 3, 'baseAssetPrecision': 8, 'quotePrecision': 8, 'underlyingType': 'COIN', 'underlyingSubType': [], 'settlePlan': 0, 'triggerProtect': '0.0500', 'liquidationFee': '0.012000', 'marketTakeBound': '0.05', 'filters': [{'minPrice': '556.72', 'maxPrice': '4529764', 'filterType': 'PRICE_FILTER', 'tickSize': '0.01'}, {'stepSize': '0.001', 'filterType': 'LOT_SIZE', 'maxQty': '1000', 'minQty': '0.001'}, {'stepSize': '0.001', 'filterType': 'MARKET_LOT_SIZE', 'maxQty': '200', 'minQty': '0.001'}, {'limit': 200, 'filterType': 'MAX_NUM_ORDERS'}, {'limit': 10, 'filterType': 'MAX_NUM_ALGO_ORDERS'}, {'notional': '5', 'filterType': 'MIN_NOTIONAL'}, {'multiplierDown': '0.9500', 'multiplierUp': '1.0500', 'multiplierDecimal': '4', 'filterType': 'PERCENT_PRICE'}], 'orderTypes': ['LIMIT', 'MARKET', 'STOP', 'STOP_MARKET', 'TAKE_PROFIT', 'TAKE_PROFIT_MARKET', 'TRAILING_STOP_MARKET'], 'timeInForce': ['GTC', 'IOC', 'FOK', 'GTX']},
{'symbol': 'ETHUSDT', 'pair': 'ETHUSDT', 'contractType': 'PERPETUAL', 'deliveryDate': 4133404800000, 'onboardDate': 1569398400000, 'status': 'TRADING', 'maintMarginPercent': '2.5000', 'requiredMarginPercent': '5.0000', 'baseAsset': 'ETH', 'quoteAsset': 'USDT', 'marginAsset': 'USDT', 'pricePrecision': 2, 'quantityPrecision': 3, 'baseAssetPrecision': 8, 'quotePrecision': 8, 'underlyingType': 'COIN', 'underlyingSubType': [], 'settlePlan': 0, 'triggerProtect': '0.0500', 'liquidationFee': '0.005000', 'marketTakeBound': '0.05', 'filters': [{'minPrice': '39.86', 'maxPrice': '306177', 'filterType': 'PRICE_FILTER', 'tickSize': '0.01'}, {'stepSize': '0.001', 'filterType': 'LOT_SIZE', 'maxQty': '10000', 'minQty': '0.001'}, {'stepSize': '0.001', 'filterType': 'MARKET_LOT_SIZE', 'maxQty': '2000', 'minQty': '0.001'}, {'limit': 200, 'filterType': 'MAX_NUM_ORDERS'}, {'limit': 10, 'filterType': 'MAX_NUM_ALGO_ORDERS'}, {'notional': '5', 'filterType': 'MIN_NOTIONAL'}, {'multiplierDown': '0.9500', 'multiplierUp': '1.0500', 'multiplierDecimal': '4', 'filterType': 'PERCENT_PRICE'}], 'orderTypes': ['LIMIT', 'MARKET', 'STOP', 'STOP_MARKET', 'TAKE_PROFIT', 'TAKE_PROFIT_MARKET', 'TRAILING_STOP_MARKET'], 'timeInForce': ['GTC', 'IOC', 'FOK', 'GTX']}...
and so on.
I need to access the Value of 'quantityPrecision':.
Is there a way to like filter this list for the symbol value like 'BTCUSDT' and then return the Value of 'quantityPrecision':?
Thanks in Advance for any help.
info = client.futures_exchange_info()
def get_precision(symbol):
for x in info['symbols']:
if x['symbol'] == symbol:
return x['quantityPrecision']
print(get_precision('LTCUSDT'))
async function getLimits(asset) {
var filtered = await client.futures_exchange_info()
return Object.values( filtered.symbols).filter(O => O.symbol===asset)[0]
}
getLimits("BTCUSDT")
I have a problem...again. It is related to my previous question in Cron. I've got JSON value and I want to enter it in database. I need help in getting values in this nested dict. Plz help!
JSON
{'folders': [{'id': 94, 'name': 'Retargeting January 2021', 'totalBlacklisted': 606, 'uniqueSubscribers': 19988, 'totalSubscribers': 19382},
{'id': 90, 'name': 'Leads', 'totalBlacklisted': 0, 'uniqueSubscribers': 0, 'totalSubscribers': 0},
{'id': 84, 'name': 'Retargeting Year End', 'totalBlacklisted': 1367, 'uniqueSubscribers': 18847, 'totalSubscribers': 17480},
{'id': 79, 'name': 'CRM Folder', 'totalBlacklisted': 0, 'uniqueSubscribers': 3, 'totalSubscribers': 3},
{'id': 56, 'name': 'Curioo P', 'totalBlacklisted': 282, 'uniqueSubscribers': 3279, 'totalSubscribers': 2997}]}
Python
res = simplejson.loads(response.text)
self.env['get.folders'].create({
'id' : self.id,
'name': res['name'],
'email_blacklist': res['totalBlacklisted'],
'email_subscribers': res['totalSubscribers'],
'unique_subscribers': res['uniqueSubscribers'],
'foldersId': res['id'],
})
EDIT
At last it works. I try to spell out the values and I don't know how but it works this way. Thanks #Jack Dane for your help.
for folder in folders.get("folders"):
names = folder['name']
ids = folder['id']
blacklist = folder['totalBlacklisted']
subscribe = folder['totalSubscribers']
unique = folder['uniqueSubscribers']
self.env['sendinblue.get_folders'].create({
# 'id' : folder['id'],
'name_folder': names,
'email_blacklist': blacklist,
'email_subscribers': subscribe,
'unique_subscribers': unique,
'foldersId': ids,
})
You can loop through the folders using a foreach loop call the create function:
folders = {'folders': [{'id': 94, 'name': 'Retargeting January 2021', 'totalBlacklisted': 606, 'uniqueSubscribers': 19988, 'totalSubscribers': 19382},
{'id': 90, 'name': 'Leads', 'totalBlacklisted': 0, 'uniqueSubscribers': 0, 'totalSubscribers': 0},
{'id': 84, 'name': 'Retargeting Year End', 'totalBlacklisted': 1367, 'uniqueSubscribers': 18847, 'totalSubscribers': 17480},
{'id': 79, 'name': 'CRM Folder', 'totalBlacklisted': 0, 'uniqueSubscribers': 3, 'totalSubscribers': 3},
{'id': 56, 'name': 'Curioo P', 'totalBlacklisted': 282, 'uniqueSubscribers': 3279, 'totalSubscribers': 2997}]}
for folder in folders.get("folders"):
self.env['get.folders'].create({
'id' : self.id,
'name': folder['name'],
'email_blacklist': folder['totalBlacklisted'],
'email_subscribers': folder['totalSubscribers'],
'unique_subscribers': folder['uniqueSubscribers'],
'foldersId': folder['id'],
})
In my case, I have used folders as the variable which will be returned as a JSON.
If you need any clarification let me know,
Thanks,
messages=%5B%7B%22values%22%3A+%7B%22momentum%22%3A+%220.00%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22momentum%22%2C+%22indicator_number%22%3A+0%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22signal%22%3A+%5B%22momentum%22%5D%2C+%22hot%22%3A+0%2C+%22cold%22%3A+0%2C+%22candle_period%22%3A+%224h%22%2C+%22period_count%22%3A+10%7D%2C+%22status%22%3A+%22hot%22%7D%2C+%22status%22%3A+%22hot%22%2C+%22last_status%22%3A+%22hot%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22%22%2C+%22indicator_label%22%3A+%22%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%2C+%7B%22values%22%3A+%7B%22leading_span_a%22%3A+%220.00%22%2C+%22leading_span_b%22%3A+%220.00%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22ichimoku%22%2C+%22indicator_number%22%3A+1%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22signal%22%3A+%5B%22leading_span_a%22%2C+%22leading_span_b%22%5D%2C+%22hot%22%3A+true%2C+%22cold%22%3A+true%2C+%22candle_period%22%3A+%224h%22%2C+%22hot_label%22%3A+%22Bullish+Alert%22%2C+%22cold_label%22%3A+%22Bearish+Alert%22%2C+%22indicator_label%22%3A+%22ICHIMOKU+4+hr%22%2C+%22mute_cold%22%3A+false%7D%2C+%22status%22%3A+%22cold%22%7D%2C+%22status%22%3A+%22cold%22%2C+%22last_status%22%3A+%22cold%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22Bearish+Alert%22%2C+%22indicator_label%22%3A+%22ICHIMOKU+4+hr%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%2C+%7B%22values%22%3A+%7B%22bbp%22%3A+%220.96%22%2C+%22mfi%22%3A+%2298.05%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22bbp%22%2C+%22indicator_number%22%3A+1%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22candle_period%22%3A+%224h%22%2C+%22period_count%22%3A+20%2C+%22hot%22%3A+0.09%2C+%22cold%22%3A+0.8%2C+%22std_dev%22%3A+2%2C+%22signal%22%3A+%5B%22bbp%22%2C+%22mfi%22%5D%2C+%22hot_label%22%3A+%22Lower+Band%22%2C+%22cold_label%22%3A+%22Upper+Band+BB%22%2C+%22indicator_label%22%3A+%22Bollinger+4+hr%22%2C+%22mute_cold%22%3A+false%7D%2C+%22status%22%3A+%22cold%22%7D%2C+%22status%22%3A+%22cold%22%2C+%22last_status%22%3A+%22cold%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22Upper+Band+BB%22%2C+%22indicator_label%22%3A+%22Bollinger+4+hr%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%5D
i need to convert this data in python3 to standard json for post json api
any solution ?
thanks
That looks like it's been URL form encoded.
Try
import urllib.parse
import json
# note **without** the message= part
stuff = "%5B%7B%22values%22%3A+%7B%22momentum%22%3A+%220.00%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22momentum%22%2C+%22indicator_number%22%3A+0%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22signal%22%3A+%5B%22momentum%22%5D%2C+%22hot%22%3A+0%2C+%22cold%22%3A+0%2C+%22candle_period%22%3A+%224h%22%2C+%22period_count%22%3A+10%7D%2C+%22status%22%3A+%22hot%22%7D%2C+%22status%22%3A+%22hot%22%2C+%22last_status%22%3A+%22hot%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22%22%2C+%22indicator_label%22%3A+%22%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%2C+%7B%22values%22%3A+%7B%22leading_span_a%22%3A+%220.00%22%2C+%22leading_span_b%22%3A+%220.00%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22ichimoku%22%2C+%22indicator_number%22%3A+1%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22signal%22%3A+%5B%22leading_span_a%22%2C+%22leading_span_b%22%5D%2C+%22hot%22%3A+true%2C+%22cold%22%3A+true%2C+%22candle_period%22%3A+%224h%22%2C+%22hot_label%22%3A+%22Bullish+Alert%22%2C+%22cold_label%22%3A+%22Bearish+Alert%22%2C+%22indicator_label%22%3A+%22ICHIMOKU+4+hr%22%2C+%22mute_cold%22%3A+false%7D%2C+%22status%22%3A+%22cold%22%7D%2C+%22status%22%3A+%22cold%22%2C+%22last_status%22%3A+%22cold%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22Bearish+Alert%22%2C+%22indicator_label%22%3A+%22ICHIMOKU+4+hr%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%2C+%7B%22values%22%3A+%7B%22bbp%22%3A+%220.96%22%2C+%22mfi%22%3A+%2298.05%22%7D%2C+%22exchange%22%3A+%22binance%22%2C+%22market%22%3A+%22BNT%2FETH%22%2C+%22base_currency%22%3A+%22BNT%22%2C+%22quote_currency%22%3A+%22ETH%22%2C+%22indicator%22%3A+%22bbp%22%2C+%22indicator_number%22%3A+1%2C+%22analysis%22%3A+%7B%22config%22%3A+%7B%22enabled%22%3A+true%2C+%22alert_enabled%22%3A+true%2C+%22alert_frequency%22%3A+%22once%22%2C+%22candle_period%22%3A+%224h%22%2C+%22period_count%22%3A+20%2C+%22hot%22%3A+0.09%2C+%22cold%22%3A+0.8%2C+%22std_dev%22%3A+2%2C+%22signal%22%3A+%5B%22bbp%22%2C+%22mfi%22%5D%2C+%22hot_label%22%3A+%22Lower+Band%22%2C+%22cold_label%22%3A+%22Upper+Band+BB%22%2C+%22indicator_label%22%3A+%22Bollinger+4+hr%22%2C+%22mute_cold%22%3A+false%7D%2C+%22status%22%3A+%22cold%22%7D%2C+%22status%22%3A+%22cold%22%2C+%22last_status%22%3A+%22cold%22%2C+%22prices%22%3A+%22+Open%3A+0.000989+High%3A+0.000998+Low%3A+0.000980+Close%3A+0.000998%22%2C+%22lrsi%22%3A+%22%22%2C+%22creation_date%22%3A+%222020-05-10+16%3A16%3A23%22%2C+%22hot_cold_label%22%3A+%22Upper+Band+BB%22%2C+%22indicator_label%22%3A+%22Bollinger+4+hr%22%2C+%22price_value%22%3A+%7B%22open%22%3A+0.000989%2C+%22high%22%3A+0.000998%2C+%22low%22%3A+0.00098%2C+%22close%22%3A+0.000998%7D%2C+%22decimal_format%22%3A+%22%25.6f%22%7D%5D"
parsed = urllib.parse.unquote_plus(stuff) # <<< encoded form, get rid of +
as_json = json.loads(parsed)
print(as_json)
gives me
[{'values': {'momentum': '0.00'}, 'exchange': 'binance', 'market': 'BNT/ETH', 'base_currency': 'BNT', 'quote_currency': 'ETH', 'indicator': 'momentum', 'indicator_number': 0, 'analysis': {'config': {'enabled': True, 'alert_enabled': True, 'alert_frequency': 'once', 'signal': ['momentum'], 'hot': 0, 'cold': 0, 'candle_period': '4h', 'period_count': 10}, 'status': 'hot'}, 'status': 'hot', 'last_status': 'hot', 'prices': ' Open: 0.000989 High: 0.000998 Low: 0.000980 Close: 0.000998', 'lrsi': '', 'creation_date': '2020-05-10 16:16:23', 'hot_cold_label': '', 'indicator_label': '', 'price_value': {'open': 0.000989, 'high': 0.000998, 'low': 0.00098, 'close': 0.000998}, 'decimal_format': '%.6f'}, {'values': {'leading_span_a': '0.00', 'leading_span_b': '0.00'}, 'exchange': 'binance', 'market': 'BNT/ETH', 'base_currency': 'BNT', 'quote_currency': 'ETH', 'indicator': 'ichimoku', 'indicator_number': 1, 'analysis': {'config': {'enabled': True, 'alert_enabled': True, 'alert_frequency': 'once', 'signal': ['leading_span_a', 'leading_span_b'], 'hot': True, 'cold': True, 'candle_period': '4h', 'hot_label': 'Bullish Alert', 'cold_label': 'Bearish Alert', 'indicator_label': 'ICHIMOKU 4 hr', 'mute_cold': False}, 'status': 'cold'}, 'status': 'cold', 'last_status': 'cold', 'prices': ' Open: 0.000989 High: 0.000998 Low: 0.000980 Close: 0.000998', 'lrsi': '', 'creation_date': '2020-05-10 16:16:23', 'hot_cold_label': 'Bearish Alert', 'indicator_label': 'ICHIMOKU 4 hr', 'price_value': {'open': 0.000989, 'high': 0.000998, 'low': 0.00098, 'close': 0.000998}, 'decimal_format': '%.6f'}, {'values': {'bbp': '0.96', 'mfi': '98.05'}, 'exchange': 'binance', 'market': 'BNT/ETH', 'base_currency': 'BNT', 'quote_currency': 'ETH', 'indicator': 'bbp', 'indicator_number': 1, 'analysis': {'config': {'enabled': True, 'alert_enabled': True, 'alert_frequency': 'once', 'candle_period': '4h', 'period_count': 20, 'hot': 0.09, 'cold': 0.8, 'std_dev': 2, 'signal': ['bbp', 'mfi'], 'hot_label': 'Lower Band', 'cold_label': 'Upper Band BB', 'indicator_label': 'Bollinger 4 hr', 'mute_cold': False}, 'status': 'cold'}, 'status': 'cold', 'last_status': 'cold', 'prices': ' Open: 0.000989 High: 0.000998 Low: 0.000980 Close: 0.000998', 'lrsi': '', 'creation_date': '2020-05-10 16:16:23', 'hot_cold_label': 'Upper Band BB', 'indicator_label': 'Bollinger 4 hr', 'price_value': {'open': 0.000989, 'high': 0.000998, 'low': 0.00098, 'close': 0.000998}, 'decimal_format': '%.6f'}]
Whereas if you want a JSON string to POST somewhere, call as_string = json.dumps(parsed)