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algorithms – Tight upper bound for forming an $n$ element Red-Black Tree from scratch

I learnt that in a order-statistic tree (augmented Red-Black Tree, in which each node $x$ contains an extra field denoting the number of nodes in the sub-tree rooted at $x$) finding the $i$ th order statistics can be done in $O(lg(n))$ time in the worst case. Now in case of an array representing the dynamic set of elements finding the $i$ th order statistic can be achieved in the $O(n)$ time in the worst case.( where $n$ is the number of elements).

Now I felt like finding a tight upper bound for forming an $n$ element Red-Black Tree so that I could comment about which alternative is better : “maintain the set elements in an array and perform query in $O(n)$ time” or “maintaining the elements in a Red-Black Tree (formation of which takes $O(f(n))$ time say) and then perform query in $O(lg(n))$ time”.


So a very rough analysis is as follows, inserting an element into an $n$ element Red-Black Tree takes $O(lg(n))$ time and there are $n$ elements to insert , so it takes $O(nlg(n))$ time. Now this analysis is quite loose as when there are only few elements in the Red-Black tree the height is quite less and so is the time to insert in the tree.

I tried to attempt a detailed analysis as follows (but failed however):

Let while trying to insert the $j=i+1$ th element the height of the tree is atmost $2.lg(i+1)+1$. For an appropriate $c$, the total running time,

$$T(n)leq sum_{j=1}^{n}c.(2.lg(i+1)+1)$$

$$=c.sum_{i=0}^{n-1}(2.lg(i+1)+1)$$

$$=c.left(sum_{i=0}^{n-1}2.lg(i+1)+sum_{i=0}^{n-1}1right)$$

$$=2csum_{i=0}^{n-1}lg(i+1)+cntag1$$

Now

$$sum_{i=0}^{n-1}lg(i+1)=lg(1)+lg(2)+lg(3)+…+lg(n)=lg(1.2.3….n)tag2$$

Now $$prod_{k=1}^{n}kleq n^n, text{which is a very loose upper bound}tag 3$$

Using $(3)$ in $(2)$ and substituting the result in $(1)$ we have $T(n)=O(nlg(n))$ which is the same as the rough analysis…

Can I do anything better than $(3)$?


All the nodes referred to are the internal nodes in the Red-Black Tree.

Reinvent the wheel – an Echo program, mostly in C and completely new from scratch

That is a echo Program without runtime or standard library. It should be compiled with -nostdlib on an amd64 Linux system.

static signed long mywrite(int fd, const void *buf, unsigned long count) {
    signed long retval;
    __asm__ __volatile__(
        "syscall" :
        "=a" (retval) :
        "a" (1), "D" (fd), "S" (buf), "d" (count) :
        "rcx", "r11", "memory"
    );
    return retval;
}

static void myexit(int status) __attribute__((__noreturn__));
static void myexit(int status) {
    __asm__ __volatile__(
        "syscall" :
        :
        "a" (60), "D" (status) :

    );
    __builtin_unreachable();
}

static unsigned long mystrlen(const char *str) {
    const char *pos = str;
    while(*pos) ++pos;
    return pos - str;
}

static void writearg(char *str, char end) {
    unsigned long size = mystrlen(str) + 1;
    unsigned long written = 0;
    str(size - 1) = end;
    do {
        signed long result = mywrite(1, str + written, size - written);
        if(result < 0) myexit(1);
        written += result;
    } while(written < size);
}

void _start(void) __attribute__((__naked__, __noreturn__));
void _start(void) {
    __asm__(
        "lea 8(%rsp), %rdint"
        "call startargs"
    );
}

static void startargs(char *argv()) __attribute__((__noreturn__, __used__));
static void startargs(char *argv()) {
    if(!*argv || !*++argv) {
        myexit(mywrite(1, "n", 1) != 1);
    }
    for(;;) {
        char *str = *argv;
        if(*++argv) {
            writearg(str, ' ');
        } else {
            writearg(str, 'n');
            myexit(0);
        }
    }
}

Some of my concerns:

  • Does my program's behavior fully conform to the standard for echo?
  • Am I making unjustified assumptions that could cause my code to not work in a future version of Linux (or compiler)? In particular, I overwrite null terminators in argv Values ​​okay?
  • Are there any other assumptions I can make since my code is only Linux-on-amd64 anyway? For example, can I assume that Linux will always be continuous? argv Values, and so you just make a big one write Call after replacing all zeros instead of one per argument? (I know I still have to make a loop write for partial writes. I also know that I can just copy the strings around me, but I prefer to write them where I got them.)
  • Instead of having _start as an assembly stub and my real code in startargsIs there any way to enter my real code? _start but still able to handle command line arguments safely? (It also feels silly, a call that will never ret, but I don't see a better way to maintain stack alignment.)

What is the best approach to build a UI library from scratch?

Which process do you prefer when creating your design systems and UI libraries with your designers and why? If you put your preferences aside (we all know that projects don't meet our expectations), what is the case in real life?

  • Suddenly component by component as an independent sprint / project
  • Define it step by step as you go through your sprints, projects, briefs, etc.

Design – what does it take to create a video conferencing app like Zoom and Webex from scratch?

The government of many countries recently banned Zoom, a video conferencing app, for security reasons. Meanwhile Govt. of India believed that India should have its own video conferencing app and announced a challenge to create one. For security reasons, this is a great idea to have an indigenous app.

But when we think in practice, those apps like Zoom and Webex that we use today have actually taken years to develop and hundreds of professionals have struggled to reach the level we are seeing today. It's not just about writing code, it requires various other skills such as operating system, network, information security and compression alogs. Etc.

I'm not against the idea or discouraging it, but given the challenges that this type of app brings, it's not a breeze to create an innovative, robust, and sophisticated video conferencing app.

So my question is exactly what different areas of knowledge are required to create such an app and what major challenges will arise when creating this app.

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Python – Use Pymongo to use multiprocessing to scratch over 4 million URLs and investigate the effects of the corona virus

I would therefore like to do some research on the effects of covid 19 on companies. I managed to create a database with the company name and associated website URLs. Now I want to scrape them all off as quickly as possible so I can analyze them. I am new to parallel programming and am skeptical that I will connect to every database as securely as possible.

from __future__ import division

from multiprocessing import Pool

import pymongo as pym
import requests
from bs4 import BeautifulSoup

# Set up local client
client = pym.MongoClient('mongodb://localhost:27017/')
# Connect to local DB
db = client.local_db
# Connect to Collections
My_Collection = db.MyCollection
ScrapedPagesAprilCollection = db.ScrapedPagesApril

# I don't want to scrape these
LIST_OF_DOMAINS_TO_IGNORE = ('google.com/', 'linkedin.com/', 'facebook.com/')


def parse(url):
    if any(domain in url for domain in LIST_OF_DOMAINS_TO_IGNORE):
        pass
    elif '.pdf' in url:
        pass
    else:
        # print(url)
        headers = {
            'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:74.0) Gecko/20100101 Firefox/74.0',
        }
        page = requests.get(url, headers=headers)
        print(f'{url}: {page.status_code}')
        if page.status_code == 200:
            soup = BeautifulSoup(page.text, 'lxml')
            text = soup.get_text(separator=" ")
            info_to_store = {
                '_id': url,
                'content': text
            }

            if 'coronavirus' in text:
                info_to_store('Impacted') = True

            # Insert into Collection
            ScrapedPagesAprilCollection.replace_one(
                {'_id': url}, info_to_store, upsert=True)

        elif page.status_code != 200:
            print(f'{url}: {str(page.status_code)}')
            pass


def covid19_scrape_pages(collection, query: dict):
    """
    Wanting to update the pages already matched

    Parameters
    ----------
    collection : pymongo.collection.Collection
    query : dict

    Yields
    -------
    A url

    """
    # Get the cursor
    mongo_cursor = collection.find(query, no_cursor_timeout=True)
    # For company in the cursor, yield the urls
    for company in mongo_cursor:
        for url in company('URLs'):
            doc = ScrapedPagesAprilCollection.find_one({'_id': url})
            # If I haven't already scraped it, then yield the url
            if doc is None:
                yield (url)


def main():
    print('Make sure LIST_OF_DOMAINS_TO_IGNORE is updated by running',
          'blacklisted_domains.py first')
    urls_gen = covid19_scrape_pages(
        My_Collection, {})
    pool = Pool(8)
    pool.map(parse, urls_gen)
    pool.close()
    pool.join()


if __name__ == "__main__":  # Required logic expression
    main()
```

Python pandas return an empty data frame when trying to scratch a table

I am trying to determine the transfer history of the 500 most valuable players on the transfer market. I managed (with some help) to go through each player's profile and scratch the picture and name. Now I want the transfer history, which can be found in a table on each player profile: player profile Enter the image description here

I want to save the table with pandas in a data frame and then write them in a CSV with season, date etc. as headings. For Monaco and PSG, for example, I only want the names of the clubs, not pictures or nationality. But at the moment I only get the following:

Empty DataFrame
Columns: ()
Index: ()

I've looked at the source and inspected the page, but can't find anything to help me other than tbody and tr. But as I do, I want to make this table more precise as there are several others.

This is my code:

import requests
from bs4 import BeautifulSoup
import csv
import pandas as pd

site = "https://www.transfermarkt.com/spieler-statistik/wertvollstespieler/marktwertetop?ajax=yw1&page={}"

headers = {
    'User-Agent': 'Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:74.0) Gecko/20100101 Firefox/74.0'
}

result = ()

def main(url):
    with requests.Session() as req:
        result = ()
        for item in range(1, 21):
            print(f"Collecting Links From Page# {item}")
            r = req.get(url.format(item), headers=headers)
            soup = BeautifulSoup(r.content, 'html.parser')

            tr = soup.find_all("tbody")(1).find_all("tr", recursive=False)

            result.extend((
                { 
                    "Season": t(1).text.strip()

                }
                for t in (t.find_all(recursive=False) for t in tr)
            ))

df = pd.DataFrame(result)

print(df)

Can I scratch URL keywords?

Hello, I hope everyone is safe and healthy. I want to know if there is a way to use Scrapebox to remove the keywords that other websites (URLs) use. If so, how would I do it?

Python – How To Scratch More Elegantly

I am in the process of scratching a website with BeautifulSoup.

In the appendix you will find the script that I used. I tried to rule out the case that the lists don't match at the end, which works.

Any suggestions to improve this and how parts of the code can be summarized?

Many thanks!

# initialize list
street=()
plz=()
city=()
country=()
phone=()
fax=()
email=()
website=()
targetgroups=()
productcats=()

for i in range(0,500):
    # URLs read out of dataframe
    URL=df.iloc(i,1)
    header={"User-Agent":"Mozilla/5.0 (Windows NT 10.0; Win64; x64; rv:70.0) Gecko/20100101 Firefox/70.0"}
    page=requests.get(URL, headers=header)
    soup=BeautifulSoup(page.content,"html.parser")


    street_soup=soup.find('span', {'itemprop':'streetAddress'})
    try:
        for element in street_soup:
            text=str(cleanhtml(str(element).strip()))
            street.append(cleanhtml(str(text)))
    except:
        street.append('')

    plz_soup=soup.find('span', {'itemprop': 'postalCode'})
    try:
        for element in plz_soup:
            text=str(cleanhtml(str(element).strip()))
            plz.append(cleanhtml(str(text)))
    except:
        plz.append('')  

    city_soup=soup.find('span', {'itemprop':'addressLocality'})
    try:
        for element in city_soup:
            text=str(cleanhtml(str(element).strip()))
            city.append(cleanhtml(str(text)))
    except:
        city.append('')      

    country_soup=soup.find('span',{'itemprop':'addressCountry'})
    try:
        for element in country_soup:
            text=str(cleanhtml(str(element).strip()))
            country.append(cleanhtml(str(text)))
    except:
         country.append('')  

    phone_soup=soup.find('span', {'itemprop':'telephone'})
    try:
        for element in phone_soup:
            text=str(cleanhtml(str(element).strip()))
            phone.append(cleanhtml(str(text)))
    except:
        phone.append('') 

    fax_soup=soup.find('span',{'itemprop':'faxNumber'})
    try:
        for element in fax_soup:
             text=str(cleanhtml(str(element).strip()))
             fax.append(cleanhtml(str(text)))
     except:
         fax.append('')     

     email_soup=soup.find('a',{'itemprop':'email'})
     try:
         for element in email_soup:
              text=str(cleanhtml(str(element).strip()))
              email.append(cleanhtml(str(text)))
     except:
         email.append('')    

     website_soup=soup.find('span',{'class':'break-word'})
     try:
         for element in website_soup:
              text=str(cleanhtml(str(element).strip()))
              website.append(cleanhtml(str(text)))
     except:
          website.append('')    

     targetgroups_soup=soup.find('div',{'class':'bg-col--lightest push--bottom'})
     try:
         for element in targetgroups_soup:
             text=str(cleanhtml(str(element).strip()))
             targetgroups.append(cleanhtml(str(text)))
     except:
         targetgroups.append('')    

     sleep(0.5)