def send(url, data, appid, sign, accesstoken=''):
utctime = datetime.datetime.utcnow()
timestamp = utctime.strftime('%Y-%m-%d %H:%M:%S')
headers = {
"X-PPD-APPID": appid,
"X-PPD-SIGN": sign,
"X-PPD-TIMESTAMP": timestamp,
"X-PPD-TIMESTAMP-SIGN": rsa.sign("%s%s" % (appid, timestamp)),
"Accept": "application/json;charset=UTF-8"
}
if accesstoken.strip():
headers["X-PPD-ACCESSTOKEN"] = accesstoken
status_code, response_str = http_client.http_post(url,
data.encode('utf-8'),
headers=headers)
retry_count = 0
while status_code != 200:
logging.warning("Service unavailable for a while.")
retry_count = retry_count + 1
time.sleep(1)
if retry_count > 3:
logging.error(
"Service failed. Please wait a moment and retry.")
# catch this at user code to wait for a reasonable long time
raise RuntimeError("Wow, requests are sent too frequently...")
status_code, response_str = http_client.http_post(
url, data.encode('utf-8'), headers=headers)
return response_str
def get_user_fund_balance(appid, access_token):
#获取用户资金余额
access_url = "http://gw.open.ppdai.com/balance/balanceService/QueryBalance"
data = {}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url,json.dumps(data) , appid, sign,access_token)
def getBalance(self):
access_url = "https://openapi.ppdai.com/balance/balanceService/QueryBalance"
data = {}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), appid, sign, self.token)
self.balance = list_result["Balance"][0]["Balance"]
log("balance end",self.balance)
return self.balance
def get_batch_listing_infos(appid, data):
#新版散标详情批量接口（请求列表不大于10）
utctime = datetime.datetime.utcnow()
#data = {"timestamp":utctime.strftime('%Y-%m-%d %H:%M:%S')}#time.strftime('%Y-%m-%d %H:%M:%S',)
access_url = "http://gw.open.ppdai.com/invest/LLoanInfoService/BatchListingInfos"
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data) , appid, sign)
def get_listingids(appid, access_token):
#获得投标标的
access_url = "http://gw.open.ppdai.com/invest/LLoanInfoService/LoanList"
data = {
"PageIndex": 3,
"StartDateTime": "2015-11-11 12:00:00.000"
}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url,json.dumps(data) , appid, sign)
def getListingIdInfo(ListingIds):
access_url = "https://openapi.ppdai.com/listing/openapiNoAuth/batchListingInfo"
data = {
"ListingIds": ListingIds
}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data) , appid, sign)
if (list_result["Result"] != 1):
log("error getListingIdInfo")
return list_result["LoanInfos"]
def get_loan_detail_list(listing_ids):
access_url = "http://gw.open.ppdai.com/invest/LLoanInfoService/BatchListingInfos"
data = {"ListingIds": listing_ids}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), appid, sign)
# check result
list_result_obj = json.loads(list_result.decode('utf-8'))
if list_result_obj["Result"] == 1:
return list_result_obj
else:
logging.error("Fail to get detail loan list.")
return None
def bid(self,ListingId):
access_url = "https://openapi.ppdai.com/listing/openapi/bid"
access_token = self.token
data = {
"ListingId": ListingId,
"Amount": 50,
"UseCoupon":"true"
}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url,json.dumps(data) , appid, sign,access_token)
if list_result["Result"] != 0:
log("bid faild",list_result)
else:
log("bid success",list_result)
def send(url, data, appid, sign, accesstoken=''):
utctime = datetime.datetime.utcnow()
timestamp = utctime.strftime('%Y-%m-%d %H:%M:%S')
headers = {
"X-PPD-APPID": appid,
"X-PPD-SIGN": sign,
"X-PPD-TIMESTAMP": timestamp,
"X-PPD-TIMESTAMP-SIGN": rsa.sign("%s%s" % (appid, timestamp))
}
if accesstoken.strip():
headers["X-PPD-ACCESSTOKEN"] = accesstoken
data = data.lower()
result = http_client.http_post(url, data, headers=headers)
print("send_data:%s" % (result))
return result
def send(url, data, appid, sign, accesstoken=''):
utctime = datetime.datetime.utcnow()
timestamp = utctime.strftime('%Y-%m-%d %H:%M:%S')
headers = {
"X-PPD-APPID": appid,
"X-PPD-SIGN": sign,
"X-PPD-TIMESTAMP": timestamp,
"X-PPD-TIMESTAMP-SIGN": rsa.sign("%s%s" % (appid, timestamp)),
"Accept": "application/json;charset=UTF-8"
}
if accesstoken.strip():
headers["X-PPD-ACCESSTOKEN"] = accesstoken
result = http_client.http_post(url, data, headers=headers)
#print("send_data:\n%s" % (result))
return json.loads(result)
def get_loan_list(index, date=None): # date "2015-11-11 12:00:00.000"
access_url = "http://gw.open.ppdai.com/invest/LLoanInfoService/LoanList"
if date is None:
data = {"PageIndex": index}
else:
data = {"PageIndex": index, "StartDateTime": date}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), appid, sign)
# check result
list_result_obj = json.loads(list_result)
if list_result_obj["Result"] == 1:
return list_result_obj
else:
logging.error("Fail to get loan list.")
return None
def getListingIdList():
access_url = "https://openapi.ppdai.com/listing/openapiNoAuth/loanList"
data = {
"PageIndex": 1,
"StartDateTime": "2015-11-11 12:00:00.000"
}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data) , appid, sign)
if (list_result["Result"] != 1):
log("error getListingIdList")
return []
ListingIds = []
for LoanInfo in list_result["LoanInfos"]:
if LoanInfo["CreditCode"] != "AA":
ListingIds.append(LoanInfo["ListingId"])
return ListingIds
def make_bid(listing_id, amount):
access_url = "http://gw.open.ppdai.com/invest/BidService/Bidding"
access_token = "1ff70da4-909e-4ce0-ab17-0f75debd5c1d"
data = {"ListingId": listing_id, "Amount": amount, "UseCoupon": "true"}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), appid, sign,
access_token)
# check result
list_result_obj = json.loads(list_result)
if list_result_obj["Result"] == 0:
logging.info("Success to bid %s", listing_id)
return list_result_obj
else:
logging.warning("Warning: fail to make bid %s. Reason: %s", listing_id,
list_result_obj["ResultMessage"])
return None
data = {
"StartTime":
time.strftime('%Y-%m-%d',
time.localtime(float(StartTime))),
"EndTime":
time.strftime('%Y-%m-%d', time.localtime(float(current))),
"PageIndex":
1,
"PageSize":
500
}
while True:
time.sleep(0.5)
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), APPID,
sign, AccessToken)
if list_result == '':
continue
else:
list_result = json.loads(list_result)
break
for item in list_result['BidList']:
if int(item['ListingId']) == 0:
continue
total += 1
listings.append([
item['ListingId'],
def invest():
if not 'OpenID' in session:
return redirect(url_for('index'))
refresh()
# report()
dataset = {}
(db, cursor) = connectdb()
cursor.execute("select * from json_data where page=%s", ['invest'])
json_data = cursor.fetchall()
dataset['json'] = {
item['keyword']: json.loads(item['json'])
for item in json_data
}
tmp = []
for key, value in dataset['json']['strategy_stat'].items():
value['name'] = key
value[u'平均金额'] = int(value[u'总金额'] / value[u'数量'])
for k, v in value.items():
if k in ['平均利率', '平均期限']:
value[k] = '%.2f' % value[k]
elif k in ['10日坏标逾期率', '30日坏标逾期率', '90日坏标逾期率']:
value[k] = '%.3f' % value[k]
tmp.append(value)
dataset['json']['strategy_stat'] = tmp
cursor.execute("select * from strategy where OpenID=%s", ['0'])
dataset['sys'] = cursor.fetchall()
cursor.execute("select * from strategy where OpenID=%s",
[session['OpenID']])
dataset['my'] = cursor.fetchall()
cursor.execute("select strategy from user where OpenID=%s",
[session['OpenID']])
if len(dataset['my']) < 4:
dataset['add'] = True
else:
dataset['add'] = False
dataset['strategy_count'] = 0
dataset['strategy_weight'] = {u'初始评级': 0, u'借款利率': 0, u'借款期限': 0}
sys_strategy = cursor.fetchone()['strategy']
if not sys_strategy == '':
sys_strategy = sys_strategy.split('-')
for s in sys_strategy:
for x in xrange(0, len(dataset['sys'])):
if int(dataset['sys'][x]['id']) == int(s):
dataset['sys'][x]['active'] = 1
dataset['strategy_count'] += 1
content = json.loads(dataset['sys'][x]['content'])
for key in content.keys():
if dataset['strategy_weight'].has_key(key):
dataset['strategy_weight'][key] += 1
break
for item in dataset['my']:
if int(item['active']) == 1:
content = json.loads(item['content'])
for key in content.keys():
if dataset['strategy_weight'].has_key(key):
dataset['strategy_weight'][key] += 1
dataset['strategy_weight'] = {
'x': [key for key in dataset['strategy_weight'].keys()],
'data': [value for value in dataset['strategy_weight'].values()]
}
cursor.execute(
"select balance, balanceBid, balanceWithdraw from user where OpenID=%s",
[session['OpenID']])
dataset['balance'] = cursor.fetchone()
cursor.execute("select count(*) as count from bidding where OpenID=%s",
[session['OpenID']])
dataset['bidding_count'] = cursor.fetchone()['count']
cursor.execute(
"select count(*) as count from strategy where OpenID=%s and active=%s",
[session['OpenID'], 1])
dataset['strategy_count'] += cursor.fetchone()['count']
dates = []
start = 1483200000
while True:
b = time2str(start, '%Y-%m-%d')
if b[:4] == '2017':
dates.append(b)
start += 3600 * 24
else:
break
dataset['calendar'] = {
'count': {d: 0
for d in dates},
'amount': {d: 0
for d in dates}
}
cursor.execute(
"select * from bidding where OpenID=%s order by timestamp asc",
[session['OpenID']])
biddings = cursor.fetchall()
for item in biddings:
d = time2str(float(item['timestamp']), '%Y-%m-%d')
dataset['calendar']['count'][d] += 1
dataset['calendar']['amount'][d] += item['amount']
dataset['calendar']['max_count'] = np.max(
[v for v in dataset['calendar']['count'].values()])
dataset['calendar']['count'] = [[
d, dataset['calendar']['count'][d], dataset['calendar']['amount'][d]
] for d in dates]
if len(biddings) > 0:
cursor.execute(
"select ListingId, CreditCode, Months, CurrentRate, Title from listing where ListingId in %s",
[[x['ListingId'] for x in biddings]])
tmp = cursor.fetchall()
tmp = {str(t['ListingId']): t for t in tmp}
d = []
for x in range(0, len(biddings)):
lid = str(biddings[x]['ListingId'])
if tmp.has_key(lid):
biddings[x]['CreditCode'] = tmp[lid]['CreditCode']
biddings[x]['Months'] = tmp[lid]['Months']
biddings[x]['CurrentRate'] = tmp[lid]['CurrentRate']
biddings[x]['Title'] = tmp[lid]['Title']
biddings[x]['timestamp'] = time2str(
float(biddings[x]['timestamp']), "%Y-%m-%d %H:%M:%S")
d.append(biddings[x])
biddings = d
cursor.execute(
"select id, name from strategy where OpenID=%s or OpenID=%s",
['0', session['OpenID']])
tmp = cursor.fetchall()
tmp = {str(t['id']): t['name'] for t in tmp}
for x in range(0, len(biddings)):
biddings[x]['strategy'] = tmp[str(biddings[x]['strategyId'])]
dataset['biddings'] = biddings
while True:
access_url = "http://gw.open.ppdai.com/invest/LLoanInfoService/LoanList"
data = {
"PageIndex": 1,
}
sort_data = rsa.sort(data)
sign = rsa.sign(sort_data)
list_result = client.send(access_url, json.dumps(data), APPID, sign)
if list_result == '':
continue
else:
list_result = json.loads(list_result)
break
mapping = {}
mapping['AAA'] = 15
mapping['AA'] = 10
mapping['A'] = 5
mapping['B'] = 3
mapping['C'] = 1
mapping['D'] = 0
mapping['E'] = 0
mapping['F'] = 0
colorset = {}
colorset['AAA'] = 'rgba(243, 230, 162, 0.9)'
colorset['AA'] = 'rgba(234, 126, 83, 0.9)'
colorset['A'] = 'rgba(221, 107, 102, 0.9)'
colorset['B'] = 'rgba(230, 157, 135, 0.9)'
colorset['C'] = 'rgba(215, 135, 230, 0.9)'
colorset['D'] = 'rgba(110, 113, 199, 0.9)'
colorset['E'] = 'rgba(109, 188, 191, 0.9)'
colorset['F'] = 'rgba(117, 179, 117, 0.9)'
for x in range(0, len(list_result['LoanInfos'])):
item = list_result['LoanInfos'][x]
list_result['LoanInfos'][x]['score'] = mapping[item['CreditCode']] * (
int(item['Rate']) - 9) * (6 / float(item['Months']))
list_result['LoanInfos'][x][
'ratio'] = 95 - 95 * item['RemainFunding'] / item['Amount']
list_result['LoanInfos'][x]['color'] = colorset[item['CreditCode']]
list_result['LoanInfos'].sort(key=lambda x: x['score'], reverse=True)
dataset['listings'] = list_result['LoanInfos'][:10]
if len(dataset['listings']) == 0:
data['listing_max'] = 0.0000001
else:
dataset['listing_max'] = np.max(
[float(x['score']) for x in dataset['listings']])
for x in xrange(0, len(dataset['listings'])):
dataset['listings'][x]['score'] = '%.2f' % (
0.98 * dataset['listings'][x]['score'] / dataset['listing_max'])
dataset['listings'][x]['Amount'] = int(
dataset['listings'][x]['Amount'])
dataset['listings'][x]['RemainFunding'] = int(
dataset['listings'][x]['RemainFunding'])
closedb(db, cursor)
return render_template('invest.html',
auth=is_auth(),
datasetJson=json.dumps(dataset),
dataset=dataset)
