Season 1 Lesson 6 Part 3 - Your First Steps - Join will fail on Numbers - in Python #pythonprogramming #codingtutorial #python #softwaredeveloper #jupyternotebook #dataanalysis#learncoding #pythoncode #dataengineer
π° Getting Started with Python Async Programming
Build faster Python applications by mastering async programming and learning how to handle I/O bound workloads efficiently with real world examples.
π° Source: KDnuggets
π Link: https://www.kdnuggets.com/getting-started-with-python-async-programming

How many NaNs in a #Python #Pandas series? Use isna (returns True/False) then sum/value_counts:
s = pd.Series([10, 20, np.nan, 40, 50, np.nan, 70, 80])
s.isna().sum() # returns 2
s.isna().value_counts() # count True/False
Hint: Pass normalize=True for the percentage

Solve Car Talk's Fishing for Thirds puzzler in Python
https://rodstephensbooks.com/fishing_for_thirds.html

Excited to announce that Iβve been selected for the Data Fellowship Program 2025/26.
Over the next 30 days, I will be diving deep into the world of Data Science, AI, and Machine Learning through structured learning and hands-on practice. I am looking forward to connecting with fellow learners and building valuable skills in this ever-evolving field.
#LearningChallenge #DataScience #DataFellowship #MachineLearning #DataCamp #python #learncoding #dailycoding

We are live on YouTube in 60 minutes. Join us and be part of the show with @mkennedy and Charlie Marsh, Jonathan Dekhtiar, and Ralph Gommers. #python #podcast
Topic: Wheel Next + PEPs in Python Packaging
https://www.youtube.com/watch?v=761htncGZpU
How to Stop Your Decorator From Breaking Introspection
functools.wraps copies __name__ and __doc__. One line. Fixed metadata.
#python #decorator #wraps #introspection #howto
https://www.youtube.com/watch?v=mSgVU7GOcYQ
[New Blog Post] State of Knuckledragger III: Kernel Changes, Symbolic Union, AI, and more https://www.philipzucker.com/state_o_knuck_3/ #python #logic #theoremproving
ΠΡ ΡΠΊΠ°Π»ΡΡΠ½ΠΎΠΉ ΡΠΎΡΠΊΠΈ ΠΊ SIMD-ΡΠΉΡΠΎΡΠΈΠΈ: ΠΊΠ°ΠΊ ΠΏΠΎΠ΄ΡΡΠΆΠΈΡΡ IDA Pro Ρ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΡΠΌΠΈ RISC-V P Extension
Π£ Π½Π°Ρ Π² Β«ΠΠ°Π±ΠΎΡΠ°ΡΠΎΡΠΈΠΈ ΠΠ°ΡΠΏΠ΅ΡΡΠΊΠΎΠ³ΠΎΒ» Π΅ΡΡΡ ΠΊΠΎΠΌΠ°Π½Π΄Π° Π°Π½Π°Π»ΠΈΠ·Π° Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΡΡΠΈ, Π·Π°Π½ΠΈΠΌΠ°ΡΡΠ°ΡΡΡ ΠΏΠΎΠΈΡΠΊΠΎΠΌ ΡΡΠ·Π²ΠΈΠΌΠΎΡΡΠ΅ΠΉ Π² ΡΠ°ΠΌΡΡ ΡΠ°Π·Π½ΠΎΠΎΠ±ΡΠ°Π·Π½ΡΡ ΡΠΈΡΡΠ΅ΠΌΠ°Ρ . Π Π½Π΅ΠΉ ΡΠ°Π±ΠΎΡΠ°ΡΡ ΡΠΊΡΠΏΠ΅ΡΡΡ, ΡΠΏΠΎΡΠΎΠ±Π½ΡΠ΅ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΡ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ Π»ΡΠ±ΠΎΠ΅ ΡΡΡΡΠΎΠΉΡΡΠ²ΠΎ (ΠΈ ΠΏΡΠ±Π»ΠΈΠΊΡΡΡΠΈΠ΅ ΡΠ΅Ρ Π½ΠΈΡΠ΅ΡΠΊΠΈΠ΅ Π·Π°ΠΌΠ΅ΡΠΊΠΈ ΠΎ ΡΠ²ΠΎΠΈΡ Π½Π°Ρ ΠΎΠ΄ΠΊΠ°Ρ ). ΠΠΎ Π² ΠΆΠΈΠ·Π½ΠΈ ΠΏΡΠ°ΠΊΡΠΈΡΠ΅ΡΠΊΠΈ ΠΊΠ°ΠΆΠ΄ΠΎΠ³ΠΎ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»Ρ Π±Π΅Π·ΠΎΠΏΠ°ΡΠ½ΠΎΡΡΠΈ ΠΏΡΠΎΡΠΈΠ²ΠΎΠΊ ΠΎΠ΄Π½Π°ΠΆΠ΄Ρ Π½Π°ΡΡΡΠΏΠ°Π΅Ρ ΠΌΠΎΠΌΠ΅Π½Ρ, ΠΊΠΎΠ³Π΄Π° ΠΎΠ½ ΠΈΠ»ΠΈ ΠΎΠ½Π° ΡΡΠ°Π»ΠΊΠΈΠ²Π°Π΅ΡΡΡ Ρ Π½ΠΎΠ²ΡΠΌ ΠΈΠ»ΠΈ Π½Π΅ ΠΎΡΠΎΠ±ΠΎ ΠΈΠ·Π²Π΅ΡΡΠ½ΡΠΌ ΠΌΠΈΠΊΡΠΎΠΊΠΎΠ½ΡΡΠΎΠ»Π»Π΅ΡΠΎΠΌ ΠΈΠ»ΠΈ ΡΠ²Π΅ΠΆΠ΅ΠΉ ΠΏΡΠΎΡΠ΅ΡΡΠΎΡΠ½ΠΎΠΉ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΠΎΠΉ Ρ ΠΊΠ°ΡΡΠΎΠΌΠ½ΡΠΌΠΈ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΡΠΌΠΈ. Π ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅Π΅ Π²ΡΠ΅ΠΌΡ ΡΠ°ΠΊΠΈΠ΅ ΠΌΠΎΠΌΠ΅Π½ΡΡ Π½Π°ΡΡΡΠΏΠ°ΡΡ Π²ΡΠ΅ ΡΠ°ΡΠ΅ β Π·Π° ΠΏΡΠΎΡΠ΅Π΄ΡΠΈΠ΅ Π½Π΅ΡΠΊΠΎΠ»ΡΠΊΠΎ Π»Π΅Ρ ΡΡΠ½ΠΎΠΊ Π½Π°ΠΏΠΎΠ»Π½ΠΈΠ»ΡΡ ΠΎΠ³ΡΠΎΠΌΠ½ΡΠΌ ΠΊΠΎΠ»ΠΈΡΠ΅ΡΡΠ²ΠΎΠΌ Π½ΠΎΠ²ΡΡ ΡΠΈΠΏΠΎΠ² ΠΈΠ· ΠΠΎΠ΄Π½Π΅Π±Π΅ΡΠ½ΠΎΠΉ, Π² ΡΠ°ΡΡΠ½ΠΎΡΡΠΈ, Π½Π° Π±Π°Π·Π΅ RISC-V, ΡΠΎ ΡΠ²ΠΎΠΈΠΌΠΈ ΡΠΎΠ±ΡΡΠ²Π΅Π½Π½ΡΠΌΠΈ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΡΠΌΠΈ ΠΈ ΡΠ΅Π°Π»ΠΈΠ·Π°ΡΠΈΡΠΌΠΈ ΡΠ΄Π΅Ρ. Π Π²ΠΎΡ Π½Π΅ ΡΠ°ΠΊ Π΄Π°Π²Π½ΠΎ Π½Π° Π°Π½Π°Π»ΠΈΠ· Π½Π°ΡΠΈΠΌ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΡΠΌ ΠΏΠΎΠΏΠ°Π»ΠΎ ΡΡΡΡΠΎΠΉΡΡΠ²ΠΎ c ΡΠ°ΠΊΠΈΠΌ ΡΠΈΠΏΠΎΠΌ Π½Π° Π±Π°Π·Π΅ RISC-V, c Π±Π°Π·ΠΎΠ²ΡΠΌ Π½Π°Π±ΠΎΡΠΎΠΌ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΉ RV32I ΠΈ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΠ΅ΠΌ P (ΠΏΡΠΈΡΠ΅ΠΌ Π΅ΡΠ΅ ΠΈ Π½Π΅ ΠΏΠΎΡΠ»Π΅Π΄Π½Π΅ΠΉ Π²Π΅ΡΡΠΈΠΈ), Π΄ΠΎΠ±Π°Π²Π»ΡΡΡΠΈΠΌ ΠΊΠΎΡΠΎΡΠΊΠΈΠ΅ SIMD -ΠΎΠΏΠ΅ΡΠ°ΡΠΈΠΈ (Packed-SIMD Instructions). Π’ΠΎ, ΡΡΠΎ Π½Π°ΡΠΈ ΡΠΊΡΠΏΠ΅ΡΡΡ Π²ΠΈΠ΄Π΅Π»ΠΈ Π΅Π³ΠΎ Π²ΠΏΠ΅ΡΠ²ΡΠ΅ β Π°Π±ΡΠΎΠ»ΡΡΠ½ΠΎ Π½ΠΎΡΠΌΠ°Π»ΡΠ½ΠΎ. ΠΠΎ, ΠΏΠΎ Π²ΡΠ΅ΠΉ Π²ΠΈΠ΄ΠΈΠΌΠΎΡΡΠΈ, Π΅Π³ΠΎ Π²ΠΏΠ΅ΡΠ²ΡΠ΅ Π²ΠΈΠ΄Π΅Π» ΠΈ IDA Pro β ΠΈΠ½ΡΡΡΡΠΌΠ΅Π½Ρ, ΠΊΠΎΡΠΎΡΡΠΌ ΠΏΠΎΠ»ΡΠ·ΡΡΡΡΡ Π½Π°ΡΠΈ ΠΈΡΡΠ»Π΅Π΄ΠΎΠ²Π°ΡΠ΅Π»ΠΈ. ΠΠΎΡΡΠΎΠΌΡ ΠΈΠΌ ΠΏΡΠΈΡΠ»ΠΎΡΡ Π½Π΅ ΡΠΎΠ»ΡΠΊΠΎ ΠΈΠ·ΡΡΠΈΡΡ ΡΠ°Π½Π½ΠΈΠΉ ΡΠ΅ΡΠ½ΠΎΠ²ΠΈΠΊ ΡΠ°ΡΡΠΈΡΠ΅Π½ΠΈΡ P (ΠΎΠ½ΠΎ ΠΆΠ΅ Packed-SIMD Extension), Π½ΠΎ ΡΠ°ΠΊΠΆΠ΅ ΡΠ΅Π°Π»ΠΈΠ·ΠΎΠ²Π°ΡΡ ΠΏΠΎΠ΄Π΄Π΅ΡΠΆΠΊΡ IDA Pro ΡΡΠ΄Π° ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΉ ΠΈΠ· Π½Π΅Π³ΠΎ ΠΈ ΠΏΡΠΎΠΈΠ·Π²Π΅ΡΡΠΈ Π»ΠΈΡΡΠΈΠ½Π³, ΡΠΎ Π΅ΡΡΡ ΡΡΠ°Π½ΡΠ»ΡΡΠΈΡ ΠΈΠ½ΡΡΡΡΠΊΡΠΈΠΉ Π² ΠΏΡΠΎΠΌΠ΅ΠΆΡΡΠΎΡΠ½ΠΎΠ΅ ΠΏΡΠ΅Π΄ΡΡΠ°Π²Π»Π΅Π½ΠΈΠ΅ ΠΈΠ»ΠΈ ΡΠ·ΡΠΊ, ΠΏΠΎΠ½ΡΡΠ½ΡΠ΅ Π΄Π΅ΠΊΠΎΠΌΠΏΠΈΠ»ΡΡΠΎΡΡ. ΠΠΌΠ΅Π½Π½ΠΎ ΡΡΠΈΠΌ ΠΎΠΏΡΡΠΎΠΌ ΠΎΠ½ΠΈ ΠΈ ΡΠ΅ΡΠΈΠ»ΠΈ ΠΏΠΎΠ΄Π΅Π»ΠΈΡΡΡΡ Π² Π΄Π°Π½Π½ΠΎΠΉ ΡΡΠ°ΡΡΠ΅. ΠΠΎ ΠΏΡΠ΅ΠΆΠ΄Π΅ ΡΠ΅ΠΌ ΠΏΠ΅ΡΠ΅Ρ ΠΎΠ΄ΠΈΡΡ ΠΊ ΠΎΠΏΠΈΡΠ°Π½ΠΈΡ ΡΠ΅ΡΠ΅Π½ΠΈΡ ΡΡΠΈΡ Π·Π°Π΄Π°Ρ, ΡΡΠΎΠΈΡ ΠΏΠΎΠ½ΡΡΡ, Ρ ΡΠ΅ΠΌ ΠΌΡ ΠΈΠΌΠ΅Π΅ΠΌ Π΄Π΅Π»ΠΎ, ΠΏΠΎΡΡΠΎΠΌΡ Π½Π°ΡΠ°ΡΡ ΡΠ»Π΅Π΄ΡΠ΅Ρ ΡΠΎ Π·Π½Π°ΠΊΠΎΠΌΡΡΠ²Π° Ρ Π΄ΠΎΠΊΡΠΌΠ΅Π½ΡΠ°ΡΠΈΠ΅ΠΉ ΠΏΠΎ Π°ΡΡ ΠΈΡΠ΅ΠΊΡΡΡΠ΅ RISC-V.
https://habr.com/ru/companies/kaspersky/articles/1005630/
#riscv #ida_pro #python #Π°Π½Π°Π»ΠΈΠ·_Π·Π°ΡΠΈΡΠ΅Π½Π½ΠΎΡΡΠΈ #simd_extension #rv32i #ΠΎΠΏΠΊΠΎΠ΄Ρ #Π΄Π΅ΠΊΠΎΠ΄Π΅Ρ #Π΄Π΅ΠΊΠΎΠΌΠΏΠΈΠ»ΡΡΠΎΡ #ΡΠ΅Π²Π΅ΡΡΠΈΠ½ΠΆΠΈΠ½ΠΈΡΠΈΠ½Π³
Honored to join #JetBrains #PyTV #Python on 4 March and to share the stage with some increadible people.
Check it out. It's FREE and online
https://www.youtube.com/watch?v=8KblH4leUVA
https://lp.jetbrains.com/python-unplugged/
Every query in SQL for Python Devs returned all the rows. That's fine for learning, but it's wasting bandwidth and processing power.
WHERE filters rows before they ever leave the database. It's the SQL equivalent of Python's list comprehension if clause:
[c for c in customers if c['is_premium']]
This week covers WHERE and its friends AND, OR, IN, BETWEEN, LIKE, and the quirky IS NULL syntax.
https://jamalhansen.com/blog/where-filtering-your-data
#SQL #Python #DuckDB #DataScience #Programming
Python Tip: String join() Performance
# Slow: O(n^2)
result = ''
for s in strings:
result += s
# Fast: O(n)
result = ''.join(strings)
str.join() is O(n) while += concatenation is O(n^2). For 10,000 strings, join() is 100x faster.
https://raccoonette.gumroad.com/l/Python-for-Beginners-From-Zero-to-Your-First-Projects
#Python #CodingTips #Programming