Let’s grasp the concept of decorator in Python PEP 318 with short snippets.
Step 1: Function as a parameter def f1(): print("Called f1.") def f2(f): f() f2(f1) # Called f1 f2 takes a function (object) as a parameter.
Step 2: Wapping function def f1(fun): def wrap(): print("Start wrap") fun() print("End wrap") return wrap def f(): print("In function f") f1(f)() ### python test.py #Start wrap #In function f #End wrap Step 3: Use decorator def f1(fun): def wrap(): print("Start wrap") fun() print("End wrap") return wrap @f1 def f(): print("In function f") f() ### python test.
Original source I followed the linke below.
https://hatemtayeb2.medium.com/hello-graphql-a-practical-guide-a2f7f9f70ab4
Install library pip -U install graphene Use it scheme.py
import graphene import json class Query(graphene.ObjectType): hello = graphene.String() def resolve_hello(self, info): return "world" schema = graphene.Schema(query=Query) result = schema.execute( ''' { hello } ''' ) data = dict(result.data.items()) print(json.dumps(data,indent=2)) Try the code.
$ python schema.py { "hello": "world" } GraphQL concepts Every GraphQL implementation needs a Query class that contains some fields, every field (not always) must have a resolver function that return data related to the field.
Basic information about dataframe df.info() #basic information about dataframe len(df.index) #rethrn the number of rows (data) df.count() #return the number of values which are non-NaN on each column df.head() df.tail() Count the data in a column In this example, the column is “Product”.
df["Product"].value_counts() unique values to series.
df["Product"].unique() # the type numpy.ndarray check distrivution in graph # Check the data distribution # The column is Score ax = df["Score"]value_counts().plot(kind='bar') fig = ax.
Open file with with statement with open("path/to/file", "r") as in_file blabla... Loop with index words = ["You", "are", "a", "genious", "!"] for i,word in enumerate(words): print(f"{i:{10}}{word:{12}}") Exit loop break
Concept There are manuy useful PDF documents in the internet. These are very useful when we get data for training.
PyPDF2 is a library for manipulating PDF files via Python.
PyPDF2 Official Documentation
Install You can install PyPDF2 via pip.
pip install PyPDF2 How to use - read a PDF file PdfFileReader Class - Official PyPDF2 document
We should open a file with mode rb. Read the file with PyPDF2.PdfFileReader(file_object) import PyPDF2 with open("sample.
Installing stacks You may be confused at first the differences between,
pyenv virtualenv pyenv-virtualenv Especially, virtualenv sounds like Linux virtual environment, but it isn’t at all. Here is the good answer about that.
Conclusion: pyenv-virtualenv is the best choice.
pyenv-virtualenv official: https://github.com/pyenv/pyenv-virtualenv
Install pyenv Install pyenv in macOS (or other Linux environments).
# Download source under ~/.pyenv git clone https://github.com/yyuu/pyenv.git ~/.pyenv # Set PATH and another variable echo -e '\n export PYENV_ROOT=$HOME/.
Environment macOS: 10.15.3 Python: pyenv installed Install pip install -U pip pip install jupyter How to Run jupyter-notebook run the Jupyter.
% jupyter-notebook [I 19:21:07.376 NotebookApp] Serving notebooks from local directory: /Users/atlex/nlp [I 19:21:07.376 NotebookApp] The Jupyter Notebook is running at: [I 19:21:07.376 NotebookApp] http://localhost:8888/?token=8637cf3f5b526b4ac33e93964844ecf7626ccd7be92616a2 [I 19:21:07.376 NotebookApp] or http://127.0.0.1:8888/?token=8637cf3f5b526b4ac33e93964844ecf7626ccd7be92616a2 [I 19:21:07.376 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation). [C 19:21:07.381 NotebookApp] To access the notebook, open this file in a browser: file:///Users/atlex/Library/Jupyter/runtime/nbserver-15083-open.
— title: “uv” date: 2020-04-30T16:13:23+02:00 categories: - “Draft” tags: - “dummy_tag” isCKJLanguage: false mathjax: false comments: false draft: true How it manages version Pyton version, under ~/.local/bin:
uv python install 3.12.7 --preview # Adds `python3.12` to `~/.local/bin` Project structd tree. . ├── .python-version ├── README.md ├── main.py └── pyproject.toml ❯ cat .python-version 3.10 ❯ cat pyproject.toml [project] name = "hello-world" version = "0.1.0" description = "Add your description here" readme = "README.