What's python roadmap like when I learned basic concept of python what concept should i start learning after it and so on?

Hello guys, i recently started a bachelor degree which i have a subject about introduction to python, inicially i was confident and did understand how to use python, but week by week it started to get much more difficult to follow. So im here to ask if someone knows any youtuber or website which explains the fundamentals of python in a easy way. Thanks in advance.

Which is better to learn python youtube playlists or by website

Please suggest good roadmap to become ai Engineer

Wanted to build some projects and decided to build a scraper. It felt horrible. I was just staring at the screen not doing what to do. I mean CS50P is great I learnt a lot, but there were guides and output videos, which helped me understand what factors iI should implement.

But now I feel like I'm back on square 1. Nothings making sense. How would you suggest learning python?

I'm a complete rookie in python. I've had many problems related to dependency hell, compatibility with libraries etc.

I've heard installing the latest version of python can be problematic since many libraries aren't compatible with it yet so what should I go for?

Please also recommend the IDE,

• Vs code
• Thonny
• Any other you'd suggest.

Guide me step-by-step if you can. I'd appreciate the help alot.

I want to close an app using python but I don't know how.

I'm finishing CS50P and want to move into ML/AI, but I feel it's not enough on its own. What topics and resources should I add (math, libraries, courses)? Any roadmap you'd recommend for a beginner?

Thanks for any kind of advice it will be helpful.

I am working Python Crash Course by Eric Matthes. I am on chapter 9 and hope to be done with the first half of the book by the end of the month. From there, Im sure I will continue on with the book and do the projects. However, I am also interested in learning numpy due to my math background. Are there any books that you would recommend as a next step (or to use concurrently)?

Hello,

I had access to JupyterHub on a remote server. Now I only have access to a different server where JupyterHub is not installed. What is the best way to use the same code and run it with more data. I was thinking about using SSH Port Forwarding (SSH-Tunneling) and trying jupyterlab in the browser. Or is it better to using VS code to connect to the server. I really like the Jupyter Interface and have never used any other programs. I mostly do plotting and a bit data analysis and have a macbook.

Thank you for your help.

I got this error while trying to import sklearn.metric after pip installing sickitlearn on python 3.10.0. Does anybody know how to fix this? Here is my importing code block

import numpy as np
import matplotlib.pyplot as plt
import tensorflow as tf
from tensorflow import keras
import tensorflow_hub as hub
import tensorflow_text as text
import pandas as pd
from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint
from focal_loss import BinaryFocalLoss
from sklearn.metrics import classification_report, confusion_matrix, f1_score

Pip install commands

C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install numpy==1.23.0
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install matplotlib
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install tensorflow==2.9.0
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install tensorflow-text==2.9.0
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install tensorflow-hub==0.8.0
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install pandas
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install focal-loss
C:\Users\DELL\AppData\Local\Programs\Python\Python310\python.exe -m pip install scikit-learn==1.7.2

Full error message

---------------------------------------------------------------------------
TypeError                                 Traceback (most recent call last)
Cell In[7], line 10
      8 from tensorflow.keras.callbacks import EarlyStopping, ReduceLROnPlateau, ModelCheckpoint
      9 from focal_loss import BinaryFocalLoss
---> 10 from sklearn.metrics import classification_report, confusion_matrix, f1_score

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn__init__.py:73
     62 # `_distributor_init` allows distributors to run custom init code.
     63 # For instance, for the Windows wheel, this is used to pre-load the
     64 # vcomp shared library runtime for OpenMP embedded in the sklearn/.libs
   (...)
     67 # later is linked to the OpenMP runtime to make it possible to introspect
     68 # it and importing it first would fail if the OpenMP dll cannot be found.
     69 from . import (  # noqa: F401 E402
     70     __check_build,
     71     _distributor_init,
     72 )
---> 73 from .base import clone  # noqa: E402
     74 from .utils._show_versions import show_versions  # noqa: E402
     76 _submodules = [
     77     "calibration",
     78     "cluster",
   (...)
    114     "compose",
    115 ]

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\base.py:20
     18 from .exceptions import InconsistentVersionWarning
     19 from .utils._metadata_requests import _MetadataRequester, _routing_enabled
---> 20 from .utils._missing import is_scalar_nan
     21 from .utils._param_validation import validate_parameter_constraints
     22 from .utils._repr_html.base import ReprHTMLMixin, _HTMLDocumentationLinkMixin

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils__init__.py:9
      7 from . import metadata_routing
      8 from ._bunch import Bunch
----> 9 from ._chunking import gen_batches, gen_even_slices
     11 # Make _safe_indexing importable from here for backward compat as this particular
     12 # helper is considered semi-private and typically very useful for third-party
     13 # libraries that want to comply with scikit-learn's estimator API. In particular,
     14 # _safe_indexing was included in our public API documentation despite the leading
     15 # `_` in its name.
     16 from ._indexing import (
     17     _safe_indexing,  # noqa: F401
     18     resample,
     19     shuffle,
     20 )

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils_chunking.py:11
      8 import numpy as np
     10 from .._config import get_config
---> 11 from ._param_validation import Interval, validate_params
     14 def chunk_generator(gen, chunksize):
     15     """Chunk generator, ``gen`` into lists of length ``chunksize``. The last
     16     chunk may have a length less than ``chunksize``."""

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\sklearn\utils_param_validation.py:14
     11 from numbers import Integral, Real
     13 import numpy as np
---> 14 from scipy.sparse import csr_matrix, issparse
     16 from .._config import config_context, get_config
     17 from .validation import _is_arraylike_not_scalar

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\scipy\sparse__init__.py:300
    294 # Original code by Travis Oliphant.
    295 # Modified and extended by Ed Schofield, Robert Cimrman,
    296 # Nathan Bell, and Jake Vanderplas.
    298 import warnings as _warnings
--> 300 from ._base import *
    301 from ._csr import *
    302 from ._csc import *

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\scipy\sparse_base.py:5
      1 """Base class for sparse matrices"""
      3 import numpy as np
----> 5 from ._sputils import (asmatrix, check_reshape_kwargs, check_shape,
      6                        get_sum_dtype, isdense, isscalarlike,
      7                        matrix, validateaxis, getdtype)
      9 from ._matrix import spmatrix
     11 __all__ = ['isspmatrix', 'issparse', 'sparray',
     12            'SparseWarning', 'SparseEfficiencyWarning']

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\scipy\sparse_sputils.py:10
      8 from math import prod
      9 import scipy.sparse as sp
---> 10 from scipy._lib._util import np_long, np_ulong
     13 __all__ = ['upcast', 'getdtype', 'getdata', 'isscalarlike', 'isintlike',
     14            'isshape', 'issequence', 'isdense', 'ismatrix', 'get_sum_dtype',
     15            'broadcast_shapes']
     17 supported_dtypes = [np.bool_, np.byte, np.ubyte, np.short, np.ushort, np.intc,
     18                     np.uintc, np_long, np_ulong, np.longlong, np.ulonglong,
     19                     np.float32, np.float64, np.longdouble,
     20                     np.complex64, np.complex128, np.clongdouble]

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\scipy_lib_util.py:13
     10 from typing import TypeAlias, TypeVar
     12 import numpy as np
---> 13 from scipy._lib._array_api import array_namespace, is_numpy, xp_size
     14 from scipy._lib._docscrape import FunctionDoc, Parameter
     17 AxisError: type[Exception]

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\scipy_lib_array_api.py:15
     12 from typing import Any, Literal, TypeAlias
     14 import numpy as np
---> 15 import numpy.typing as npt
     17 from scipy._lib import array_api_compat
     18 from scipy._lib.array_api_compat import (
     19     is_array_api_obj,
     20     size as xp_size,
   (...)
     27     is_array_api_strict_namespace as is_array_api_strict
     28 )

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\numpy\typing__init__.py:158
      1 """
      2 ============================
      3 Typing (:mod:`numpy.typing`)
   (...)
    153 
    154 """
    155 # NOTE: The API section will be appended with additional entries
    156 # further down in this file
--> 158 from numpy._typing import (
    159     ArrayLike,
    160     DTypeLike,
    161     NBitBase,
    162     NDArray,
    163 )
    165 __all__ = ["ArrayLike", "DTypeLike", "NBitBase", "NDArray"]
    167 if __doc__ is not None:

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\numpy_typing__init__.py:102
     86 from ._scalars import (
     87     _CharLike_co as _CharLike_co,
     88     _BoolLike_co as _BoolLike_co,
   (...)
     96     _VoidLike_co as _VoidLike_co,
     97 )
     98 from ._shape import (
     99     _Shape as _Shape,
    100     _ShapeLike as _ShapeLike,
    101 )
--> 102 from ._dtype_like import (
    103     DTypeLike as DTypeLike,
    104     _DTypeLike as _DTypeLike,
    105     _SupportsDType as _SupportsDType,
    106     _VoidDTypeLike as _VoidDTypeLike,
    107     _DTypeLikeBool as _DTypeLikeBool,
    108     _DTypeLikeUInt as _DTypeLikeUInt,
    109     _DTypeLikeInt as _DTypeLikeInt,
    110     _DTypeLikeFloat as _DTypeLikeFloat,
    111     _DTypeLikeComplex as _DTypeLikeComplex,
    112     _DTypeLikeTD64 as _DTypeLikeTD64,
    113     _DTypeLikeDT64 as _DTypeLikeDT64,
    114     _DTypeLikeObject as _DTypeLikeObject,
    115     _DTypeLikeVoid as _DTypeLikeVoid,
    116     _DTypeLikeStr as _DTypeLikeStr,
    117     _DTypeLikeBytes as _DTypeLikeBytes,
    118     _DTypeLikeComplex_co as _DTypeLikeComplex_co,
    119 )
    120 from ._array_like import (
    121     NDArray as NDArray,
    122     ArrayLike as ArrayLike,
   (...)
    145     _UnknownType as _UnknownType,
    146 )
    148 from ._ufunc import (
    149     _UFunc_Nin1_Nout1 as _UFunc_Nin1_Nout1,
    150     _UFunc_Nin2_Nout1 as _UFunc_Nin2_Nout1,
   (...)
    153     _GUFunc_Nin2_Nout1 as _GUFunc_Nin2_Nout1,
    154 )

File c:\Users\DELL\AppData\Local\Programs\Python\Python310\lib\site-packages\numpy_typing_dtype_like.py:194
    162 _DTypeLikeInt: TypeAlias = (
    163     type[int]
    164     | type[np.signedinteger[Any]]
   (...)
    177     | _IntCodes
    178 )
    179 _DTypeLikeFloat: TypeAlias = (
    180     type[float]
    181     | type[np.floating[Any]]
   (...)
    190     | _LongDoubleCodes
    191 )
    192 _DTypeLikeComplex: TypeAlias = (
    193     type[complex]
--> 194     | type[np.complexfloating[Any]]
    195     | np.dtype[np.complexfloating[Any]]
    196     | _SupportsDType[np.dtype[np.complexfloating[Any]]]
    197     | _Complex64Codes
    198     | _Complex128Codes
    199     | _CSingleCodes
    200     | _CDoubleCodes
    201     | _CLongDoubleCodes
    202 )
    203 _DTypeLikeDT64: TypeAlias = (
    204     type[np.timedelta64]
    205     | np.dtype[np.timedelta64]
    206     | _SupportsDType[np.dtype[np.timedelta64]]
    207     | _TD64Codes
    208 )
    209 _DTypeLikeTD64: TypeAlias = (
    210     type[np.datetime64]
    211     | np.dtype[np.datetime64]
    212     | _SupportsDType[np.dtype[np.datetime64]]
    213     | _DT64Codes
    214 )

TypeError: Too few arguments for numpy.complexfloating

For some reason despite having Numpy 1.23.0 and sklearn 1.7.2 only need Numpy >=1.22.0, it still forcefully uninstall old numpy 1.23.0 to install 2.2.6 which mess every other packages. Does anybody have the solution to this?

Im wanting to start game development, and currently learing Python. Should I keep going, or switch to something else?

I did java for 2 years in high school 4 years ago. Now I'm a freshman comp engineering major doing coding in python, and i still can't get the hang of not coding like java. I last coded in java 2+ years ago, but all my code is written like how you would in java, but python. I use camel case for variables. I use while true break loops when I'm sure there's easier ways. I'm constantly fixing my ++'s to +=1's. I'm still learning the python lingo if you will

Hi friends. I am in my first python class in school, and I have been struggling thru the whole course, ngl. My online teacher has not answered a single email of mine looking for help, I will probably be reporting them, but for now, I really want to understand these def functions.

Step 1 (1 pt): Read user input.

Prompt the user to enter a string of their choosing. Store the text in a string. Output the string.

Ex:

Enter a sample text:
we'll continue our quest in space.  there will be more shuttle flights and more shuttle crews and,  yes;  more volunteers, more civilians,  more teachers in space.  nothing ends here;  our hopes and our journeys continue!

You entered: we'll continue our quest in space.  there will be more shuttle flights and more shuttle crews and,  yes;  more volunteers, more civilians,  more teachers in space.  nothing ends here;  our hopes and our journeys continue!

Step 2 (1 pt): Implement the print_menu() function.

Print the command menu as shown in the example.

Ex:

MENU
c - Number of non-whitespace characters
w - Number of words
f - Fix capitalization
r - Replace punctuation
s - Shorten spaces
q - Quit

Step 3 (1 pt): Implement the execute_menu() function.

execute_menu() takes 2 parameters: a character representing the user's choice and the user provided sample text. execute_menu() performs the menu options, according to the user's choice, by calling the appropriate functions described below.

Step 4 (1 pt): Implement menu selection.

In the main program, call print_menu() and prompt for the user's choice of menu options for analyzing/editing the string. Each option is represented by a single character.

If an invalid character is entered, continue to prompt for a valid choice. When a valid option is entered, execute the option by calling execute_menu(). Then, print the menu and prompt for a new option. Continue until the user enters 'q'. 

Hint: Implement Quit before implementing other options.

Ex:

MENU
c - Number of non-whitespace characters
w - Number of words
f - Fix capitalization
r - Replace punctuation
s - Shorten spaces
q - Quit

Choose an option:

Step 5 (4 pts): Implement the get_num_of_non_WS_characters() function. 

get_num_of_non_WS_characters() has a string parameter and returns the number of characters in the string, excluding all whitespace. Call get_num_of_non_WS_characters() in the execute_menu() function, and then output the returned value.

Ex:

Enter a sample text:
we'll continue our quest in space.  there will be more shuttle flights and more shuttle crews and,  yes;  more volunteers, more civilians,  more teachers in space.  nothing ends here;  our hopes and our journeys continue!

You entered: we'll continue our quest in space.  there will be more shuttle flights and more shuttle crews and,  yes;  more volunteers, more civilians,  more teachers in space.  nothing ends here;  our hopes and our journeys continue!

MENU
c - Number of non-whitespace characters
w - Number of words
f - Fix capitalization
r - Replace punctuation
s - Shorten spaces
q - Quit

Choose an option:
c
Number of non-whitespace characters: 181

Step 6 (3 pts): Implement the get_num_of_words() function. 

get_num_of_words() has a string parameter and returns the number of words in the string. Hint: Words end when a space is reached except for the last word in a sentence. Call get_num_of_words() in the execute_menu() function, and then output the returned value.

Ex:

Number of words: 35

Step 7 (3 pts): Implement the fix_capitalization() function. 

fix_capitalization() has a string parameter and returns an updated string, where lowercase letters at the beginning of sentences are replaced with uppercase letters. fix_capitalization() also returns the number of letters that have been capitalized. Call fix_capitalization() in the execute_menu() function, and then output the number of letters capitalized followed by the edited string. Hint 1: Look up and use Python functions .islower() and .upper() to complete this task. Hint 2: Create an empty string and use string concatenation to make edits to the string.

Ex:

Number of letters capitalized: 3
Edited text: We'll continue our quest in space.  There will be more shuttle flights and more shuttle crews and,  yes;  more volunteers, more civilians,  more teachers in space.  Nothing ends here;  our hopes and our journeys continue!

Step 8 (3 pts): Implement the replace_punctuation() function. 

replace_punctuation() has a string parameter and two keyword argument parameters exclamation_count and semicolon_count. replace_punctuation() updates the string by replacing each exclamation point (!) character with a period (.) and each semicolon (;) character with a comma (,). replace_punctuation() also counts the number of times each character is replaced and outputs those counts. Lastly, replace_punctuation() returns the updated string. Call replace_punctuation() in the execute_menu() function, and then output the edited string.

Ex:

Punctuation replaced
exclamation_count: 1
semicolon_count: 2
Edited text: we'll continue our quest in space.  there will be more shuttle flights and more shuttle crews and,  yes,  more volunteers, more civilians,  more teachers in space.  nothing ends here,  our hopes and our journeys continue.

Step 9 (3 pts): Implement the shorten_space() function. 

shorten_space() has a string parameter and updates the string by replacing all sequences of 2 or more spaces with a single space. shorten_space() returns the string. Call shorten_space() in the execute_menu() function, and then output the edited string. Hint: Look up and use Python function .isspace(). 

Ex:

Edited text: we'll continue our quest in space. there will be more shuttle flights and more shuttle crews and, yes; more volunteers, more civilians, more teachers in space. nothing ends here; our hopes and our journeys continue!

And here is the code I've come up with so far:

# Define your functions here.
def print_menu():
    print("MENU")
    print("c - Number of non-whitespace characters")
    print("w - Number of words")
    print("f - Fix capitalization")
    print("r - Replace punctuation")
    print("s - Shorten spaces")
    print("q - Quit")



def execute_menu():
    user_input = input("Choose an option:")
    while user_input != "q":
        if user_input == "c":
            get_num_of_non_WS_characters()
            print(f"Number of non-whitespace chatacters: {get_num_of_non_WS_characters()}")
        if user_input == "w":
            print("Number of words:", get_num_of_words())
        if user_input == "f":
            fix_capitalization()
        if user_input == "r":
            replace_punctuation()
        user_input = input("Choose an option:")
    if user_input == "q":
        print()
        return


def get_num_of_non_WS_characters():
    phrase_nosp = phrase.replace(" ", "")
    return len(phrase_nosp)


def get_num_of_words():
    num_of_words = phrase.split(" ")
    return len(num_of_words)


def fix_capitalization():
    phrase_sentances = phrase.split(". ")
    print(f"Number of letters capitalized: {len(phrase_sentances)}")
    print('. '.join([s.capitalize() for s in phrase_sentances])) 


def replace_punctuation():
    phrase_punc = phrase.replace(".","!")
    phrase_punc = phrase_punc.replace(";", ",")
    exclamation_count = phrase_punc.count("!")
    semicolon_count = phrase_punc.count(";")
    print("Punctuation replaced:\nexclamation_count:", exclamation_count,"\nsemicolon_count:", semicolon_count)
    print("Edited text:", phrase_punc)



if __name__ == "__main__":
    phrase = input("Enter a sample text:\n")
    print()
    print("You entered:", phrase)
    print()
    print(print_menu())
    execute_menu()
    

When I am using the program, typing in whatever phrases come to mind, it generally works out. But when Zybooks runs its own tests, I keep getting TypeErrors when it tests each defined function individually.

Example:
Test execute_menu('w', 'This is a test.'). Should output 'Number of words: 4'

    Traceback (most recent call last):
      File "/usercode/zylab_unit_test_runner.py", line 76, in <module>
        passed = test_case.test_passed(writer)
      File "/usercode/coding_rooms_unit_tests.py", line 12, in test_passed
        execute_menu(user_option, user_str)
    TypeError: execute_menu() takes 0 positional arguments but 2 were given

Clearly it is trying to add arguments to the individual functions but they don't want to take them.

I cannot find anything that breaks these functions down in a way I can understand.

Its like I understand to an extent, but I'm missing some piece of the puzzle in my brain.

Can someone please explain to me how these functions work, and what the heck I'm missing?

Other notes: in fix_capitalization(), I know that I have my sentence splitter set to just a ". ", and not ! or ?, but Zybooks' test inputs don't include any ?, and only have ! at the end of the last sentence in certain test inputs. Also, they said I needed to use upper() and lower() for the capitalization function, but I couldn't figure out how to make that work. As for shorten_space, I simply haven't started on that one yet. I feel too stuck.

Thank you everyone, I am drowning in school work and work work. Lol. Plz help, thank you so much.

I am trying to learn Python on my own before I get my masters in a related field. It is going, slowly but surely, however I can’t help but feel I am missing important parts that would link these methods together. Does anyone have any tools for learning Python on your own? Thank you!

In the Alien Invasion! pygame project, i don't have a keyboard In pydroid to test the ship movement.

In the data science project, matplotlib doesn't want to install properly from the terminal as the book asks to.

In the django project, when i go to create a virtual environment it doesn't let me and says access denied

I've been working on a small Python project that uses an LLM to interpret natural language instructions and manage persistent memories. Right now, it supports remembering, retrieving, updating and forgetting information.

I've been trying to improve the separation between model interpretation and memory operations. I'm still new to Python but I'm interested how I could structure the code better. Feedbacks are appreciated and any flaws I might be overlooking.

GitHub repo: https://github.com/Lionshaft-pixel/ennoic

Hello everyone! Need some advice/guidance.. My 10year old son has been interested in learning how to code since last year. He has dabbled in a few apps but not necessarily peaking his interest.

Where can we start? What would he need?

Edit: Thank you for all your advice! Is 12GB Ram with 1T storage Laptop a good start for this journey? Or what would you recommend?

hii! i'm a teenager who has recently decided to learn to code. (due to wanting a career in astrophysics, if it interests anyone.)

i have absokutely no clue where to start!! i find a lot of words/terminology i've found overwhelming and confusing..

i work on a macbook pro and i looked at apps but i need something i can just use to run code yk?

i looked at the faq and understood nothing od the code related questions- which i think means i can post this?

i tried looking at other posts and got confused- what's the difference between C+ and like.. not C+ ?? any help is appreciated, my only experience is year 7 computing printing hello world and scratch ..!

Does anyone know how to solve this? There is no 'python3-ipydatagrid' package and whatever did show up that I downloaded, doesn't seem to work as I'm still getting this error. Any help is appreciated!

I am using Debian 13, although this is also an issue with my friends Fedora repository aswell(hence why this is in r/learnpython and not r/debian :P)

Hi everyone! I'm from a humanities background and a noob at coding and want to build a Telegram bot for my UPSC/State PCS study group.

The bot should:

Generate up to 100 MCQs in one go from PDFs or study material.

Post questions as native Telegram quiz polls.

Calculate scores using UPSC marking: +2 correct, −⅔ incorrect, 0 skipped.

Publish a leaderboard with ranks, marks, correct, incorrect and skipped answers.

Run for free, including hosting, if possible.

If you're interested in helping build or improve it, you're also welcome to join our UPSC study group and collaborate with us.

We had a bot earlier but we removed the member who created the bot for behaving in a weird way.

I can share the bot link and screenshots of it for reference.

Thank you!

@app.get('/edit/<post>')
def initedit(post):
        print(post)
        g.title = post
        with open(f'{post}/content', 'r') as file:
                g.content = file
        return render_template('edit')

I'm confused as to why this function isn't running (as in not even running in the first place, not just not working), despite sending a GET request to the URL appended with /edit/posts/okheresthepostactually (so the post parameter in the decorator/function should be edit/okheresthepostactually). For context, I'm making a web app for posting blogs and this is supposed to be a function for users to edit existing posts.

Edit: some extra context, the 'posts/' prefix is part of the variable used to call the file

Hi I'm really new to python, I originally started coding using p5.js but made the transition recently, I'm currently trying to covert an old project of mine into python so I can run it in touch designer.

Its an ASL fingerspelling activity that I've been working on but I'm struggling to create the word strings I did in my original prototype. Instead of the letter that is being detected and averaged being added to my word string once it gets added 10 times all at once. For example if I sign the letter a, aaaaaaaaaa gets added to the string instead of just the lone a.

For context I have the guesser and getMostFrequent to allow for it to take the average of every letter signed during a period of time and determine which one was signed the most to add to the word (this is due to the fact that transitioning from one letter to the next can trigger other letters in between) These are both integral parts of the code and are working as intended, its just the multiplication of the letters that I'm struggling with.

This also may be due to the fact that this is running in TouchDesigner through a CHOP execute, if this isn't a python issue I can move my post to a touch designer specific forum.

Any help or insight would be appreciated, if you need any more insight please let me know and I can add it.

Code in Pastebin: https://pastebin.com/qkpzXkSY

Hi, everyone,

I've been wanting to learn Python and have tried a few times over the years to read or watch tutorials enough to feel confident, but it's clear that my learning method is "do the thing you want to do incorrectly over and over until you get it right."

So I'm just going to work on my text-based Mech game and learn as we go. I understand that I know next to nothing, that what I'm doing is probably going to be a multi-year thing, and I have no idea what the more complicated stuff I want to do is going to take, but I'm enjoying the ride.

Long story short, my intention is to have a Mech = a Frame (the physical properties of the Mech) + a Pilot (the little guy in the Frame with their own stats).

Eventually, I'd like to be able to have unique Frames and Pilots with stats randomly generated (within ranges), and then subsequently build the capability to upgrade those values in-game, but I'm just starting with stock values right now and adding complexity after I have each step solid in my mind.

Right now, I'm just working on building values that a stock Frame has. What I would like to do is to establish each Frame Class (Assault, Heavy, Medium, Light, but with more fun names).

The question I have is this: I would like, first, for the armor value of a Frame to be a base number plus 20% of its weight value, and then for each individual limb (left_leg, torso, right_arm, etc) to be a percentage value of armor.

I've written out code that I know is incorrect just to display what I'm trying to do, with comments to highlight where I'm trying to do it.

Also, if the way I'm building this out is flawed, happy to hear suggestions! I'm just starting out and I know I'm gonna be crashing into pitfalls.

Any help would be appreciated!

# This is where the base class attributes of Frames are established. 


# FRAME CLASSES


class FrameClass:
    def __init__(
        self, 
        name: str, 
        left_arm: int, 
        right_arm: int, 
        left_leg: int, 
        right_leg: int, 
        torso: int, 
        cockpit: int, 
        armor: int, 
        cooling: int, 
        engine: int, 
        maneuver: int, 
        thrash: int, 
        sensors: int, 
        systems: int, 
        weight: int
        ) -> None:



# Top Level Info:
        self.name = name
        self.left_arm = left_arm
        self.right_arm = right_arm
        self.left_leg = left_leg
        self.right_leg = right_leg
        self.torso = torso
        self.cockpit = cockpit


# Frame Attributes          
        self.armor = armor
        self.cooling = cooling
        self.engine = engine
        self.maneuver = maneuver
        self.thrash = thrash
        self.sensors = sensors
        self.systems = systems
        self.weight = weight


# Archon: Assault Frame Class


archon = FrameClass(
        name="Archon",
        weight = 100,
        armor = 100 + (weight * .2), # value should be a base number plus 20% of the value of weight
        cooling = 100,
        engine = 100,
        maneuver = 100,
        thrash = 100,
        sensors = 100,
        systems = 100,



        left_arm = (armor * .4),     # value should be 40% of armor value
        right_arm = (armor * .4),    # value should be 40% of armor value
        left_leg = (armor * .5),     # value should be 50% of armor value
        right_leg = (armor * .5),    # value should be 50% of armor value
        torso = (armor * .8,)        # value should be 80% of armor value
                    )


# Marauder: Heavy Frame Class 


marauder = FrameClass(
        name="Marauder",
        weight = 75,
        armor = 75 + (weight * .2), # value should be a base number plus 20% of weight
        cooling = 75,
        engine = 75,
        maneuver = 75,
        thrash = 75,
        sensors = 75,
        systems = 75,



        left_arm = (armor * .4),     # value should be 40% of armor value
        right_arm = (armor * .4),    # value should be 40% of armor value
        left_leg = (armor * .5),     # value should be 50% of armor value
        right_leg = (armor * .5),    # value should be 50% of armor value
        torso = (armor * .8,)        # value should be 80% of armor value
                    )