You will be an engineer in 100 days --Day 33 --Python --Basics of the Python language 8
Today is a continuation of the basics of Python, but today the basics are over.
Click here for the last time [You will be an engineer in 100 days --Day 32 --Python --Basics of Python language 7] (https://qiita.com/otupy/items/9e70a3b36f32fccacadf)
Object-oriented story
The python language is a object-oriented programming language.
So what is object-oriented?
In the python language, everything handled is the concept of object.
All data stored in variables is also treated as object.
** String object **
For example, if you assign the string ʻabc to the variable ʻa,
This variable ʻa becomes a string type object`.
#String type object
a = 'abc'
print(a)
abc
** Functions and methods **
Next, let's declare the variable l and the element of list type.
Then this variable l becomes a list type object,
At the same time, you can use the function method of the list object.
#Define list type
lis1 = [1,2,3]
#List type method
lis1.append(4)
print(lis1)
[1, 2, 3, 4]
Strictly speaking, function and method are different.
To put it simply, add data as a list type ʻappend Etc. are operations on thelist objectitself It will be treated as amethod`.
In object-oriented, it is defined by an object
A function that is written in the same way as a function is called a method.
Others are called functions.
If you create a string type object,
The function that the object has can be said to be a method.
** Concept of object thinking **
Object-oriented is a programming language composed of some kind of thing object.
Objects include variables, data types, functions, and classs.
The idea of making something on the program and handling it
It becomes the basic idea of object-oriented.
Because this area is conceptual You don't have to know right now, or if it's a simple program you don't know It's something that can be done. Please remember eventually.
In this next installment, I'll go into more detail about class.
About class
Last time I explained the concept of object-oriented.
After learning the concept of object-oriented, the next step is actually in python
Let's create a class that will be the object.
** How to make a class **
class class name():
def __init__(self,):
processing
** How to call a class **
Variable name = class name ()
Let's create a simple class.
class class_a():
def __init__(self,):
print('Initialization')
self.ac = 'aaa'
You have now created a class.
** Instance and instantiation **
A instance is amaterializedof a class.
To use data and methods of class
You need to create something called an instance.
Call the class and store it in a variable.
Instantiate this thing
The created variable is also called instance.
#Instantiation
a = class_a()
Initialization
Here, the part of the method called ʻinitis When creating ainstance called a constructor`
This is the process called at the very beginning.
When calling class and storing it in a variable
ʻInit` is called and the processing in it is executed.
In this ʻinit process, there is a variable name selfas an argument. The variableself points to itself, and this argument is mandatory for class`
If you do not write it, an error will occur.
In the process of ʻinit, the variable self.ac is used as a value. Substituting ʻaaa.
Now you have allocated a variable called ʻac in this class` and assigned the value.
You will be able to use this variable in the part you call after creating the class.
** How to call class variables and methods **
Class variable name. Method name
aa = class_a()
print(aa.ac)
Initialization aaa
Let's add a variable for the class.
aa.b = 2
print(aa.b)
2
The variable b was allocated in the class and the value 2 was assigned.
You will be able to reuse this variable later.
The variables defined in this class are called attributes.
In class, functions can be defined separately from constructor,
The function defined in this class is called the method.
Let's add a method.
#Class definition
class class_a():
def __init__(self,):
print('Initialization')
self.ac = 'aaa'
#Method definition
def anaa(self, ):
print(1)
#Call a class and store it in a variable
aa = class_a()
#Call a method of the class.
aa.anaa()
Initialization 1
In this way, a class has multiple methods and variables.
It will be a object.
The method and attribute are
Because it can only be called from within that class
The variable ʻac defined in class` cannot be used as it is.
print(ac)
NameError Traceback (most recent call last)
Must be used with class variables.
print(aa.ac)
aaa
When do you use class?
It can be used to group large processes in a program
This is useful when you want to reuse it in another program.
Once as one program, classify
It is common to reuse it in another program.
** Class inheritance **
The class also has the concept of inheritance.
First of all, as what is supposed to be inherited
Create a parent-child class and create a method in it.
class oya():
def oyano_method(self):
print('oyano')
#Specify the inherited class as an argument
class ko(oya):
def kono_method(self):
print('kono')
For the child class, specify the parent class` as an argument.
By doing so, when you generate a child class,
You will be able to use the method of the parent class.
#Call a child class.
k = ko()
#You can call the parent class inherited by the child class
k.kono_method()
k.oyano_method()
kono oyano
As you can see, it wasn't in the child class
You will be able to call the method of the parent class.
This is a derivation of the existing class,
When you want to create a new class, etc.
This is a convenient function that can be used.
It's hard to remember the concept and mechanism of class,
If you remember it, the range of programming will be greatly expanded.
Please try to remember slowly and surely
Exception handling
I think that error was displayed several times in the lectures so far.
For example
#Define list type
aqq = [1,2,3]
#Extract value by index
print(aqq[31])
IndexError Traceback (most recent call last)
If you specify a value outside the index range of the list type
list index out of range
I get the error, which is an error output that is out of the list.
When such a error occurs, the program will end there.
So try not to generate an error
You need to take action when an error occurs.
Since it is difficult to suppress the occurrence of error,
By writing a description that avoids error, the program will not be terminated.
That is exception handling.
** How to write python exception handling **
try:
processing
except:
Exception processing
Exception handling in python is where error is likely to occur
Enclose it in the phrase try --except.
ʻException` is an English word meaning exception. Please remember.
try:
aqq = [1,2,3]
#I get an error here
print(aqq[31])
except:
#This is called when an error occurs
print('error')
error
Write the processing when a error occurs in the ʻexcept` block.
If nothing is done even if a error occurs
If you do not write anything, a syntax error will occur.
Write pass.
try:
aqq = [1,2,3]
print(aqq[31])
except:
#If you do not write any processing, an error will occur
File "
If you do not write any processing, an error will occur
^ SyntaxError: unexpected EOF while parsing
try:
aqq = [1,2,3]
print(aqq[31])
except:
#If the process is undecided, write pass
pass
In the above, you can see that the error has occurred,
I don't know what's going on.
So if you can expect a error in advance
You can write multiple processes when a error occurs.
try:
processing
except error name:
Exception processing
except error name:
Exception processing
try:
aqq = [1,2,3]
#Index error occurs here
print(aqq[31])
except IndexError:
#Catch the Index error here
print('index error')
except Exception:
print('exception')
index error
By writing error name after ʻexcept`,
You can write the processing when the corresponding error occurs.
In the above example, if ʻIndex error occurs The processing of the part of ʻIndexError will be executed.
ʻException` picks up all errors.
** Python error type **
ZeroDivisionError
Occurs when a number is divided by 0
1/0
ZeroDivisionError Traceback (most recent call last)
NameError
Occurs when trying to reference a variable or method that does not exist
print(asokokoks)
NameError Traceback (most recent call last)
This is a grammatical mistake in the first place, so
This is a usage that is not often used in try-except.
KeyError
Occurs when there is no dictionary type key
d ={1:2,3:4}
print(d[5])
KeyError Traceback (most recent call last)
There are many other errors. The following code displays a python built-in error.
[i for i in dir(__builtins__) if 'Error' in i]
['ArithmeticError',
'AssertionError',
'AttributeError',
'BlockingIOError',
'BrokenPipeError',
'BufferError',
'ChildProcessError',
'ConnectionAbortedError',
'ConnectionError',
'ConnectionRefusedError',
'ConnectionResetError',
'EOFError',
'EnvironmentError',
'FileExistsError',
'FileNotFoundError',
'FloatingPointError',
'IOError',
'ImportError',
'IndentationError',
'IndexError',
'InterruptedError',
'IsADirectoryError',
'KeyError',
'LookupError',
'MemoryError',
'NameError',
'NotADirectoryError',
'NotImplementedError',
'OSError',
'OverflowError',
'PermissionError',
'ProcessLookupError',
'RecursionError',
'ReferenceError',
'RuntimeError',
'SyntaxError',
'SystemError',
'TabError',
'TimeoutError',
'TypeError',
'UnboundLocalError',
'UnicodeDecodeError',
'UnicodeEncodeError',
'UnicodeError',
'UnicodeTranslateError',
'ValueError',
'ZeroDivisionError']
If you don't know the error that occurs, enclose it in try --except for the time being.
Later, it is better to add processing according to the error content.
Be sure to remember exception handling as it is a required technique in your program.
Use of the library
For the program language, you can use programs created by other people, It has convenient functions that allow you to use the programs you have created.
That is the library.
In python, there is a library that can be used immediately for work or research.
There are many, such as machine learning and statistical analysis.
It's easy to do with the library.
Using the library is very simple.
** How to load the library **
ʻImport library name from package name import library name`
Now let's use the library.
Load the random library that produces random values.
import random
How to call the function randint () to generate a random integer
random.randint (minimum, maximum)
random.randint(1,10)
10
#Call a random method 10 times
for i in range(10):
print(random.randint(1,10))
9 5 3 8 2 9 2 1 4 7
Many libraries function specific processes.
The library is also called the module in another name.
If there is an expression such as loading module,
It's okay to think that you are loading a other program.
** Main python libraries **
*** os library *** You can operate files and directories on your PC
import os
#List files and folders in your PC's directory
print(os.listdir('/'))
['.DocumentRevisions-V100', '.file', '.fseventsd', '.PKInstallSandboxManager', '.Spotlight-V100', '.Trashes', '.vol', 'anaconda', 'Applications', 'bin', 'cores', 'dev', 'etc', 'home', 'installer.failurerequests', 'Library', 'Live2D_Cache', 'net', 'Network', 'opt', 'private', 'sbin', 'System', 'tmp', 'Users', 'usr', 'var', 'Volumes']
ʻOs.listdir (files, directories, etc.) `
If you specify a directory in the argument of listdir, it will be in that directory.
Files and folders are returned as list values.
Find files and directories on your PC, Use the list of files to load a specific file or It is useful for writing programs that operate.
*** time library *** A library for time-related operations in a program
import time
#Stop the program for 2 seconds
time.sleep(2)
print(2)
time.sleep(1)
print(1)
2 1
** How to use your own library **
If you create a python file, you can load your own library. The extension of the library that can be imported is .py.
First, let's create a simple python executable file.
This notebook is placed
Create a python file in the folder.
Create it with a text editor and save the extension as .py.
sample.py
def hello(aa):
print(aa)
After creating the python file
It can be read as a library, and methods etc. can be used.
#Loading your own library
import sample
#Method call
sample.hello('hello')
hello
There are innumerable libraries, and when installed with anaconda, there are about 400 types. The library is ready to use. The name of the library is confusing, so let's take a look at the installed library.
On a notebook for mac
! pip list
Now you can run the command and view it.
In case of windows, at the command prompt etc.
Please take ! And execute it.
! pip list
DEPRECATION: The default format will switch to columns in the future. You can use --format=(legacy|columns) (or define a format=(legacy|columns) in your pip.conf under the [list] section) to disable this warning.
adal (0.4.5)
alabaster (0.7.10)
alembic (0.9.6)
anaconda-client (1.6.3)
anaconda-navigator (1.6.2)
anaconda-project (0.6.0)
appnope (0.1.0)
appscript (1.0.1)
argcomplete (1.0.0)
asn1crypto (0.22.0)
astroid (1.4.9)
astropy (1.3.2)
azure (2.0.0rc6)
azure-batch (1.0.0)
azure-common (1.1.6)
azure-datalake-store (0.0.12)
azure-graphrbac (0.30.0)
azure-keyvault (0.3.5)
azure-mgmt (0.30.0rc6)
azure-mgmt-authorization (0.30.0)
azure-mgmt-batch (1.0.0)
azure-mgmt-cdn (0.30.3)
azure-mgmt-cognitiveservices (1.0.0)
azure-mgmt-compute (0.30.0rc6)
azure-mgmt-containerregistry (0.2.1)
azure-mgmt-datalake-analytics (0.1.6)
azure-mgmt-datalake-nspkg (2.0.0)
azure-mgmt-datalake-store (0.1.6)
azure-mgmt-devtestlabs (2.0.0)
azure-mgmt-dns (1.0.1)
azure-mgmt-documentdb (0.1.3)
azure-mgmt-iothub (0.2.2)
azure-mgmt-keyvault (0.30.0rc6)
azure-mgmt-logic (1.0.0)
azure-mgmt-monitor (0.2.1)
azure-mgmt-network (0.30.0rc6)
azure-mgmt-nspkg (2.0.0)
azure-mgmt-rdbms (0.1.0)
azure-mgmt-redis (1.0.0)
azure-mgmt-resource (0.30.0rc6)
azure-mgmt-scheduler (1.0.0)
azure-mgmt-sql (0.5.3)
azure-mgmt-storage (0.30.0rc6)
azure-mgmt-trafficmanager (0.30.0)
azure-mgmt-web (0.32.0)
azure-nspkg (2.0.0)
azure-servicebus (0.20.3)
azure-servicefabric (5.6.130)
azure-servicemanagement-legacy (0.20.4)
azure-storage (0.20.3)
Babel (2.4.0)
backports.shutil-get-terminal-size (1.0.0)
bcolz (0.12.1)
beautifulsoup4 (4.6.0)
bitarray (0.8.1)
blaze (0.10.1)
bleach (1.5.0)
bokeh (0.12.5)
boto (2.46.1)
Bottleneck (1.2.1)
bs4 (0.0.1)
certifi (2017.4.17)
cffi (1.10.0)
chardet (3.0.4)
charts (0.4.6)
chest (0.2.3)
click (6.7)
cloudpickle (0.2.2)
clyent (1.2.2)
colorama (0.3.9)
conda (4.5.11)
conda-build (3.0.19)
conda-verify (2.0.0)
configobj (5.0.6)
contextlib2 (0.5.5)
coverage (4.4.2)
cryptography (1.9)
cssselect (1.0.1)
cycler (0.10.0)
cyordereddict (1.0.0)
Cython (0.27.2)
cytoolz (0.8.2)
dask (0.14.3)
datashape (0.5.4)
decorator (4.0.11)
dill (0.2.6)
distributed (1.16.3)
Django (1.10.6)
django-bootstrap3 (8.2.2)
django-crispy-forms (1.6.1)
django-debug-toolbar (1.8)
django-pure-pagination (0.3.0)
django-registration-redux (1.5)
django-storages (1.6.3)
django-torina-blog (0.5)
docutils (0.13.1)
dynd (0.7.3.dev1)
empyrical (0.3.2)
entrypoints (0.2.2)
et-xmlfile (1.0.1)
fastcache (1.0.2)
fbprophet (0.2.1)
filelock (2.0.7)
Flask (0.12.2)
Flask-Cors (3.0.2)
future (0.16.0)
gevent (1.2.1)
glob2 (0.5)
greenlet (0.4.12)
h5py (2.7.0)
HeapDict (1.0.0)
html5lib (0.999999999)
idna (2.5)
imagesize (0.7.1)
intervaltree (2.1.0)
ipykernel (4.6.1)
ipython (5.3.0)
ipython-genutils (0.2.0)
ipywidgets (6.0.0)
isodate (0.5.4)
isort (4.2.5)
itsdangerous (0.24)
Janome (0.3.5)
jdcal (1.3)
jedi (0.10.2)
Jinja2 (2.9.6)
jsonschema (2.6.0)
jupyter (1.0.0)
jupyter-client (5.0.1)
jupyter-console (5.1.0)
jupyter-core (4.3.0)
keyring (10.4.0)
lazy-object-proxy (1.2.2)
line-bot-sdk (1.0.2)
llvmlite (0.18.0)
locket (0.2.0)
Logbook (1.1.0)
lru-dict (1.1.6)
lxml (3.7.3)
Mako (1.0.7)
MarkupSafe (0.23)
matplotlib (2.0.2)
mistune (0.7.4)
mpmath (0.19)
msgpack-python (0.4.8)
msrest (0.4.11)
msrestazure (0.4.11)
multipledispatch (0.4.9)
navigator-updater (0.1.0)
nb-anacondacloud (1.4.0)
nb-conda (2.2.0)
nb-conda-kernels (2.1.0)
nbconvert (5.1.1)
nbformat (4.4.0)
nbpresent (3.0.2)
networkx (1.11)
nltk (3.2.4)
nose (1.3.7)
notebook (5.0.0)
numba (0.33.0)
numexpr (2.6.4)
numpy (1.12.1)
numpydoc (0.6.0)
oauthlib (2.0.2)
odo (0.5.0)
olefile (0.44)
opencv-python (3.4.5.20)
openpyxl (2.4.7)
packaging (16.8)
pandas (0.20.1)
pandas-datareader (0.5.0)
pandas-highcharts (0.5.2)
pandocfilters (1.4.1)
partd (0.3.8)
pathlib2 (2.2.1)
patsy (0.4.1)
pep8 (1.7.0)
pexpect (4.2.1)
pickleshare (0.7.4)
Pillow (4.1.1)
pip (9.0.1)
pkginfo (1.4.1)
plotly (2.3.0)
ply (3.10)
prompt-toolkit (1.0.14)
psutil (5.2.2)
psycopg2 (2.7.1)
ptyprocess (0.5.1)
py (1.4.33)
py-d3 (0.2.7)
PyAlgoTrade (0.18)
pyasn1 (0.2.3)
pycosat (0.6.3)
pycparser (2.18)
pycrypto (2.6.1)
pycurl (7.43.0)
pyflakes (1.5.0)
Pygments (2.2.0)
PyJWT (1.5.2)
pylint (1.6.4)
pyodbc (4.0.16)
pyOpenSSL (17.0.0)
pyparsing (2.1.4)
pystan (2.17.0.0)
pytest (3.0.7)
python-dateutil (2.6.0)
python-editor (1.0.3)
python-highcharts (0.4.1)
pytz (2017.2)
PyWavelets (0.5.2)
PyYAML (3.12)
pyzmq (16.0.2)
QtAwesome (0.4.4)
qtconsole (4.3.0)
QtPy (1.2.1)
redis (2.10.5)
requests (2.18.1)
requests-file (1.4.2)
requests-ftp (0.3.1)
requests-oauthlib (0.8.0)
rope-py3k (0.9.4.post1)
scikit-image (0.13.0)
scikit-learn (0.18.1)
scipy (0.19.0)
seaborn (0.7.1)
selenium (3.0.2)
setuptools (27.2.0)
simplegeneric (0.8.1)
singledispatch (3.4.0.3)
six (1.10.0)
snowballstemmer (1.2.1)
sockjs-tornado (1.0.3)
sortedcollections (0.5.3)
sortedcontainers (1.5.7)
Sphinx (1.5.6)
sphinx-rtd-theme (0.2.4)
spyder (3.1.4)
SQLAlchemy (1.1.9)
sqlparse (0.2.3)
statsmodels (0.8.0)
sympy (1.0)
tables (3.4.2)
tblib (1.3.2)
terminado (0.6)
testpath (0.3)
toolz (0.8.2)
tornado (4.5.1)
traitlets (4.3.2)
unicodecsv (0.14.1)
urllib3 (1.21.1)
wcwidth (0.1.7)
webencodings (0.5)
Werkzeug (0.12.2)
wheel (0.29.0)
widgetsnbextension (2.0.0)
wrapt (1.10.10)
xlrd (1.0.0)
XlsxWriter (0.9.6)
xlwings (0.10.4)
xlwt (1.2.0)
zict (0.1.2)
zipline (1.1.1)
The name of the library does not have to be the same as this name, so If you get stuck in a search, change the name.
If you use your name, company name, nickname, etc. I think this area will be covered.
The use of libraries has become commonplace in programs, Programs that can already be used without writing the program yourself It is wise to call it from the library.
What kind of library can be used I can't show you all, so that's all for the basics.
Summary
The Python language is an object-oriented language, so all data is objects. Let's understand how to handle data together with the concept of classes.
Exception handling and loading the library are indispensable when writing a program. It's a good idea to practice how to write so that you can use both smoothly.
I can't cover all the commonly used libraries here. Let's write the code and try it while examining it for yourself.
For the frequently used code, I made a summary as a cheat sheet.
I will post a link here, so please refer to it. https://note.com/otupy/n/n1bedb9f36e54
67 days until you become an engineer
Author information
Otsu py's HP: http://www.otupy.net/
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