Blog 04-20-22

 en.wikipedia.org/wiki/Summer_Time_Rendering

Summer Time Rendering (Japanese: サマータイムレンダ, Hepburn: Samā Taimu Renda) is a Japanese manga series written and illustrated by Yasuki Tanaka. It was serialized on Shueisha’s digital magazine Shōnen Jump+ from October 2017 to February 2021. An anime television series adaptation by OLM premiered in April 2022. A live-action adaptation and a real escape game have also been announced.

Following the death of his parents, Shinpei Ajiro grew up with the Kofune sisters Ushio and Mio. In adulthood, Shinpei lives in Tokyo, until he hears the startling news that Ushio passed away by drowning. He returns to the isolated island town, but becomes suspicious when he notices that Ushio’s body has marks around her neck; implying that she was strangled. Now haunted by her ghost and assisted by Mio, Shinpei tries to find the answers to what really happened to Ushio and possibly save the residents from a strange dark enigma.

An anime adaptation was announced at the end of the series’ 139th and final chapter in February 2021. It was later confirmed to be a 25-episode television series. The series is produced by OLM and directed by Ayumu Watanabe, with Hiroshi Seko overseeing the series’ scripts, Miki Matsumoto designing the characters, and Kusanagi handling the art.

TV Anime “Summer Time Render” 1st Opening Theme Special News [April 2022 TV Broadcast / Distribution Start]:

https://www.youtube.com/watch?v=VNtEcf3iuCQ


/images/log2/blog04-20-22/Pinus_1.jpg

There are two limited furniture sets back to back in this mini-event, [Pinus Sylvestris Break Room] and Secret Occult Society], each costing 5000+ Furniture Parts, therefore I have to farm [SK-5] to convert Carbon Bricks to Furniture Parts, which is a tedious task (Sanity should go to farm more Orirock).


My [PS-6] Stage (chaotic) Clear:


 Operational Intelligence Event Page

/images/log2/blog04-20-22/FlameBringer_1.jpg
Operation Intelligence Record
/images/log2/blog04-20-22/FlameBringer_2.jpg
Flamebringer First-hire
/images/log2/blog04-20-22/FlameBringer_3.jpg
Flamebringer’s Personal Letter
/images/log2/blog04-20-22/FlameBringer_4.jpg
Improve potential
/images/log2/blog04-20-22/FlameBringer_5.jpg
Max potential
/images/log2/blog04-20-22/FlameBringer_6.jpg
Operation Intelligence Portrait

[Airtight Anti-Chemical Safety Cabin] Themed Furniture is now permanently added to furniture shop.

Continue from Exusiai S3M1

Exusiai S3M2 Training ~ click to expand
Exusiai S3M2 process
Exusiai S3M2 process
Exusiai S3M2 material
Exusiai S3M2 material
Exusiai in training room
Exusiai in training room
Exusiai S3M2
Exusiai S3M2

Mastery is very straightforward - more damage. The increase to initial SP is again, irrelevant, due to this skill’s serious need for overcharge. However, the damage boost aspect is rather sizable, and can somewhat mitigate her lack of presence before the skill ramps up. If one simply wants this skill to be better at its intended purpose, the investment is very worthwhile.

https://sanitygone.help/operators/carnelian

Carnelian S3M1 Training ~ click to expand
Carnelian S3M1 process
Carnelian S3M1 process
Carnelian S3M1 material
Carnelian S3M1 material
Carnelian in training room
Carnelian in training room
Exusiai S3M2
Carnelian S3M2

Duration: April 15, 2022, 04:00(UTC-7) - April 25, 2022, 03:59(UTC-7)

/images/log2/blog04-20-22/Dragon_Boat.jpg

[A Wanderer in the Wind] Period: April 14, 2022, 10:00(UTC-7) - April 28, 2022, 03:59(UTC-7)

I was actually aiming for Ashlock and wasn’t expecting to pull Fartooth, but Malticore spooked me instead. I kept rolling a little longer to see if I could get Ashlock, and I ended up with  Fartooth.

Because a limited banner is coming up soon, I didn’t want to waste any more pulls, so I stopped.

Click to fold
Wanderer in the wind banner
Wanderer in the wind banner
/images/log2/blog04-20-22/Fartooth.jpg
Fartooth First-hire
/images/log2/blog04-20-22/Dorm1.jpg
Fartooth in the dormitory

//Echo of the Horrorlair - Shamare

Witch Feast character script “Horrorlair Order” customised costume/ Echo of the Horrorlair. The actor is the transformation of the horrorlair. Pacing in the corridors, guarding and protecting the castle against theft of its riches.

To protect the horrorlair, Shamare needs to give orders to the other actors to guarantee that the treasure would not be dyed. She might be the only operator who acts as herself among all the actors.

/images/log2/blog04-20-22/Shamare_Skin_1.jpg
Witch Feast
/images/log2/blog04-20-22/Shamare_Skin_2.jpg
Buy the Outfit
/images/log2/blog04-20-22/Shamare_Skin_3.jpg
Echo of the Horrorlair
/images/log2/blog04-20-22/ShamareSkinGIFBas_0.gif

//Moon Catastrborn - Blemishine

Witch Feast character script “Horrorlair Order” customized costume/ Moon Catastrborn. The actor will be the descending disaster who has divided the moon into two and set foot on earth. There is no way for a hero to win a head-on match.

Everyone knows that Blemishine is not suitable to act as a villain, but isn’t that what makes this fun? Anyway, she and her two relatives only want to enjoy the fun of play-acting, and don’t care about the outcome.

/images/log2/blog04-20-22/Blemishine_Skin_1.jpg
Witch Feast
/images/log2/blog04-20-22/Blemishine_Skin_2.jpg
Buy the Outfit
/images/log2/blog04-20-22/Blemishine_Skin_3.jpg
Moon Catastrborn

If you missed Operator Operator Grani before, you can now get her with the latest update. Aside from that, a new rewarded portrait that can be used as a personal avatar has been included.

/images/log2/blog04-20-22/Grani_RecordRestore_1.jpg
Record Restore
/images/log2/blog04-20-22/Grani_RecordRestore_2.jpg
Already max potential
/images/log2/blog04-20-22/Grani_RecordRestore_3.jpg
Grani and Knight Treasure Portrait

When you get the hang of it, this quest is quite simple. Simply use the Rope skill on higher DEF enemies to pull them to the hole, and position Shaw to the right to kick some Reunion thugs out of the building.

Popukar Paradox Simulation
Popukar Paradox Simulation
/images/log2/blog04-20-22/Popukar_paradox_2.jpg
Activate Rope skill with careful timing
/images/log2/blog04-20-22/Popukar_paradox_3.jpg
Operation End

I got a good Recruitment tag combination, which granted me  Pramanix. I didn’t choose Summon tag because Mayer is max potential already.

Pramanix ~ click to expand
/images/log2/blog04-20-22/Pramanix_1.jpg
tag combination
/images/log2/blog04-20-22/Pramanix_2.jpg
Pramanix
/images/log2/blog04-20-22/Pramanix_3.jpg
Pramanix’s Token
/images/log2/blog04-20-22/Pramanix_4.jpg
Pramanix Pot 2

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You should consider upgrading via the 'c:\users\...\appdata\local\programs\python\python39\python.exe -m pip install --upgrade pip' command.

C:\cmder
λ python -m pip install --upgrade pip
Requirement already satisfied: pip in c:\users\...\appdata\local\programs\python\python39\lib\site-packages (21.2.4)
Collecting pip
  Downloading pip-22.0.4-py3-none-any.whl (2.1 MB)
     |████████████████████████████████| 2.1 MB 3.3 MB/s
Installing collected packages: pip
  Attempting uninstall: pip
    Found existing installation: pip 21.2.4
    Uninstalling pip-21.2.4:
      Successfully uninstalled pip-21.2.4
Successfully installed pip-22.0.4
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pip install notebook
Collecting notebook
  Using cached notebook-6.4.10-py3-none-any.whl (9.9 MB)
Collecting pyzmq>=17
  Downloading pyzmq-22.3.0-cp310-cp310-win_amd64.whl (1.1 MB)
     ---------------------------------------- 1.1/1.1 MB 4.4 MB/s eta 0:00:00
Collecting ipykernel
  Using cached ipykernel-6.13.0-py3-none-any.whl (131 kB)
Collecting ipython-genutils
  Using cached ipython_genutils-0.2.0-py2.py3-none-any.whl (26 kB)
Collecting terminado>=0.8.3
  Using cached terminado-0.13.3-py3-none-any.whl (14 kB)
Collecting tornado>=6.1
  Downloading tornado-6.1.tar.gz (497 kB)
     ---------------------------------------- 497.4/497.4 KB 3.9 MB/s eta 0:00:00
  Preparing metadata (setup.py) ... done
Collecting jinja2
  Using cached Jinja2-3.1.1-py3-none-any.whl (132 kB)
Collecting nest-asyncio>=1.5
  Using cached nest_asyncio-1.5.5-py3-none-any.whl (5.2 kB)
Collecting prometheus-client
  Using cached prometheus_client-0.14.1-py3-none-any.whl (59 kB)
Collecting jupyter-client>=5.3.4
  Using cached jupyter_client-7.2.2-py3-none-any.whl (130 kB)
Collecting nbconvert>=5
  Using cached nbconvert-6.5.0-py3-none-any.whl (561 kB)
Collecting traitlets>=4.2.1
  Using cached traitlets-5.1.1-py3-none-any.whl (102 kB)
Collecting jupyter-core>=4.6.1
  Using cached jupyter_core-4.9.2-py3-none-any.whl (86 kB)
Collecting nbformat
  Using cached nbformat-5.3.0-py3-none-any.whl (73 kB)
Collecting Send2Trash>=1.8.0
  Using cached Send2Trash-1.8.0-py3-none-any.whl (18 kB)
Collecting argon2-cffi
  Using cached argon2_cffi-21.3.0-py3-none-any.whl (14 kB)
Collecting entrypoints
  Using cached entrypoints-0.4-py3-none-any.whl (5.3 kB)
Requirement already satisfied: python-dateutil>=2.8.2 in c:\users\...\appdata\local\programs\python\python310\lib\site-packages (from jupyter-client>=5.3.4->notebook) (2.8.2)
Collecting pywin32>=1.0
  Downloading pywin32-303-cp310-cp310-win_amd64.whl (9.2 MB)
     ---------------------------------------- 9.2/9.2 MB 7.8 MB/s eta 0:00:00
Collecting mistune<2,>=0.8.1
  Using cached mistune-0.8.4-py2.py3-none-any.whl (16 kB)
Collecting MarkupSafe>=2.0
  Downloading MarkupSafe-2.1.1-cp310-cp310-win_amd64.whl (17 kB)
Collecting jupyterlab-pygments
  Using cached jupyterlab_pygments-0.2.2-py2.py3-none-any.whl (21 kB)
Collecting bleach
  Using cached bleach-5.0.0-py3-none-any.whl (160 kB)
Collecting defusedxml
  Using cached defusedxml-0.7.1-py2.py3-none-any.whl (25 kB)
Collecting pygments>=2.4.1
  Using cached Pygments-2.11.2-py3-none-any.whl (1.1 MB)
Requirement already satisfied: packaging in c:\users\...\appdata\local\programs\python\python310\lib\site-packages (from nbconvert>=5->notebook) (21.3)
Collecting pandocfilters>=1.4.1
  Using cached pandocfilters-1.5.0-py2.py3-none-any.whl (8.7 kB)
Collecting tinycss2
  Using cached tinycss2-1.1.1-py3-none-any.whl (21 kB)
Collecting nbclient>=0.5.0
  Using cached nbclient-0.6.0-py3-none-any.whl (70 kB)
Collecting beautifulsoup4
  Using cached beautifulsoup4-4.11.1-py3-none-any.whl (128 kB)
Collecting jsonschema>=2.6
  Using cached jsonschema-4.4.0-py3-none-any.whl (72 kB)
Collecting fastjsonschema
  Using cached fastjsonschema-2.15.3-py3-none-any.whl (22 kB)
Collecting pywinpty>=1.1.0
  Downloading pywinpty-2.0.5-cp310-none-win_amd64.whl (1.4 MB)
     ---------------------------------------- 1.4/1.4 MB 8.1 MB/s eta 0:00:00
Collecting argon2-cffi-bindings
  Using cached argon2_cffi_bindings-21.2.0-cp36-abi3-win_amd64.whl (30 kB)
Collecting matplotlib-inline>=0.1
  Using cached matplotlib_inline-0.1.3-py3-none-any.whl (8.2 kB)
Collecting ipython>=7.23.1
  Using cached ipython-8.2.0-py3-none-any.whl (750 kB)
Collecting debugpy>=1.0
  Downloading debugpy-1.6.0-cp310-cp310-win_amd64.whl (4.3 MB)
     ---------------------------------------- 4.3/4.3 MB 5.3 MB/s eta 0:00:00
Collecting psutil
  Downloading psutil-5.9.0-cp310-cp310-win_amd64.whl (245 kB)
     ---------------------------------------- 245.5/245.5 KB 1.2 MB/s eta 0:00:00
Collecting decorator
  Using cached decorator-5.1.1-py3-none-any.whl (9.1 kB)
Requirement already satisfied: setuptools>=18.5 in c:\users\...\appdata\local\programs\python\python310\lib\site-packages (from ipython>=7.23.1->ipykernel->notebook) (58.1.0)
Collecting prompt-toolkit!=3.0.0,!=3.0.1,<3.1.0,>=2.0.0
  Using cached prompt_toolkit-3.0.29-py3-none-any.whl (381 kB)
Collecting stack-data
  Using cached stack_data-0.2.0-py3-none-any.whl (21 kB)
Collecting backcall
  Using cached backcall-0.2.0-py2.py3-none-any.whl (11 kB)
Collecting pickleshare
  Using cached pickleshare-0.7.5-py2.py3-none-any.whl (6.9 kB)
Collecting colorama
  Using cached colorama-0.4.4-py2.py3-none-any.whl (16 kB)
Collecting jedi>=0.16
  Using cached jedi-0.18.1-py2.py3-none-any.whl (1.6 MB)
Collecting pyrsistent!=0.17.0,!=0.17.1,!=0.17.2,>=0.14.0
  Downloading pyrsistent-0.18.1-cp310-cp310-win_amd64.whl (61 kB)
     ---------------------------------------- 61.6/61.6 KB 3.2 MB/s eta 0:00:00
Collecting attrs>=17.4.0
  Using cached attrs-21.4.0-py2.py3-none-any.whl (60 kB)
Requirement already satisfied: six>=1.5 in c:\users\...\appdata\local\programs\python\python310\lib\site-packages (from python-dateutil>=2.8.2->jupyter-client>=5.3.4->notebook) (1.16.0)
Collecting cffi>=1.0.1
  Downloading cffi-1.15.0-cp310-cp310-win_amd64.whl (180 kB)
     ---------------------------------------- 180.3/180.3 KB 5.5 MB/s eta 0:00:00
Collecting soupsieve>1.2
  Using cached soupsieve-2.3.2.post1-py3-none-any.whl (37 kB)
Collecting webencodings
  Using cached webencodings-0.5.1-py2.py3-none-any.whl (11 kB)
Requirement already satisfied: pyparsing!=3.0.5,>=2.0.2 in c:\users\...\appdata\local\programs\python\python310\lib\site-packages (from packaging->nbconvert>=5->notebook) (3.0.8)
Collecting pycparser
  Using cached pycparser-2.21-py2.py3-none-any.whl (118 kB)
Collecting parso<0.9.0,>=0.8.0
  Using cached parso-0.8.3-py2.py3-none-any.whl (100 kB)
Collecting wcwidth
  Using cached wcwidth-0.2.5-py2.py3-none-any.whl (30 kB)
Collecting executing
  Using cached executing-0.8.3-py2.py3-none-any.whl (16 kB)
Collecting asttokens
  Using cached asttokens-2.0.5-py2.py3-none-any.whl (20 kB)
Collecting pure-eval
  Using cached pure_eval-0.2.2-py3-none-any.whl (11 kB)
Using legacy 'setup.py install' for tornado, since package 'wheel' is not installed.
Installing collected packages: webencodings, wcwidth, Send2Trash, pywin32, pure-eval, pickleshare, mistune, ipython-genutils, fastjsonschema, executing, backcall, traitlets, tornado, tinycss2, soupsieve, pyzmq, pywinpty, pyrsistent, pygments, pycparser, psutil, prompt-toolkit, prometheus-client, parso, pandocfilters, nest-asyncio, MarkupSafe, jupyterlab-pygments, entrypoints, defusedxml, decorator, debugpy, colorama, bleach, attrs, asttokens, terminado, stack-data, matplotlib-inline, jupyter-core, jsonschema, jinja2, jedi, cffi, beautifulsoup4, nbformat, jupyter-client, ipython, argon2-cffi-bindings, nbclient, ipykernel, argon2-cffi, nbconvert, notebook
  Running setup.py install for tornado ... done
Successfully installed MarkupSafe-2.1.1 Send2Trash-1.8.0 argon2-cffi-21.3.0 argon2-cffi-bindings-21.2.0 asttokens-2.0.5 attrs-21.4.0 backcall-0.2.0 beautifulsoup4-4.11.1 bleach-5.0.0 cffi-1.15.0 colorama-0.4.4 debugpy-1.6.0 decorator-5.1.1 defusedxml-0.7.1 entrypoints-0.4 executing-0.8.3 fastjsonschema-2.15.3 ipykernel-6.13.0 ipython-8.2.0 ipython-genutils-0.2.0 jedi-0.18.1 jinja2-3.1.1 jsonschema-4.4.0 jupyter-client-7.2.2 jupyter-core-4.9.2 jupyterlab-pygments-0.2.2 matplotlib-inline-0.1.3 mistune-0.8.4 nbclient-0.6.0 nbconvert-6.5.0 nbformat-5.3.0 nest-asyncio-1.5.5 notebook-6.4.10 pandocfilters-1.5.0 parso-0.8.3 pickleshare-0.7.5 prometheus-client-0.14.1 prompt-toolkit-3.0.29 psutil-5.9.0 pure-eval-0.2.2 pycparser-2.21 pygments-2.11.2 pyrsistent-0.18.1 pywin32-303 pywinpty-2.0.5 pyzmq-22.3.0 soupsieve-2.3.2.post1 stack-data-0.2.0 terminado-0.13.3 tinycss2-1.1.1 tornado-6.1 traitlets-5.1.1 wcwidth-0.2.5 webencodings-0.5.1

Change directory path to access .ipynb folders. Then lauch Jupyter Notebook with command jupyter notebook.

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C:\cmder
λ cd D:\GITHUB\Py-Exercises\Python_Data_handling_analysis_visualization

C:\cmder
λ D:

D:\GITHUB\Py-Exercises\Python_Data_handling_analysis_visualization (main -> origin)
λ jupyter notebook
[I 10:37:07.829 NotebookApp] Serving notebooks from local directory: D:\GITHUB\Py-Exercises\Python_Data_handling_analysis_visualization
[I 10:37:07.829 NotebookApp] Jupyter Notebook 6.4.10 is running at:
[I 10:37:07.829 NotebookApp] http://localhost:8888/?token=2489822117fa4869b4551212d0032f2b6dcbc7013d4f0ccb
[I 10:37:07.829 NotebookApp]  or http://127.0.0.1:8888/?token=2489822117fa4869b4551212d0032f2b6dcbc7013d4f0ccb
[I 10:37:07.829 NotebookApp] Use Control-C to stop this server and shut down all kernels (twice to skip confirmation).
[C 10:37:07.907 NotebookApp]

    To access the notebook, open this file in a browser:
        file:///C:/Users/.../AppData/Roaming/jupyter/runtime/nbserver-6100-open.html
    Or copy and paste one of these URLs:
        http://localhost:8888/?token=2489822117fa4869b4551212d0032f2b6dcbc7013d4f0ccb
     or http://127.0.0.1:8888/?token=2489822117fa4869b4551212d0032f2b6dcbc7013d4f0ccb

If you require environment management as opposed to just installation, look into conda, mamba, and pipenv.