AttributeError on Oandapy API - python-3.7

I'm trying to do "100 lines of python code" for algorithmic trading and have been stopped early in my tracks with an attribute error.
I'm using sublime text and running it on python 3.7.
Here is the code I used:
import configparser
import oandapy as opy
config = configparser.ConfigParser()
config.read("oanda.cfg")
oanda = opy.API(environment = "practice",
access_token = config["oanda"] ["access_token"] )
Here are the results:
Traceback (most recent call last):
File "100lines.py", line 7, in <module>
oanda = opy.API(environment = "practice",
AttributeError: module 'oandapy' has no attribute 'API'


Try this:
# Print all attributes/functions in module
print(dir(opy))
and check the modules present
I think you'll have to use 'APIv20' rather than just 'API'


The api method is now called APIv20 in the current version (0.0.9).
so changing the last line to:
oanda = opy.APIv20(environment='practice', access_token=config['oanda']['access_token'])
will make solve your issue.

Related

IBM Cloud-Watson NLC - TypeError: __init__() got an unexpected keyword argument 'iam_apikey'

I am currently trying to deploy an application from a repo. (https://github.com/IBM/nlc-icd10-classifier#run-locally) But it gives me this error:
Traceback (most recent call last):
File "app.py", line 34, in <module>
iam_apikey=nlc_iam_apikey
TypeError: __init__() got an unexpected keyword argument 'iam_apikey'
I am on Python 3.6.8
app.py:
load_dotenv(os.path.join(os.path.dirname(__file__), ".env"))
nlc_username = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_USERNAME")
nlc_password = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_PASSWORD")
nlc_iam_apikey = os.environ.get("NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY")
classifier_id = os.environ.get("CLASSIFIER_ID")
# Use provided credentials from environment or pull from IBM Cloud VCAP
if nlc_iam_apikey != "placeholder":
NLC_SERVICE = NaturalLanguageClassifierV1(
iam_apikey=nlc_iam_apikey
)
elif nlc_username != "placeholder":
NLC_SERVICE = NaturalLanguageClassifierV1(
username=nlc_username,
password=nlc_password
.env:
CLASSIFIER_ID=<add_NLC_classifier_id>
#NATURAL_LANGUAGE_CLASSIFIER_USERNAME=<add_NLC_username>
#NATURAL_LANGUAGE_CLASSIFIER_PASSWORD=<add_NLC_password>
NATURAL_LANGUAGE_CLASSIFIER_IAM_APIKEY="placeholderapikeyforstackoverflolw"

It seems that you ran into an issue with the Watson SDK. Recently, with V4, they introduced a breaking change which I found in their release notes. There is a new, more abstract authentication mechanism that caters to different authentication types. You would need to slightly change the code for how NLC is initialized.
This is from the migration instructions:
For example, to pass a IAM apikey:
Before
from ibm_watson import MyService
service = MyService(
iam_apikey='{apikey}',
url='{url}'
)
After(V4.0)
from ibm_watson import MyService
from ibm_cloud_sdk_core.authenticators import IAMAuthenticator
authenticator = IAMAuthenticator('{apikey}')
service = MyService(
authenticator=authenticator
)
service.set_service_url('{url}')

Problem with connect facebookads library for extract data from Facebook with Marketing API using Python

I want to get info about ad campaign. And I start from this code to get campaign name. and I get this error :
Traceback (most recent call last):
File "C:/Users/win7/PycharmProjects/API_Facebook/dd.py", line 2, in <module>
from facebookads.adobjects.adaccount import AdAccount
File "C:\Users\win7\AppData\Local\Programs\Python\Python37-32\lib\site-packages\facebookads\adobjects\adaccount.py", line 1582
def get_insights(self, fields=None, params=None, async=False, batch=None, pending=False):
^
SyntaxError: invalid syntax
^
What is may be reason? and if you want, can give code examples how can I get more info about campaign?
Click here to view image: code and error

If you're using Python 3.7, use async_, not only async.
import os, re
path = r"path facebookads"
python_files = []
for dirpath, dirnames, filenames in os.walk(path):
for filename in filenames:
if filename.endswith(".py"):
python_files.append(os.path.join(dirpath, filename))
for dirpath, dirnames, filenames in os.walk(path):
for filename in filenames:
if filename.endswith(".py"):
python_files.append(os.path.join(dirpath, filename))
for python_file in python_files:
with open(python_file, "r") as f:
text = f.read()
revised_text = re.sub("async", "async_", text)
with open(python_file, "w") as f:
f.write(revised_text)

They updated and renamed the library, now it's facebook_ads and async argument was renamed to is_async

Try updating facebookads:
$ pip install --upgrade facebookads
I'm using facebookads==2.11.4.
More info: https://pypi.org/project/facebookads/

Hyperopt mongotrials issue with Pickle: AttributeError: 'module' object has no attribute

I'm trying to use Hyperopt parallel search with MongoDB, and encountered some issues with Mongotrials, which have been discussed here. I've tried all their methods, and I am still unable to find solutions to my specific problem. The specific model I'm trying to minimize is RadomForestRegressor from sklearn.
I've followed this tutorial. And I'm able to print out the calculated "fmin" with no issue.
Here are my steps so far:
1) Activate a virtual environment called "tensorflow" (I've installed all my libraries there)
2) Start MongoDB:
(tensorflow) bash-3.2$ mongod --dbpath . --port 1234 --directoryperdb --journal --nohttpinterface
3) Initiate workers:
(tensorflow) bash-3.2$ hyperopt-mongo-worker --mongo=localhost:1234/foo_db --poll-interval=0.1
4) Run my python code, and my python code is as follows:
import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error
from hyperopt import hp, fmin, tpe, STATUS_OK, Trials
from hyperopt.mongoexp import MongoTrials
# Preprocessing data
train_xg = pd.read_csv('train.csv')
n_train = len(train_xg)
print "Whole data set size: ", n_train
# Creating columns for features, and categorical features
features_col = [x for x in train_xg.columns if x not in ['id', 'loss', 'log_loss']]
cat_features_col = [x for x in train_xg.select_dtypes(include=['object']).columns if x not in ['id', 'loss', 'log_loss']]
for c in range(len(cat_features_col)):
train_xg[cat_features_col[c]] = train_xg[cat_features_col[c]].astype('category').cat.codes
# Use this to train random forest regressor
train_xg_x = np.array(train_xg[features_col])
train_xg_y = np.array(train_xg['loss'])
space_rf = { 'min_samples_leaf': hp.choice('min_samples_leaf', range(1,100)) }
trials = MongoTrials('mongo://localhost:1234/foo_db/jobs', exp_key='exp1')
def minMe(params):
# Hyperopt tuning for hyperparameters
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestRegressor
from hyperopt import STATUS_OK
try:
import dill as pickle
print('Went with dill')
except ImportError:
import pickle
def hyperopt_rf(params):
rf = RandomForestRegressor(**params)
return cross_val_score(rf, train_xg_x, train_xg_y).mean()
acc = hyperopt_rf(params)
print 'new acc:', acc, 'params: ', params
return {'loss': -acc, 'status': STATUS_OK}
best = fmin(fn=minMe, space=space_rf, trials=trials, algo=tpe.suggest, max_evals=100)
print "Best: ", best
5) After I run the above Python code, I get the following errors:
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:PROTOCOL mongo
INFO:hyperopt.mongoexp:USERNAME None
INFO:hyperopt.mongoexp:HOSTNAME localhost
INFO:hyperopt.mongoexp:PORT 1234
INFO:hyperopt.mongoexp:PATH /foo_db/jobs
INFO:hyperopt.mongoexp:DB foo_db
INFO:hyperopt.mongoexp:COLLECTION jobs
INFO:hyperopt.mongoexp:PASS None
INFO:hyperopt.mongoexp:no job found, sleeping for 0.7s
INFO:hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
INFO:hyperopt.mongoexp:job exception: 'module' object has no attribute 'minMe'
Traceback (most recent call last):
File "/Users/WernerChao/tensorflow/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1064, in run_one
domain = pickle.loads(blob)
AttributeError: 'module' object has no attribute 'minMe'
INFO:hyperopt.mongoexp:exiting with N=9223372036854775803 after 4 consecutive exceptions
6) Then Mongo workers would shut off.
Things I've tried:
install "dill" as the error suggested -> didn't work
Put global imports into the objective function so it can pickle -> didn't work
Put try except with "dill" or "pickle" as import -> didn't work
Does anyone have similar issues? I'm running out of ideas to try, and have been working on this for 2 days in vain. I think I am missing something really simple here, just can't seem to find it.
What am I missing?
Any suggestion is welcomed please!

Had the same problem in python 3.5. Installing Dill didn't help, nor dir setting workdir in MongoTrials or hyperopt-mongo-worker cli. hyperopt-mongo-worker doesn't seem to have access to __main__ where the function was defined:
AttributeError: Can't get attribute 'minMe' on <module '__main__' from ...hyperopt-mongo-worker
As #jaikumarm suggested, I circumvented the problem by writing a module file with all the required functions. However, instead of soft-linking it into the bin directory, I extended the PYTHONPATH before running hyperopt-mongo-worker:
export PYTHONPATH="${PYTHONPATH}:<dir_with_the_module.py>"
hyperopt-mongo-worker ...
That way, the hyperopt-monogo-worker is able to import the module containing minMe.

I fought with this for several days before coming up with a workable solution. there are two problems:
1. the mongo worker spawns off a separate process to run the optimizer so any context from your original python file is lost and unavailable for this new process.
2. the imports on this new process happen in the context of the hyperopt-mongo-worker scipy, which is in your case will be /Users/WernerChao/tensorflow/bin/.
So my solution is to make this new optimizer function completely self sufficient
optimizer.py
import numpy as np
import pandas as pd
from sklearn.metrics import mean_absolute_error
# Preprocessing data
train_xg = pd.read_csv('train.csv')
n_train = len(train_xg)
print "Whole data set size: ", n_train
# Creating columns for features, and categorical features
features_col = [x for x in train_xg.columns if x not in ['id', 'loss', 'log_loss']]
cat_features_col = [x for x in train_xg.select_dtypes(include=['object']).columns if x not in ['id', 'loss', 'log_loss']]
for c in range(len(cat_features_col)):
train_xg[cat_features_col[c]] = train_xg[cat_features_col[c]].astype('category').cat.codes
# Use this to train random forest regressor
train_xg_x = np.array(train_xg[features_col])
train_xg_y = np.array(train_xg['loss'])
def minMe(params):
# Hyperopt tuning for hyperparameters
from sklearn.model_selection import cross_val_score
from sklearn.ensemble import RandomForestRegressor
from hyperopt import STATUS_OK
try:
import dill as pickle
print('Went with dill')
except ImportError:
import pickle
def hyperopt_rf(params):
rf = RandomForestRegressor(**params)
return cross_val_score(rf, train_xg_x, train_xg_y).mean()
acc = hyperopt_rf(params)
print 'new acc:', acc, 'params: ', params
return {'loss': -acc, 'status': STATUS_OK}
wrapper.py
from hyperopt import hp, fmin, tpe, STATUS_OK, Trials
from hyperopt.mongoexp import MongoTrials
import optimizer
space_rf = { 'min_samples_leaf': hp.choice('min_samples_leaf', range(1,100)) }
best = fmin(fn=optimizer.minMe, space=space_rf, trials=trials, algo=tpe.suggest, max_evals=100)
print "Best: ", best
trials = MongoTrials('mongo://localhost:1234/foo_db/jobs', exp_key='exp1')
Once you have this code link the optimizer.py to the bin folder
ln -s /Users/WernerChao/Git/test/optimizer.py /Users/WernerChao/tensorflow/bin/
now run the wrapper.py and then the mongo worker it should be able to import the optimizer from its local context and run the minMe function.

Try to install Dill in the Python environment of your tensorflow (or possibly the worker):
/Users/WernerChao/tensorflow/lib/python2.7/site-packages/hyperopt
Your aim is to get rid of the hyperopt error message:
hyperopt.mongoexp:Error while unpickling. Try installing dill via "pip install dill" for enhanced pickling support.
This is because the Python by default cannot marshal a function. It requires dill library to extend Python's pickling module for serialising/de-serialising Python objects. In your case, it failed to serialise your function minMe().

I made a separate file which calculates the loss and copied it to /anaconda2/bin/
and
/anaconda2/lib/python2.7/site-packages/hyperopt
it is working fine.
This was my Traceback
Traceback (most recent call last):
File "/home/greatskull/anaconda2/bin/hyperopt-mongo-worker", line 6, in <module>
sys.exit(hyperopt.mongoexp.main_worker())
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1302, in main_worker
return main_worker_helper(options, args)
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1249, in main_worker_helper
mworker.run_one(reserve_timeout=float(options.reserve_timeout))
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/mongoexp.py", line 1073, in run_one
with temp_dir(workdir, erase_created_workdir), working_dir(workdir):
File "/home/greatskull/anaconda2/lib/python2.7/contextlib.py", line 17, in __enter__
return self.gen.next()
File "/home/greatskull/anaconda2/lib/python2.7/site-packages/hyperopt/utils.py", line 229, in temp_dir
os.makedirs(dir)
File "/home/greatskull/anaconda2/lib/python2.7/os.py", line 150, in makedirs
makedirs(head, mode)
File "/home/greatskull/anaconda2/lib/python2.7/os.py", line 157, in makedirs
mkdir(name, mode)

OSError: cannot identify image file <_io.StringIO object at 0x00000000022810D8>

Use win8 and python3.4,I need to convert text to images.So I try to implement a himself.But I encounter a OSError.I try to use BytesIO instead of StringIO,it will pop error "OSError: cannot identify image file <_io.BytesIO object at xxxx>.
I still can't find the reason.
Codes as follow:
# -*- coding: utf-8 -*-
import os
import pygame
from io import StringIO,BytesIO
from PIL import Image
pygame.init()
text = u'This is a test text，test 123.'
font_path = "C:/windows/fonts/simsun.ttc"
im = Image.new("RGB",(300,50),(255,255,255))
font = pygame.font.Font(os.path.join(font_path),22)
rtext = font.render(text, True, (0,0,0),(255,255,255))
sio = StringIO()
print(sio.getvalue())
pygame.image.save(rtext, sio)
sio.seek(0)
#print(sio.getvalue())
line = Image.open(sio)
im.paste(line,(10,5))
im.show()
im.save("t1.png")
As is I get this error:
Traceback (most recent call last):
File "D:/mypython/learn/demo.py", line 19, in <module>
line = Image.open(sio)
File "D:\Python34\lib\site-packages\PIL\Image.py", line 2319, in open
% (filename if filename else fp))
OSError: cannot identify image file <_io.StringIO object at 0x00000000022810D8>

line = Image.open(sio)
As far as I am concerned, sio is still a StringIO(). If you are trying to open it as an image, try opening it with line = Image.open(name), where name is the actual name of the image, not a StringIO().

Tornado on python3

My goal is to run http server on python3 using tornado (http://www.tornadoweb.org/).
I started with running example code found on their webpage:
import tornado.httpserver
import tornado.ioloop
from tornado import httputil
def handle_request(request):
message = "You requested %s\n" % request.uri
request.connection.write_headers(
httputil.ResponseStartLine('HTTP/1.1', 200, 'OK'),
{"Content-Length": str(len(message))})
request.connection.write(message)
request.connection.finish()
http_server = tornado.httpserver.HTTPServer(handle_request)
http_server.listen(8080)
tornado.ioloop.IOLoop.instance().start()
This code throws following exception when receiving any http request:
ERROR:tornado.application:Uncaught exception
Traceback (most recent call last):
File "/usr/local/lib/python3.4/dist-packages/tornado/http1connection.py", line 234, in _read_message
delegate.finish()
File "/usr/local/lib/python3.4/dist-packages/tornado/httpserver.py", line 280, in finish
self.server.request_callback(self.request)
File "test.py", line 10, in handle_request
{"Content-Length": str(len(message))})
File "/usr/local/lib/python3.4/dist-packages/tornado/http1connection.py", line 367, in write_headers
lines.extend([utf8(n) + b": " + utf8(v) for n, v in headers.get_all()])
AttributeError: 'dict' object has no attribute 'get_all'
Whats wrong ? This is sample code, so it should work and problem is somewhere in my enviroment ?
I tried this both on latest Ubuntu and Win 7 and it gave me same error.
Thanks in advance

The documentation had a bug, fixed recently. For any version of Python, you can't pass a raw dict to write_headers. Instead you must wrap the dict in an HTTPHeaders object. For Python 3, the message must be a bytes instance. With both fixes:
def handle_request(request):
message = ("You requested %s\n" % request.uri).encode('ascii')
request.connection.write_headers(
httputil.ResponseStartLine('HTTP/1.1', 200, 'OK'),
httputil.HTTPHeaders({"Content-Length": str(len(message))}))
request.connection.write(message)
request.connection.finish()