Planet Python

Last update: July 20, 2019 09:47 PM UTC

July 20, 2019

Weekly Python StackOverflow Report

(clxxxvii) stackoverflow python report

These are the ten most rated questions at Stack Overflow last week.
Between brackets: [question score / answers count]
Build date: 2019-07-20 20:30:24 GMT

1. Concatenation using the + and += operators in Python - [37/1]
2. Issues implementing the "Wave Collapse Function" algorithm in Python 2.7 - [26/1]
3. Finding all combinations based on multiple conditions for a large list - [10/1]
4. Custom Neural Network Implementation on MNIST using Tensorflow 2.0? - [9/2]
5. Fast combination of non-unique rows in numpy array, mapped to columns (i.e. fast pivot table problem, without Pandas) - [8/4]
6. Why does python allow list[a:b] but not list[a] if a and b are out of index range? - [7/4]
7. What is wrong with the comparison a,b == 1,2? - [7/2]
8. dictionary keys to replace strings in pandas dataframe column with dictionary values and perform evaluate - [6/5]
9. Fastest way to search a list of named tuples? - [6/5]
10. Filling cell based on existing cells - [6/3]

July 20, 2019 08:30 PM UTC

PSF GSoC students blogs

GSoC week #7

Hey everyone,

This is week 7th of Google Summer of Code 2019. So far, I have made the backend of my project and only some things need to be done (regarding deployment and hosting) and it will be working fine. This week I am preparing to start with the left over front end part. So I started with desigining prototype on Adobe XD. Since my project is 70% backend and the front end part is almost similar to the Cheatsheet part which other GSoC student is already working on, so I have to take his prototype and code and just implement my Icons Picker features in it. 

Here is the link to the prototype: https://xd.adobe.com/view/6ed4e66f-e6f5-486e-4e74-340d073d1771-18e5/

PS: Link might not work later because adobe only allows one active link :P

Thanks for reading

Cheers!

July 20, 2019 05:41 PM UTC

Django Weblog

The first PyCon Africa

In just a few weeks, from the 6th to 10th of August, the first ever pan-African PyCon will take place in Accra, Ghana.

PyCon Africa 2019 is an amazing step for the rapidly growing Python community in Africa.

July 20, 2019 03:20 PM UTC

ListenData

Python : Complete Guide to Date and Time Functions

In this tutorial, we will cover python datetime module and how it is used to handle date, time and datetime formatted columns (variables). It includes various practical examples which would help you to gain confidence in dealing dates and times with python functions. In general, Date types columns are not easy to manipulate as it comes with a lot of challenges like dealing with leap years, different number of days in a month, different date and time formats or if date values are stored in string (character) format etc.

Table of Contents

---

Introduction : datetime module

It is a python module which provides several functions for dealing with dates and time. It has four classes as follows which are explained in the latter part of this article how these classes work.

1. datetime
2. date
3. time
4. timedelta

People who have no experience of working with real-world datasets might have not encountered date columns. They might be under impression that working with dates is rarely used and not so important. To enlighten them, I have listed down real-world examples wherein using datetime module can be beneficial.

1. Selecting all the saving account holders who were active on 30th June, 2018 and checking their status whether they are still active
2. Identifying insureds who filed more than 20 claims in the last 3 months
3. Identifying customers who made multiple transactions in the last 6 months
4. Extracting dates from timestamp values

Import datetime module

You can import or load datetime module by using the command below -

import datetime

You don't need to install this module as it comes bundled with the installation of python software.

Dates

Here we are using datetime.date class which is used to represent calendar date values. today() method is used to fetch current date.

datetime.date.today()

Output
datetime.date(2019, 7, 19)

In order to display it like a proper calendar date, we can wrap it within print( ) command.

print(datetime.date.today())

Output
2019-07-19

July 20, 2019 09:38 AM UTC

July 19, 2019

NumFOCUS

Meet our 2019 Google Summer of Code Students (Part 1)

The post Meet our 2019 Google Summer of Code Students (Part 1) appeared first on NumFOCUS.

July 19, 2019 10:13 PM UTC

PSF GSoC students blogs

Weekly check in [week 7 - 08/07 - 14/07]

July 19, 2019 09:41 PM UTC

Week 7: Waypoints and their Interaction

What did I do this week?

I restored most of previous functionality I stripped off for simpler progress. Further major time was spent on getting the working of waypoints correct. After changing most of plotting routines into cartopy, the waypoints were working with all their functions but thy lost functionality and couldn't adapt to change in projection. So I also worked on solving that and did solved it at the end.

What is up next?

Currenty, testing for bugs and making sure the correct functionality of all the option controls like:

    1. WMS
    2. KML
    3. Satellite

Apart from that options to manually enable/disable the features and changing the color is also to be done.

Did you get stuck anywhere?

Yes, I think solving the waypoints issue maybe took a bit more time than needed but I think it was necessary for a confidence boost to me about my abilities to debug and trace the most delicate issues and solve them on my own. 

July 19, 2019 07:58 PM UTC

Blog post: Week 8

This week I focused in two things:

• Start writing new classes for previously existing atomic sources to bypass the SQL database and store data directly in HDF5 format. This is a much simpler approach and will speed things up for TARDIS developers when they need to build new atomic files. For an example, see PR #144.
• We started the process to set up a pipeline to download, extract and convert the entire CMFGEN database to HDF5. See PR #143.

Also in the process I learned a couple of things:

• How to use the module logger from the Python standard library (and why it's a good idea to use it).
• Why you should never use a bare `except` statement. Yep, learned this in the worst possible way.
• I'm getting good at writing regular expresions.

I will continue working at these two items the next week.

The second part of GSoC is almost ending and we already have some good results, but lot of work is ahead!

July 19, 2019 07:11 PM UTC

Roberto Alsina

Old Guy @ The Terminal Ep 2: Python Sucks!

July 19, 2019 06:52 PM UTC

Stack Abuse

Python List Sorting with sorted() and sort()

In this article, we'll examine multiple ways to sort lists in Python.

Python ships with two built-in methods for sorting lists and other iterable objects. The method chosen for a particular use-case often depends on whether we want to sort a list in-place or return a new version of the sorted list.

Assuming we want to sort a list in place, we can use the list.sort() method as follows:

>>> pets = ['Turtle', 'Cat', 'Fish', 'Dingo']
>>> pets.sort()
>>> pets
['Cat', 'Dingo', 'Fish', 'Turtle']

By default, the list is sorted in ascending order. Notice how the original pets list is changed after the sort method is called on it. If we don't want this to happen, we can use the built-in sorted() function to return a new sorted list while leaving the original list unchanged:

>>> pets = ['Turtle', 'Cat', 'Fish', 'Dingo']
>>> new_pets = sorted(pets)
>>> new_pets
['Cat', 'Dingo', 'Fish', 'Turtle']
>>> pets
['Turtle', 'Cat', 'Fish', 'Dingo']

The reverse argument can be used to sort lists in descending order:

>>> pets = ['Turtle', 'Cat', 'Fish', 'Dingo']
>>> new_pets = sorted(pets, reverse=True)
>>> new_pets
['Turtle', 'Fish', 'Dingo', 'Cat']
>>> pets.sort(reverse=True)
>>> pets
['Turtle', 'Fish', 'Dingo', 'Cat']

However, there are scenarios where we might want to sort a list based on custom criteria that we define. For example, we may want to sort our pets list by the length of each entry. In that case Python offers the key argument, which accepts a user-defined function to specify the sorting criteria:

>>> pets = ['Turtle', 'Cat', 'Fish', 'Dingo']
>>> get_len(x):
...    return len(x)
...
>>> new_pets = sorted(pets, key=get_len)
>>> new_pets
['Cat', 'Fish', 'Dingo', 'Turtle']
>>> pets.sort(key=get_len)
>>> pets
['Cat', 'Fish', 'Dingo', 'Turtle']

Now let's consider a slightly more complex example. Here we have a list of dictionaries that contain data about a group of people, and we want to sort the list based the peoples' ages, in descending order. To do this we will use both the key and reverse keyword arguments, as well as a Python lambda function. That way we can create the sorting function on the fly, instead of defining it beforehand:

>>> data = [ { 'name': 'Billy', 'age': 26, 'country': 'USA' }, { 'name': 'Timmy', 'age': 5, 'country': 'Australia' }, { 'name': 'Sally', 'age': 19, 'country': 'Costa Rica' }, { 'name': 'Tommy', 'age': 67, 'country': 'Serbia' } ]
>>> new_data = sorted(data, key=lambda x: x['age'], reverse=True)
>>> new_data
[{'country': 'Serbia', 'age': 67, 'name': 'Tommy'}, {'country': 'USA', 'age': 26, 'name': 'Billy'}, {'country': 'Costa Rica', 'age': 19, 'name': 'Sally'}, {'country': 'Australia', 'age': 5, 'name': 'Timmy'}]
>>> data.sort(key=lambda x: x['age'], reverse=True)
>>> data
[{'country': 'Serbia', 'age': 67, 'name': 'Tommy'}, {'country': 'USA', 'age': 26, 'name': 'Billy'}, {'country': 'Costa Rica', 'age': 19, 'name': 'Sally'}, {'country': 'Australia', 'age': 5, 'name': 'Timmy'}]

Notice how the dictionaries startd in a seamingly random order and then ended up with the oldest people first and youngest people last in the list.

Using the sorting functions and lambdas in this way allows us to easily sort complex data structures, all in one line of code. And the order of the sort can be set to descending order by setting reverse=True.

About the Author

This article was written by Jacob Stopak, a software consultant and developer with a passion for helping others improve their lives through code. Jacob is the creator of Code Card - a convenient tool for developers to look up, copy, and paste common code snippets.

July 19, 2019 12:35 PM UTC

Made With Mu

Mu at EuroPython

Mu made a number of appearances at last week’s wonderful EuroPython 2019 conference in Basel, Switzerland. This is a report of what happened…

EuroPython is a famously friendly event, and well known for welcoming folks who are new to the Python community. One of the most effective ways of achieving this is the beginners’ day, run during the tutorial sessions that preceed the main conference. Many folks who have contributed to Mu volunteered their time to organise the beginners’ day and support those taking their first steps into programming. The latest version of Mu was used as the development platform for each of the activities that took place, and it was a huge relief to avoid spending the first hour helping folks download, install, configure and setup Python and a code editor. Mu’s bundled approach saved a huge amount of time!

The following photographs, taken by the talented Gaetano Scognamiglio, give a flavour of the day.

Many thanks especially to Kassia, Dan and Tiago for leading, presenting and planning several of the Mu based activities with which the beginners engaged. By the end of the day they had created computer art with Python’s turtle module, made a simple website with Flask, used MicroPython to program some BBC micro:bits (kindly donated by the micro:bit foundation) and made a cat game with PyGameZero. The afternoon was particularly good fun since the participants were encouraged to let their creative juices flow and come up with simple coding projects of their own.

These two videos capture the sorts of things folks got up to. First up is a hilarious splat-a-cat game.

I particularly like how this participant made a mashup of micro:bit and PyGameZero.

Members of the Mu community were also speaking at EuroPython.

Long time contributor, Tiago, gave a barn storming performance of live coding in front of an appreciative audience, where he created a simple arcade game using just Python’s turtle module and a few lines of code. What I particularly enjoyed about Tiago’s talk was the way he was able to tell the story of how the code is built up in simple steps to create a rather compelling and entertaining game.

I (Nicholas) also gave a talk about how we go about developing Mu. This was a story of the sorts of things we focus on, the technical choices that result and the motivation that keeps us working on Mu.

Finally, at the end of the conference were “code sprints”, where developers got together to code with each on various different projects. During this time Tiago was able to make quite a large number of issues, pull requests and other contributions via Mu’s GitHub repository. Hopefully these will make their way into the upcoming alpha 3 release of Mu.

All that remains is for me to thank the organisers of EuroPython for putting on such a well organised, relaxed, welcoming and community focused conference.

I’m already looking forward to next year’s edition.

July 19, 2019 08:45 AM UTC

PyCharm

PyCharm 2019.2 Release Candidate

PyCharm 2019.2 is almost ready to be released, and we’re happy to announce that a release candidate is available for download now.

New in PyCharm

Enable of actions during indexing

• We identified certain actions that have no reason for being disabled while the indexing process is happening. This version will now let you run and debug your application, create a new project and change the interpreter while indexing is in progress.

Further improvements

• Fix for unresolved references error using Python 2.7 interpreter
• The error stopping Django server run configuration over SSH is now fixed
• Unnecessary stacktrace removed when stopping a remote interpreter over SSH
• Bug fixes and enhancements coming from Datagrip and Webstorm

Read the release notes to learn more.

Interested?

Download the RC from our website. Alternatively, you can use the JetBrains Toolbox App to stay up to date.

If you’re on Ubuntu 16.04 or later, you can use snap to get PyCharm RC versions, and stay up to date. You can find the installation instructions on our website.

The release candidate (RC) is not an early access program (EAP) build, and does not bundle an EAP license. If you get PyCharm Professional Edition RC, you will either need a currently active PyCharm subscription, or you will receive a 30-day free trial.

July 19, 2019 06:52 AM UTC

Kushal Das

Setting up WKD

We fetch any GPG public key from the keyservers using the GPG fingerprint (or parts of it). This step is still a problematic one for most of us. As the servers may not be responding, or the key is missing (not pushed) to the server. Also, if we only have the email address, there is no easy way to download the corresponding GPG key.

Web Key Directory to rescue

The Web Key Directory comes to the picture. We use WKD to enable others to get our GPG keys for email addresses very easily. In simple terms:

The Web Key Directory is the HTTPS directory from which keys can be fetched.

Let us first see this in action:

gpg --auto-key-locate clear,wkd --locate-key mail@kushaldas.in

The above will fetch you the key for the email address, and you can also assume the person who owns the key also has access to the https://kushaldas.in server.

There are many available email clients, which will do this for you. For example Thunderbird/Enigmail 2.0 or Kmail version 5.6 onwards.

Setting up WKD for your domain

I was going through the steps mentioned in the GNUPG wiki, while weasel pointed to me to a Makefile to keep things even more straightforward.

all: update install

update:
        rm -rfv openpgpkey
        mkdir -v openpgpkey
        echo 'A85FF376759C994A8A1168D8D8219C8C43F6C5E1 mail@kushaldas.in' | /usr/lib/gnupg/gpg-wks-client -v --install-key
        chmod -v 0711 openpgpkey/kushaldas.in
        chmod -v 0711 openpgpkey/kushaldas.in/hu
        chmod -v 0644 openpgpkey/kushaldas.in/hu/*
        touch openpgpkey/kushaldas.in/policy

        ln -s kushaldas.in/hu openpgpkey/
        ln -s kushaldas.in/policy openpgpkey/

install: update
        rsync -Pravz --delete ./openpgpkey root@kushaldas.in:/usr/local/www/kushaldas.in/.well-known/

.PHONY: all update install

The above Makefile is using gpg-wks-client executable and also pushing the changes to the right directory on the server.

Email providers like protonmail already allow users to publish similar information. I hope this small Makefile will help you to set up your domain.

July 19, 2019 05:35 AM UTC

PSF GSoC students blogs

Week 7 P2

After doing some traceback of the program, I found that when running multithread scanning, each thread instantiates a nvd object NVDSQLite, while in nvd.get_cvelist_if_stale() the object tries to call init_database() regardless of the database situation, and in line 131 of NVDAutoUpdate.py, it will execute the CREATE TABLE IF NOT EXISTS. Since this is not thread-safe, the database might be locked.

Therefore, there might be a logical incorrection in previous code, which is posted in issue #177. I think in getting cves we don't need to check database status since we have already checked it before, if not we could manually checked the status first and then try to get cve, therefore, we only need to make a cursor and connect to the database. So I will fix that first and then test mutithread mode.

Actually I don't think sqlite3 is a good fit with multithread since in python's official document it says "Older SQLite versions had issues with sharing connections between threads. That’s why the Python module disallows sharing connections and cursors between threads. If you still try to do so, you will get an exception at runtime."

July 19, 2019 02:16 AM UTC

Week 7

This week I'm working on implementing mutithread extracting and scaning. So far the extracting works. From this week I acquired how does multithread pool work in Python. The pool has a method called `map`, which is basically same as `map` in Python: taking a function and an iterable as input, apply the function to the iterable in a multithread way. For extracting, this is easy to implement because we don't need to worry about thread-safe issue. However, for scanning, this could be a problem. We know that multiprocessing in operating system is really hard because we need to keep all processes/threads synchronized by using locks/mutex/semaphore. At first I thought this is okay because in scanning function we are supposed to just run mutiple queries at the same time, so we don't need lock.

But acutally this becomes a problem. I will explain later.

Another problem is the difference of pool.map() between python2 and python3. In python3, pool is supported as a context manager, thus we could use something like "*pool.map()", while this is invalid in python2. So we had to go back to use try/finally or the pool will not terminate correctly.

July 19, 2019 02:08 AM UTC

ListenData

Drop one or more columns in Pandas Dataframe

In this tutorial, we will cover how to drop or remove one or multiple columns from pandas dataframe.

What is pandas in Python?

pandas is a python package for data manipulation. It has several functions for the following data tasks:

1. Drop or Keep rows and columns
2. Aggregate data by one or more columns
3. Sort or reorder data
4. Merge or append multiple dataframes
5. String Functions to handle text data
6. DateTime Functions to handle date or time format columns

Import or Load Pandas library

To make use of any python library, we first need to load them up by using import command.

import pandas as pd
import numpy as np

Let's create a fake dataframe for illustration

The code below creates 4 columns named A through D.

df = pd.DataFrame(np.random.randn(6, 4), columns=list('ABCD'))

          A         B         C         D
0 -1.236438 -1.656038  1.655995 -1.413243
1  0.507747  0.710933 -1.335381  0.832619
2  0.280036 -0.411327  0.098119  0.768447
3  0.858730 -0.093217  1.077528  0.196891
4 -0.905991  0.302687  0.125881 -0.665159
5 -2.012745 -0.692847 -1.463154 -0.707779

Drop a column in python

In pandas, drop( ) function is used to remove column(s).axis=1 tells Python that you want to apply function on columns instead of rows.

df.drop(['A'], axis=1)

Column A has been removed. See the output shown below.

          B         C         D
0 -1.656038  1.655995 -1.413243
1  0.710933 -1.335381  0.832619
2 -0.411327  0.098119  0.768447
3 -0.093217  1.077528  0.196891
4  0.302687  0.125881 -0.665159
5 -0.692847 -1.463154 -0.707779

In order to create a new dataframe newdf storing remaining columns, you can use the command below.

newdf = df.drop(['A'], axis=1)

To delete the column permanently from original dataframe df, you can use the option inplace=True

df.drop(['A'], axis=1, inplace=True)

#Check columns in df after dropping column A
df.columns

Output
Index(['B', 'C', 'D'], dtype='object')

The parameter inplace= can be deprecated (removed) in future which means you might not see it working in the upcoming release of pandas package. You should avoid using this parameter if you are not already habitual of using it. Instead you can store your data after removing columns in a new dataframe (as explained in the above section).

If you want to change the existing dataframe, try this df = df.drop(['A'], axis=1)

Remove Multiple Columns in Python

You can specify all the columns you want to remove in a list and pass it in drop( ) function.

Method I

df2 = df.drop(['B','C'], axis=1)

Method II

cols = ['B','C']
df2 = df.drop(cols, axis=1)

Select or Keep Columns

If you wish to select a column (instead of drop), you can use the command

df['A']

To select multiple columns, you can submit the following code.

df[['A','B']]

How to drop column by position number from pandas Dataframe?

You can find out name of first column by using this command df.columns[0]. Indexing in python starts from 0.

df.drop(df.columns[0], axis =1)

To drop multiple columns by position (first and third columns), you can specify the position in list [0,2].

cols = [0,2]
df.drop(df.columns[cols], axis =1)

Drop columns by name pattern

df = pd.DataFrame({"X1":range(1,6),"X_2":range(2,7),"YX":range(3,8),"Y_1":range(2,7),"Z":range(5,10)})

   X1  X_2  YX  Y_1  Z
0   1    2   3    2  5
1   2    3   4    3  6
2   3    4   5    4  7
3   4    5   6    5  8
4   5    6   7    6  9

Drop column whose name starts with letter 'X'

df.loc[:,~df.columns.str.contains('^X')]

How it works?

1. ^X is a expression of regex language which refers to beginning of letter 'X'
2. df.columns.str.contains('^X') returns array [True, True, False, False, False].
   True where condition meets. Otherwise False
3. Sign ~ refers to negate the condition.
4. df.loc[ ] is used to select columns

It can also be written like :

df.drop(df.columns[df.columns.str.contains('^X')], axis=1)

Other Examples

#Removing columns whose name contains string 'X'
df.loc[:,~df.columns.str.contains('X')]

#Removing columns whose name contains string either 'X' or 'Y'
df.loc[:,~df.columns.str.contains('X|Y')]

#Removing columns whose name ends with string 'X'
df.loc[:,~df.columns.str.contains('X$')]

Drop columns where percentage of missing values is greater than 50%

df = pd.DataFrame({'A':[1,3,np.nan,5,np.nan],
                   'B':[4,np.nan,np.nan,5,np.nan]
                   })

% of missing values can be calculated by mean of NAs in each column.

cols = df.columns[df.isnull().mean()>0.5]
df.drop(cols, axis=1)

July 19, 2019 01:08 AM UTC

July 18, 2019

Mike Driscoll

New Malicious Python Libraries Found Targeting Linux

The post New Malicious Python Libraries Found Targeting Linux appeared first on The Mouse Vs. The Python.

July 18, 2019 09:00 PM UTC

PSF GSoC students blogs

Weekly Check-in #8 : (12 July - 18 July)

What did you do this week?

• Protego is now compatible with Google's parser. Protego pass all testcase in Google's parser testsuite.
• Documented Protego - functions now have docstrings, and I have created a readme file.
• Protego is now on PyPI. To install Protego, simply type `pip install protego`.
• Made few changes to improve performance as suggested by mentors.

What is coming up next?

• Additions to CI - making sure Protego doesn't throw exceptions on robots.txt of top 1000 alexa websites.
• Benchmark Protego.

Did you get stuck anywhere?

Nothing major.

July 18, 2019 05:09 PM UTC

Talk Python to Me

#221 Empowering developers by embedding Python

How do we get kids excited about programming? Make programming tangible with embedded devices. Did you know that after kids learned to code with the BBC micro:bit, 90% of kids "thought coding was for everyone" and 86% said it made CS topics more interesting?

July 18, 2019 08:00 AM UTC

Python Bytes

#139 f"Yes!" for the f-strings

July 18, 2019 08:00 AM UTC

IslandT

Start a new Cryptocurrency project with Python

1. Start a new python cryptocurrency project in PyCharm.
2. Install related module needs for this new project.
3. Write a simple program to find out whether the new module is working or not.

Hello and welcome to another episode of the “Python Programming Journey” article series. Starting from today I have restructured the Python category of this website into these few sections.

1. Project: Create around 3 projects within this year. I have already started the web analytic project a few days ago and today I have included this new cryptocurrency project. I will restart one of the previous projects which are now on Github anytime soon. All these projects will be uploaded to Github once they have shown some progress and I welcome those of you who know python to contribute to these open projects on Github as well.
2. Example: We will continue to solve some simple problems with Python once a while on this website.
3. Tool: Python developer needs a tool, thus once in a while, I will introduce to you all some new tools or IDE used to write the python program.

With that said I am now ready and have a ton of python related materials to write about throughout this year.

As I have mentioned before at the beginning of this article we will start a new Cryptocurrency project with Python, so let get started!

Start a new python cryptocurrency project in PyCharm :

Start the PyCharm IDE, if you do not have one then you can download it for free on its website. After you have opened up PyCharm IDE, Goto File->New Projects. Fill in the necessary details to create this new cryptocurrency project.

Install the cryptocurrency module needs in this project then write a simple python program to see the outcome :

Right-click on the project folder, then select New->Directory, give the new directory a name then click on the ‘OK’ button to create the new project directory where we will keep all the python files in it. Right-click on the newly created directory and select Mark Directory as -> Source Root. Next, we will need to install three python packages (Pandas for extracting data, Requests which is required by the Cryptocompy package and Cryptocompy for retrieving the related cryptocurrency market data) before writing that simple python program. Goto File->Settings to open up the Settings panel, then on the left side of the Settings panel select Project Interpreter. On the right side of the Settings’ panel, click on the plus sign to open up the installation panel, then type in the name of those packages to search for them and then install them to your project. You might need to close the installation panel and click on the plus sign again to start the installation panel again to install another package after you have installed one of the packages.

Finally, right-click on the new directory you have created just now and then select New->Python File, give the new python file a name and then click on the ‘OK’ button to create that new python file. Next, enter these lines of code into that new python file you have just created.

import pandas as pd
from cryptocompy import price

coin_data = price.get_current_price("BTC", ["EUR", "USD"])
print(pd.DataFrame.from_records(coin_data)) # read the returned dictionary object with Pandas then print those data

The average price of BTC vs EUR and BTC vs USD

I just take a look at Google search for these two prices and find out there is a little bit different as compared to those from the REST call, therefore I think those prices might be the average price either from Google or from the CryptoCompare data. Cryptocompy is actually using the CryptoCompare API call to gather those data. If we use the cryptocompy package to make the API call then we do not need to sign up for a free API key from CryptoCompare to make a call to get the required data, therefore I think maybe the data is a little bit outdated which means perhaps the author of this package has downloaded the weekly data and stored on his or her online storage site and thus that API call is actually calling the author website instead of direct call to the CryptoCompare data storage site. If we make a direct call to the CryptoCompare site then there will be a 100,000 calls per month limit under the free API plan package. Anyhow, I will use this python package for a while just for this project.

Hey people, this article takes me a lot of time to create, if you like this article then don’t forget to share it with your friends. Don’t forget to subscribe to the Python-related rss feed through this link with your favorite rss reader to get notified and read the latest article related to Python programming!

July 18, 2019 06:45 AM UTC

PSF GSoC students blogs

4th weekly check-in

July 18, 2019 12:16 AM UTC

My path this far - 3rd blog post

Hello guys!

This seems to be the post that goes by my 3rd blog post (July 8). I genuinely misunderstood the blog post assignment and I'm sorry I'm late with them.

I had motivation issues the last 2 weeks due to the fact I was really focused with the semester ending in my university. Not only I had exams every week, I had to finish some studies I had late the past weeks, and that contributed negatively to my focus to the project.

Even though I had a good start, I delayed a lot my unit tests and feedback reviewing, which delayed all my cronogram and showed me I was really optimistic with my timings.

My schedule was really good, and I had my feature implemented by the end of the 3rd week; but feature per feature isn't enough, and I was reminded I am contributing to a open source project after all. It's not only about the thing being done, but done right, with tests, clear and maintainable. More than once I was reminded of PEP20, and my efforts were more towards making my code usable by the project than anything else.

For the future, I'll need more steps planned so I can make good schedules of my tasks. It's not only about the code, but the community. It's not only about the features, but all the processes involved in making the feature something good for the project.

I'm really grateful I can experience this and be in contact with so much talented people.

Leonardo Rodrigues.

July 18, 2019 12:12 AM UTC

Catalin George Festila

Python 3.7.3 : The pandas python module.

Since I started learning python programming language I have not found a more complex and complete module for viewing complex data. The official documentation of this python module tells us: pandas is a Python package providing fast, flexible, and expressive data structures designed to make working with “relational” or “labeled” data both easy and intuitive. It aims to be the fundamental

July 18, 2019 12:11 AM UTC

July 17, 2019

Roberto Alsina

Old Guy @ The Terminal: Episodio 1!

July 17, 2019 08:33 PM UTC

• • RSS feed
  • Titles Only
  • Powered by Planet!
• Other Python Planets
  • Python Summer of Code
  • Planet Python Francophone
  • Planet Python Argentina
  • Planet Python Japan
  • Planet Python Brasil
  • Planet Python Indonesia
  • Planet Python Poland
• Python Libraries
  • PySoy
  • SciPy
  • SymPy
  • Twisted
• Python/Web Planets
  • CherryPy
  • Django Community
  • Plone
  • Turbogears
• Other Languages
  • Haskell
  • Lisp
  • Parrot
  • Perl
  • Ruby
• Databases
  • MySQL
  • PostgreSQL
• Subscriptions
  • [OPML feed]
  • "Control F'd"
  • "Fredrik Håård's Blaag"
  • "Menno's Musings"
  • "Michael J.T. O'Kelly"
  • "Morphex's Blogologue"
  • "Speno's Pythonic Avocado"
  • "William's Journal"
  • 2degrees
  • 4teamwork
  • A. Jesse Jiryu Davis
  • ABlog for Sphinx
  • AWeber Engineering
  • Aahz
  • Abhijeet Pal
  • Abu Ashraf Masnun
  • Adam Pletcher
  • Agendaless Consulting
  • Al-Ahmadgaid Asaad
  • Albert Hopkins
  • Alec Munro
  • Alex Clark
  • Alex Grönholm
  • Alex Morozov
  • Alexander Limi
  • Alexandre Conrad
  • Alexandre Vassalotti
  • Alexey Evseev
  • Allison Kaptur
  • Amit Saha
  • Amjith Ramanujam
  • AmvTek
  • Anarcat
  • Anastasios Hatzis
  • Anatoly Techtonik
  • Andre Roberge
  • Andrea Grandi
  • Andrew Dalke
  • Andriy Kornatskyy
  • Andy Dustman
  • Andy R. Terrel
  • Ankit Chandawala
  • Anna Martelli Ravenscroft
  • Anthony Baxter
  • Anton Belyaev
  • Anton Bobrov
  • Anwesha Das
  • AppNeta Blog
  • Armin Ronacher
  • Arnav Khare
  • Artem Golubin
  • Artem Rys
  • Ashish Vidyarthi
  • Astro Code School
  • Atul Varma -- Toolness
  • Audrey Roy Greenfeld
  • Automating OSINT
  • Baiju Muthukadan
  • Bajusz Tamás
  • Balthazar Rouberol
  • BangPypers
  • BeDjango
  • Ben Bass
  • Ben Rousch
  • Ben Tappin
  • Benjamin Peterson
  • Benji York
  • Bertrand Mathieu
  • Bhishan Bhandari
  • Bill Ward / AdminTome
  • BioPython News
  • Bit of Cheese
  • Blue Yonder Tech
  • BlueBream
  • Bojan Mihelac
  • Brad Lucas
  • Brandon Rhodes
  • BreadcrumbsCollector
  • Brendan Scott
  • Brett Cannon
  • Brian Harring
  • Brian Okken
  • Bruno Oliveira
  • Bruno Rocha
  • Caktus Consulting Group
  • Calvin Cheng
  • Calvin Spealman
  • Carl Chenet
  • Carl Trachte
  • Carlos Eduardo de Paula
  • Carlos de la Guardia
  • Casey Duncan
  • Catalin George Festila
  • Catherine Devlin
  • Checking and Sharing
  • Chris Hager
  • Chris Leary
  • Chris McAvoy
  • Chris McDonough
  • Chris Miles
  • Chris Miller
  • Chris Mitchell
  • Chris Moffitt
  • Chris Rose
  • Chris Warrick
  • Christian Barra
  • Christian Heimes
  • Christian Scholz
  • Christoph Zwerschke
  • Christopher Lenz
  • Chuck Thier
  • ClusterHQ
  • Cobe.io
  • CodeGrades
  • CodeSnipers
  • Codementor
  • Coding Diet
  • Collin Winter
  • Continuum Analytics Blog
  • Continuum Analytics News
  • Continuum Blog
  • Core Software
  • Corey Goldberg
  • Corey Oordt
  • Cormoran Project
  • Craig Kerstiens
  • Cross-Platform Command Line Tools
  • CubicWeb
  • Curtis Miller
  • DSPIllustrations.com
  • DaPythonista
  • Daily Tech Video (Python)
  • Dalius Dobravolskas
  • Dallas Fort Worth Pythoneers
  • Damián Avila
  • Dan Crosta
  • Dan Stromberg
  • Dan Yeaw
  • Daniel Bader
  • Daniel Nouri
  • Daniel Roy Greenfeld
  • Dariusz Suchojad
  • Data Community DC
  • Data School
  • DataCamp
  • Dataquest
  • Dave Beazley
  • David Goodger
  • David Grant
  • David J C Beach
  • David MacIver
  • David Malcolm
  • David Marte
  • David Stanek
  • David Szotten
  • Davide Moro
  • Davy Mitchell
  • Davy Wybiral
  • DeGizmo
  • Denis Kurov
  • Derrick Petzold
  • Dethe Elza
  • Diego Garcia
  • Django Weblog
  • Django Weekly
  • Djangostars
  • Doing Math with Python
  • Doug Hellmann
  • Doug Latornell
  • Dougal Matthews
  • Douglas Napoleone
  • DreamHost
  • Duncan McGreggor
  • Dusty Phillips
  • EasyGUI
  • Ed Crewe
  • Ed Taekema
  • Edward K. Ream
  • Eko S. Wibowo
  • Eli Bendersky
  • Eniram Ltd.
  • Enthought
  • Eray Özkural (examachine)
  • Eric Holscher
  • Erik Marsja
  • Etienne Desautels
  • EuroPython
  • EuroPython Society
  • Even Wiik Thomassen
  • Evennia
  • Experienced Django
  • Fabio Zadrozny
  • Fazal Majid
  • Filip Wasilewski
  • Filipe Saraiva
  • Flavio Coelho
  • Flavio Percoco
  • Floris Bruynooghe
  • Francisco Souza
  • Frank Wierzbicki
  • François Dion
  • François Marier
  • Frederik Rietdijk
  • Fredrik Lundh
  • From Python Import Podcast
  • Full Stack Python
  • Gaël Varoquaux
  • Gabriel Pettier
  • Galvanize
  • Gary Bernhardt
  • Gary Wilson
  • Geek Scrap
  • Georg Brandl
  • Georges Dubus
  • Ghaandee on IT
  • Giampaolo Rodola
  • Giulio Fidente
  • Glenn Franxman
  • Glyph Lefkowitz
  • Go Deh
  • GoDjango
  • Gocept Weblog
  • Godson Gera
  • Gonçalo Margalho
  • Graeme Cross
  • Graham Dumpleton
  • Graham Wheeler
  • Grant Baillie
  • Grant Rettke
  • Greg Taylor
  • Gridarrow
  • Grig Gheorghiu
  • Grzegorz Śliwiński
  • Guido van Rossum
  • Guilherme Toti
  • Gustavo Narea
  • Gustavo Niemeyer
  • Guyon Moree
  • Gökhan Sever
  • Hany Fahim
  • Hector Garcia
  • Heikki Toivonen
  • Hernan Grecco
  • Hilary Mason
  • Holger Krekel
  • Holger Peters
  • Hynek Schlawack
  • IO Digital Sec
  • Ian Ozsvald
  • Ilian Iliev
  • Import Python
  • Intellimath blog
  • Ionel Cristian Maries
  • Iraj Jelodari
  • IronPython-URLs
  • Ishan Chattopadhyaya
  • IslandT
  • Israel Fruchter
  • Itamar Turner Trauring
  • Ivan Krstic
  • J. Pablo Fernández
  • Jack Diederich
  • Jacob Perkins
  • Jahongir Rahmonov
  • Jaime Buelta
  • Jamal Moir
  • James Bennett
  • James Mills
  • Jan-Carel Brand
  • Janusworx
  • Jarrod Millman
  • Jason Meyers
  • Jason Webb
  • Jaysinh Shukla
  • Jean-Louis Fuchs
  • Jean-Paul Calderone
  • Jeethu Rao
  • Jeff Bisbee
  • Jeff Bradberry
  • Jeff Hinrichs
  • Jeff Knupp
  • Jeff Shell
  • Jeremy Epstein
  • Jeremy Hylton
  • Jim Fulton
  • Jim Hughes
  • Joe Abbate
  • Joe Pitz
  • Johan Dahlin
  • John Anderson
  • John Burns
  • John Cook
  • John Jacobsen
  • John Paulett
  • Jon Parise
  • Jonathan Dobson
  • Jonathan Ellis
  • Jonathan Harrington
  • Jonathan Hartley
  • Jonathan LaCour
  • Jonathan Street
  • Jorge Niedbalski
  • Jorge Puente Sarrín
  • Jorgen Schäfer
  • Juan Manuel Contreras
  • Juan Rodríguez Monti
  • Juho Vepsäläinen
  • Julien Danjou
  • Julien Palard
  • Julien Tayon
  • Juri Pakaste
  • Just a little Python
  • Justin Mayer
  • Kai Lautaportti
  • Karim Elghamrawy
  • Kate Editor
  • Kay Hayen
  • Kay Schluehr
  • Kelly Yancey
  • Kenneth Reitz
  • Kevin Dahlhausen
  • Kevin Dangoor
  • Kiwi PyCon
  • Kogan Dev
  • Konrad Delong
  • Koodaamo
  • Kracekumar Ramaraju
  • Kristján Valur Jónsson
  • Kriti Godey
  • Kulbir Saini
  • Kumar McMillan
  • Kushal Das
  • Károly Nagy
  • Laurence Rowe
  • Laurent Luce
  • Laurent Szyster
  • Learn PyQt
  • Leigh Honeywell
  • Lennart Regebro
  • Leonhard Vogt
  • Lightning Fast Shop
  • Lintel Technologies
  • Lion Kimbro
  • Lionel Tan
  • ListenData
  • Logilab
  • Low Kian Seong
  • Luca Botti
  • Ludovic Gasc
  • Ludvig Ericson
  • Luke Macken
  • Luke Plant
  • Maciej Fijalkowsk
  • Made With Mu
  • Mahmoud Hashemi
  • Malthe Borch
  • Manuel de la Pena Saenz
  • Marc Garcia
  • Marc Kerins
  • Marc Richter
  • Marc-André Lemburg
  • Marcos Dione
  • Marius Gedminas
  • Mark Dufour
  • Mark McLoughlin
  • Mark McMahon
  • Mark Mruss
  • Mark Ramm
  • Marko Samastur
  • Martijn Faassen
  • Martijn Pieters
  • Martin Fitzpatrick
  • Mathieu Virbel
  • Mats Kindahl
  • Matt Harrison
  • Matt Layman
  • Matt Reid
  • Matt Wilkes
  • Matthew Rocklin
  • Matthew Rollings
  • Matthew Wilson
  • Mattias Brändström
  • Mauveweb
  • Max Ischenko
  • Michael Bayer
  • Michael Becker
  • Michael Droettboom
  • Michael Foord
  • Michael Hudson
  • Michael Nelson
  • Michael Sparks
  • Michal Kwiatkowski
  • Michał Bultrowicz
  • Michele Simionato
  • Michy Alice
  • Mike C. Fletcher
  • Mike Driscoll
  • Mike Müller
  • Mikeal Rogers
  • Mikhail Korobov
  • Mikko Ohtamaa
  • Mitch Chapman
  • Mitchell Garnaat
  • Mitya Sirenef
  • Montreal Python User Group
  • Morten W Petersen
  • Moshe Zadka
  • Moya Project
  • Mozilla Web Development
  • Muharem Hrnjadovic
  • Mycli
  • Nadav Samet
  • Nadia Alramli
  • Naomi Ceder
  • Natan Zabkar
  • Nathan Lemoine
  • Nathan Piccini Data Science Dojo Blog
  • Ned Batchelder
  • Neil Schemenauer
  • Ng Pheng Siong
  • Nicholas Amorim
  • Nick Coghlan
  • Nick Craig-Wood
  • Nick Efford
  • Nick Janetakis
  • Nicola Iarocci
  • Nicolas Dumazet
  • Nicolas Paris
  • Nigel Babu
  • Nikola
  • Nikolaos Diamantis
  • Not Invented Here
  • NumFOCUS
  • Obey the Testing Goat
  • Ofosos
  • Oliver Andrich
  • Omaha Python Users Group
  • Ondřej Čertík
  • OpenHatch Python posts
  • PSF GSoC students blogs
  • Paolo Melchiorre
  • Pathwright
  • Patrice Neff
  • Patricio Paez
  • Patrick Kennedy
  • Patrick Stinson
  • Paul Bissex
  • Paul Everitt
  • Paul Harrison
  • Paul Redman
  • Paweł Fertyk
  • PayPal Engineering Blog
  • Pedro Lima
  • Petecode
  • Peter Bengtsson
  • Peter Eisentraut
  • Peter Fankhänel
  • Peter Harkins
  • Peter Hoffmann
  • Phil Hassey
  • Philip Jenvey
  • Philip Semanchuk
  • Philipp von Weitershausen
  • Philippe Normand
  • Phillip J. Eby
  • Pierre Carbonnelle
  • Podcast.__init__
  • Polyglot.Ninja()
  • Possbility and Probability
  • Pradeep Gowda
  • Pranav Pandey
  • Praveen Gollakota
  • Programando Ciência
  • Programiz
  • Programming Ideas With Jake
  • Przemysław Kołodziejczyk
  • PyBites
  • PyCarolinas
  • PyCharm
  • PyCoder’s Weekly
  • PyCon
  • PyCon Australia
  • PyCon Pune
  • PyCon.DE & PyData Karlsruhe
  • PyPy Development
  • PyTennessee
  • PyTexas
  • Pypix
  • Python 4 Kids
  • Python 411 Podcast
  • Python Advocacy
  • Python Anywhere
  • Python Bytes
  • Python Celery - Weekly Celery Tutorials and How-tos
  • Python Circle
  • Python Data
  • Python Diary
  • Python Does What?!
  • Python Engineering at Microsoft
  • Python Insider
  • Python Open Mike
  • Python Piedmont Triad User Group
  • Python Software Foundation
  • Python Sweetness
  • Python Testing Cookbook
  • Python User Groups
  • Python on Karan
  • Python with Myo
  • Python(x,y) News
  • PythonClub - A Brazilian collaborative blog about Python
  • PythonDebugging.com
  • PythonThreads
  • Pythonicity
  • Pythonology
  • Péter Szabó
  • Péter Zsoldos
  • Quansight Labs Blog
  • R David Murray
  • RMOTR
  • Ralph Bean
  • Ralph Heinkel
  • Ram Rachum
  • Randell Benavidez
  • Randle Taylor
  • Randy Zwitch
  • Raymond Hettinger
  • Read the Docs
  • Real Python
  • Red Hat Developers
  • Reinout van Rees
  • Rene Dudfield
  • Reuven Lerner
  • Richard Gomes
  • Richard Jones
  • Richard Tew
  • Richard Wall
  • Rickard Lindberg
  • Rob Galanakis
  • Rob Golding
  • Rob Miller
  • Robert Brewer
  • Robert Collins
  • Robert Zaremba
  • Roberto Alsina
  • Robin Parmar
  • Robin Wilson
  • Roche Compaan
  • Rodrigo Araúj
  • Roman Imankulov
  • RoseHosting Blog
  • Ruslan Spivak
  • Ryan Cox
  • S. Lott
  • S. R. Krishnan
  • SDJournal
  • SPE Weblog
  • Salim Fadhley
  • Salman Haq
  • Samuel Sutch
  • Sandipan Dey
  • Sandro Tosi
  • Sayan Chowdhury
  • Scripting the web with Python
  • Sean McGrath
  • Selena Deckelmann
  • Semaphore Community
  • Senthil Kumaran
  • Server Density
  • Shannon -jj Behrens
  • ShiningPanda
  • Shopkick Tech Blog
  • Simeon Franklin
  • Simeon Visser
  • Simon
  • Simon Brunning
  • Simon Wittber
  • Simple is Better Than Complex
  • SoftFormance
  • Speed Matters
  • Spike ekipS
  • Spyder IDE
  • Stack Abuse
  • Stacks
  • Stanislas Morbieu
  • Starzel.de
  • Stefan Behnel
  • Stefan Petrea
  • Stefan Scherfke
  • Stein Magnus Jodal
  • Stephen Ferg
  • Steve Dower
  • Steve Holden
  • Steven Klass
  • Stijn Debrouwere
  • Stories in My Pocket
  • Stuart Gordon Reid
  • Stéphane Wirtel
  • Sumana Harihareswara - Cogito, Ergo Sumana
  • Sumith - Blog about SymPy/Python
  • Swaroop C H
  • Swisscom ICT
  • Sylvain Hellegouarch
  • Talk Python to Me
  • Tarek Ziade
  • Taylor Edmiston
  • TechBeamers Python
  • Techiediaries - Django
  • Ted Leung
  • Tennessee Leeuwenburg
  • Terri Oda
  • Terry Jones
  • Terry Peppers
  • Test and Code
  • The Artificial Intelligence Cookbook
  • The Code Bits
  • The Data Scientist
  • The Digital Cat
  • The No Title® Tech Blog
  • The Occasional Occurrence
  • The Parcon Blog
  • The Python Papers
  • The Three of Wands
  • TheAutomatic.net
  • Thibauld Nion
  • Thomas Guest
  • Thomas Vander Stichele
  • Thomi Richards
  • Tiago Montes
  • Tibo Beijen
  • Tim Arnold / reachtim
  • Tim Gilbert
  • Tim Golden
  • Tim Knapp
  • Tim Lesher
  • Tim van der Linden
  • Tobias Ivarsson
  • Toes to the Edge
  • Tom Christie
  • Tomasz Ducin
  • Tomasz Früboes
  • Tomaž Muraus
  • Tomer Filiba
  • Tony Breyal
  • Torsten Engelbrecht
  • Toshio Kuratomi
  • Travis Oliphant
  • Trey Hunner
  • Troy Melhase
  • Tryton News
  • Turnkey Linux
  • Twisted Matrix Labs
  • Two Bit Arcade
  • Uche Ogbuji
  • United Coders
  • V.S. Babu
  • Varun Nischal
  • Vasudev Ram
  • Vinay Sajip
  • Vinay Sajip (Logging)
  • Vinta Software
  • Virgil Dupras
  • Vladimir Iakolev
  • Vladimir Perić
  • Wallaroo Labs
  • Wallix
  • Wayne Witzel
  • Weekly Python Chat
  • Weekly Python StackOverflow Report
  • Wes Mason
  • Wesley Chun
  • Wichert Akkerman
  • Will Kahn-Greene
  • Will McGugan
  • Will Pierce
  • William Minchin
  • William Reade
  • William Thompson
  • Wingware Blog
  • Wingware News
  • Wraithan
  • Yaco
  • Yaniv Aknin
  • Yann Larrivée
  • Yasoob Khalid
  • Yuval Greenfield
  • Zaki Akhmad
  • Zato Blog
  • Zero-with-Dot (Oleg Żero)
  • ZeroDB
  • bottlepy-dev
  • codeboje
  • codingdirectional
  • eGenix.com
  • eRambler
  • gamingdirectional
  • hypothesis.works articles
  • kdev-python
  • leftmouseclickin
  • meejah.ca
  • nl-project
  • pgcli
  • py.CheckIO
  • pythonwise
  • qutebrowser development blog
  • saaj/recollection
  • tryexceptpass
  • Éric Araujo
  • Łukasz Langa
  • بايثون العربي
  • To request addition or removal:
    Open an issue on github
    or e-mail planet at python.org
    (note, responses can take up to a few days)