├── os ├── example_pipeline.py ├── os_module_puzzle.pdf └── README.rst ├── cover.jpg ├── cover.png ├── re ├── regex.pdf ├── kingkong.py ├── exercises │ ├── regex_sub.py │ ├── regex_exercises.md │ ├── regex_sub_solution.py │ ├── regex_search.py │ └── regex_solution.py ├── phone.py ├── fox.py ├── biological_seq │ ├── finditer.py │ └── SRC_HUMAN.fasta └── README.rst ├── PuLP ├── bricks.png ├── bricks_solution.png ├── README.md ├── magic_sqare.py ├── BricksLinear.ipynb └── bricks.svg ├── images ├── imap.png ├── wave.gif ├── balls.png ├── barplot.png ├── errorbars.png ├── histogram.png ├── lineplot.png ├── piechart.png ├── sinfunc.png └── ipythonblocks.png ├── numpy ├── blur.png ├── dim.png ├── flip.png ├── roll.png ├── purple.png ├── mandelbrot.png ├── python_logo.png ├── mandelbrot.py ├── transform_logo.py └── README.rst ├── oauth_git ├── run.sh └── github.py ├── pillow ├── five.png ├── python_logo.png ├── snowflake3.png ├── carrots │ ├── arial.ttf │ ├── brain.png │ ├── carrot.png │ ├── step07_final.png │ ├── step01-paste.py │ ├── step02-resize.py │ ├── step03-arrow.py │ ├── step06-text.py │ ├── step05-filters.py │ ├── step04-gradient.py │ └── step07-full_image.py ├── pylogo_warhol.png ├── dice_images │ ├── drei.png │ ├── eins.png │ ├── vier.png │ ├── zwei.png │ ├── blank.png │ ├── fuenf.png │ ├── sechs.png │ ├── wuerfel.png │ ├── double_dice.png │ └── wuerfel.py ├── flower_movie │ ├── flower.jpg │ ├── flower_movie.avi │ └── flower_movie.py ├── half_size.py ├── dice.py ├── README.md ├── warhol.py └── snowflake.py ├── scipy ├── fit.png ├── curve_fit.py └── README.rst ├── moviepy ├── panda.png ├── end_credits.avi ├── end_credits.txt └── end_credits.py ├── pandas ├── panda.png ├── hexpanda.png ├── README.rst └── hexpanda.py ├── pydocx ├── hamlet.docx ├── read_word_doc.py ├── create_doc.py └── README.md ├── tkinter ├── titanic.png ├── titanic2.png ├── README.rst ├── titanic.py └── titanic_sinks.svg ├── wordcloud ├── cloud.png ├── README.md └── create_wordcloud.py ├── matplotlib ├── barplot.png ├── errorbars.png ├── lineplot.png ├── piechart.png ├── scatterplot.png ├── lineplot.py ├── errorbars.py ├── balls.py ├── piechart.py ├── barplot.py └── README.md ├── tqdm ├── progress_bar.py └── README.rst ├── scikit_image ├── python_logo.png ├── wave │ ├── out000.png │ ├── out001.png │ ├── out002.png │ ├── out003.png │ ├── out004.png │ ├── out005.png │ ├── out006.png │ ├── out007.png │ ├── out008.png │ ├── out009.png │ ├── out010.png │ ├── out011.png │ ├── out012.png │ ├── out013.png │ ├── out014.png │ ├── out015.png │ ├── out016.png │ ├── out017.png │ ├── out018.png │ └── out019.png ├── README.md └── wave_transform.py ├── random ├── random_order.py ├── example_random.py ├── random_set.py └── README.rst ├── httpx ├── example_requests.py ├── search_with_parameters.py └── README.rst ├── pytesseract ├── ocr.py └── README.md ├── email ├── README.md ├── smtp_example.py └── send_email.py ├── xml ├── hamlet.xml ├── parse_xml.py ├── write_xml.py └── README.rst ├── turtle ├── fibo_spiral.py ├── snowflake.py ├── koch.py ├── dragon.py └── many_snowflakes.py ├── fuzzywuzzy ├── README.md └── fuzzy_search.py ├── pypdf2 ├── merge.py ├── README.md └── extras │ ├── pdf.py │ └── pdf2txt.py ├── vader ├── vader.py └── README.rst ├── playwright ├── playwright_example.py └── README.md ├── psycopg2 ├── docker-compose.yml └── crud.py ├── itertools ├── example_itertools.py └── README.rst ├── networkx ├── README.md ├── city_pairs.csv └── page_rank.py ├── beautiful_soup ├── README.md └── example_bs4.py ├── folium ├── README.md └── berlin_map.py ├── sqlalchemy ├── README.md └── example_sqlalchemy.py ├── flask ├── README.md ├── run_flask_server.py └── templates │ └── main.html ├── sqlite3 ├── README.md └── example_sqlite.py ├── sklearn ├── example_sklearn.py └── README.md ├── paramiko └── ssh_task.py ├── pymongo ├── pymongo_connect.py └── README.rst ├── curses ├── README.rst └── pac.py ├── zipfile └── README.rst ├── math └── README.rst ├── LICENSE.TXT ├── json └── README.rst ├── sys └── README.rst ├── .gitignore ├── time └── README.rst ├── ipyvolume └── volume.ipynb ├── index.rst ├── ipywidgets └── ipywidgets.ipynb └── README.md /os/example_pipeline.py: -------------------------------------------------------------------------------- 1 | 2 | -------------------------------------------------------------------------------- /cover.jpg: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/krother/Python3_Package_Examples/HEAD/cover.jpg -------------------------------------------------------------------------------- /cover.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/krother/Python3_Package_Examples/HEAD/cover.png -------------------------------------------------------------------------------- /re/regex.pdf: -------------------------------------------------------------------------------- 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| data = ['A','B','C','D'] 4 | 5 | shuffle(data) 6 | print(data) 7 | -------------------------------------------------------------------------------- /pillow/dice_images/double_dice.png: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/krother/Python3_Package_Examples/HEAD/pillow/dice_images/double_dice.png -------------------------------------------------------------------------------- /pillow/flower_movie/flower_movie.avi: -------------------------------------------------------------------------------- https://raw.githubusercontent.com/krother/Python3_Package_Examples/HEAD/pillow/flower_movie/flower_movie.avi -------------------------------------------------------------------------------- /httpx/example_requests.py: -------------------------------------------------------------------------------- 1 | 2 | import httpx 3 | 4 | r = httpx.get('https://www.python.org') 5 | print(r.status_code) 6 | print(r.text[:1000]) 7 | -------------------------------------------------------------------------------- /pytesseract/ocr.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image 3 | import pytesseract 4 | 5 | im = Image.open('myimage.jpg') 6 | print(pytesseract.image_to_string(im)) 7 | -------------------------------------------------------------------------------- /email/README.md: -------------------------------------------------------------------------------- 1 | 2 | # email 3 | 4 | ### What is it good for? 5 | 6 | Sends emails. You still need to have a mail server (SMTP). 7 | 8 | ### Installed by default? 9 | 10 | yes -------------------------------------------------------------------------------- /random/example_random.py: -------------------------------------------------------------------------------- 1 | import random 2 | 3 | print(random.randint(1, 6)) # integer 4 | print(random.random()) # float 5 | print(random.gauss(0.0, 1.0)) # standard normal dist 6 | -------------------------------------------------------------------------------- /xml/hamlet.xml: -------------------------------------------------------------------------------- 1 | 2 | 3 | the Prince of Denmark 4 | Ophelias father 5 | 6 | -------------------------------------------------------------------------------- /pydocx/read_word_doc.py: -------------------------------------------------------------------------------- 1 | 2 | from docx import Document 3 | 4 | document = Document('hamlet.docx') 5 | 6 | print(document) 7 | 8 | for para in document.paragraphs: 9 | print(para.text) 10 | -------------------------------------------------------------------------------- /turtle/fibo_spiral.py: -------------------------------------------------------------------------------- 1 | 2 | import turtle 3 | 4 | a = 1 5 | b = 1 6 | 7 | depth = 0 8 | maxdepth = 15 9 | 10 | while depth < maxdepth: 11 | turtle.circle(a, 90) 12 | a, b = b, a + b 13 | depth += 1 14 | 15 | input() 16 | -------------------------------------------------------------------------------- /scikit_image/README.md: -------------------------------------------------------------------------------- 1 | 2 | # Scikit-Image 3 | 4 | ### What it is good for? 5 | 6 | Advanced image filters and transformations 7 | 8 | ### Installed with Python or Anaconda 9 | 10 | no 11 | 12 | ## Example 13 | 14 | ![](../images/wave.gif) 15 | -------------------------------------------------------------------------------- /fuzzywuzzy/README.md: -------------------------------------------------------------------------------- 1 | 2 | # Fuzzywuzzy 3 | 4 | ### What it is good for? 5 | 6 | Match strings with typos. 7 | 8 | ### Installed with Python or Anaconda 9 | 10 | no 11 | 12 | ### How to install it? 13 | 14 | :::text 15 | pip install fuzzywuzzy 16 | -------------------------------------------------------------------------------- /pydocx/create_doc.py: -------------------------------------------------------------------------------- 1 | 2 | # Create a Word document: 3 | 4 | from docx import Document 5 | 6 | d = Document() 7 | 8 | d.add_heading('Hamlet') 9 | d.add_heading('dramatis personae', 2) 10 | d.add_paragraph('Hamlet, the Prince of Denmark') 11 | 12 | d.save('hamlet.docx') 13 | -------------------------------------------------------------------------------- /pypdf2/merge.py: -------------------------------------------------------------------------------- 1 | 2 | from PyPDF2 import PdfFileMerger 3 | 4 | merger = PdfFileMerger() 5 | 6 | merger.append(open("doc1.pdf", "rb")) 7 | merger.append(open("doc2.pdf", "rb")) 8 | 9 | # Write to an output PDF document 10 | output = open("result.pdf", "wb") 11 | merger.write(output) 12 | -------------------------------------------------------------------------------- /httpx/search_with_parameters.py: -------------------------------------------------------------------------------- 1 | 2 | import httpx 3 | 4 | # Search scientific articles on PubMed: 5 | url = "https://eutils.ncbi.nlm.nih.gov/entrez/eutils/esearch.fcgi" 6 | param_dict = {'db':'pubmed', 'term':'escherichia', 'rettype':'uilist'} 7 | 8 | r = httpx.get(url, params=param_dict) 9 | print(r.text) 10 | -------------------------------------------------------------------------------- /random/random_set.py: -------------------------------------------------------------------------------- 1 | 2 | import random 3 | 4 | # random set with repeats 5 | ALPHABET = list('AGCT') 6 | dna = [random.choice(ALPHABET) for i in range(50)] 7 | print(''.join(dna)) 8 | 9 | 10 | # random set without repeats 11 | NUMBERS = range(1, 101) 12 | print(random.sample(NUMBERS, 10)) 13 | -------------------------------------------------------------------------------- /pillow/carrots/step01-paste.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image 3 | 4 | img = Image.new('RGBA', (800, 500), "white") 5 | 6 | carrot = Image.open('carrot.png') 7 | brain = Image.open('brain.png') 8 | 9 | img.paste(carrot, (100, 80)) 10 | img.paste(brain, (500, 100)) 11 | 12 | img.save('step01.png') 13 | 14 | -------------------------------------------------------------------------------- /re/kingkong.py: -------------------------------------------------------------------------------- 1 | """ 2 | Advanced example: 3 | Why is humpty-dumpty not matched? 4 | """ 5 | 6 | import re 7 | 8 | text = """ 9 | ping-pong 10 | king-kong 11 | flip-flop 12 | hip-hop 13 | humpty-dumpty 14 | """ 15 | 16 | for line in text.split(): 17 | if re.search(r"^(\w+)i(\w+)[- ]\1o\2", line): 18 | print(line) 19 | -------------------------------------------------------------------------------- /pytesseract/README.md: -------------------------------------------------------------------------------- 1 | 2 | # Pytesseract 3 | 4 | ### What it is good for? 5 | 6 | Extract text from images (Optical Character Recognition / OCR). 7 | 8 | ### Installed with Python or Anaconda 9 | 10 | no 11 | 12 | ### How to install it? 13 | 14 | :::text 15 | sudo apt install tesseract-ocr 16 | pip install pytesseract 17 | -------------------------------------------------------------------------------- /vader/vader.py: -------------------------------------------------------------------------------- 1 | from vaderSentiment.vaderSentiment import SentimentIntensityAnalyzer 2 | 3 | s = SentimentIntensityAnalyzer() 4 | 5 | text_a = "\ntoday is a great day to code!" 6 | text_b = "\nsyntax errors really suck" 7 | 8 | print(text_a) 9 | print(s.polarity_scores(text_a)) 10 | 11 | print(text_b) 12 | print(s.polarity_scores(text_b)) 13 | -------------------------------------------------------------------------------- /fuzzywuzzy/fuzzy_search.py: -------------------------------------------------------------------------------- 1 | 2 | from fuzzywuzzy import process 3 | 4 | movie_titles = ['Titanic', 'Star Wars', 'Breakfast at Tiffanys'] 5 | 6 | # find the most similar match and a quality score 7 | print(process.extractOne('Star Wors', movie_titles)) 8 | print(process.extractOne('Star', movie_titles)) 9 | print(process.extractOne('Tutunuc', movie_titles)) 10 | -------------------------------------------------------------------------------- /tqdm/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to create a progress bar on the console? 3 | ============================================ 4 | 5 | The `tqdm` library has just one purpose: Drawing progress bars. 6 | 7 | Install it with: 8 | 9 | .. code:: 10 | 11 | pip install tqdm 12 | 13 | Here is an example code piece: 14 | 15 | .. literalinclude:: progress_bar.py 16 | -------------------------------------------------------------------------------- /pillow/carrots/step02-resize.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image 3 | 4 | img = Image.new('RGBA', (800, 500), "white") 5 | 6 | carrot = Image.open('carrot.png') 7 | brain = Image.open('brain.png') 8 | 9 | carrot = carrot.resize((250, 250)) 10 | 11 | img.paste(carrot, (100, 80)) 12 | img.paste(brain, (500, 100)) 13 | 14 | img.save('step02.png') 15 | 16 | -------------------------------------------------------------------------------- /playwright/playwright_example.py: -------------------------------------------------------------------------------- 1 | 2 | from playwright.sync_api import sync_playwright 3 | 4 | 5 | with sync_playwright() as p: 6 | browser = p.firefox.launch(headless=False) 7 | page = browser.new_page() 8 | page.goto("http://www.academis.eu") 9 | page.is_visible('#headline') 10 | html = page.inner_html('#headline') 11 | print(html[:190]) 12 | -------------------------------------------------------------------------------- /xml/parse_xml.py: -------------------------------------------------------------------------------- 1 | 2 | from xml.dom.minidom import parse 3 | 4 | document = parse('hamlet.xml') 5 | 6 | actors = document.getElementsByTagName("actor") 7 | for act in actors: 8 | name = act.getAttribute('name') 9 | for node in act.childNodes: 10 | if node.nodeType == node.TEXT_NODE: 11 | print("{} - {}".format(name, node.data)) 12 | -------------------------------------------------------------------------------- /wordcloud/README.md: -------------------------------------------------------------------------------- 1 | 2 | # wordcloud 3 | 4 | ### What it does 5 | 6 | `wordcloud` draws word clouds from a string of words. 7 | 8 | It allows to create clouds in arbitrary shapes. 9 | 10 | ![word cloud](cloud.png) 11 | 12 | ### Installed with Python or Anaconda 13 | 14 | no 15 | 16 | ### How to install it 17 | 18 | :::text 19 | pip install wordcloud 20 | 21 | -------------------------------------------------------------------------------- /pillow/half_size.py: -------------------------------------------------------------------------------- 1 | 2 | # Convert all `.png` images in the directory to half their size 3 | from PIL import Image 4 | import os 5 | 6 | for filename in os.listdir('.'): 7 | if filename.endswith('.png'): 8 | im = Image.open(filename) 9 | x = im.size[0] // 2 10 | y = im.size[1] // 2 11 | small = im.resize((x, y)) 12 | small.save('sm_' + filename) 13 | -------------------------------------------------------------------------------- /matplotlib/lineplot.py: -------------------------------------------------------------------------------- 1 | 2 | from matplotlib import pyplot as plt 3 | import math 4 | 5 | plt.figure() 6 | 7 | x = [0.01 * i for i in range(1000)] 8 | y = [math.sin(j) for j in x] 9 | 10 | plt.plot(x, y, 'k-', linewidth=1) 11 | plt.text(5, 0, "$y = sin(x)$", horizontalalignment='center', fontsize=20) 12 | plt.axis([0, 3*math.pi, -1.2, 1.2]) 13 | 14 | plt.savefig('sinfunc.png') 15 | -------------------------------------------------------------------------------- /psycopg2/docker-compose.yml: -------------------------------------------------------------------------------- 1 | version: '3.8' 2 | 3 | services: 4 | db: 5 | image: postgres:latest 6 | container_name: postgres 7 | environment: 8 | POSTGRES_USER: myuser 9 | POSTGRES_PASSWORD: mypassword 10 | POSTGRES_DB: mydatabase 11 | ports: 12 | - "8000:5432" 13 | volumes: 14 | - pgdata:/home/kristian/pgdata 15 | 16 | volumes: 17 | pgdata: 18 | -------------------------------------------------------------------------------- /re/exercises/regex_sub.py: -------------------------------------------------------------------------------- 1 | import re 2 | 3 | text = "7 apples, 24 bananas, 14 carrots, and oranges are fruit" 4 | 5 | # replace one word by another 6 | result = re.sub('','',text) 7 | assert result == "7 apples, 24 bananas, 14 pears, and oranges are fruit" 8 | 9 | # remove all numbers 10 | result = re.sub('','',text) 11 | assert result == "apples, bananas, carrots, and oranges are fruit" 12 | -------------------------------------------------------------------------------- /pillow/dice.py: -------------------------------------------------------------------------------- 1 | # generate dice image 2 | 3 | from PIL import Image 4 | from PIL import ImageDraw 5 | 6 | five = Image.new('RGB', (64,64), '#80b940') 7 | d = ImageDraw.Draw(five) 8 | 9 | d.ellipse(((26, 26), (38, 38)), '#ffffff') 10 | d.ellipse(((10, 10), (22, 22)), '#ffffff') 11 | d.ellipse(((42, 42), (54, 54)), '#ffffff') 12 | d.ellipse(((10, 42), (22, 54)), '#ffffff') 13 | d.ellipse(((42, 10), (54, 22)), '#ffffff') 14 | five.save('five.png') 15 | -------------------------------------------------------------------------------- /turtle/snowflake.py: -------------------------------------------------------------------------------- 1 | 2 | from turtle import forward, left, right, width, color, clearscreen 3 | 4 | clearscreen() 5 | color("lightblue") 6 | width(3) 7 | 8 | for i in range(6): 9 | forward(50) 10 | left(60) 11 | forward(25) 12 | left(180) 13 | forward(25) 14 | left(60) 15 | forward(25) 16 | left(180) 17 | forward(25) 18 | right(120) 19 | forward(25) 20 | left(180) 21 | forward(75) 22 | left(120) 23 | -------------------------------------------------------------------------------- /re/phone.py: -------------------------------------------------------------------------------- 1 | 2 | import re 3 | 4 | phone = re.compile("(00|0 0|\+)\s*4\s*9[0-9 ]+") 5 | 6 | examples = [ 7 | "0049 190 34 57 90", 8 | "+49 190 34 57 90", 9 | "00 00 00 49 190 34 57 90 33", 10 | "00 49 190 34 57 90", 11 | "0049190345790", 12 | "+48 60 60 606 9", 13 | "+41 55 55 55 55" 14 | ] 15 | 16 | for e in examples: 17 | if phone.match(e): 18 | print(e, "is a German phone number") 19 | else: 20 | print(e, "is some other number") 21 | -------------------------------------------------------------------------------- /re/fox.py: -------------------------------------------------------------------------------- 1 | 2 | import re 3 | 4 | text = "the quick brown fox jumps over the lazy dog" 5 | 6 | # Search for `o` and show adjacent characters: 7 | print(re.findall(".o.", text)) 8 | 9 | # Search for three-letter words enclosed by whitespace: 10 | print(re.findall("\s(\wo\w)\s*", text)) 11 | 12 | # Substitute any of `dflj` by a `w`: 13 | print(re.sub("[dflj]", "w", text)) 14 | 15 | # Check if `jumps` or `swims` occurs and return details: 16 | print(re.search('jumps|swims', text)) 17 | -------------------------------------------------------------------------------- /pypdf2/README.md: -------------------------------------------------------------------------------- 1 | 2 | # PyPDF2 3 | 4 | ### What is it good for? 5 | 6 | `PyPDF2` manipulates PDF documents on the page level, e.g. merging two or more PDFs. 7 | 8 | 9 | ### Installed with Python or Anaconda 10 | 11 | no 12 | 13 | ### How to install it? 14 | 15 | :::text 16 | pip install pypdf2 17 | 18 | ### Where to learn more? 19 | 20 | There are a few other PDF libraries that allow to read PDFs or create them from scratch. 21 | See :::file extras/pdf.py or :::file extras/pdf2txt.py 22 | 23 | -------------------------------------------------------------------------------- /itertools/example_itertools.py: -------------------------------------------------------------------------------- 1 | 2 | import itertools 3 | 4 | # concatenate lists 5 | ch = itertools.chain([1, 2], [3, 4], [5, 6]) 6 | print(list(ch)) 7 | 8 | # repeat lists 9 | print(list(itertools.repeat([1, 2], 3))) 10 | 11 | # Permutations and combinations of list elements: 12 | p = itertools.permutations([1, 2, 3]) 13 | print(list(p)) 14 | 15 | c = itertools.combinations([1, 2, 3], 2) 16 | print(list(c)) 17 | 18 | # Pairwise combinations 19 | pr = itertools.product("ABC", [1, 2, 3]) 20 | print(list(pr)) 21 | -------------------------------------------------------------------------------- /matplotlib/errorbars.py: -------------------------------------------------------------------------------- 1 | 2 | from matplotlib import pyplot as plt 3 | 4 | plt.figure() 5 | 6 | # scatterplot with error bars 7 | x1 = [0.1, 0.3, 0.5, 0.6, 0.7] 8 | y1 = [1, 5, 5, 10, 20] 9 | err1 = [3, 3, 3, 10, 12] 10 | plt.errorbar(x1, y1, err1 , fmt='ro') 11 | 12 | # barplot with error bars 13 | x2 = [1.1, 1.2, 1.3, 1.4, 1.5] 14 | y2 = [10, 15, 10, 15, 17] 15 | err2 = (2, 3, 4, 1, 2) 16 | width = 0.05 17 | plt.bar(x2, y2, width, color='r', yerr=err2, ecolor="black") 18 | 19 | plt.savefig('errorbars.png') 20 | -------------------------------------------------------------------------------- /networkx/README.md: -------------------------------------------------------------------------------- 1 | 2 | # NetworkX 3 | 4 | ### What it does 5 | 6 | `NetworkX` processes and plots graphs. 7 | 8 | ### Installed with Python or Anaconda 9 | 10 | no 11 | 12 | ### How to install it 13 | 14 | :::text 15 | pip install networkx 16 | 17 | ### Example: PageRank 18 | 19 | The example below uses the [PageRank algorithm](https://en.wikipedia.org/wiki/PageRank) to calculate the importance (centrality) of nodes in the graph. 20 | 21 | The code uses the file :::file city_pairs.csv . 22 | 23 | -------------------------------------------------------------------------------- /xml/write_xml.py: -------------------------------------------------------------------------------- 1 | 2 | import xml.etree.ElementTree as ET 3 | 4 | data = ET.Element('play') 5 | 6 | # add subtags with attributes 7 | actors = ET.SubElement(data, 'actors') 8 | 9 | ham = ET.SubElement(actors, 'actor') 10 | ham.set('name', 'Hamlet') 11 | ham.text = "Hamlet, the Prince of Denmark" 12 | 13 | oph = ET.SubElement(actors, 'actress') 14 | oph.set('name', 'Ophelia') 15 | oph.text = "Ophelia" 16 | 17 | # write as a binary string 18 | with open("actors.xml", "wb") as f: 19 | f.write(ET.tostring(data)) 20 | -------------------------------------------------------------------------------- /beautiful_soup/README.md: -------------------------------------------------------------------------------- 1 | 2 | # BeautifulSoup 3 | 4 | ### What it is good for? 5 | 6 | BeautifulSoup parses HTML pages. 7 | 8 | Beautiful soup is much, much easier to use than the default HTML parser installed with Python. 9 | 10 | ### Installed with Python or Anaconda 11 | 12 | no 13 | 14 | ### How to install it? 15 | 16 | :::text 17 | pip install bs4 18 | 19 | ### Where to learn more? 20 | 21 | [http://www.crummy.com/software/BeautifulSoup/bs4/doc/](http://www.crummy.com/software/BeautifulSoup/bs4/doc/) 22 | -------------------------------------------------------------------------------- /folium/README.md: -------------------------------------------------------------------------------- 1 | 2 | # folium 3 | 4 | ### What it does 5 | 6 | `folium` plots maps. 7 | 8 | The package is built on top of the JavaScript library **leaflet** (hence the name). 9 | It produces HTML documents: 10 | 11 | ### Installed with Python or Anaconda 12 | 13 | no 14 | 15 | ### How to install it 16 | 17 | :::text 18 | pip install folium 19 | 20 | ### See also 21 | 22 | [https://python-visualization.github.io/folium/quickstart.html](https://python-visualization.github.io/folium/quickstart.html) 23 | 24 | -------------------------------------------------------------------------------- /pydocx/README.md: -------------------------------------------------------------------------------- 1 | 2 | # python-docx 3 | 4 | ### What it is good for? 5 | 6 | `python-docx` reads and writes MS Word documents. 7 | 8 | A straightforward library to access documents in MS Word format. Available features include text, labeled sections, pictures and tables. 9 | 10 | ### Installed with Python or Anaconda 11 | 12 | no 13 | 14 | ### How to install it? 15 | 16 | :::text 17 | pip install python-docx 18 | 19 | ### Where to learn more? 20 | 21 | [https://python-docx.readthedocs.org](https://python-docx.readthedocs.org) 22 | -------------------------------------------------------------------------------- /re/exercises/regex_exercises.md: -------------------------------------------------------------------------------- 1 | ## Regex and Text Processing exercises 2 | 3 | Wörter: Wie oft kommt Löw im Text vor? 4 | 5 | Wörter in Tabelle schreiben 6 | 7 | Lukas Podolski einlesen 8 | 9 | Regex Crossword lösen 10 | 11 | Warum manchmal nur ein Land? 12 | 13 | Spielergebnisse parsen 14 | 15 | Count number of words in a text. 16 | 17 | Count most frequent character in a text. 18 | 19 | Count which pairs of subsequent words occurs most often. 20 | 21 | Calculate the entropy of some data. 22 | 23 | Filter certain words out of a text. 24 | -------------------------------------------------------------------------------- /sqlalchemy/README.md: -------------------------------------------------------------------------------- 1 | 2 | # SQLAlchemy 3 | 4 | ### What it is good for? 5 | 6 | Create and use a *SQL* databases. 7 | 8 | SQLAlchemy is a generic interface to all databases. 9 | You can use it so connect to MySQL, PostGreSQL, Oracle(?), SQLite and many others with the same or very similar code. 10 | 11 | It contains a powerful ORM (Object-Relational Mapper) where you define your tables as classes. 12 | 13 | ### Installed with Python? 14 | 15 | no 16 | 17 | ### Where to learn more? 18 | 19 | [http://sqlalchemy.org/](http://sqlalchemy.org/) 20 | -------------------------------------------------------------------------------- /itertools/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to flatten a list of lists? 3 | =============================== 4 | 5 | The builtin module `itertools` contains plenty of functions to work with lists and iterators. 6 | Most functions in this module return *iterators* themselves, so they can be consumed by loops or `next()`. You can also convert them to a list. 7 | 8 | Below you find a few examples: 9 | 10 | .. literalinclude:: example_itertools.py 11 | 12 | .. seealso:: 13 | 14 | `Documentation of the itertools module `__ 15 | -------------------------------------------------------------------------------- /matplotlib/balls.py: -------------------------------------------------------------------------------- 1 | 2 | import math 3 | import random 4 | from matplotlib import pyplot as plt 5 | 6 | # prepare random data 7 | n_balls = 50 8 | x = [random.triangular() for i in range(n_balls)] 9 | y = [random.gauss(0.5, 0.15) for i in range(n_balls)] 10 | colors = [random.randint(1, 4) for i in range(n_balls)] 11 | areas = [math.pi * random.randint(5, 15)**2 for i in range(n_balls)] 12 | 13 | # draw the figure 14 | plt.figure() 15 | plt.scatter(x, y, s=areas, c=colors, alpha=0.75) 16 | plt.axis([0.0, 1.0, 0.0, 1.0]) 17 | plt.savefig('balls.png') 18 | -------------------------------------------------------------------------------- /flask/README.md: -------------------------------------------------------------------------------- 1 | 2 | # flask 3 | 4 | ### What is it good for? 5 | 6 | `flask` is a lightweight web server. 7 | 8 | You can create APIs and simple web pages with very little code. 9 | 10 | 11 | ### Installed with Python or Anaconda 12 | 13 | no 14 | 15 | ### How to install it? 16 | 17 | :::text 18 | pip install flask 19 | 20 | ### Where to learn more? 21 | 22 | * [flask.palletsprojects.com](https://flask.palletsprojects.com) 23 | * [The Flask Mega Tutorial](https://blog.miguelgrinberg.com/post/the-flask-mega-tutorial-part-i-hello-world) by Miguel Grinberg 24 | -------------------------------------------------------------------------------- /flask/run_flask_server.py: -------------------------------------------------------------------------------- 1 | 2 | from flask import Flask, render_template 3 | 4 | app = Flask(__name__) 5 | 6 | @app.route("/hello") 7 | def hello(): 8 | return """

Hello World!

""" 9 | 10 | @app.route("/hello/") 11 | def hello_name(name): 12 | return f"""

Hello {name}!

""" 13 | 14 | @app.route("/") 15 | def main(): 16 | return render_template('main.html', 17 | title='Start page', 18 | animals=['cat', 'dog', 'fish', 'platypus'] 19 | ) 20 | 21 | 22 | if __name__ == "__main__": 23 | app.run() 24 | -------------------------------------------------------------------------------- /tkinter/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to create a graphical desktop window? 3 | ========================================= 4 | 5 | Tkinter allows you to create graphical interfaces. 6 | It's a bit oldschool and the class structure appears convoluted in 2025, but some might want to try it anyway. 7 | 8 | `Tk` is installed with Python by default. 9 | 10 | Here is an example program with two images: 11 | 12 | - :download:`titanic.py` 13 | - :download:`titanic.png` 14 | - :download:`titanic2.png` 15 | 16 | .. seealso:: 17 | 18 | `Tkinter documentation `__ 19 | -------------------------------------------------------------------------------- /vader/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to calculate a simple sentiment score for a text? 3 | ===================================================== 4 | 5 | The `vader` libary provides a straightforward sentiment score. 6 | It is based on a word list, so it is not super accurate and does not catch any nuances. 7 | But it is fast and sufficient for a quick scan. 8 | 9 | Installation 10 | ------------ 11 | 12 | :: 13 | 14 | pip install vaderSentiment 15 | 16 | Usage 17 | ----- 18 | 19 | .. literalinclude:: vader.py 20 | 21 | The sentiment includes a positive, negative and neutral score, which add up to 1.0. 22 | -------------------------------------------------------------------------------- /PuLP/README.md: -------------------------------------------------------------------------------- 1 | 2 | # PuLP 3 | 4 | ### What it is good for? 5 | 6 | PuLP is a simple **Linear Problem Solver**. It solves systems with many linear equations, e.g. Sudokus, scheduling trains and many more. For complex LES problems you will need commercial software (like Gurobi), but PuLP helps you get the taste of it. 7 | 8 | ### Installed with Python or Anaconda 9 | 10 | no 11 | 12 | ### How to install it? 13 | 14 | :::text 15 | pip install pulp 16 | 17 | ## Example 18 | 19 | Solve a magic square (insert the numbers 1..9 in to a 3x3 square 20 | so that all rows and columns sum up to 15). 21 | -------------------------------------------------------------------------------- /flask/templates/main.html: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 5 | 6 | 7 | 8 | 9 | 10 | {{title}} 11 | 12 | 13 | 14 | 15 |

{{ title }}

16 | Hello World page 17 |
    18 | {% for ani in animals %} 19 |
  • {{ ani }}
    • 20 | {% endfor %} 21 |
22 | 23 | 24 | 25 | -------------------------------------------------------------------------------- /beautiful_soup/example_bs4.py: -------------------------------------------------------------------------------- 1 | from bs4 import BeautifulSoup 2 | 3 | html = """ 4 |

Hamlet

5 |
    6 |
  • Hamlet
    • 7 |
  • Polonius
    • 8 |
  • Ophelia
    • 9 |
  • Claudius
    • 10 |
11 |
    12 |
  • William Shakespeare
    • 13 |
14 | """ 15 | 16 | soup = BeautifulSoup(html, "lxml") 17 | 18 | for ul in soup.find_all('ul'): 19 | if "cast" in ul.get('class', []): 20 | for item in ul.find_all('li'): 21 | print(item.get_text(), end=", ") 22 | print() 23 | -------------------------------------------------------------------------------- /random/README.rst: -------------------------------------------------------------------------------- 1 | 2 | 3 | How to generate random numbers? 4 | ------------------------------- 5 | 6 | .. literalinclude:: example_random.py 7 | 8 | How to put a list in random order? 9 | ---------------------------------- 10 | 11 | .. literalinclude:: random_order.py 12 | 13 | How to pick a random sample? 14 | ---------------------------- 15 | 16 | .. literalinclude:: random_set.py 17 | 18 | .. seealso:: 19 | 20 | The `random` module generates random numbers from common distributions. 21 | It does not require installation. 22 | 23 | `Documentation for the random module `__ 22 | -------------------------------------------------------------------------------- /numpy/mandelbrot.py: -------------------------------------------------------------------------------- 1 | """ 2 | Drawing the Mandelbrot set 3 | based on R code by Myles Harrison 4 | http://www.everydayanalytics.ca 5 | """ 6 | import numpy as np 7 | from PIL import Image 8 | 9 | 10 | SIZE = 500 11 | 12 | x = np.linspace(-2.0, 1.0, SIZE) 13 | y = np.linspace(-1.5, 1.5, SIZE) 14 | 15 | ones = np.ones(SIZE) 16 | 17 | c = np.outer(x, ones) + 1j * np.outer(ones, y) 18 | 19 | z = np.zeros((SIZE, SIZE)) * 1j 20 | k = np.zeros((SIZE, SIZE)) 21 | 22 | for i in range(100): 23 | index = z < 2 24 | z[index] = z[index] ** 2 + c[index] 25 | k[index] = k[index] + 1 26 | 27 | 28 | # save the image 29 | im = Image.fromarray(k).convert('RGB') 30 | im.save('mandelbrot.png') 31 | -------------------------------------------------------------------------------- /folium/berlin_map.py: -------------------------------------------------------------------------------- 1 | import folium 2 | 3 | 4 | berlin_map = folium.Map(location=[52.50, 13.35], zoom_start=13) 5 | 6 | folium.Marker( 7 | (52.5157669, 13.3771557), 8 | popup="Brandenburger Tor", 9 | icon=folium.Icon(icon="map-marker", color="blue"), 10 | ).add_to(berlin_map) 11 | 12 | folium.Marker( 13 | (52.5141987, 13.350284), 14 | popup="Siegessäule", 15 | icon=folium.Icon(icon="star", color="orange"), 16 | ).add_to(berlin_map) 17 | 18 | folium.Marker( 19 | (52.4681216, 13.332078), popup="Home", icon=folium.Icon(icon="home", color="green") 20 | ).add_to(berlin_map) 21 | 22 | berlin_map.save("berlin_map.html") 23 | 24 | berlin_map # in Jupyter to see the result 25 | -------------------------------------------------------------------------------- /re/biological_seq/finditer.py: -------------------------------------------------------------------------------- 1 | ''' 2 | 3 | Pattern Matching - Example 4 | 5 | The script checks if the SRC_HUMAN sequence has 6 | the following phosphorylation site: 'R(.)[ST][^P]' and prints 7 | the match, the start and end of the match and the 8 | amino acid in the second position of the match. 9 | 10 | ''' 11 | 12 | import re 13 | 14 | F = open('SRC_HUMAN.fasta') 15 | seq = '' 16 | for line in F: 17 | if line[0] != '>': 18 | seq = seq + line.strip() 19 | 20 | S = 'R(.)[ST][^P]' 21 | regexp = re.compile(S) 22 | iter = regexp.finditer(seq) 23 | for s in iter: 24 | print("match:", s.group(0)) 25 | print("start, end", s.span()) 26 | print("aa in second position:", s.group(1)) 27 | -------------------------------------------------------------------------------- /re/biological_seq/SRC_HUMAN.fasta: -------------------------------------------------------------------------------- 1 | >sp|P12931|SRC_HUMAN Proto-oncogene tyrosine-protein kinase Src OS=Homo sapiens GN=SRC PE=1 SV=3 2 | MGSNKSKPKDASQRRRSLEPAENVHGAGGGAFPASQTPSKPASADGHRGPSAAFAPAAAE 3 | PKLFGGFNSSDTVTSPQRAGPLAGGVTTFVALYDYESRTETDLSFKKGERLQIVNNTEGD 4 | WWLAHSLSTGQTGYIPSNYVAPSDSIQAEEWYFGKITRRESERLLLNAENPRGTFLVRES 5 | ETTKGAYCLSVSDFDNAKGLNVKHYKVALITGGGSGITSRTQFNSLQQLVAYYSKHADGL 6 | CHRLTTVCPTSKPQTQGLAKDAWEIPRESLRLEVKLGQGCFGEVWMGTWNGTTRVAIKTL 7 | KPGTMSPEAFLQEAQVMKKLRHEKLVQLYAVVSEEPIYIVTEYMSKGSLLDFLKGETGKY 8 | LRLPQLVDMAAQIASGMAYVERMNYVHRDLRAANILVGENLVCKVADFGLARLIEDNEYT 9 | ARQGAKFPIKWTAPEAALYGRFTIKSDVWSFGILLTELTTKGRVPYPGMVNREVLDQVER 10 | GYRMPCPPECPESLHDLMCQCWRKEPEERPTFEYLQAFLEDYFTSTEPQYQPGENL 11 | -------------------------------------------------------------------------------- /matplotlib/barplot.py: -------------------------------------------------------------------------------- 1 | 2 | from matplotlib import pyplot as plt 3 | 4 | nucleotides = ["A", "G", "C", "U"] 5 | 6 | counts = [ 7 | [606, 1024, 759, 398], 8 | [762, 912, 639, 591], 9 | ] 10 | 11 | plt.figure() 12 | 13 | x1 = [2.0, 4.0, 6.0, 8.0] 14 | x2 = [x - 0.5 for x in x1] 15 | 16 | plt.xticks(x1, nucleotides) 17 | 18 | plt.bar(x1, counts[1], width=0.5, color="#cccccc", label="E.coli 23S") 19 | plt.bar(x2, counts[0], width=0.5, color="#808080", label="T.thermophilus 23S") 20 | 21 | plt.legend() 22 | plt.axis([1.0, 9.0, 0, 1200]) 23 | 24 | plt.title('RNA nucleotides in the ribosome') 25 | plt.xlabel('RNA') 26 | plt.ylabel('base count') 27 | plt.savefig('barplot.png') 28 | -------------------------------------------------------------------------------- /numpy/transform_logo.py: -------------------------------------------------------------------------------- 1 | # 2 | # more examples that transform the Python logo 3 | # 4 | 5 | import numpy as np 6 | from PIL import Image 7 | 8 | 9 | def imsave(filename, a): 10 | Image.fromarray(a).convert('RGB').save(filename) 11 | 12 | im = Image.open('python_logo.png') 13 | a = np.array(im) 14 | 15 | 16 | # reduce brightness 17 | d = a // 2 18 | imsave('dim.png', d) 19 | 20 | # flip over 21 | b = a[:,::-1,:] 22 | imsave('flip.png', b) 23 | 24 | # remove color channel 25 | g = np.array(a) 26 | g[:,:,1] = 0 27 | imsave('purple.png', g) 28 | 29 | # rolling displacement 30 | roll = np.array(a) 31 | roll[:,:,2] = np.roll(roll[:,:,2], 25) 32 | roll[:,:,1] = np.roll(roll[:,:,1], 50) 33 | imsave('roll.png', roll) 34 | -------------------------------------------------------------------------------- /scipy/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to optimize parameters of a function with SciPy? 3 | ==================================================== 4 | 5 | .. figure:: fit.png 6 | 7 | Scipy is a Python library for **numerical analyses** like fitting functions, signal processing, Fourier Transform, generating random datasets and many more. Scipy uses `numpy` and `matplotlib`. 8 | 9 | Install it with: 10 | 11 | .. code:: 12 | 13 | pip install scipy 14 | 15 | The following code creates noisy data and fits a polynomial function to it: 16 | 17 | .. literalinclude:: curve_fit.py 18 | 19 | In :download:`peak_recognition.ipynb` you find a notebook for recognizing peaks. 20 | 21 | .. seealso:: 22 | 23 | `scipy.org/ `__ 24 | -------------------------------------------------------------------------------- /wordcloud/create_wordcloud.py: -------------------------------------------------------------------------------- 1 | 2 | import numpy as np 3 | from matplotlib import pyplot as plt 4 | import wordcloud 5 | import this 6 | 7 | # store the Zen of Python in a string 8 | text = ''.join([this.d.get(c, ' ') for c in this.s]).lower() 9 | 10 | # leave a blank square in the cloud 11 | mask = np.zeros((500, 500, 3), np.uint8) 12 | mask[150:350,150:350,:] = 255 13 | 14 | cloud = wordcloud.WordCloud(background_color="white", 15 | max_words=50, 16 | mask=mask, 17 | collocations=False, 18 | contour_color='steelblue').generate(text) 19 | 20 | plt.figure(num = None, figsize = (8, 8)) 21 | plt.imshow(cloud, interpolation='bilinear') 22 | plt.savefig('cloud.png') 23 | -------------------------------------------------------------------------------- /turtle/koch.py: -------------------------------------------------------------------------------- 1 | 2 | # by: Kristian Rother, Nils Goldmann 3 | 4 | from turtle import * 5 | import time 6 | 7 | def move_to(x,y): 8 | up() 9 | setx(x) 10 | sety(y) 11 | down() 12 | 13 | 14 | def curve(length, depth): 15 | if depth==0: 16 | forward(length) 17 | else: 18 | curve(length*0.333,depth-1) 19 | right(60) 20 | curve(length*0.333,depth-1) 21 | left(120) 22 | curve(length*0.333,depth-1) 23 | right(60) 24 | curve(length*0.333,depth-1) 25 | 26 | reset() 27 | left(180) 28 | 29 | move_to(100, 100) 30 | curve(200, 1) 31 | 32 | move_to(100, 0) 33 | curve(200, 2) 34 | 35 | move_to(100, -100) 36 | curve(200, 3) 37 | -------------------------------------------------------------------------------- /pillow/carrots/step06-text.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageChops, ImageFont 3 | 4 | img = Image.new('RGBA', (800, 500), "white") 5 | 6 | carrot = Image.open('carrot.png') 7 | brain = Image.open('brain.png') 8 | 9 | carrot = carrot.resize((250, 250)) 10 | 11 | arrow = Image.open('arrow.png') 12 | gradient = Image.open('gradient.png') 13 | 14 | arrow = ImageChops.screen(arrow, gradient) 15 | 16 | img.paste(carrot, (100, 80)) 17 | img.paste(arrow, (325, 150)) 18 | img.paste(brain, (500, 100)) 19 | 20 | draw = ImageDraw.Draw(img) 21 | arial = ImageFont.truetype('arial.ttf', 40) 22 | draw.text((220, 360), "Carrots rock your brain!", fill=(0,0,0), font=arial) 23 | 24 | img.save('step06.png') 25 | 26 | -------------------------------------------------------------------------------- /pandas/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to section a panda into hexagons with pandas? 3 | ================================================= 4 | 5 | .. figure:: hexpanda.png 6 | 7 | `pandas` is an extremely powerful library to analyze, combine and manipulate data in many ways. 8 | It provides a class for tables called *DataFrames* that are inspired from R. DataFrames have an index column and functions for plotting and reading from CSV or Excel files are included by default. Pandas uses `numpy` under the hood. 9 | 10 | Install it with: 11 | 12 | .. code:: 13 | 14 | pip install pandas 15 | 16 | The following code creates some eye candy: 17 | 18 | .. literalinclude:: hexpanda.py 19 | 20 | .. seealso:: 21 | 22 | - `pandas.pydata.org/ `__ 23 | -------------------------------------------------------------------------------- /turtle/dragon.py: -------------------------------------------------------------------------------- 1 | from turtle import * 2 | 3 | def vorbereiten(): 4 | reset() 5 | up() 6 | setx(-200) 7 | sety(50) 8 | down() 9 | 10 | 11 | def kurve(laenge,tiefe): 12 | if tiefe==1: 13 | forward(laenge) 14 | else: 15 | kurve(laenge*0.25,tiefe-1) 16 | left(90) 17 | kurve(laenge*0.25,tiefe-1) 18 | right(90) 19 | kurve(laenge*0.25,tiefe-1) 20 | right(90) 21 | kurve(laenge*0.5,tiefe-1) 22 | left(90) 23 | kurve(laenge*0.25,tiefe-1) 24 | left(90) 25 | kurve(laenge*0.25,tiefe-1) 26 | right(90) 27 | kurve(laenge*0.25,tiefe-1) 28 | 29 | speed('fastest') 30 | vorbereiten() 31 | kurve(400, 3) 32 | 33 | -------------------------------------------------------------------------------- /numpy/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to draw a fractal image with NumPy? 3 | ======================================= 4 | 5 | .. figure:: mandelbrot.png 6 | 7 | The Numpy library makes it easy to work with matrices in Python. 8 | 9 | Because it is implemented in C, `numpy` accelerates many calculations. It is also type-safe - all elements of a matrix have the same type. Many of the most powerful Python libraries like `pandas`, `scikit-learn` and `PILLOW` have been built on top of numpy. 10 | 11 | Install it with: 12 | 13 | .. code:: 14 | 15 | pip install numpy 16 | 17 | The following code draws the the Mandelbrot set: 18 | 19 | .. literalinclude:: mandelbrot.py 20 | 21 | 22 | .. seealso:: 23 | 24 | - `Numpy Graphics Tutorial `__ 25 | - `www.numpy.org/ `__ 26 | -------------------------------------------------------------------------------- /pymongo/pymongo_connect.py: -------------------------------------------------------------------------------- 1 | import pymongo 2 | 3 | client = pymongo.MongoClient("localhost", 27017) # not necessary on localhost 4 | db = client.test 5 | print(db.name) 6 | 7 | print(db.my_collection) 8 | db.my_collection.insert_one({"x": 10}) 9 | db.my_collection.insert_one({"x": 8}) 10 | db.my_collection.insert_one({"x": 11}) 11 | 12 | # get one entry 13 | print(db.my_collection.find_one()) 14 | 15 | # iterate over entries 16 | for item in db.my_collection.find(): 17 | print(item["x"]) 18 | 19 | # accelerate query with an index 20 | db.my_collection.create_index("x") 21 | 22 | # sort results 23 | for item in db.my_collection.find().sort("x", pymongo.ASCENDING): 24 | print(item["x"]) 25 | 26 | # chain multiple functions 27 | print([item["x"] for item in db.my_collection.find().limit(2).skip(1)]) 28 | -------------------------------------------------------------------------------- /pymongo/README.rst: -------------------------------------------------------------------------------- 1 | How to connect Python to MongoDB? 2 | ================================= 3 | 4 | The `pymongo` library connects to a Mongo database server. 5 | It is capable of interacting with both local and remote databases. 6 | To connect to a local instance, no extra parameters are necessary. 7 | 8 | Install it with: 9 | 10 | .. code:: 11 | 12 | pip install pymongo 13 | 14 | Launch MongoDB through docker 15 | ----------------------------- 16 | 17 | To try MongoDB, it is best to launch it in a local docker container: 18 | 19 | .. code:: 20 | 21 | docker run -d -p 27017:27017 mongo 22 | 23 | Run queries 24 | ----------- 25 | 26 | The following code connects and runs a few queries: 27 | 28 | .. literalinclude:: pymongo_connect.py 29 | 30 | .. seealso:: 31 | 32 | `Pymongo documentation `__ 33 | -------------------------------------------------------------------------------- /curses/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to create a 2D game in the terminal? 3 | ======================================== 4 | 5 | The `curses` library creates x/y output in a console window. 6 | It supports colors and Unicode tiles (depending on your terminal). 7 | `curses` is installed with Python by default. 8 | 9 | On Windows you may need to install `windows-curses`. 10 | 11 | Running the example: 12 | -------------------- 13 | 14 | In :download:`pac.py`, you find a minimalistic Pac game. 15 | Run it from a terminal. 16 | 17 | 18 | .. warning:: 19 | 20 | If you get the error message: 21 | 22 | ``curses function returned NULL`` 23 | 24 | It likely means that your window is too small. 25 | 26 | .. seealso:: 27 | 28 | My first contact with curses was inspired by `manti_go `__ written by my course participants. 29 | -------------------------------------------------------------------------------- /networkx/page_rank.py: -------------------------------------------------------------------------------- 1 | # draw a graph between cities and color by PageRank 2 | 3 | import pandas as pd 4 | import networkx as nx 5 | import matplotlib.pyplot as plt 6 | 7 | 8 | pairs1 = pd.read_csv("city_pairs.csv", names=["city1", "city2"]) 9 | pairs2 = pd.read_csv("city_pairs.csv", names=["city2", "city1"]) 10 | pairs = pd.concat([pairs1, pairs2]) 11 | 12 | # create adjacency matrix 13 | cities = pd.crosstab(pairs["city1"], pairs["city2"]) 14 | 15 | # create graph object with NetworkX library 16 | g = nx.from_pandas_adjacency(cities) 17 | 18 | # calculate node centrality with the PageRank algorithm 19 | rank = nx.pagerank(g, alpha=0.80) 20 | cities["rank"] = pd.Series(rank) / max(rank.values()) 21 | 22 | # draw graph, color by rank 23 | plt.figure() 24 | nx.draw(g, node_color=cities["rank"], cmap='coolwarm', labels=dict(zip(g.nodes(), g.nodes()))) 25 | 26 | plt.show() 27 | -------------------------------------------------------------------------------- /sqlite3/example_sqlite.py: -------------------------------------------------------------------------------- 1 | 2 | import sqlite3 3 | 4 | DB_SETUP = ''' 5 | CREATE TABLE IF NOT EXISTS person ( 6 | id INTEGER, 7 | name VARCHAR(32), 8 | description TEXT 9 | ); 10 | 11 | CREATE UNIQUE INDEX IF NOT EXISTS i1 ON person(id); 12 | ''' 13 | 14 | # watch out for the file 'hamlet.db' being created. 15 | db = sqlite3.connect('hamlet.db') 16 | db.executescript(DB_SETUP) 17 | 18 | # write data 19 | query = 'INSERT INTO person VALUES (?,?,?)' 20 | # The ?,?,? are a SQLite-specific way of formating strings. 21 | # There are special precautions against SQL injection 22 | db.execute(query, (1, "Hamlet", "the prince of Denkmark")) 23 | db.execute(query, (2, "Polonius", "Ophelias father")) 24 | 25 | # read data 26 | query = '''SELECT name, description FROM person''' 27 | result = db.execute(query) # returns an iterator 28 | print(list(result)) 29 | 30 | 31 | db.close() 32 | -------------------------------------------------------------------------------- /pillow/carrots/step05-filters.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageChops 3 | 4 | carrot = Image.open('carrot.png') 5 | brain = Image.open('brain.png') 6 | 7 | carrot = carrot.resize((250, 250)) 8 | 9 | arrow = Image.new('RGBA', (250, 250), "white") 10 | draw = ImageDraw.Draw(arrow) 11 | draw.rectangle((0, 50, 100, 100), fill="black") 12 | draw.polygon((100, 25, 100, 125, 150, 75), fill="black") 13 | 14 | gradient = Image.new('RGBA', (250, 250), "white") 15 | draw = ImageDraw.Draw(gradient) 16 | for x in range(250): 17 | box = (x, 0, x+1, 250) 18 | color = (255, (255-x), 0) 19 | draw.rectangle(box, fill=color) 20 | 21 | f1 = ImageChops.multiply(brain, carrot) 22 | f1.save('filter1.png') 23 | 24 | f2 = ImageChops.blend(brain, carrot, 0.2) 25 | f2.save('filter2.png') 26 | 27 | f3 = ImageChops.screen(carrot, gradient) 28 | f3.save('filter3.png') 29 | -------------------------------------------------------------------------------- /pandas/hexpanda.py: -------------------------------------------------------------------------------- 1 | 2 | # create a hex-binned plot from randomly sampled panda pixels 3 | 4 | import pandas as pd 5 | import pylab as plt 6 | from PIL import Image 7 | import numpy as np 8 | 9 | # read image and convert it to a numpy array 10 | panda = np.array(Image.open('panda.png')) 11 | panda = panda[:,:,:3].mean(axis=2) # aggregate each color channel separately 12 | print(panda.shape) # rows and columns 13 | 14 | pixels = pd.DataFrame(255 - panda) 15 | 16 | # extract dark pixels 17 | pixels = pixels.unstack() 18 | pixels = pixels[pixels > 0] 19 | 20 | # select 10% of pixels 21 | n_points = pixels.shape[0] // 10 22 | sample = pixels.sample(n_points) 23 | 24 | # create new table from indices 25 | coords = sample.index.to_frame().values 26 | df = pd.DataFrame({'x': coords[:,0], 'y': -coords[:,1], 'n': sample.values}) 27 | 28 | df.plot.hexbin(x='x', y='y', gridsize=24, cmap=plt.get_cmap('Greys')) 29 | 30 | plt.savefig('hexpanda.png') 31 | -------------------------------------------------------------------------------- /httpx/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to Download a web page? 3 | =========================== 4 | 5 | The `httpx` library sends HTTP requests to web pages and allows you to read their content. 6 | Most standard tasks are much easier than the standard module `urllib` and implemented cleaner than the outdated `requests` library. 7 | Sending data to web forms via HTTP GET and POST, submitting files and managing cookies are features of this useful library. 8 | 9 | Install `httpx` with: 10 | 11 | .. code:: 12 | 13 | pip install requests 14 | 15 | The following code reads a static web page: 16 | 17 | .. literalinclude:: example_requests.py 18 | 19 | How to submit a HTTP GET request from Python? 20 | ============================================= 21 | 22 | Here is a search with HTTP GET parameters: 23 | 24 | .. literalinclude:: search_with_parameters.py 25 | 26 | .. seealso:: 27 | 28 | `https://www.python-httpx.org/ `__ 29 | -------------------------------------------------------------------------------- /sqlalchemy/example_sqlalchemy.py: -------------------------------------------------------------------------------- 1 | 2 | from sqlalchemy import create_engine, text 3 | 4 | # connection string - specifies 5 | engine = create_engine("sqlite:///example.db", echo=False) 6 | 7 | with engine.connect() as conn: 8 | 9 | # write data 10 | conn.execute(text(''' 11 | CREATE TABLE IF NOT EXISTS person ( 12 | id INTEGER, 13 | name VARCHAR(32), 14 | description TEXT 15 | );''')) 16 | 17 | conn.execute(text('INSERT INTO person VALUES (:id,:name,:role)'), 18 | [ 19 | {"id": 1, "name": "Hamlet", "role": "the prince of Denkmark"}, 20 | {"id": 2, "name": "Kunigunde", "role": "the queen of Denkmark"}, 21 | ]) 22 | conn.commit() # writes to DB 23 | 24 | # read data 25 | result = conn.execute(text('SELECT name, description FROM person')) 26 | for name, description in result: 27 | print(name, description) 28 | -------------------------------------------------------------------------------- /pillow/README.md: -------------------------------------------------------------------------------- 1 | 2 | # Pillow 3 | 4 | ### What it is good for? 5 | 6 | `Pillow` reads, writes and edits images. 7 | 8 | It contains simple drawing tools and filters that can be applied to pixel based images. 9 | The most important feature of `Pillow` is that it can read and write almost all popular image formats. 10 | 11 | ### Installed with Python by default 12 | 13 | no 14 | 15 | ### Installed with Anaconda 16 | 17 | yes 18 | 19 | ### How to install it? 20 | 21 | :::text 22 | pip install pillow 23 | 24 | ### Where to learn more? 25 | 26 | [https://pillow.readthedocs.org](https://pillow.readthedocs.org) 27 | 28 | ### Shrink images 29 | 30 | :::include half_size.py 31 | 32 | ### Create a dice image 33 | 34 | ![](five.png) 35 | 36 | :::include dice.py 37 | 38 | ### Mix color channels 39 | 40 | ![](pylogo_warhol.png) 41 | 42 | :::include warhol.py 43 | 44 | ### Create turtle graphics 45 | 46 | ![](snowflake3.png) 47 | 48 | :::include snowflake.py 49 | 50 | -------------------------------------------------------------------------------- /pillow/carrots/step04-gradient.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageChops 3 | 4 | img = Image.new('RGBA', (800, 500), "white") 5 | 6 | carrot = Image.open('carrot.png') 7 | brain = Image.open('brain.png') 8 | 9 | carrot = carrot.resize((250, 250)) 10 | 11 | arrow = Image.new('RGBA', (250, 250), "white") 12 | draw = ImageDraw.Draw(arrow) 13 | draw.rectangle((0, 50, 100, 100), fill="black") 14 | draw.polygon((100, 25, 100, 125, 150, 75), fill="black") 15 | arrow.save('arrow.png') 16 | 17 | gradient = Image.new('RGBA', (250, 250), "white") 18 | draw = ImageDraw.Draw(gradient) 19 | for x in range(250): 20 | box = (x, 0, x+1, 250) 21 | color = (255, (255-x), 0) 22 | draw.rectangle(box, fill=color) 23 | gradient.save('gradient.png') 24 | 25 | arrow = ImageChops.screen(arrow, gradient) 26 | arrow.save('grad_arrow.png') 27 | 28 | img.paste(carrot, (100, 80)) 29 | img.paste(arrow, (325, 150)) 30 | img.paste(brain, (500, 100)) 31 | 32 | img.save('step04.png') 33 | 34 | -------------------------------------------------------------------------------- /email/smtp_example.py: -------------------------------------------------------------------------------- 1 | import smtplib 2 | from email.mime.multipart import MIMEMultipart 3 | from email.mime.text import MIMEText 4 | 5 | # Set up the email parameters 6 | sender_email = 'your_email@gmail.com' 7 | sender_password = 'your_password' 8 | receiver_email = 'recipient@example.com' 9 | subject = 'Hello from Python!' 10 | message = 'This is a test email sent from Python.' 11 | 12 | # Create the email message 13 | msg = MIMEMultipart() 14 | msg['From'] = sender_email 15 | msg['To'] = receiver_email 16 | msg['Subject'] = subject 17 | msg.attach(MIMEText(message, 'plain')) 18 | 19 | # Connect to Gmail's SMTP server 20 | try: 21 | server = smtplib.SMTP('smtp.gmail.com', 587) 22 | server.starttls() 23 | server.login(sender_email, sender_password) 24 | 25 | # Send the email 26 | server.sendmail(sender_email, receiver_email, msg.as_string()) 27 | print("Email sent successfully!") 28 | 29 | # Close the SMTP server 30 | server.quit() 31 | except Exception as e: 32 | print(f"An error occurred: {str(e)}") 33 | -------------------------------------------------------------------------------- /zipfile/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to create a zip archive? 3 | ============================ 4 | 5 | With the builtin module `zipfile`, you can add both existing files and strings to a zip file. If you are adding strings you need to specify the file name it is written to. When you extract files to a folder, the output folder is automatically created. 6 | 7 | .. code:: python3 8 | 9 | import zipfile 10 | 11 | z = zipfile.ZipFile('archive.zip', 'w') 12 | z.write('myfile.txt') # already existing file 13 | z.writestr('test.txt', 'Hello World') # string to new file 14 | z.close() 15 | 16 | How to read a zip archive? 17 | ========================== 18 | 19 | List the contents of a zip file: 20 | 21 | .. code:: python3 22 | 23 | z = zipfile.ZipFile('archive.zip') 24 | print(z.namelist()) 25 | 26 | 27 | Extract a file to a new folder: 28 | 29 | .. code:: python3 30 | 31 | print(z.extract('test.txt', 'myfolder')) 32 | z.close() 33 | 34 | 35 | .. seealso:: 36 | 37 | `Documentation of the zipfile module `__ 38 | -------------------------------------------------------------------------------- /math/README.rst: -------------------------------------------------------------------------------- 1 | 2 | 3 | How to calculate a square root? 4 | =============================== 5 | 6 | .. code:: python3 7 | 8 | import math 9 | 10 | print(math.sqrt(49)) 11 | 12 | 13 | How to calculate a trigonometric function? 14 | ========================================== 15 | 16 | .. code:: python3 17 | 18 | import math 19 | 20 | print(math.sin(math.pi / 2)) 21 | 22 | How to calculate an exponential function? 23 | ========================================= 24 | 25 | .. code:: python3 26 | 27 | import math 28 | 29 | print(math.exp(1.0) == math.e) 30 | 31 | How to calculate a logarithm? 32 | ============================= 33 | 34 | .. code:: python3 35 | 36 | import math 37 | 38 | print(math.log(256, 2)) 39 | 40 | .. seealso:: 41 | 42 | The builtin `math` module contains mathematical functions similar to a scientific calculator. 43 | In the module, you find various trigonometric and exponential functions. In addition the two constants `pi` and `e` are included. 44 | 45 | `math documentation `__ 46 | -------------------------------------------------------------------------------- /pillow/warhol.py: -------------------------------------------------------------------------------- 1 | 2 | # example: create Andy-Warhol like images 3 | 4 | from PIL import Image, ImageDraw 5 | 6 | pylogo = Image.open("python_logo.png") 7 | print(pylogo.size) 8 | 9 | r, g, b, a = pylogo.split() 10 | 11 | pylogo1 = Image.merge("RGB", (b, g, r)) 12 | pylogo2 = Image.merge("RGB", (r, b, g)) 13 | pylogo3 = Image.merge("RGB", (g, b, r)) 14 | pylogo4 = Image.merge("RGB", (g, r, b)) 15 | 16 | collage = Image.new("RGBA",(600,600), "#FFFFFF") 17 | 18 | collage.paste(pylogo1,(58,58)) 19 | collage.paste(pylogo2,(354,58)) 20 | collage.paste(pylogo3,(58,354)) 21 | collage.paste(pylogo4,(354,354)) 22 | 23 | draw_tool = ImageDraw.Draw(collage) 24 | draw_tool.line(((5, 5),(595, 5)), fill=(0,0,0),width=5) 25 | draw_tool.line(((595, 5),(595, 595)), fill=(0,0,0),width=5) 26 | draw_tool.line(((5, 5),(5, 595)), fill=(0,0,0),width=5) 27 | draw_tool.line(((5, 595),(595, 595)), fill=(0,0,0),width=5) 28 | draw_tool.line(((300, 5),(300, 595)), fill=(0,0,0),width=5) 29 | draw_tool.line(((5, 300),(595, 300)), fill=(0,0,0),width=5) 30 | 31 | collage.save('pylogo_warhol.png') 32 | collage.show() 33 | -------------------------------------------------------------------------------- /turtle/many_snowflakes.py: -------------------------------------------------------------------------------- 1 | 2 | from turtle import forward, left, right, width, color, clearscreen 3 | from turtle import setx, sety, speed, up, down 4 | from random import randint 5 | 6 | 7 | def zeichne_flocke(groesse): 8 | """ 9 | Funktion, wird hier definiert 10 | und weiter unten verwendet. 11 | """ 12 | for i in range(6): 13 | forward(groesse) 14 | left(60) 15 | forward(groesse / 2) 16 | left(180) 17 | forward(groesse / 2) 18 | left(60) 19 | forward(groesse / 2) 20 | left(180) 21 | forward(groesse / 2) 22 | right(120) 23 | forward(groesse / 2) 24 | left(180) 25 | forward(groesse * 1.5) 26 | left(120) 27 | 28 | 29 | # Hauptprogramm 30 | clearscreen() 31 | color("lightblue") 32 | width(3) 33 | speed(20) 34 | 35 | for i in range(10): 36 | # Stift an zufällige Position setzen 37 | up() 38 | setx(randint(-250, 250)) 39 | sety(randint(-200, 200)) 40 | down() 41 | # Flocke in zufälliger Größe zeichnen 42 | groesse = randint(10, 30) 43 | zeichne_flocke(groesse) 44 | 45 | -------------------------------------------------------------------------------- /LICENSE.TXT: -------------------------------------------------------------------------------- 1 | MIT License 2 | 3 | Copyright (c) 2017 Dr. Kristian Rother 4 | 5 | Permission is hereby granted, free of charge, to any person obtaining a copy 6 | of this software and associated documentation files (the "Software"), to deal 7 | in the Software without restriction, including without limitation the rights 8 | to use, copy, modify, merge, publish, distribute, sublicense, and/or sell 9 | copies of the Software, and to permit persons to whom the Software is 10 | furnished to do so, subject to the following conditions: 11 | 12 | The above copyright notice and this permission notice shall be included in all 13 | copies or substantial portions of the Software. 14 | 15 | THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR 16 | IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY, 17 | FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE 18 | AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER 19 | LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM, 20 | OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN THE 21 | SOFTWARE. 22 | -------------------------------------------------------------------------------- /json/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to write a JSON file? 3 | ========================= 4 | 5 | The builtin module `json` module converts Python dictionaries to JSON and back. 6 | The *JavaScript Object Notation (JSON)* is frequently used to send structured data around the web or store it painlessly in files. 7 | The `json` modules utilizes the similarity of the JSON format to Python dictionaries. 8 | 9 | .. code:: python3 10 | 11 | import json 12 | 13 | data = {"apples": 1, "bananas": "two", "cherries": [3,4,5]} 14 | with open("data.json", "w") as f: 15 | jj = json.dumps(data) 16 | f.write(jj) 17 | 18 | .. note:: 19 | 20 | You could write to the file directly with `json.dump`. 21 | 22 | How to read a JSON file? 23 | ======================== 24 | 25 | Loading a JSON data structure from a file results in a list or dictionary: 26 | 27 | .. code:: python3 28 | 29 | with open("data.json") as f: 30 | data = json.loads(f.read()) 31 | print(data) 32 | 33 | Instead of parsing a string object, you could parse from the file directly with `json.load()` 34 | 35 | .. seealso:: 36 | 37 | `Documentation of the json module `__ 38 | -------------------------------------------------------------------------------- /matplotlib/README.md: -------------------------------------------------------------------------------- 1 | 2 | # matplotlib 3 | 4 | ### What it is good for? 5 | 6 | Plotting diagrams. 7 | 8 | `matplotlib` is capable of producing static images of all common types of diagrams in print quality: line plots, scatter plots, bar charts, pie charts, histograms, heat maps etc. 9 | 10 | 11 | ### Installed with Anaconda 12 | 13 | yes 14 | 15 | ### How to install it: 16 | 17 | :::text 18 | pip install matplotlib 19 | 20 | ### Where to learn more? 21 | 22 | A good way to learn what you can do is to browse the examples gallery on [matplotlib.org/](http://matplotlib.org/) 23 | 24 | You find a comprehensive tutorial on [https://scipy-lectures.org/intro/matplotlib/index.html](https://scipy-lectures.org/intro/matplotlib/index.html) 25 | 26 | 27 | ### Scatterplot 28 | 29 | ![scatterplot](scatterplot.png) 30 | 31 | :::include balls.py 32 | 33 | ### Bar Plot 34 | 35 | ![barplot](barplot.png) 36 | 37 | :::include barplot.py 38 | 39 | ### Line Plot 40 | 41 | ![line plot](lineplot.png) 42 | 43 | :::include lineplot.py 44 | 45 | ### Error Bars 46 | 47 | ![error bars](errorbars.png) 48 | 49 | :::include errorbars.py 50 | 51 | ### Pie Chart 52 | 53 | ![pie chart](piechart.png) 54 | 55 | :::include piechart.py 56 | -------------------------------------------------------------------------------- /pillow/carrots/step07-full_image.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageChops, ImageFont 3 | 4 | img = Image.new('RGBA', (800, 500), "white") 5 | 6 | # load starting bitmaps 7 | logo = Image.open('python_logo.png') 8 | brain = Image.open('brain.png') 9 | 10 | logo = logo.resize((150, 150)) 11 | 12 | # draw an arrow 13 | arrow = Image.new('RGBA', (250, 250), "white") 14 | draw = ImageDraw.Draw(arrow) 15 | draw.rectangle((0, 50, 100, 100), fill="black") 16 | draw.polygon((100, 25, 100, 125, 150, 75), fill="black") 17 | 18 | # add gradient to arrow 19 | gradient = Image.new('RGBA', (250, 250), "white") 20 | draw = ImageDraw.Draw(gradient) 21 | for x in range(250): 22 | box = (x, 0, x+1, 250) 23 | color = (255, (255-x), 0) 24 | draw.rectangle(box, fill=color) 25 | 26 | arrow = ImageChops.screen(arrow, gradient) 27 | 28 | # combine all component images 29 | img.paste(logo, (100, 147)) 30 | img.paste(arrow, (325, 150)) 31 | img.paste(brain, (500, 100)) 32 | 33 | # add text 34 | draw = ImageDraw.Draw(img) 35 | arial = ImageFont.truetype('arial.ttf', 40) 36 | draw.text((220,360),"Python rocks your brain!",fill=(0,0,0),font=arial) 37 | 38 | img.save('step07_final.png') 39 | 40 | -------------------------------------------------------------------------------- /re/exercises/regex_search.py: -------------------------------------------------------------------------------- 1 | 2 | # Exercise: Regular expression search 3 | # 4 | # Find the right regular expressions that find something in the text. 5 | # 6 | # 1. Replace the 'regex' in the code 7 | # 2. Run the program to see whether it works. 8 | # 3. As soon as it does, uncomment the next example. 9 | 10 | import re 11 | 12 | text = """ 13 | 2ow8 3.71 tRNA_Phe ribosome_(p-site) 14 | 1b23 2.60 tRNA_Cys Ef-Tu 15 | 1qrt 2.70 tRNA_Gln GlnRS 16 | 1qf6 2.90 tRNA_Thr ThrRS 17 | 1j1u 1.95 tRNA_Tyr TyrRS 18 | 2fk6 2.90 tRNA_Thr RNase_Z 19 | 2hgr 4.51 tRNA_Phe ribosome_(e_or_p-site) 20 | """ 21 | 22 | # find all words 'tRNA' 23 | result = re.findall('regex',text) 24 | assert len(result) == 7 25 | 26 | # extract all PDB codes 27 | #result = re.findall('regex',text) 28 | # assert result == ['2ow8','1b23','1qrt','1qf6','1j1u','2fk6','2hgr'] 29 | 30 | # extract all aromatic amino acids 31 | #result = re.findall('regex',text) 32 | # assertt result == ['tRNA_Phe','tRNA_Tyr','tRNA_Phe'] 33 | 34 | # extract elements flanked by spaces on the left and right (2 middle columns) 35 | # result = re.findall('regex',text) 36 | # assertt len(result) == 14 37 | 38 | # extract a whole line containing key phrase 'Ef-Tu' 39 | # result = re.findall('regex',text) 40 | # assertt result == ['1b23 2.60 tRNA_Cys Ef-Tu'] 41 | -------------------------------------------------------------------------------- /re/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to search text with Regular Expressions? 3 | ============================================ 4 | 5 | The builtin module `re` implements **Regular Expression**, a powerful syntax for search patterns in text. 6 | You need to know some special characters to build your own patterns, although LLMs should be able to assist with that. 7 | Regular Expressions are very similar in most programming languages. 8 | 9 | Here are a couple of examples in Python: 10 | 11 | .. literalinclude:: fox.py 12 | 13 | .. seealso:: 14 | 15 | - `Regex 101 `__ - Shows matched text with explanation. 16 | - `regexone.com/ `__ - Learn regular expressions by simple, interactive examples. Great place to start. 17 | - `Regex crossword `__ - Train proper use of single characters, wildcards and square brackets. Easy. 18 | - `Regex golf `__ - Advanced exercises. Match as many phrases with as few key strokes as possible. 19 | - `Python Regex HOWTO `__ 20 | - `docs.python.org/3/library/re.html `__ 21 | - `Quick Reference `__ - a reference sheet for looking up metacharacters. Uses the **Python syntax**. 22 | -------------------------------------------------------------------------------- /scikit_image/wave_transform.py: -------------------------------------------------------------------------------- 1 | import numpy as np 2 | import matplotlib.pyplot as plt 3 | from skimage.transform import PiecewiseAffineTransform, warp 4 | from imageio import imread, imsave 5 | 6 | image = imread('python_logo.png') 7 | 8 | rows, cols = image.shape[0], image.shape[1] 9 | 10 | src_cols = np.linspace(0, cols, 20) 11 | src_rows = np.linspace(0, rows, 10) 12 | src_rows, src_cols = np.meshgrid(src_rows, src_cols) 13 | src = np.dstack([src_cols.flat, src_rows.flat])[0] 14 | 15 | # add sinusoidal oscillation to row coordinates 16 | FRAMES = 20 17 | for i in range(0, FRAMES): 18 | amplitude = 15 19 | phase = i / FRAMES * 2 * np.pi 20 | 21 | dst_rows = src[:, 1] - np.sin(np.linspace(phase, phase + 3 * np.pi, src.shape[0])) * amplitude 22 | dst_cols = src[:, 0] 23 | dst_rows *= 1.5 24 | dst_rows -= 1.5 * 50 25 | dst = np.vstack([dst_cols, dst_rows]).T 26 | 27 | tform = PiecewiseAffineTransform() 28 | tform.estimate(src, dst) 29 | 30 | out = warp(image, tform, output_shape=(rows, cols)) 31 | imsave(f'wave/out{i:03d}.png', out) 32 | 33 | 34 | # create animated GIF 35 | import imageio 36 | import os 37 | 38 | f = [] 39 | for fn in sorted(os.listdir('wave')): 40 | fn = 'wave/' + fn 41 | f.append(imageio.imread(fn)) 42 | 43 | imageio.mimsave('output.gif', f, fps=20) 44 | -------------------------------------------------------------------------------- /psycopg2/crud.py: -------------------------------------------------------------------------------- 1 | # pip install psycopg2-binary 2 | 3 | import psycopg2 4 | 5 | # Database connection details (must match your Docker container setup) 6 | DB_NAME = "mydatabase" 7 | DB_USER = "myuser" 8 | DB_PASS = "mypassword" 9 | DB_HOST = "localhost" # or "127.0.0.1" 10 | DB_PORT = "8000" 11 | 12 | # Connect to PostgreSQL 13 | conn = psycopg2.connect( 14 | dbname=DB_NAME, 15 | user=DB_USER, 16 | password=DB_PASS, 17 | host=DB_HOST, 18 | port=DB_PORT 19 | ) 20 | 21 | cur = conn.cursor() 22 | 23 | # 1) Create table 24 | cur.execute(""" 25 | CREATE TABLE IF NOT EXISTS flowers ( 26 | id SERIAL PRIMARY KEY, 27 | name VARCHAR(50), 28 | latin_species VARCHAR(100), 29 | color VARCHAR(30) 30 | ); 31 | """) 32 | 33 | # 2) Insert 3 rows 34 | flowers = [ 35 | ("Rose", "Rosa rubiginosa", "Red"), 36 | ("Sunflower", "Helianthus annuus", "Yellow"), 37 | ("Lavender", "Lavandula angustifolia", "Purple") 38 | ] 39 | 40 | cur.executemany( 41 | "INSERT INTO flowers (name, latin_species, color) VALUES (%s, %s, %s);", 42 | flowers 43 | ) 44 | 45 | # Commit the transaction 46 | conn.commit() 47 | 48 | # 3) Read them 49 | cur.execute("SELECT * FROM flowers;") 50 | rows = cur.fetchall() 51 | 52 | print("🌸 Flowers in database:") 53 | for row in rows: 54 | print(row) 55 | 56 | # Clean up 57 | cur.close() 58 | conn.close() 59 | -------------------------------------------------------------------------------- /pillow/dice_images/wuerfel.py: -------------------------------------------------------------------------------- 1 | """ 2 | Generiert Bilder von Wuerfelseiten 3 | """ 4 | 5 | from PIL import Image 6 | from PIL import ImageDraw 7 | 8 | w = Image.new('RGB', (64,64), '#80b940') 9 | 10 | blank = w.copy() 11 | blank.save('blank.png') 12 | 13 | d = ImageDraw.Draw(w) 14 | 15 | d.ellipse(((26, 26), (38, 38)), '#ffffff') 16 | eins = w.copy() 17 | eins.save('eins.png') 18 | 19 | d.ellipse(((10, 10), (22, 22)), '#ffffff') 20 | d.ellipse(((42, 42), (54, 54)), '#ffffff') 21 | drei = w.copy() 22 | drei.save('drei.png') 23 | 24 | d.ellipse(((10, 42), (22, 54)), '#ffffff') 25 | d.ellipse(((42, 10), (54, 22)), '#ffffff') 26 | fuenf = w.copy() 27 | fuenf.save('fuenf.png') 28 | 29 | d.ellipse(((26, 26), (38, 38)), '#80b940') 30 | vier = w.copy() 31 | vier.save('vier.png') 32 | 33 | d.ellipse(((10, 42), (22, 54)), '#80b940') 34 | d.ellipse(((42, 10), (54, 22)), '#80b940') 35 | zwei = w.copy() 36 | zwei.save('zwei.png') 37 | 38 | d.ellipse(((10, 42), (22, 54)), '#ffffff') 39 | d.ellipse(((42, 10), (54, 22)), '#ffffff') 40 | d.ellipse(((26, 10), (38, 22)), '#ffffff') 41 | d.ellipse(((26, 42), (38, 54)), '#ffffff') 42 | sechs = w.copy() 43 | sechs.save('sechs.png') 44 | 45 | w = Image.new('RGB', (64*6,64), '#80b940') 46 | w.paste(eins, box=(64 * 0, 0)) 47 | w.paste(zwei, box=(64 * 1, 0)) 48 | w.paste(drei, box=(64 * 2, 0)) 49 | w.paste(vier, box=(64 * 3, 0)) 50 | w.paste(fuenf, box=(64 * 4, 0)) 51 | w.paste(sechs, box=(64 * 5, 0)) 52 | w.save('wuerfel.png') 53 | -------------------------------------------------------------------------------- /sys/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to find out where the interpreter is looking for importable modules? 3 | ======================================================================== 4 | 5 | The builtin module `sys` provides an access point to the Python environment. 6 | You find there command line arguments, the import path settings, the standard input, output and error stream and many more. 7 | 8 | The `sys.path` variable contains the current directory, everything from the `PYTHONPATH` environment variable, and Pythons own folders. 9 | 10 | .. code:: python3 11 | 12 | print(sys.path) 13 | 14 | 15 | How to call a Python program with command-line parameters? 16 | ========================================================== 17 | 18 | The variable ``sys.argv`` contains a list of command-line arguments. 19 | The first one is usually the name of the called script. 20 | 21 | .. code:: python3 22 | 23 | import sys 24 | 25 | print sys.argv 26 | 27 | When you call this program with any of: 28 | 29 | :: 30 | 31 | python script.py 32 | python script.py hello world 33 | python script.py 1 2 3 34 | 35 | You should see a difference. 36 | 37 | How to terminate a Python program gracefully? 38 | ============================================= 39 | 40 | The `sys.exit()` function ends execution of the Python interpreter immediately. 41 | 42 | .. code:: python3 43 | 44 | import sys 45 | 46 | sys.exit() 47 | 48 | 49 | .. seealso:: 50 | 51 | `Documentation of the sys module `__ 52 | -------------------------------------------------------------------------------- /oauth_git/github.py: -------------------------------------------------------------------------------- 1 | """ 2 | https://developer.github.com/apps/building-oauth-apps/creating-an-oauth-app/ 3 | https://developer.github.com/apps/building-oauth-apps/authorizing-oauth-apps/ 4 | """ 5 | 6 | import requests 7 | from flask import Flask, redirect, url_for, escape, request 8 | import re 9 | 10 | app = Flask(__name__) 11 | 12 | CLIENT_ID = "..." 13 | CLIENT_SECRET = "..." 14 | AUTH_URL = "https://github.com/login/oauth/authorize" 15 | REDIRECT_URI = "http://localhost:5000/redirect/" 16 | 17 | 18 | app = Flask(__name__) 19 | 20 | 21 | @app.route('/') 22 | def login(): 23 | """1. Request a user's GitHub identity""" 24 | url = AUTH_URL + f"?client_id={CLIENT_ID}&login=krother&redirect_uri={REDIRECT_URI}" 25 | return redirect(url) 26 | 27 | 28 | @app.route('/redirect/') 29 | def redirect_from_github(): 30 | """2. Users are redirected back to your site by GitHub""" 31 | params = {'client_id': CLIENT_ID, 32 | 'client_secret': CLIENT_SECRET, 33 | 'code': request.args['code'], 34 | } 35 | r = requests.post("https://github.com/login/oauth/access_token", params) 36 | if r.status_code == 200: 37 | print(r.text) 38 | access_token = re.findall('access_token\=([^\&]+)', r.text)[0] 39 | print(access_token) 40 | # 41 | # now do stuff with access token 42 | # 43 | return redirect(url_for('goal')) 44 | return redirect(url_for('fail')) 45 | 46 | 47 | @app.route('/goal') 48 | def goal(): 49 | return "DONE!!!" 50 | 51 | @app.route('/fail') 52 | def fail(): 53 | return "*** FAIL ***" 54 | -------------------------------------------------------------------------------- /moviepy/end_credits.txt: -------------------------------------------------------------------------------- 1 | ; 2 | Moderation;Florian Kindermann 3 | ;Eva Hieninger 4 | ;Peter Henrich 5 | 6 | Redner;Andrej Laue 7 | ;Barbara Bosch 8 | 9 | Bewerter;Kristian Rother 10 | ;Sascha Goldmann 11 | ;Jan Schmeiser 12 | 13 | Zeitnehmer;Marek Schiffer 14 | ; 15 | Produktionsleitung;Sascha Goldmann 16 | Regie;David Madry 17 | Drehbuch;Kristian Rother 18 | Redaktion;Wendy Wallace Husser 19 | 20 | Kamera;Thomas Lewin 21 | ;Carsten Bellon 22 | ;Jörg Langrock 23 | Bildregie;Klaus Boettcher 24 | Licht;Martin Christoph 25 | Ton;Martin Christoph 26 | Tonassistenz;Angelika Firschke 27 | Intro und Abspann;Kristian Rother 28 | Schnitt;Klaus Boettcher 29 | ;Robert Klein 30 | 31 | Gästebetreuung;Antje Bellon 32 | Maske;Sabine Niemann 33 | Runner;Jörg Langrock 34 | Helfer;Gérald Hägele 35 | ;Fritz Boettcher 36 | ;Tristan Strauß 37 | 38 | Beratung;Schifra Wittkopp 39 | Studio CvD;Andrea Brehme 40 | 41 | Abspann erstellt mit;moviepy (by zulko) 42 | 43 | 44 | #wir danken ALEX Berlin 45 | #für die Unterstützung bei den Dreharbeiten. 46 | 47 | 48 | 49 | #Disclaimer: 50 | 51 | #Toastmasters International® and all other 52 | #Toastmasters International trademarks and 53 | #copyrights are the sole property of 54 | #Toastmasters International. This video was 55 | #created by Sascha Goldmann (District 95) 56 | #and is independent of Toastmasters International. 57 | #It is not authorized, endorsed, sponsored, 58 | #affiliated, or otherwise approved 59 | #training material by Toastmasters International. 60 | 61 | 62 | 63 | 64 | 65 | 66 | 67 | 68 | 69 | Sendungsverantwortlicher;Sascha Goldmann 70 | 71 | May 2016, Berlin, Germany 72 | -------------------------------------------------------------------------------- /PuLP/magic_sqare.py: -------------------------------------------------------------------------------- 1 | 2 | from pulp import * 3 | 4 | prob = LpProblem("PULPTEST", LpMinimize) 5 | 6 | # model variables 7 | XCOORD = [0, 1, 2] 8 | YCOORD = [0, 1, 2] 9 | NUMBERS = [1, 2, 3, 4, 5, 6, 7, 8, 9] 10 | 11 | # variable is a 3 x 3 x 9 matrix of binary values 12 | allocation = LpVariable.dicts("square", (XCOORD, YCOORD, NUMBERS), 0, 1, LpInteger) 13 | 14 | # target function 15 | prob += 0, "Arbitrary Objective Function" 16 | 17 | # constraint: sum over rows 18 | for x in XCOORD: 19 | prob += lpSum([n * allocation[x][y][n] for y in YCOORD for n in NUMBERS]) == 15 20 | 21 | # constraint: sum over columns 22 | for y in YCOORD: 23 | prob += lpSum([n * allocation[x][y][n] for x in XCOORD for n in NUMBERS]) == 15 24 | 25 | # constraint: each number only once 26 | for n in NUMBERS: 27 | prob += lpSum([allocation[x][y][n] for x in XCOORD for y in YCOORD]) == 1 28 | 29 | # constraint: three numbers per column 30 | for x in XCOORD: 31 | prob += lpSum([allocation[x][y][n] for y in YCOORD for n in NUMBERS]) == 3 32 | 33 | # constraint: three numbers per row 34 | for y in YCOORD: 35 | prob += lpSum([allocation[x][y][n] for x in XCOORD for n in NUMBERS]) == 3 36 | 37 | # constraint: 9 numbers set 38 | prob += lpSum([allocation[x][y][n] for x in XCOORD for y in YCOORD for n in NUMBERS]) == 9 39 | 40 | # run the solver 41 | prob.solve() 42 | 43 | print("Status:", LpStatus[prob.status]) 44 | 45 | # print the numbers that have been found 46 | for y in YCOORD: 47 | for x in XCOORD: 48 | for n in NUMBERS: 49 | if value(allocation[x][y][n]) == 1: 50 | print(n, end=' ') 51 | #print(x, y, n) 52 | print() 53 | -------------------------------------------------------------------------------- /os/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to check whether a file exists? 3 | =================================== 4 | 5 | The `os` module provides an easy way to interact with files, directories and other parts of your operating system. It contains many functions to list, change, copy, remove and examine files and directories. 6 | 7 | .. code:: python3 8 | 9 | import os 10 | 11 | print(os.path.exists('README.rst')) 12 | 13 | How to copy or remove a file? 14 | ============================= 15 | 16 | `os` does these as well: 17 | 18 | .. code:: python3 19 | 20 | import os 21 | 22 | os.system('cp README.md copy.md') 23 | 24 | os.remove('copy.md') 25 | 26 | 27 | How to loop over all files in a directory? 28 | ========================================== 29 | 30 | The following code prints all Python files in a given folder: 31 | 32 | .. code:: python3 33 | 34 | import os 35 | 36 | for filename in os.listdir("/home/participant/"): 37 | if filename.endswith(".py"): 38 | print(filename) 39 | 40 | 41 | How to run a command-line program from Python? 42 | ============================================== 43 | 44 | A very simple way to start other processes is the `os.system()` function. 45 | The following example starts a program to list contents of a folder and redirects the output to a file: 46 | 47 | .. code:: python3 48 | 49 | import os 50 | 51 | os.system("ls -l > result.txt") 52 | 53 | .. warning:: 54 | 55 | `os.system` does not allow for any communication with the running process. 56 | If it crashes or runs forever, your Python code won't learn about it. 57 | A safer alternative is the `multiprocessing` module. 58 | 59 | .. seealso:: 60 | 61 | `Documentation of the os module `__ 62 | -------------------------------------------------------------------------------- /.gitignore: -------------------------------------------------------------------------------- 1 | # Byte-compiled / optimized / DLL files 2 | __pycache__/ 3 | *.py[cod] 4 | *$py.class 5 | 6 | # C extensions 7 | *.so 8 | 9 | # Distribution / packaging 10 | .Python 11 | build/ 12 | develop-eggs/ 13 | dist/ 14 | downloads/ 15 | eggs/ 16 | .eggs/ 17 | lib/ 18 | lib64/ 19 | parts/ 20 | sdist/ 21 | var/ 22 | wheels/ 23 | *.egg-info/ 24 | .installed.cfg 25 | *.egg 26 | MANIFEST 27 | 28 | # PyInstaller 29 | # Usually these files are written by a python script from a template 30 | # before PyInstaller builds the exe, so as to inject date/other infos into it. 31 | *.manifest 32 | *.spec 33 | 34 | # Installer logs 35 | pip-log.txt 36 | pip-delete-this-directory.txt 37 | 38 | # Unit test / coverage reports 39 | htmlcov/ 40 | .tox/ 41 | .coverage 42 | .coverage.* 43 | .cache 44 | nosetests.xml 45 | coverage.xml 46 | *.cover 47 | .hypothesis/ 48 | .pytest_cache/ 49 | 50 | # Translations 51 | *.mo 52 | *.pot 53 | 54 | # Django stuff: 55 | *.log 56 | local_settings.py 57 | db.sqlite3 58 | 59 | # Flask stuff: 60 | instance/ 61 | .webassets-cache 62 | 63 | # Scrapy stuff: 64 | .scrapy 65 | 66 | # Sphinx documentation 67 | docs/_build/ 68 | 69 | # PyBuilder 70 | target/ 71 | 72 | # Jupyter Notebook 73 | .ipynb_checkpoints 74 | 75 | # pyenv 76 | .python-version 77 | 78 | # celery beat schedule file 79 | celerybeat-schedule 80 | 81 | # SageMath parsed files 82 | *.sage.py 83 | 84 | # Environments 85 | .env 86 | .venv 87 | env/ 88 | venv/ 89 | ENV/ 90 | env.bak/ 91 | venv.bak/ 92 | 93 | # Spyder project settings 94 | .spyderproject 95 | .spyproject 96 | 97 | # Rope project settings 98 | .ropeproject 99 | 100 | # mkdocs documentation 101 | /site 102 | 103 | # mypy 104 | .mypy_cache/ 105 | -------------------------------------------------------------------------------- /email/send_email.py: -------------------------------------------------------------------------------- 1 | 2 | import smtplib 3 | from email.mime.text import MIMEText 4 | 5 | class MailAccount: 6 | """ 7 | Stores settings for an email account. 8 | """ 9 | def __init__(self, server, login, password, sender_email, \ 10 | sender_name, use_tls=False): 11 | self.server = server 12 | self.login = login 13 | self.password = password 14 | self.mail = sender_email 15 | self.sender = '"%s" <%s>'%(sender_name, sender_email) 16 | self.use_tls = use_tls 17 | 18 | def send_email(self, recipient_email, subject, body): 19 | """Sends an email to a defined address. """ 20 | # prepare message 21 | message = MIMEText(body) 22 | message["Subject"] = subject 23 | message["From"] = self.mail 24 | message["To"] = recipient_email 25 | msg = message.as_string() 26 | 27 | server = smtplib.SMTP(self.server) 28 | server.set_debuglevel(1) 29 | 30 | if self.use_tls: # deliberately starts tls if using TLS 31 | server.ehlo() 32 | server.starttls() 33 | server.ehlo() 34 | 35 | server.login(self.login, self.password) 36 | server.sendmail(self.mail, recipient_email, msg) 37 | server.quit() 38 | 39 | if __name__ == '__main__': 40 | accounts = [ 41 | MailAccount('mailserver_address', \ 42 | 'your_account', 'your_password', 'your_email', \ 43 | 'Your Name', use_tls=True), 44 | ] 45 | 46 | for account in accounts: 47 | try: 48 | account.send_email('test@testdomain.de', 'Title', 'Content') 49 | print ('\nSENT!!\n\n\n') 50 | except smtplib.SMTPAuthenticationError: 51 | print ('\nFAIL\n\n') 52 | -------------------------------------------------------------------------------- /time/README.rst: -------------------------------------------------------------------------------- 1 | 2 | How to format the current time as a string? 3 | =========================================== 4 | 5 | The builtin module `time` contains a convenient one-stop function: 6 | 7 | .. code:: python3 8 | 9 | import time 10 | 11 | print(time.asctime()) 12 | 13 | An alternative is to retrieve the time and date as a `datetime` object that can be formated to custom strings: 14 | 15 | .. code:: python3 16 | 17 | print(time.strftime('%a %d.%m.', time.localtime())) 18 | 19 | How to use a datetime object? 20 | ============================= 21 | 22 | The `date` and `datetime` objects have attributes for time components: 23 | 24 | .. code:: python3 25 | 26 | import datetime 27 | 28 | date = datetime.date(2025, 9, 30) 29 | print(date.year, date.month, date.day) 30 | 31 | You can use explicit attribute names when creating date objects: 32 | 33 | .. code:: python3 34 | 35 | timestamp = datetime.datetime(year=2025, month=9, day=30, hour=7, minute=25, second=0) 36 | print(timestamp.minute) 37 | 38 | How to let a program wait for a while? 39 | ====================================== 40 | 41 | The `time.sleep()` function gives back control to the Python interpreter. If you are running multiple threads they may do something. 42 | 43 | .. code:: python3 44 | 45 | import time 46 | 47 | time.sleep(3) 48 | 49 | Note that if you are in an asynchronous function, you will have to use `asyncio.sleep()`. 50 | 51 | .. code:: python3 52 | 53 | import asyncio 54 | 55 | async def wait(): 56 | await asyncio.sleep(3) 57 | 58 | asyncio.run(wait()) 59 | 60 | .. seealso:: 61 | 62 | - `Documentation for the time module `__ 63 | - `Documentation for the datetime module `__ 64 | -------------------------------------------------------------------------------- /tkinter/titanic.py: -------------------------------------------------------------------------------- 1 | import tkinter as tk 2 | from tkinter.messagebox import showwarning 3 | from PIL import Image, ImageTk 4 | 5 | 6 | class Application(tk.Frame): 7 | def __init__(self, master=None): 8 | super().__init__(master) 9 | self.titanic = Image.open("titanic.png") 10 | self.titanic2 = Image.open("titanic2.png") 11 | self.pack() 12 | self.create_widgets() 13 | 14 | def send_sos(self): 15 | showwarning(title="S.O.S.", message="we are sinking") 16 | 17 | def collision(self): 18 | photo = ImageTk.PhotoImage(self.titanic2) 19 | self.canvas.image = photo 20 | self.im = self.canvas.create_image(0, 0, image=photo, anchor='nw') 21 | 22 | def create_widgets(self): 23 | photo = ImageTk.PhotoImage(self.titanic) 24 | self.canvas = tk.Canvas(self, width=700, height=178, bg='black') 25 | self.canvas.pack(side='top', fill='both', expand='yes') 26 | self.canvas.image = photo # keep a reference! 27 | self.im = self.canvas.create_image(0, 0, image=photo, anchor='nw') 28 | 29 | self.quit = tk.Button(self, text="Abandon ship", 30 | command=root.destroy) 31 | self.quit.pack(side="bottom", fill="both", expand="yes") 32 | 33 | self.sos = tk.Button(self, fg="red") 34 | self.sos["text"] = "Send out S.O.S." 35 | self.sos["command"] = self.send_sos 36 | self.sos.pack(side="bottom", fill="both", expand="yes") 37 | 38 | self.sink = tk.Button(self) 39 | self.sink["text"] = "Full Speed" 40 | self.sink["command"] = self.collision 41 | self.sink.pack(side="bottom", fill="both", expand="yes") 42 | 43 | 44 | 45 | root = tk.Tk() 46 | app = Application(master=root) 47 | app.master.title("Titanic-Simulator 1.0") 48 | app.mainloop() 49 | -------------------------------------------------------------------------------- /moviepy/end_credits.py: -------------------------------------------------------------------------------- 1 | 2 | import gizeh as gz 3 | import moviepy.editor as mpy 4 | from moviepy.editor import ImageClip, CompositeVideoClip 5 | from faker import Factory 6 | 7 | W, H = 1200, 1000 8 | 9 | DURATION = 25 # seconds 10 | 11 | LEFTCOL = 450 12 | RIGHTCOL = 490 13 | TEXTSIZE = 28 14 | LINE_HEIGHT = 50 15 | 16 | SCROLLSPEED = 130 17 | BOTTOM_START = H * 1.2 18 | 19 | N_NAMES = 30 20 | 21 | # load image that does not move at all 22 | LOGO_POS = 950, 300 23 | LOGO_SIZE = 235, 298 24 | LOGO = ImageClip("panda.png").resize(LOGO_SIZE).set_pos(LOGO_POS) 25 | LOGO.duration = DURATION 26 | 27 | 28 | # create fake text 29 | fake = Factory.create() 30 | text = [] 31 | while len(text) < N_NAMES: 32 | job = fake.job() 33 | name = fake.name() 34 | if len(job) < 25: 35 | text.append((job, name)) 36 | 37 | 38 | def make_frame(t): 39 | """Draw text elements in each frame""" 40 | surface = gz.Surface(W, H, bg_color=(0,0,0)) 41 | for i, line in enumerate(text): 42 | job, name = line 43 | ypos = LINE_HEIGHT * i - int(t * SCROLLSPEED) + BOTTOM_START 44 | 45 | txt = gz.text(job, "Amiri", TEXTSIZE, fontweight='bold', \ 46 | h_align='right', fill=(1,1,1)) 47 | left = gz.Group([txt]).translate((LEFTCOL, ypos)) 48 | left.draw(surface) 49 | txt = gz.text(name, "Amiri", TEXTSIZE, \ 50 | fontweight='normal',h_align='left', fill=(1,1,1)) 51 | right = gz.Group([txt]).translate((RIGHTCOL, ypos)) 52 | right.draw(surface) 53 | return surface.get_npimage() 54 | 55 | 56 | clip = mpy.VideoClip(make_frame, duration=DURATION) 57 | 58 | # mix text and logo together 59 | final = CompositeVideoClip([clip, LOGO]) 60 | final.subclip(0, DURATION).write_videofile("abspann.avi", codec="h264", fps=24) 61 | #final.subclip(0, DURATION).write_videofile("abspann.mp4", codec="mpeg4", fps=24) 62 | -------------------------------------------------------------------------------- /ipyvolume/volume.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "code", 5 | "execution_count": null, 6 | "metadata": {}, 7 | "outputs": [], 8 | "source": [ 9 | "import ipyvolume as ipv\n", 10 | "import numpy as np" 11 | ] 12 | }, 13 | { 14 | "cell_type": "code", 15 | "execution_count": null, 16 | "metadata": {}, 17 | "outputs": [], 18 | "source": [ 19 | "x, y, z = np.random.normal(0.0, 1.0, (3, 1000))" 20 | ] 21 | }, 22 | { 23 | "cell_type": "code", 24 | "execution_count": null, 25 | "metadata": {}, 26 | "outputs": [], 27 | "source": [ 28 | "fig = ipv.quickscatter(x, y, z, size=1, marker=\"sphere\")\n", 29 | "fig" 30 | ] 31 | }, 32 | { 33 | "cell_type": "code", 34 | "execution_count": null, 35 | "metadata": {}, 36 | "outputs": [], 37 | "source": [ 38 | "V = np.zeros((128,128,128)) # our 3d array\n", 39 | "# outer box\n", 40 | "V[30:-30,30:-30,30:-30] = 0.75\n", 41 | "V[35:-35,35:-35,35:-35] = 0.0\n", 42 | "# inner box\n", 43 | "V[50:-50,50:-50,50:-50] = 0.25\n", 44 | "V[55:-55,55:-55,55:-55] = 0.0\n", 45 | "ipv.quickvolshow(V, level=[0.25, 0.75], opacity=0.03, level_width=0.1, data_min=0, data_max=1)" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": null, 51 | "metadata": {}, 52 | "outputs": [], 53 | "source": [] 54 | } 55 | ], 56 | "metadata": { 57 | "kernelspec": { 58 | "display_name": "Python 3", 59 | "language": "python", 60 | "name": "python3" 61 | }, 62 | "language_info": { 63 | "codemirror_mode": { 64 | "name": "ipython", 65 | "version": 3 66 | }, 67 | "file_extension": ".py", 68 | "mimetype": "text/x-python", 69 | "name": "python", 70 | "nbconvert_exporter": "python", 71 | "pygments_lexer": "ipython3", 72 | "version": "3.6.1" 73 | } 74 | }, 75 | "nbformat": 4, 76 | "nbformat_minor": 2 77 | } 78 | -------------------------------------------------------------------------------- /re/exercises/regex_solution.py: -------------------------------------------------------------------------------- 1 | 2 | import re 3 | from compare import compare 4 | 5 | def substitution_examples(): 6 | """Some examples of using regular expression substitution.""" 7 | # example text 8 | text = "7 apples, 24 bananas, 14 carrots, and oranges are fruit" 9 | 10 | # replace one word by another 11 | result = re.sub('carrots','pears',text) 12 | compare(result,"7 apples, 24 bananas, 14 pears, and oranges are fruit") 13 | 14 | # remove all numbers 15 | result = re.sub('\d+ ','',text) 16 | compare(result,"apples, bananas, carrots, and oranges are fruit") 17 | 18 | 19 | 20 | def search_examples(): 21 | """Some examples of using regular expression search.""" 22 | # example text body: tRNA structures from the PDB 23 | text = """ 24 | 2ow8 3.71 tRNA_Phe ribosome_(p-site) 25 | 1b23 2.60 tRNA_Cys Ef-Tu 26 | 1qrt 2.70 tRNA_Gln GlnRS 27 | 1qf6 2.90 tRNA_Thr ThrRS 28 | 1j1u 1.95 tRNA_Tyr TyrRS 29 | 2fk6 2.90 tRNA_Thr RNase_Z 30 | 2hgr 4.51 tRNA_Phe ribosome_(e_or_p-site) 31 | """ 32 | 33 | # count frequency of the word 'tRNA' 34 | result = re.findall('tRNA',text) 35 | compare(len(result),7) 36 | 37 | # extract all PDB codes 38 | result = re.findall('\d\w\w\w',text) 39 | compare(result,['2ow8','1b23','1qrt','1qf6','1j1u','2fk6','2hgr']) 40 | 41 | # extract all aromatic amino acids 42 | result = re.findall('tRNA_Phe|tRNA_Tyr|tRNA_Trp',text) 43 | compare(result,['tRNA_Phe','tRNA_Tyr','tRNA_Phe']) 44 | 45 | # extract elements separated by spaces (2 middle columns) 46 | result = re.findall(' [^ ]+ ',text) 47 | compare(len(result),14) 48 | 49 | # extract a whole line containing key phrase 'Ef-Tu' 50 | result = re.findall('(\d.*Ef-Tu.*)\n',text) 51 | compare(result,['1b23 2.60 tRNA_Cys Ef-Tu']) 52 | 53 | 54 | # run both examples 55 | substitution_examples() 56 | search_examples() 57 | -------------------------------------------------------------------------------- /pillow/snowflake.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageFont, ImageFilter 3 | import math 4 | 5 | 6 | class Turtle: 7 | """ 8 | Draws turtle graphics on a white background. 9 | 10 | The turtle has a position and a direction, 11 | and can move forward and turn left and right. 12 | """ 13 | def __init__(self): 14 | """Initializes the turtle.""" 15 | self.x = 0 16 | self.y = 200 17 | self.angle = 0.0 18 | self.image = Image.new('RGB', (500, 250), (255,255,255)) 19 | self.draw_tool = ImageDraw.Draw(self.image) 20 | 21 | def turn_left(self,ang): 22 | self.angle -= ang 23 | if self.angle<0: self.angle += 360 24 | 25 | def turn_right(self,ang): 26 | self.angle += ang 27 | if self.angle>=360: self.angle -= 360 28 | 29 | def move_forward(self,length,draw=True): 30 | """ 31 | Moves the turtle forward in its current direction. 32 | It draws a line (can be turned off optionally.""" 33 | new_x = self.x + length * math.cos(math.radians(self.angle)) 34 | new_y = self.y + length * math.sin(math.radians(self.angle)) 35 | self.draw_tool.line(((self.x,self.y),(new_x,new_y)), fill=(0,0,0),width=2) 36 | self.x = new_x 37 | self.y = new_y 38 | 39 | 40 | 41 | def snowflake(turtle, length, depth): 42 | """Draws a recursive snowflake curve with the given turtle.""" 43 | if depth == 0: 44 | turtle.move_forward(length) 45 | else: 46 | snowflake(turtle, length * 0.333, depth-1) 47 | turtle.turn_left(60) 48 | snowflake(turtle, length * 0.333, depth-1) 49 | turtle.turn_right(120) 50 | snowflake(turtle, length * 0.333, depth-1) 51 | turtle.turn_left(60) 52 | snowflake(turtle, length * 0.333, depth-1) 53 | 54 | 55 | 56 | if __name__ == '__main__': 57 | """Main program. Starts the turtle and draws a snowflake.""" 58 | # try different values for 'depth' 59 | t = Turtle() 60 | snowflake(t, 500, 1) 61 | t.image.save('snowflake1.png') 62 | t = Turtle() 63 | snowflake(t, 500, 2) 64 | t.image.save('snowflake2.png') 65 | t = Turtle() 66 | snowflake(t, 500, 5) 67 | t.image.save('snowflake3.png') 68 | -------------------------------------------------------------------------------- /curses/pac.py: -------------------------------------------------------------------------------- 1 | import curses 2 | import random 3 | import time 4 | 5 | # WASD keys + exit key (X) 6 | KEY_COMMANDS = {97: (-1, 0), 100: (1, 0), 119: (0, -1), 115: (0, 1), 120: (0, 0)} 7 | 8 | # prepare the screen 9 | screen = curses.initscr() 10 | curses.start_color() 11 | curses.init_pair(1, curses.COLOR_YELLOW, curses.COLOR_BLACK) 12 | curses.curs_set(0) 13 | curses.noecho() 14 | curses.raw() 15 | screen.keypad(False) 16 | 17 | win = curses.newwin(30, 15, 0, 0) 18 | win.nodelay(True) 19 | 20 | 21 | def draw(level, player, ghost, screen, win): 22 | """create a 2D landscape""" 23 | screen.clear() 24 | for y, row in enumerate(level): 25 | for x, char in enumerate(row): 26 | screen.addch(y, x*2, char, curses.color_pair(1)) 27 | screen.addch(player[1], player[0] * 2, "O", curses.color_pair(1)) 28 | screen.addch(ghost[1], ghost[0] * 2, "G", curses.color_pair(1)) 29 | win.refresh() 30 | screen.refresh() 31 | 32 | 33 | def move(position, direction, level): 34 | """change positions""" 35 | x, y = position 36 | dx, dy = direction 37 | nx, ny = x + dx, y + dy 38 | if level[ny][nx] == "#": 39 | return x, y 40 | return nx, ny 41 | 42 | 43 | def move_player(player, direction, level): 44 | """changes position and eats dots""" 45 | x, y = move(player, direction, level) 46 | level[y] = level[y][:x] + " " + level[y][x+1:] 47 | return x, y 48 | 49 | 50 | def move_ghost(ghost, level): 51 | direction = random.choice(list(KEY_COMMANDS.values())[:-1]) 52 | return move(ghost, direction, level) 53 | 54 | 55 | def get_keyboard(win): 56 | char = win.getch() 57 | return KEY_COMMANDS.get(char) 58 | 59 | def pac_game(screen): 60 | """called by curses""" 61 | level = """ 62 | ########### 63 | #....#....# 64 | #.##...##.# 65 | #.#..#..#.# 66 | #....#....# 67 | ##.#####.## 68 | #....#....# 69 | #.#..#..#.# 70 | #.##...##.# 71 | #....#....# 72 | ###########""".strip().split() 73 | player = 1, 1 74 | ghost = 9, 9 75 | 76 | while player != ghost and any([row for row in level if "." in row]): 77 | ghost = move_ghost(ghost, level) 78 | draw(level, player, ghost, screen, win) 79 | if direction := get_keyboard(win): 80 | if direction == (0, 0): 81 | player = ghost 82 | else: 83 | player = move_player(player, direction, level) 84 | else: 85 | time.sleep(0.1) 86 | 87 | 88 | if __name__ == "__main__": 89 | curses.wrapper(pac_game) 90 | curses.endwin() -------------------------------------------------------------------------------- /pillow/flower_movie/flower_movie.py: -------------------------------------------------------------------------------- 1 | 2 | from PIL import Image, ImageDraw, ImageFont, ImageFilter 3 | import random 4 | 5 | 6 | NPIECES = 25 # 16 7 | EDGEWIDTH = 16 # 25 8 | VEC_GROWTH = 1.020 # 1.03 9 | PHASE1_FRAMES = 250 10 | PHASE2_FRAMES = 100 11 | 12 | 13 | def create_pieces(filename): 14 | """ 15 | Takes a picture and dissects it into NPIECES**2 16 | smaller images 17 | """ 18 | flower = Image.open(filename, 'r') 19 | flower = flower.resize((NPIECES * EDGEWIDTH, NPIECES * EDGEWIDTH)) 20 | 21 | pieces = [] 22 | positions = [] 23 | for x in range(NPIECES): 24 | for y in range(NPIECES): 25 | copy = flower.copy() 26 | piece = copy.crop((x * EDGEWIDTH, y * EDGEWIDTH, 27 | (x + 1) * EDGEWIDTH, (y + 1) * EDGEWIDTH)) 28 | pieces.append(piece) 29 | positions.append((x * EDGEWIDTH, y * EDGEWIDTH)) 30 | return pieces, positions 31 | 32 | 33 | def increment(): 34 | """Returns a random number from +-0.1 .. 1.1""" 35 | inc = random.random() + 0.1 36 | if random.random() > 0.5: 37 | return -inc 38 | return inc 39 | 40 | 41 | def randvec(): 42 | """Returns a random (x, y) vector""" 43 | return increment(), increment() 44 | 45 | 46 | def create_image(pieces, positions): 47 | """Assembles all small pieces to a big image""" 48 | img = Image.new("RGB", (NPIECES * EDGEWIDTH, NPIECES * EDGEWIDTH)) 49 | for pc, pos in zip(pieces, positions): 50 | img.paste(pc, pos) 51 | return img 52 | 53 | 54 | def move_pieces(positions, vectors): 55 | """modifies positions of images""" 56 | new_pos = [] 57 | for pos, vec in zip(positions, vectors): 58 | new_pos.append((pos[0] + int(vec[0]), pos[1] + int(vec[1]))) 59 | return new_pos 60 | # TODO: this would be much easier with pandas!!! 61 | 62 | 63 | def increase_vectors(vectors): 64 | """accelerate so that pieces move faster in earlier frames""" 65 | new_vecs = [] 66 | for vec in vectors: 67 | new_vecs.append((vec[0]*VEC_GROWTH, vec[1]*VEC_GROWTH)) 68 | return new_vecs 69 | 70 | 71 | if __name__ == '__main__': 72 | pcs, pos = create_pieces('flower.jpg') 73 | vecs = [randvec() for i in pos] 74 | 75 | # writing standstill frames at the end. 76 | img = create_image(pcs, pos) 77 | for iframe in range(PHASE1_FRAMES, PHASE1_FRAMES + PHASE2_FRAMES): 78 | img.save('out/frame_{:04d}.png'.format(iframe)) 79 | 80 | # writing gradually dissipating frames 81 | for iframe in range(PHASE1_FRAMES, 0, -1): 82 | img = create_image(pcs, pos) 83 | img.save('out/frame_{:04d}.png'.format(iframe)) 84 | pos = move_pieces(pos, vecs) 85 | vecs = increase_vectors(vecs) 86 | -------------------------------------------------------------------------------- /index.rst: -------------------------------------------------------------------------------- 1 | Python Library Examples 2 | ======================= 3 | 4 | Here you find easy copy-paste examples of my favourite Python libraries. 5 | 6 | 7 | Builtin modules 8 | --------------- 9 | 10 | .. toctree:: 11 | :maxdepth: 2 12 | 13 | itertools/README.rst 14 | math/README.rst 15 | os/README.rst 16 | pathlib/README.rst 17 | random/README.rst 18 | re/README.rst 19 | sys/README.rst 20 | time/README.rst 21 | 22 | Reading and Writing Files 23 | ------------------------- 24 | 25 | .. toctree:: 26 | :maxdepth: 2 27 | 28 | json/README.rst 29 | xml/README.rst 30 | zipfile/README.rst 31 | 32 | 33 | :: 34 | 35 | pydocx](pydocx/) | read Word documents | 36 | pypdf2](pypdf2/) | merge PDF documents | 37 | 38 | 39 | Data Science 40 | ------------ 41 | 42 | .. toctree:: 43 | :maxdepth: 2 44 | 45 | numpy/README.rst 46 | pandas/README.rst 47 | scipy/README.rst 48 | 49 | scikit-learn](sklearn/) | Machine Learning | 50 | PuLP](PuLP/) | linear equation solver | 51 | fuzzywuzzy](fuzzywuzzy/) | fuzzy text search | 52 | vader/README.rst 53 | statsmodels (external)](http://statsmodels.sourceforge.net/) | Hypothesis tests and statistical models | 54 | 55 | 56 | Plotting 57 | -------- 58 | 59 | folium](folium/) | drawing maps | 60 | matplotlib](matplotlib/) | plotting diagrams | 61 | NetworkX](networkx/) | analyze and plot graphs | 62 | wordcloud](wordcloud/) | plot word clouds | 63 | 64 | Image Processing 65 | ---------------- 66 | 67 | pillow - image manipulation](pillow/) | | 68 | pytesseract](pytesseract/) | extract text from images (OCR) | 69 | scikit-image](scikit_image/) | Advanced image processing | 70 | 71 | Databases 72 | --------- 73 | 74 | pymongo/README.rst 75 | sqlite3](sqlite3/) | a simple SQL database | 76 | 77 | Web programming 78 | --------------- 79 | 80 | httpx/README.rst 81 | BeautifulSoup4](beautiful_soup/) | parse HTML pages | 82 | email](email/) | send emails | 83 | flask](flask/) | a simple web server | 84 | OAUTH - authentication](oauth_git/) | authentication | 85 | scrapy (external)](http://scrapy.org/) | collect data from entire websites | 86 | 87 | User Interfaces 88 | --------------- 89 | 90 | .. toctree:: 91 | :maxdepth: 2 92 | 93 | tqdm/README.rst 94 | tkinter/README.rst 95 | curses/README.rst 96 | 97 | Acknowledgements 98 | ---------------- 99 | 100 | Thanks to Emely Henninger for finding a nasty bug in networkx! 101 | 102 | 103 | .. topic:: License 104 | 105 | © 2025 Dr. Kristian Rother (`kristian.rother@posteo.de`) 106 | 107 | The code is distributed under the conditions of the MIT License. See :download:`LICENSE.TXT` for details. 108 | 109 | Text may be reused under the conditions of the Creative Commons Attribution Share-alike License 4.0 (CC-BY-SA 4.0). 110 | See `creativecommons.org `__ for details 111 | -------------------------------------------------------------------------------- /pypdf2/extras/pdf.py: -------------------------------------------------------------------------------- 1 | import textract # modul zum extrahieren von text aus pdf datein 2 | import re # reguläre ausdrücke 3 | import operator # hilfe beim sortieren nach value 4 | 5 | # text aus pdf extrahieren 6 | text = textract.process("skript_101.pdf", encoding="utf-8") 7 | # bytestring zu utf-8 dekodieren 8 | text = text.decode('utf-8') 9 | 10 | # zeilen am newline character "\n" splitten 11 | lines = text.split('\n') 12 | 13 | titleIndex = 0 # dokumententitel 14 | authorIndex = 1 # dokumentenautorin 15 | dropIndex = [3,4] # müll 16 | 17 | title = lines[titleIndex] 18 | author = lines[authorIndex] 19 | 20 | # überschriften + unnötige lines im skript löschen 21 | counter = 0 22 | for i in drop_index: 23 | del lines[i-counter] 24 | counter += 1 25 | del lines[authorIndex] 26 | del lines[titleIndex] 27 | 28 | # funktion um herauszufinden welcher teil vom skript einem sprecher zuzuordnen ist 29 | def isName(str): 30 | if str: 31 | if len(str.split(' ')) == 1 and \ 32 | str[0].isupper() and \ 33 | str[-1:].isalpha(): 34 | return True 35 | return False 36 | 37 | # zeilen für jeden sprecher in ein dictionary einsortieren 38 | speakerText = dict() 39 | for i, l in enumerate(lines): 40 | if isName(l): 41 | name = l 42 | text = "" 43 | counter = 2 44 | # suche nach zusätzlichen zeilen 45 | tmp = lines[i+counter] # potentielle neue zeile 46 | while tmp: # tmp ist nicht leer 47 | if counter > 2: # neue zeile gefunden 48 | text += " " # trennen mit leerzeichen 49 | text += tmp # zeilen kombinieren 50 | counter += 1 # zähler erhöhen 51 | tmp = lines[i+counter] # tmp updaten 52 | if not text: # text ist leer 53 | continue # nächste zeile 54 | if name in speakerText: # key (name des sprechers) vorhanden 55 | speakerText[name].append(text) # array anfügen 56 | else: # key unbekannt 57 | speakerText[name] = [text] # neues array mit text 58 | 59 | # für jeden sprecher die worthäufigkeit zählen 60 | speakerWordCount = dict() 61 | for name, lines in speakerText.items(): 62 | wordCount = dict() 63 | for l in lines: # für jede zeile 64 | # ignoriere alle satzzeichen, finde wörter 65 | words = re.findall("[A-Za-z\[\]äöüß]+", l.lower()) 66 | for w in words: 67 | if w in wordCount: # key vorhanden 68 | wordCount[w] += 1 69 | else: # key unbekannt 70 | wordCount[w] = 1 71 | speakerWordCount[name] = wordCount 72 | 73 | # wortanzahl pro sprecher 74 | speakerCount = dict() 75 | for name in wordFrequency: 76 | total = 0 77 | for key,value in wordFrequency[name].items(): 78 | total += value # summiere worthäufigkeit 79 | speakerCount[name] = total 80 | 81 | # sortierte wortzahl 82 | sorted(speakerCount.items(), key=operator.itemgetter(1),reverse=True) 83 | 84 | # justus häufigste wörter 85 | sorted(wordFrequency["Justus"].items(), key=operator.itemgetter(1),reverse=True) 86 | 87 | # peters häufigste wörter 88 | sorted(wordFrequency["Peter"].items(), key=operator.itemgetter(1),reverse=True) 89 | 90 | # bobs häufigste wörter 91 | sorted(wordFrequency["Bob"].items(), key=operator.itemgetter(1),reverse=True) 92 | 93 | 94 | -------------------------------------------------------------------------------- /ipywidgets/ipywidgets.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# IPywidgets\n", 8 | "see https://ipywidgets.readthedocs.io/en/stable/examples/Widget%20List.html" 9 | ] 10 | }, 11 | { 12 | "cell_type": "code", 13 | "execution_count": 1, 14 | "metadata": {}, 15 | "outputs": [], 16 | "source": [ 17 | "from ipywidgets import interact, widgets" 18 | ] 19 | }, 20 | { 21 | "cell_type": "code", 22 | "execution_count": 2, 23 | "metadata": {}, 24 | "outputs": [ 25 | { 26 | "data": { 27 | "application/vnd.jupyter.widget-view+json": { 28 | "model_id": "b4ccba38a0164c59bf72c2a64ee7c6cd", 29 | "version_major": 2, 30 | "version_minor": 0 31 | }, 32 | "text/plain": [ 33 | "interactive(children=(IntSlider(value=30, description='x', max=60, step=2), Output()), _dom_classes=('widget-i…" 34 | ] 35 | }, 36 | "metadata": {}, 37 | "output_type": "display_data" 38 | }, 39 | { 40 | "data": { 41 | "text/plain": [ 42 | "" 43 | ] 44 | }, 45 | "execution_count": 2, 46 | "metadata": {}, 47 | "output_type": "execute_result" 48 | } 49 | ], 50 | "source": [ 51 | "def show_number(x):\n", 52 | " print('=' * x)\n", 53 | " \n", 54 | "interact(show_number, x=(0, 60, 2))" 55 | ] 56 | }, 57 | { 58 | "cell_type": "code", 59 | "execution_count": 3, 60 | "metadata": {}, 61 | "outputs": [ 62 | { 63 | "data": { 64 | "application/vnd.jupyter.widget-view+json": { 65 | "model_id": "1ef02f50e77d401e86f2350046c85dee", 66 | "version_major": 2, 67 | "version_minor": 0 68 | }, 69 | "text/plain": [ 70 | "interactive(children=(ColorPicker(value='blue', description='Pick a color'), Output()), _dom_classes=('widget-…" 71 | ] 72 | }, 73 | "metadata": {}, 74 | "output_type": "display_data" 75 | }, 76 | { 77 | "data": { 78 | "text/plain": [ 79 | "" 80 | ] 81 | }, 82 | "execution_count": 3, 83 | "metadata": {}, 84 | "output_type": "execute_result" 85 | } 86 | ], 87 | "source": [ 88 | "col = widgets.ColorPicker(\n", 89 | " concise=False,\n", 90 | " description='Pick a color',\n", 91 | " value='blue',\n", 92 | " disabled=False\n", 93 | ")\n", 94 | "\n", 95 | "def clicked(color):\n", 96 | " print(\"you picked: \", color)\n", 97 | " \n", 98 | "interact(clicked, color=col)" 99 | ] 100 | }, 101 | { 102 | "cell_type": "code", 103 | "execution_count": null, 104 | "metadata": {}, 105 | "outputs": [], 106 | "source": [] 107 | } 108 | ], 109 | "metadata": { 110 | "kernelspec": { 111 | "display_name": "Python 3", 112 | "language": "python", 113 | "name": "python3" 114 | }, 115 | "language_info": { 116 | "codemirror_mode": { 117 | "name": "ipython", 118 | "version": 3 119 | }, 120 | "file_extension": ".py", 121 | "mimetype": "text/x-python", 122 | "name": "python", 123 | "nbconvert_exporter": "python", 124 | "pygments_lexer": "ipython3", 125 | "version": "3.6.5" 126 | } 127 | }, 128 | "nbformat": 4, 129 | "nbformat_minor": 2 130 | } 131 | -------------------------------------------------------------------------------- /README.md: -------------------------------------------------------------------------------- 1 | 2 | # Python Library Examples 3 | 4 | Here you find easy copy-paste examples of my favourite Python libraries. 5 | 6 | ## Builtin modules 7 | 8 | | package | description | 9 | |---------|-------------| 10 | | [itertools](itertools/) | working with lists and generators | 11 | | [math](math/) | mathematical functions | 12 | | [os](os/) | working with files and directories | 13 | | [random](random/) | generating random numbers | 14 | | [re](re/) | pattern matching in text | 15 | | [sys](sys/) | settings of the Python interpreter | 16 | | [time](time/) | working with dates and times | 17 | 18 | ## Reading and Writing Files 19 | 20 | | package | description | 21 | |---------|-------------| 22 | | [json](json/) | read/write JSON files | 23 | | [pydocx](pydocx/) | read Word documents | 24 | | [pypdf2](pypdf2/) | merge PDF documents | 25 | | [xml](xml/) | parse XML files | 26 | | [zipfile](zipfile/) | read and write .zip files | 27 | | [librosa (external)](https://librosa.org/) | process and analyze sound and music | 28 | 29 | 30 | ## Data Science 31 | 32 | | package | description | 33 | |---------|-------------| 34 | | [numpy](numpy/) | fast numerical calculations | 35 | | [pandas](pandas/) | analyze tabular data | 36 | | [scipy](scipy/) | scientific calculations | 37 | | [scikit-learn](sklearn/) | Machine Learning | 38 | | [RPy2](RPy/) | Use R functions from within Python | 39 | | [PuLP](PuLP/) | linear equation solver | 40 | | [fuzzywuzzy](fuzzywuzzy/) | fuzzy text search | 41 | | [vader](vader/) | sentiment analysis | 42 | | [statsmodels (external)](http://statsmodels.sourceforge.net/) | Hypothesis tests and statistical models | 43 | 44 | 45 | ## Plotting 46 | 47 | | package | description | 48 | |---------|-------------| 49 | | [folium](folium/) | drawing maps | 50 | | [matplotlib](matplotlib/) | plotting diagrams | 51 | | [NetworkX](networkx/) | analyze and plot graphs | 52 | | [wordcloud](wordcloud/) | plot word clouds | 53 | | [seaborn (external)](https://seaborn.pydata.org/) | a more powerful interface for matplotlib | 54 | | [altair (external)](https://altair-viz.github.io/) | plotting library with JSON backend | 55 | | [geopandas (external)](http://geopandas.org/) | plot DataFrames on maps | 56 | | [panel (external)](http://panel.pyviz.org/) | create interactive plots | 57 | 58 | ## Image Processing 59 | 60 | | package | description | 61 | |---------|-------------| 62 | | [pillow - image manipulation](pillow/) | | 63 | | [ipythonblocks](ipythonblocks/) | drawing blocks in notebooks | 64 | | [pytesseract](pytesseract/) | extract text from images (OCR) | 65 | | [scikit-image](scikit_image/) | Advanced image processing | 66 | | [CV2 (external)](https://docs.opencv.org/3.0-beta/doc/py_tutorials/py_tutorials.html) | processing camera images and movies | 67 | 68 | ## Databases 69 | 70 | | package | description | 71 | |---------|-------------| 72 | | [pymongo](pymongo/) | adapter for the MongoDB NoSQL database | 73 | | [sqlite3](sqlite3/) | a simple SQL database | 74 | 75 | ## Web programming 76 | 77 | | package | description | 78 | |---------|-------------| 79 | | [BeautifulSoup4](beautiful_soup/) | parse HTML pages | 80 | | [email](email/) | send emails | 81 | | [flask](flask/) | a simple web server | 82 | | [requests](requests/) | retrieve web pages | 83 | | [OAUTH - authentication](oauth_git/) | authentication | 84 | | [scrapy (external)](http://scrapy.org/) | collect data from entire websites | 85 | 86 | ## User Interfaces 87 | 88 | | package | description | 89 | |---------|-------------| 90 | | [curses](curses/) | interactive terminal interface | 91 | | [tkinter](tkinter/) | graphical user interfaces | 92 | | [tqdm](tqdm/) | draw progress bars | 93 | 94 | 95 | ## More Libraries 96 | 97 | * [Awesome Python](https://awesome-python.com/) is a curated list of Python libraries and tools. 98 | 99 | ## Source 100 | 101 | [github.com/krother/Python3_Package_Examples](https://github.com/krother/Python3_Package_Examples) 102 | 103 | ## Acknowledgements 104 | 105 | Thanks to Emely Henninger for finding a nasty bug in networkx! 106 | 107 | ## License 108 | 109 | © 2025 Dr. Kristian Rother (krother@academis.eu) 110 | 111 | The code is distributed under the conditions of the MIT License. See :::file LICENSE.TXT for details. 112 | -------------------------------------------------------------------------------- /pypdf2/extras/pdf2txt.py: -------------------------------------------------------------------------------- 1 | #!/usr/bin/env python 2 | 3 | """ 4 | Converts PDF text content (though not images containing text) to plain text, html, xml or "tags". 5 | """ 6 | import sys 7 | import logging 8 | import six 9 | import pdfminer.settings 10 | pdfminer.settings.STRICT = False 11 | import pdfminer.high_level 12 | import pdfminer.layout 13 | from pdfminer.image import ImageWriter 14 | 15 | 16 | def extract_text(files=[], outfile='-', 17 | _py2_no_more_posargs=None, # Bloody Python2 needs a shim 18 | no_laparams=False, all_texts=None, detect_vertical=None, # LAParams 19 | word_margin=None, char_margin=None, line_margin=None, boxes_flow=None, # LAParams 20 | output_type='text', codec='utf-8', strip_control=False, 21 | maxpages=0, page_numbers=None, password="", scale=1.0, rotation=0, 22 | layoutmode='normal', output_dir=None, debug=False, 23 | disable_caching=False, **other): 24 | if _py2_no_more_posargs is not None: 25 | raise ValueError("Too many positional arguments passed.") 26 | if not files: 27 | raise ValueError("Must provide files to work upon!") 28 | 29 | # If any LAParams group arguments were passed, create an LAParams object and 30 | # populate with given args. Otherwise, set it to None. 31 | if not no_laparams: 32 | laparams = pdfminer.layout.LAParams() 33 | for param in ("all_texts", "detect_vertical", "word_margin", "char_margin", "line_margin", "boxes_flow"): 34 | paramv = locals().get(param, None) 35 | if paramv is not None: 36 | setattr(laparams, param, paramv) 37 | else: 38 | laparams = None 39 | 40 | imagewriter = None 41 | if output_dir: 42 | imagewriter = ImageWriter(output_dir) 43 | 44 | if output_type == "text" and outfile != "-": 45 | for override, alttype in ( (".htm", "html"), 46 | (".html", "html"), 47 | (".xml", "xml"), 48 | (".tag", "tag") ): 49 | if outfile.endswith(override): 50 | output_type = alttype 51 | 52 | if outfile == "-": 53 | outfp = sys.stdout 54 | if outfp.encoding is not None: 55 | codec = 'utf-8' 56 | else: 57 | outfp = open(outfile, "wb") 58 | 59 | 60 | for fname in files: 61 | with open(fname, "rb") as fp: 62 | pdfminer.high_level.extract_text_to_fp(fp, **locals()) 63 | return outfp 64 | 65 | # main 66 | def main(args=None): 67 | import argparse 68 | P = argparse.ArgumentParser(description=__doc__) 69 | P.add_argument("files", type=str, default=None, nargs="+", help="Files to process.") 70 | P.add_argument("-d", "--debug", default=False, action="store_true", help="Debug output.") 71 | P.add_argument("-p", "--pagenos", type=str, help="Comma-separated list of page numbers to parse. Included for legacy applications, use -P/--page-numbers for more idiomatic argument entry.") 72 | P.add_argument("--page-numbers", type=int, default=None, nargs="+", help="Alternative to --pagenos with space-separated numbers; supercedes --pagenos where it is used.") 73 | P.add_argument("-m", "--maxpages", type=int, default=0, help = "Maximum pages to parse") 74 | P.add_argument("-P", "--password", type=str, default="", help = "Decryption password for PDF") 75 | P.add_argument("-o", "--outfile", type=str, default="-", help="Output file (default/'-' is stdout)") 76 | P.add_argument("-t", "--output_type", type=str, default="text", help = "Output type: text|html|xml|tag (default is text)") 77 | P.add_argument("-c", "--codec", type=str, default="utf-8", help = "Text encoding") 78 | P.add_argument("-s", "--scale", type=float, default=1.0, help = "Scale") 79 | P.add_argument("-A", "--all-texts", default=None, action="store_true", help="LAParams all texts") 80 | P.add_argument("-V", "--detect-vertical", default=None, action="store_true", help="LAParams detect vertical") 81 | P.add_argument("-W", "--word-margin", type=float, default=None, help = "LAParams word margin") 82 | P.add_argument("-M", "--char-margin", type=float, default=None, help = "LAParams char margin") 83 | P.add_argument("-L", "--line-margin", type=float, default=None, help = "LAParams line margin") 84 | P.add_argument("-F", "--boxes-flow", type=float, default=None, help = "LAParams boxes flow") 85 | P.add_argument("-Y", "--layoutmode", default="normal", type=str, help="HTML Layout Mode") 86 | P.add_argument("-n", "--no-laparams", default=False, action="store_true", help = "Pass None as LAParams") 87 | P.add_argument("-R", "--rotation", default=0, type=int, help = "Rotation") 88 | P.add_argument("-O", "--output-dir", default=None, help="Output directory for images") 89 | P.add_argument("-C", "--disable-caching", default=False, action="store_true", help="Disable caching") 90 | P.add_argument("-S", "--strip-control", default=False, action="store_true", help="Strip control in XML mode") 91 | A = P.parse_args(args=args) 92 | 93 | if A.page_numbers: 94 | A.page_numbers = set([x-1 for x in A.page_numbers]) 95 | if A.pagenos: 96 | A.page_numbers = set([int(x)-1 for x in A.pagenos.split(",")]) 97 | 98 | imagewriter = None 99 | if A.output_dir: 100 | imagewriter = ImageWriter(A.output_dir) 101 | 102 | if six.PY2 and sys.stdin.encoding: 103 | A.password = A.password.decode(sys.stdin.encoding) 104 | 105 | if A.output_type == "text" and A.outfile != "-": 106 | for override, alttype in ( (".htm", "html"), 107 | (".html", "html"), 108 | (".xml", "xml" ), 109 | (".tag", "tag" ) ): 110 | if A.outfile.endswith(override): 111 | A.output_type = alttype 112 | 113 | if A.outfile == "-": 114 | outfp = sys.stdout 115 | if outfp.encoding is not None: 116 | # Why ignore outfp.encoding? :-/ stupid cathal? 117 | A.codec = 'utf-8' 118 | else: 119 | outfp = open(A.outfile, "wb") 120 | 121 | ## Test Code 122 | outfp = extract_text(**vars(A)) 123 | outfp.close() 124 | return 0 125 | 126 | 127 | if __name__ == '__main__': sys.exit(main()) 128 | -------------------------------------------------------------------------------- /tkinter/titanic_sinks.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 19 | 21 | 24 | 32 | 33 | 34 | 53 | 55 | 56 | 58 | image/svg+xml 59 | 61 | 62 | 63 | 64 | 65 | 69 | 78 | 84 | 87 | 93 | 98 | 99 | 101 | 107 | 112 | 113 | 116 | 122 | 127 | 128 | 131 | 137 | 142 | 143 | 148 | 154 | 155 | 163 | 172 | muahaha 194 | 201 | 202 | 203 | -------------------------------------------------------------------------------- /PuLP/BricksLinear.ipynb: -------------------------------------------------------------------------------- 1 | { 2 | "cells": [ 3 | { 4 | "cell_type": "markdown", 5 | "metadata": {}, 6 | "source": [ 7 | "# Bricks\n", 8 | "*a linear optimization problem solved with PuLP*" 9 | ] 10 | }, 11 | { 12 | "cell_type": "markdown", 13 | "metadata": {}, 14 | "source": [ 15 | "## Problem Description\n", 16 | "\n", 17 | "We want to place a series of colored bricks in a N x M box\n", 18 | "\n", 19 | "![Bricks](bricks.png)" 20 | ] 21 | }, 22 | { 23 | "cell_type": "markdown", 24 | "metadata": {}, 25 | "source": [ 26 | "The bricks need to be placed according the following rules:\n", 27 | "\n", 28 | "* all bricks with the same colour should end up in the same column\n", 29 | "* if this is not possible, the rightmost column of one colour should be filled up first\n", 30 | "* bricks of one colour should be as close to each other on the x-axis as possible\n", 31 | "\n", 32 | "A possible solution could look like this:\n", 33 | "\n", 34 | "![solution](bricks_solution.png)\n", 35 | "\n", 36 | "This notebook shows how to solve this problem using the **linear equation solver PuLP**." 37 | ] 38 | }, 39 | { 40 | "cell_type": "markdown", 41 | "metadata": {}, 42 | "source": [ 43 | "## Preparations\n", 44 | "\n", 45 | "First, we define the bricks and their colours in Python:" 46 | ] 47 | }, 48 | { 49 | "cell_type": "code", 50 | "execution_count": 1, 51 | "metadata": { 52 | "collapsed": false 53 | }, 54 | "outputs": [], 55 | "source": [ 56 | "bricks = ['a1', 'a2', 'a3', 'b1', 'b2', 'c1', 'c2', 'c3', 'c4', 'd1', 'd2', 'e1']" 57 | ] 58 | }, 59 | { 60 | "cell_type": "markdown", 61 | "metadata": {}, 62 | "source": [ 63 | "We also define the size of the box to stack bricks in. A list of positions will help us later." 64 | ] 65 | }, 66 | { 67 | "cell_type": "code", 68 | "execution_count": 2, 69 | "metadata": { 70 | "collapsed": true 71 | }, 72 | "outputs": [], 73 | "source": [ 74 | "XSIZE = 4\n", 75 | "YSIZE = 3\n", 76 | "positions = [(x,y) for x in range(XSIZE) for y in range(YSIZE)]" 77 | ] 78 | }, 79 | { 80 | "cell_type": "markdown", 81 | "metadata": {}, 82 | "source": [ 83 | "## Modeling a Linear Equation System\n", 84 | "To model our problem using **PuLP**, we need to perform four steps:\n", 85 | "\n", 86 | "1. Define the model variables\n", 87 | "2. Define the optimization function\n", 88 | "3. Add linear constraints\n", 89 | "4. Run the solver\n" 90 | ] 91 | }, 92 | { 93 | "cell_type": "markdown", 94 | "metadata": {}, 95 | "source": [ 96 | "### Step 1: Define the model variables\n", 97 | "\n", 98 | "Our model variable will be a binary matrix with four dimensions. The first two dimensions are quite obvious: each space in the box has its own **x, y** position in the matrix. The third dimension are the bricks **b** themselves. We use them to specify, which brick occupies a certain space. \n", 99 | "\n", 100 | "The fourth dimension is probably the least obvious: It is the column **rb** in which bricks of one colour should be placed. We use it to link bricks of the same colour together." 101 | ] 102 | }, 103 | { 104 | "cell_type": "code", 105 | "execution_count": 3, 106 | "metadata": { 107 | "collapsed": false 108 | }, 109 | "outputs": [], 110 | "source": [ 111 | "from pulp import *\n", 112 | "\n", 113 | "v = LpVariable.dicts(\"bricks\", (range(XSIZE), range(YSIZE), bricks, range(XSIZE)), \\\n", 114 | " lowBound = 0, upBound = 1, cat = LpInteger)" 115 | ] 116 | }, 117 | { 118 | "cell_type": "markdown", 119 | "metadata": {}, 120 | "source": [ 121 | "#### Why don't we simply assign each brick a number instead of an extra dimension?\n", 122 | "Yes, it would be nice to cut out an extra dimension from the matrix. However, we cannot discretisize numbers in a linear equation system (e.g. say *\"If x is 3 do this, if x is 4 do something else\"*). I find this quite a strong limitation, and the binary matrix is the proper way to say *\"I have discrete bricks a, b, c.. in my system\".*.\n", 123 | "\n", 124 | "#### I don't understand why range(XSIZE) appears twice.\n", 125 | "Each brick has two X values assigned: the first is the column **x** in which the brick actually is, the second is the rightmost column **rb** in which bricks of this colour should gather. We need this second value to implement the second and third rule above." 126 | ] 127 | }, 128 | { 129 | "cell_type": "markdown", 130 | "metadata": {}, 131 | "source": [ 132 | "### Step 2: Define the Optimization Function\n", 133 | "\n", 134 | "We first tell PuLP that we have something to minimize:" 135 | ] 136 | }, 137 | { 138 | "cell_type": "code", 139 | "execution_count": 4, 140 | "metadata": { 141 | "collapsed": true 142 | }, 143 | "outputs": [], 144 | "source": [ 145 | "m = LpProblem(\"Bricks\", LpMinimize)" 146 | ] 147 | }, 148 | { 149 | "cell_type": "markdown", 150 | "metadata": {}, 151 | "source": [ 152 | "We want to tell PuLP to minimize the distance bricks have from their colleagues to the right. For that, we need to construct a penalty matrix first. We say that any block in column *x* that ought to be in colum *rb* has a penalty of `10` for each column in between:" 153 | ] 154 | }, 155 | { 156 | "cell_type": "code", 157 | "execution_count": 5, 158 | "metadata": { 159 | "collapsed": false 160 | }, 161 | "outputs": [ 162 | { 163 | "data": { 164 | "text/plain": [ 165 | "{(0, 0): 0,\n", 166 | " (0, 1): 10,\n", 167 | " (0, 2): 20,\n", 168 | " (0, 3): 30,\n", 169 | " (1, 0): 10,\n", 170 | " (1, 1): 0,\n", 171 | " (1, 2): 10,\n", 172 | " (1, 3): 20,\n", 173 | " (2, 0): 20,\n", 174 | " (2, 1): 10,\n", 175 | " (2, 2): 0,\n", 176 | " (2, 3): 10,\n", 177 | " (3, 0): 30,\n", 178 | " (3, 1): 20,\n", 179 | " (3, 2): 10,\n", 180 | " (3, 3): 0}" 181 | ] 182 | }, 183 | "execution_count": 5, 184 | "metadata": {}, 185 | "output_type": "execute_result" 186 | } 187 | ], 188 | "source": [ 189 | "penalties = {}\n", 190 | "for x in range(XSIZE):\n", 191 | " for rb in range(XSIZE):\n", 192 | " penalties[(x, rb)] = 10 * abs(rb - x)\n", 193 | "penalties" 194 | ] 195 | }, 196 | { 197 | "cell_type": "markdown", 198 | "metadata": {}, 199 | "source": [ 200 | "In a linear equation system, everything needs to be composed of terms like `a*x` that are added together. This is why you will see **sum** symbols frequently. Our minimization function *m* is:\n", 201 | "\n", 202 | "$$m(v) = \\sum_{x,y,b,rb}penalties_{x,rb} * v_{x,y,n,rb}$$ \n", 203 | "\n", 204 | "In PuLP, this minimization function is formulated as a sum with a scary-looking list comprehension:" 205 | ] 206 | }, 207 | { 208 | "cell_type": "code", 209 | "execution_count": 6, 210 | "metadata": { 211 | "collapsed": false 212 | }, 213 | "outputs": [], 214 | "source": [ 215 | "m += lpSum([penalties[(x,rb)] * v[x][y][b][rb] for x,y in positions for b in bricks for rb in range(XSIZE)])" 216 | ] 217 | }, 218 | { 219 | "cell_type": "markdown", 220 | "metadata": {}, 221 | "source": [ 222 | "### Step 3: Adding linear constraints\n", 223 | "Now we specify additional rules and conditions. We need to formulate these in the linear form as well. More sums, that is.\n", 224 | "\n", 225 | "#### Condition 1: One brick per position\n", 226 | "First, we want to specify that there can be only one brick per position. In math notation this is:\n", 227 | "\n", 228 | "$$\\sum_{b,rb} v_{x,y,b,rb} <= 1$$\n", 229 | "\n", 230 | "This condition must be true for each possible **x** and **y** value.\n", 231 | "\n", 232 | "In Python, it looks similar if you are familiar with **list comprehensions**." 233 | ] 234 | }, 235 | { 236 | "cell_type": "code", 237 | "execution_count": 7, 238 | "metadata": { 239 | "collapsed": false 240 | }, 241 | "outputs": [], 242 | "source": [ 243 | "for x, y in positions:\n", 244 | " m += lpSum([v[x][y][b][rb] for b in bricks for rb in range(XSIZE)]) <= 1" 245 | ] 246 | }, 247 | { 248 | "cell_type": "markdown", 249 | "metadata": {}, 250 | "source": [ 251 | "#### Condition 2: One position per brick\n", 252 | "Likewise, each brick can have only one position. This should be obvious, but given the binary matrix we still have to say it explicitly:" 253 | ] 254 | }, 255 | { 256 | "cell_type": "code", 257 | "execution_count": 8, 258 | "metadata": { 259 | "collapsed": false 260 | }, 261 | "outputs": [], 262 | "source": [ 263 | "for b in bricks:\n", 264 | " m += lpSum([v[x][y][b][rb] for x, y in positions for rb in range(XSIZE)]) == 1" 265 | ] 266 | }, 267 | { 268 | "cell_type": "markdown", 269 | "metadata": {}, 270 | "source": [ 271 | "#### Condition 3: no bricks right of the rb column\n", 272 | "We want to implement the column **rb** (our fourth dimension) as a hard boundary. So no bricks should appear right of it. Hopefully this results in bricks stackin up in the **rb** column, and those left over left of it.\n", 273 | "\n", 274 | "We do this by adding a constraint that certain columns need to be zero." 275 | ] 276 | }, 277 | { 278 | "cell_type": "code", 279 | "execution_count": 9, 280 | "metadata": { 281 | "collapsed": true 282 | }, 283 | "outputs": [], 284 | "source": [ 285 | "for x in range(XSIZE):\n", 286 | " for rb in range(XSIZE):\n", 287 | " if x > rb:\n", 288 | " m += lpSum([v[x][y][b][rb] for y in range(YSIZE) for b in bricks]) == 0" 289 | ] 290 | }, 291 | { 292 | "cell_type": "markdown", 293 | "metadata": {}, 294 | "source": [ 295 | "The art of formulating a linear problem with PuLP is to know, when to put a for loop into the sum (corresponding to an index in a sum symbol) or outside (corresponding to having multiple sums)." 296 | ] 297 | }, 298 | { 299 | "cell_type": "markdown", 300 | "metadata": {}, 301 | "source": [ 302 | "#### Condition 4: bricks of same colour stick together\n", 303 | "This was the tough one while developing the example. We tell our equation system that any two bricks of the same colour must have the same right boundary **rb**. This way, we enforce that the same penalties in the minimization apply to one colour.\n", 304 | "\n", 305 | "For the implementation, we need to add a separate constraint for each pair of bricks. For each pair and rb value, the corresponding values in **v** are either both 1 or both 0, which we can check by calculating their difference:" 306 | ] 307 | }, 308 | { 309 | "cell_type": "code", 310 | "execution_count": 10, 311 | "metadata": { 312 | "collapsed": true 313 | }, 314 | "outputs": [], 315 | "source": [ 316 | "pairs = [('a1', 'a2'), ('a1', 'a3'), ('a2', 'a3'), \n", 317 | " ('b1', 'b2'),\n", 318 | " ('c1', 'c2'), ('c1', 'c3'), ('c2', 'c3'), ('c1', 'c4'), ('c2', 'c4'), ('c3', 'c4'),\n", 319 | " ('d1', 'd2')\n", 320 | " ]\n", 321 | "\n", 322 | "for b1, b2 in pairs:\n", 323 | " for rb in range(XSIZE):\n", 324 | " m += lpSum([v[x][y][b1][rb] for x,y in positions] + [-v[x][y][b2][rb] for x,y in positions]) == 0" 325 | ] 326 | }, 327 | { 328 | "cell_type": "markdown", 329 | "metadata": {}, 330 | "source": [ 331 | "#### Remark\n", 332 | "You might realize two things from this:\n", 333 | "* If you were to implement this as an algorithm, it would be **much easier**. But in a linear system it is not\n", 334 | "* The number of constraints explodes if you have more bricks or a bigger box. The complexity is something like $O(b^2 * x)$, which certainly is bad news." 335 | ] 336 | }, 337 | { 338 | "cell_type": "markdown", 339 | "metadata": {}, 340 | "source": [ 341 | "### Step 4: Run the Solver\n", 342 | "Finally we can ask PuLP to solve the problem:" 343 | ] 344 | }, 345 | { 346 | "cell_type": "code", 347 | "execution_count": 11, 348 | "metadata": { 349 | "collapsed": false 350 | }, 351 | "outputs": [ 352 | { 353 | "name": "stdout", 354 | "output_type": "stream", 355 | "text": [ 356 | "Status: Optimal\n" 357 | ] 358 | } 359 | ], 360 | "source": [ 361 | "m.solve()\n", 362 | "print(\"Status:\", LpStatus[m.status])" 363 | ] 364 | }, 365 | { 366 | "cell_type": "markdown", 367 | "metadata": {}, 368 | "source": [ 369 | "## Display the result\n", 370 | "Lets see whether it really worked:" 371 | ] 372 | }, 373 | { 374 | "cell_type": "code", 375 | "execution_count": 12, 376 | "metadata": { 377 | "collapsed": false 378 | }, 379 | "outputs": [ 380 | { 381 | "name": "stdout", 382 | "output_type": "stream", 383 | "text": [ 384 | "b2[0]\ta3[1]\td1[2]\tc1[3]\t\n", 385 | "e1[0]\ta1[1]\td2[2]\tc2[3]\t\n", 386 | "b1[0]\ta2[1]\tc3[3]\tc4[3]\t\n" 387 | ] 388 | } 389 | ], 390 | "source": [ 391 | "for y in range(YSIZE):\n", 392 | " row = \"\"\n", 393 | " for x in range(XSIZE):\n", 394 | " for b in bricks:\n", 395 | " for rb in range(XSIZE):\n", 396 | " val = value(v[x][y][b][rb])\n", 397 | " if val == 1:\n", 398 | " row += '{}[{}]'.format(b, rb)\n", 399 | " row += '\\t'\n", 400 | " print(row)" 401 | ] 402 | }, 403 | { 404 | "cell_type": "markdown", 405 | "metadata": { 406 | "collapsed": true 407 | }, 408 | "source": [ 409 | "Which is one of the possible solutions." 410 | ] 411 | }, 412 | { 413 | "cell_type": "code", 414 | "execution_count": null, 415 | "metadata": { 416 | "collapsed": true 417 | }, 418 | "outputs": [], 419 | "source": [] 420 | } 421 | ], 422 | "metadata": { 423 | "kernelspec": { 424 | "display_name": "Python 3", 425 | "language": "python", 426 | "name": "python3" 427 | }, 428 | "language_info": { 429 | "codemirror_mode": { 430 | "name": "ipython", 431 | "version": 3 432 | }, 433 | "file_extension": ".py", 434 | "mimetype": "text/x-python", 435 | "name": "python", 436 | "nbconvert_exporter": "python", 437 | "pygments_lexer": "ipython3", 438 | "version": "3.4.0" 439 | } 440 | }, 441 | "nbformat": 4, 442 | "nbformat_minor": 0 443 | } 444 | -------------------------------------------------------------------------------- /PuLP/bricks.svg: -------------------------------------------------------------------------------- 1 | 2 | 3 | 4 | 18 | 20 | 38 | 40 | 41 | 43 | image/svg+xml 44 | 46 | 47 | 48 | 49 | 50 | 54 | 64 | 74 | 84 | 94 | 104 | 114 | 124 | 134 | 144 | 154 | 164 | 174 | 184 | 190 | 197 | 204 | 211 | 218 | 225 | 232 | 239 | 246 | 253 | 260 | 267 | 274 | 275 | 285 | 291 | 298 | 305 | 312 | 319 | 326 | 333 | 340 | 347 | 354 | 361 | 368 | 375 | 376 | 386 | 396 | 401 | 411 | 421 | 431 | 432 | 442 | 452 | 462 | 472 | 482 | 492 | 502 | 503 | 504 | --------------------------------------------------------------------------------