Develop Reference

Weird sequence when writing into txt document

Hi everyone this is my first time here, and I am a beginner in Python. I am in the middle of writing a program that returns a txt document containing information about a stock (Watchlist Info.txt), based on the input of another txt document containing the company names (Watchlist).
To achieve this, I have written 3 functions, of which 2 functions reuters_ticker() and stock_price() are completed as shown below:
def reuters_ticker(desired_search):
#from company name execute google search for and return reuters stock ticker
try:
from googlesearch import search
except ImportError:
print('No module named google found')
query = desired_search + ' reuters'
for j in search(query, tld="com.sg", num=1, stop=1, pause=2):
result = j
ticker = re.search(r'\w+\.\w+$', result)
return ticker.group()
Stock Price:
def stock_price(company, doc=None):
ticker = reuters_ticker(company)
request = 'https://www.reuters.com/companies/' + ticker
raw_main = pd.read_html(request)
data1 = raw_main[0]
data1.set_index(0, inplace=True)
data1 = data1.transpose()
data2 = raw_main[1]
data2.set_index(0, inplace=True)
data2 = data2.transpose()
stock_info = pd.concat([data1,data2], axis=1)
if doc == None:
print(company + '\n')
print('Previous Close: ' + str(stock_info['Previous Close'][1]))
print('Forward PE: ' + str(stock_info['Forward P/E'][1]))
print('Div Yield(%): ' + str(stock_info['Dividend (Yield %)'][1]))
else:
from datetime import date
with open(doc, 'a') as output:
output.write(date.today().strftime('%d/%m/%y') + '\t' + str(stock_info['Previous Close'][1]) + '\t' + str(stock_info['Forward P/E'][1]) + '\t' + '\t' + str(stock_info['Dividend (Yield %)'][1]) + '\n')
output.close()
The 3rd function, watchlist_report(), is where I am getting problems with writing the information in the format as desired.
def watchlist_report(watchlist):
with open(watchlist, 'r') as companies, open('Watchlist Info.txt', 'a') as output:
searches = companies.read()
x = searches.split('\n')
for i in x:
output.write(i + ':\n')
stock_price(i, doc='Watchlist Info.txt')
output.write('\n')
When I run watchlist_report('Watchlist.txt'), where Watchlist.txt contains 'Apple' and 'Facebook' each on new lines, my output is this:
26/04/20 275.03 22.26 1.12
26/04/20 185.13 24.72 --
Apple:
Facebook:
Instead of what I want and would expect based on the code I have written in watchlist_report():
Apple:
26/04/20 275.03 22.26 1.12
Facebook:
26/04/20 185.13 24.72 --
Therefore, my questions are:
1) Why is my output formatted this way?
2) Which part of my code do I have to change to make the written output in my desired format?
Any other suggestions about how I can clean my code and any libraries I can use to make my code nicer are also appreciated!

You handle two different file-handles - the file-handle inside your watchlist_report gets closed earlier so its being written first, before the outer functions file-handle gets closed, flushed and written.
Instead of creating a new open(..) in your function, pass the current file handle:
def watchlist_report(watchlist):
with open(watchlist, 'r') as companies, open('Watchlist Info.txt', 'a') as output:
searches = companies.read()
x = searches.split('\n')
for i in x:
output.write(i + ':\n')
stock_price(i, doc = output) # pass the file handle
output.write('\n')
Inside def stock_price(company, doc=None): use the provided filehandle:
def stock_price(company, output = None): # changed name here
# [snip] - removed unrelated code for this answer for brevity sake
if output is None: # check for None using IS
print( ... ) # print whatever you like here
else:
from datetime import date
output.write( .... ) # write whatever you want it to write
# output.close() # do not close, the outer function does this
Do not close the file handle in the inner function, the context handling with(..) of the outer function does that for you.
The main takeaway for file handling is that things you write(..) to your file are not neccessarily placed there immediately. The filehandler chooses when to actually persist data to your disk, the latests it does that is when it goes out of scope (of the context handler) or when its internal buffer reaches some threshold so it "thinks" it is now prudent to alter to data on your disc. See How often does python flush to a file? for more infos.

Confused by a python type errror

I've been using python for a little while and have made some improvements but this a new error to me. I'm trying to learn social media analysis for my career and that's why I am trying out this set of code here.
I've de bugged one error but this one, which appears at line 81, has got me stumped as I can't see why the function "def get_user_objects(follower_ids):" returns none and what i'd need to change it in accordance with previous advice on other questions here.
Here's script to that point for simplicity. All help appreciated.
The error, to repeat is TypeError: object of type 'NoneType' has no len()
from tweepy import OAuthHandler
from tweepy import API
from collections import Counter
from datetime import datetime, date, time, timedelta
import sys
import json
import os
import io
import re
import time
# Helper functions to load and save intermediate steps
def save_json(variable, filename):
with io.open(filename, "w", encoding="utf-8") as f:
f.write(str(json.dumps(variable, indent=4, ensure_ascii=False)))
def load_json(filename):
ret = None
if os.path.exists(filename):
try:
with io.open(filename, "r", encoding="utf-8") as f:
ret = json.load(f)
except:
pass
return ret
def try_load_or_process(filename, processor_fn, function_arg):
load_fn = None
save_fn = None
if filename.endswith("json"):
load_fn = load_json
save_fn = save_json
else:
load_fn = load_bin
save_fn = save_bin
if os.path.exists(filename):
print("Loading " + filename)
return load_fn(filename)
else:
ret = processor_fn(function_arg)
print("Saving " + filename)
save_fn(ret, filename)
return ret
# Some helper functions to convert between different time formats and
perform date calculations
def twitter_time_to_object(time_string):
twitter_format = "%a %b %d %H:%M:%S %Y"
match_expression = "^(.+)\s(\+[0-9][0-9][0-9][0-9])\s([0-9][0-9][0-9]
[09])$"
match = re.search(match_expression, time_string)
if match is not None:
first_bit = match.group(1)
second_bit = match.group(2)
last_bit = match.group(3)
new_string = first_bit + " " + last_bit
date_object = datetime.strptime(new_string, twitter_format)
return date_object
def time_object_to_unix(time_object):
return int(time_object.strftime("%s"))
def twitter_time_to_unix(time_string):
return time_object_to_unix(twitter_time_to_object(time_string))
def seconds_since_twitter_time(time_string):
input_time_unix = int(twitter_time_to_unix(time_string))
current_time_unix = int(get_utc_unix_time())
return current_time_unix - input_time_unix
def get_utc_unix_time():
dts = datetime.utcnow()
return time.mktime(dts.timetuple())
# Get a list of follower ids for the target account
def get_follower_ids(target):
return auth_api.followers_ids(target)
# Twitter API allows us to batch query 100 accounts at a time
# So we'll create batches of 100 follower ids and gather Twitter User
objects for each batch
def get_user_objects(follower_ids):
batch_len = 100
num_batches = len(follower_ids)/100
batches = (follower_ids[i:i+batch_len] for i in range(0,
len(follower_ids), batch_len))
all_data = []
for batch_count, batch in enumerate(batches):
sys.stdout.write("\r")
sys.stdout.flush()
sys.stdout.write("Fetching batch: " + str(batch_count) + "/" +
str(num_batches))
sys.stdout.flush()
users_list = auth_api.lookup_users(user_ids=batch)
users_json = (map(lambda t: t._json, users_list))
all_data += users_json
return all_data
# Creates one week length ranges and finds items that fit into those range
boundaries
def make_ranges(user_data, num_ranges=20):
range_max = 604800 * num_ranges
range_step = range_max/num_ranges
# We create ranges and labels first and then iterate these when going
through the whole list
# of user data, to speed things up
ranges = {}
labels = {}
for x in range(num_ranges):
start_range = x * range_step
end_range = x * range_step + range_step
label = "%02d" % x + " - " + "%02d" % (x+1) + " weeks"
labels[label] = []
ranges[label] = {}
ranges[label]["start"] = start_range
ranges[label]["end"] = end_range
for user in user_data:
if "created_at" in user:
account_age = seconds_since_twitter_time(user["created_at"])
for label, timestamps in ranges.iteritems():
if account_age > timestamps["start"] and account_age <
timestamps["end"]:
entry = {}
id_str = user["id_str"]
entry[id_str] = {}
fields = ["screen_name", "name", "created_at",
"friends_count", "followers_count", "favourites_count", "statuses_count"]
for f in fields:
if f in user:
entry[id_str][f] = user[f]
labels[label].append(entry)
return labels
if __name__ == "__main__":
account_list = []
if (len(sys.argv) > 1):
account_list = sys.argv[1:]
if len(account_list) < 1:
print("No parameters supplied. Exiting.")
sys.exit(0)
consumer_key="XXXXXXX"
consumer_secret="XXXXXX"
access_token="XXXXXXX"
access_token_secret="XXXXXXXX"
auth = OAuthHandler(consumer_key, consumer_secret)
auth.set_access_token(access_token, access_token_secret)
auth_api = API(auth)
for target in account_list:
print("Processing target: " + target)
# Get a list of Twitter ids for followers of target account and save it
filename = target + "_follower_ids.json"
follower_ids = try_load_or_process(filename, get_follower_ids,
target)
# Fetch Twitter User objects from each Twitter id found and save the data
filename = target + "_followers.json"
user_objects = try_load_or_process(filename, get_user_objects,
follower_ids)
total_objects = len(user_objects)
# Record a few details about each account that falls between specified age
ranges
ranges = make_ranges(user_objects)
filename = target + "_ranges.json"
save_json(ranges, filename)
# Print a few summaries
print
print("\t\tFollower age ranges")
print("\t\t===================")
total = 0
following_counter = Counter()
for label, entries in sorted(ranges.iteritems()):
print("\t\t" + str(len(entries)) + " accounts were created
within " + label)
total += len(entries)
for entry in entries:
for id_str, values in entry.iteritems():
if "friends_count" in values:
following_counter[values["friends_count"]] += 1
print("\t\tTotal: " + str(total) + "/" + str(total_objects))
print
print("\t\tMost common friends counts")
print("\t\t==========================")
total = 0
for num, count in following_counter.most_common(20):
total += count
print("\t\t" + str(count) + " accounts are following " +
str(num) + " accounts")
print("\t\tTotal: " + str(total) + "/" + str(total_objects))
print
print

The immediate problem is in load_json: you assume its return value is a list or dict, or something that can be passed to len. However, it can return None in a number of circumstances:
The file to read from isn't found
There is some error reading from the file
There is a problem decoding the contents of the file
The file contains just the JSON value null.
At no point after you call load_json do you check its return value.
Worse, you catch and ignore any exception that might occur in load_json, causing it to silently return None with no indication that something went wrong.
The function would be better written like
def load_json(filename):
with io.open(filename, "r", encoding="utf-8") as f:
return json.load(f)
At least now, any errors will raise an uncaught exception, making it more obvious that there was a problem and providing a clue as to what the problem was. The golden rule of exception handling is to only catch the exceptions you can do something about, and if you can't do anything about a caught exception, re-raise it.

You could check for the resultant value and follow accordingly:
# Fetch Twitter User objects from each Twitter id found and save the data
filename = target + "_followers.json"
res_get_user_objects = get_user_objects()
if res_get_user_objects is not None:
user_objects = try_load_or_process(filename, get_user_objects,
follower_ids)
total_objects = len(user_objects)
else:
# handle it otherwise

Data gets mixed up while trying to transfer it to arangodb

I'm trying to transfer ca. 10GB of json data (tweets in my case) to a collection in arangodb. I'm also trying to use joblib for it:
from ArangoConn import ArangoConn
import Userdata as U
import encodings
from joblib import Parallel,delayed
import json
from glob import glob
import time
def progress(total, prog, start, stri = ""):
if(prog == 0):
print("")
prog = 1;
perc = prog / total
diff = time.time() - start
rem = (diff / prog) * (total - prog)
bar = ""
for i in range(0,int(perc*20)):
bar = bar + "|"
for i in range(int(perc*20),20):
bar = bar + " "
print("\r"+"progress: " + "[" + bar + "] " + str(prog) + " of " +
str(total) + ": {0:.1f}% ".format(perc * 100) + "- " +
time.strftime("%H:%M:%S", time.gmtime(rem)) + " " + stri, end="")
def processfile(filepath):
file = open(filepath,encoding='utf-8')
s = file.read()
file.close()
data = json.loads(s)
Parallel(n_jobs=12, verbose=0, backend="threading"
(map(delayed(ArangoConn.createDocFromObject), data))
files = glob(U.path+'/*.json')
i = 1
j = len(files)
starttime = time.time()
for f in files:
progress(j,i,starttime,f)
i = i+1
processfile(f)
and
from pyArango.connection import Connection
import Userdata as U
import time
class ArangoConn:
def __init__(self,server,user,pw,db,collectionname):
self.server = server
self.user = user
self.pw = pw
self.db = db
self.collectionname = collectionname
self.connection = None
self.dbHandle = self.connect()
if not self.dbHandle.hasCollection(name=self.collectionname):
coll = self.dbHandle.createCollection(name=collectionname)
else:
coll = self.dbHandle.collections[collectionname]
self.collection = coll
def db_createDocFromObject(self, obj):
data = obj.__dict__()
doc = self.collection.createDocument()
for key,value in data.items():
doc[key] = value
doc._key= str(int(round(time.time() * 1000)))
doc.save()
def connect(self):
self.connection = Connection(arangoURL=self.server + ":8529",
username=self.user, password=self.pw)
if not self.connection.hasDatabase(self.db):
db = self.connection.createDatabase(name=self.db)
else:
db = self.connection.databases.get(self.db)
return db
def disconnect(self):
self.connection.disconnectSession()
def getAllData(self):
docs = []
for doc in self.collection.fetchAll():
docs.append(self.doc_to_result(doc))
return docs
def addData(self,obj):
self.db_createDocFromObject(obj)
def search(self,collection,search,prop):
docs = []
aql = """FOR q IN """+collection+""" FILTER q."""+prop+""" LIKE
"%"""+search+"""%" RETURN q"""
results = self.dbHandle.AQLQuery(aql, rawResults=False, batchSize=1)
for doc in results:
docs.append(self.doc_to_result(doc))
return docs
def doc_to_result(self,arangodoc):
modstore = arangodoc.getStore()
modstore["_key"] = arangodoc._key
return modstore
def db_createDocFromJson(self,json):
for d in json:
doc = self.collection.createDocument()
for key,value in d.items():
doc[key] = value
doc._key = str(int(round(time.time() * 1000)))
doc.save()
#staticmethod
def createDocFromObject(obj):
c = ArangoConn(U.url, U.user, U.pw, U.db, U.collection)
data = obj
doc = c.collection.createDocument()
for key, value in data.items():
doc[key] = value
doc._key = doc["id"]
doc.save()
c.connection.disconnectSession()
It kinda works like that. My problem is that the data that lands in the database is somehow mixed up.
as you can see in the screenshot "id" and "id_str" are not the same - as they should be.
what i investigated so far:
I thought that at some points the default keys in the databese may "collide"
because of the threading so I set the key to the tweet id.
I tried to do it without multiple threads. the threading doesn't seem to be
the problem
I looked at the data I send to the database... everything seems to be fine
But as soon as I communicate with the db the data mixes up.
My professor thought that maybe something in pyarango isn't threadsafe and it messes up the data but I don't think so as threading doesn't seem to be the problem.
I have no ideas left where this behavior could come from...
Any ideas?

The screenshot shows the following values:
id : 892886691937214500
id_str : 892886691937214465
It looks like somewhere along the way the value is converted to an IEEE754 double, which cannot safely represent the latter value. So there is potentially some precision loss due to conversion.
A quick example in node.js (JavaScript is using IEEE754 doubles for any number values greater than 0xffffffff) shows that this is likely the problem cause:
$ node
> 892886691937214500
892886691937214500
> 892886691937214465
892886691937214500
So the question is where the conversion does happen. Can you check whether the python client program is correctly sending the expected values to ArangoDB, or does it already send the converted/truncated values?
In general, any integer number that exceeds 0x7fffffffffffffff will be truncated when stored in ArangoDB, or converted to an IEEE754 double. This can be avoided by storing the number values inside a string, but of course comparing two number strings will produce different results than comparing two numbers (e.g. "10" < "9" vs. 10 > 9).

parsing a string in python for #hashtag

I am wondering, how could I make an algorithm that parses a string for the hashtag symbol ' # ' and returns the full string, but where ever a word starts with a '#' symbol, it becomes a link. I am using python with Google app engine: webapp2 and Jinja2 and I am building a blog.
Thanks

A more efficient and complete way to find the "hashwords":
import functools
def hash_position(string):
return string.find('#')
def delimiter_position(string, delimiters):
positions = filter(lambda x: x >= 0, map(lambda delimiter: string.find(delimiter), delimiters))
try:
return functools.reduce(min, positions)
except TypeError:
return -1
def get_hashed_words(string, delimiters):
maximum_length = len(string)
current_hash_position = hash_position(string)
string = string[current_hash_position:]
results = []
counter = 0
while current_hash_position != -1:
current_delimiter_position = delimiter_position(string, delimiters)
if current_delimiter_position == -1:
results.append(string)
else:
results.append(string[0:current_delimiter_position])
# Update offsets and the haystack
string = string[current_delimiter_position:]
current_hash_position = hash_position(string)
string = string[current_hash_position:]
return results
if __name__ == "__main__":
string = "Please #clarify: What do you #mean with returning somthing as a #link. #herp"
delimiters = [' ', '.', ',', ':']
print(get_hashed_words(string, delimiters))
Imperative code with updates of the haystack looks a little bit ugly but hey, that's what we get for (ab-)using mutable variables.
And I still have no idea what do you mean with "returning something as a link".
Hope that helps.

not sure where do you get the data for the link, but maybe something like:
[('%s' % word) for word in input.split() if word[0]=='#']

Are you talking about twitter? Maybe this?
def get_hashtag_link(hashtag):
if hashtag.startswith("#"):
return '%s' % (hashtag[1:], hashtag)
>>> get_hashtag_link("#stackoverflow")
'#stackoverflow'
It will return None if hashtag is not a hashtag.

Lexer for Parsing to the end of a line

If I have a keyword, how can I get it to, once it encounters a keyword, to just grab the rest of the line and return it as a string? Once it encounters an end of line, return everything on that line.
Here is the line I'm looking at:
description here is the rest of my text to collect
Thus, when the lexer encounters description, I would like "here is the rest of my text to collect" returned as a string
I have the following defined, but it seems to be throwing an error:
states = (
('bcdescription', 'exclusive'),
)
def t_bcdescription(t):
r'description '
t.lexer.code_start = t.lexer.lexpos
t.lexer.level = 1
t.lexer.begin('bcdescription')
def t_bcdescription_close(t):
r'\n'
t.value = t.lexer.lexdata[t.lexer.code_start:t.lexer.lexpos+1]
t.type="BCDESCRIPTION"
t.lexer.lineno += t.valiue.count('\n')
t.lexer.begin('INITIAL')
return t
This is part of the error being returned:
File "/Users/me/Coding/wm/wm_parser/ply/lex.py", line 393, in token
raise LexError("Illegal character '%s' at index %d" % (lexdata[lexpos],lexpos), lexdata[lexpos:])
ply.lex.LexError: Illegal character ' ' at index 40
Finally, if I wanted this functionality for more than one token, how could I accomplish that?
Thanks for your time

There is no big problem with your code,in fact,i just copy your code and run it,it works well
import ply.lex as lex
states = (
('bcdescription', 'exclusive'),
)
tokens = ("BCDESCRIPTION",)
def t_bcdescription(t):
r'\bdescription\b'
t.lexer.code_start = t.lexer.lexpos
t.lexer.level = 1
t.lexer.begin('bcdescription')
def t_bcdescription_close(t):
r'\n'
t.value = t.lexer.lexdata[t.lexer.code_start:t.lexer.lexpos+1]
t.type="BCDESCRIPTION"
t.lexer.lineno += t.value.count('\n')
t.lexer.begin('INITIAL')
return t
def t_bcdescription_content(t):
r'[^\n]+'
lexer = lex.lex()
data = 'description here is the rest of my text to collect\n'
lexer.input(data)
while True:
tok = lexer.token()
if not tok: break
print tok
and result is :
LexToken(BCDESCRIPTION,' here is the rest of my text to collect\n',1,50)
So maybe your can check other parts of your code
and if I wanted this functionality for more than one token, then you can simply capture words and when there comes a word appears in those tokens, start to capture the rest of content by the code above.

It is not obvious why you need to use a lexer/parser for this without further information.
>>> x = 'description here is the rest of my text to collect'
>>> a, b = x.split(' ', 1)
>>> a
'description'
>>> b
'here is the rest of my text to collect'