nodespecs 0.1.9

The specs summarize utilities for computer instance

hardwareSummary

Extracting and Fetching all system and hardware information such as os details, CPU and GPU information, disk and network usage in Python using platform, psutil and gputil libraries.

install and use with pip

pip install nodespecs
python -m specs
python -c "import specs; specs.bench_cpu()"
python -c "import specs; specs.hardware.get_system_info()"

python -c "import specs; specs.info_gpu()"
python -c "from specs import disk;print(disk.resolve_path())"
python -c "from specs.disk import resolve_path;print(resolve_path())"

# clean and orgnized download folder for WINDOWS user
python -m specs -u="fclean"

# for the machine not compatible with psutil
python -m specs -v
python -m specs -l=1

python -m specs -u="bcpu"
python -m specs -u="upload"
python -m specs -u="server"
python -m specs -u="cld" -i='172.25.1.228'

## server
python -c "import specs; print(specs.__version__)"

python -c "import specs; specs.whoish()"
python -c "import specs; specs.server()"
## client upload wt progress bar
python -c "import specs; specs.client('172.25.1.175', 12345,'./README.md',False)"

## client upload wo progress bar
python -c "import specs; specs.client('172.25.1.175', 12345,'./README.md',False)"
## client upload top level files in the cwd
python -c "import specs; specs.clientd('192.168.0.157')"
python -c "import specs; specs.clientd('192.168.0.157', 12345)"

sudo apt update
sudo apt install python3-pip
python3 -m pip install nodespecs && python3 -m specs

import specs

specs.info_gpu()
specs.bench_cpu()

Deprecated (install and use with git)

!git clone https://github.com/jinsanity07git/hardwareSummary && python hardwareSummary/hardware.py && python hardwareSummary/cpu-benchmark.py

git clone https://github.com/jinsanity07git/hardwareSummary && python hardwareSummary/hardware.py && python hardwareSummary/cpu-benchmark.py

sudo apt upgrade
sudo apt install python3-pip
git clone https://github.com/jinsanity07git/hardwareSummary && python3 hardwareSummary/hardware.py && python3 hardwareSummary/cpu-benchmark.py

CPU collection

Nickname	CPU	Arch	OS	Python	Benchmarking	Comb	Score
lab-aws	Intel(R) Xeon(R) Platinum 8488C	x86_64	Linux	3.11.12	11.174		38.76
TC14	13th Gen Intel(R) Core(TM) i9-13900K	AMD64	Windows 10		12.991	Core-i9-13900K	38.76
TC17 TC16	Intel(R) Core(TM) i9-14900KF	AMD64	Windows		15.654	Core-i9-14900KF	39.25
iPhone 14 Pro Max iPhone15,3[^3]	Apple A16 Bionic[^2]	arm64e	Darwin 23.4.0		15.962
10cent CloudStudio	Intel(R) Xeon(R) Platinum 8255C CPU @ 2.50GHz	x86_64	Linux	3.10.11	19.891
TC19	Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz	sAMD64	Windows 10		20.534	Core-i7-9700K	9.45
Dell Precision 5690	Intel(R) Core(TM) Ultra 9 185H	AMD64	Windows 11 Pro	3.8.12	23.824
CHINAMI	Intel(R) Xeon(R) w5-3435X	AMD64	Windows 10		23.849	Xeon w5-3435X	28.58
Dell Precision 3561	11th Gen Intel(R) Core(TM) i7-11800H @ 2.30GHz	AMD64	Windows		23.852	Core-i7-11800H	13.47
github codespaces	AMD EPYC 7763 64-Core Processor	x86_64	Linux		24.259	EPYC-7763	54.65
alibaba t5	Intel(R) Xeon(R) Platinum 8269CY CPU @ 2.50GH	x86_64	Linux	3.12.3	25.44
TC07	Intel(R) Core(TM) i7-9700K CPU @ 3.60GHz	AMD64	Windows		26.723	Core-i7-9700K	9.45
oracle cloudshell	ARM Cortex-A53	aarch64	Linux		27.489
AWS t2.micro	Intel(R) Xeon(R) CPU E5-2676 v3 @ 2.40GHz	x86_64	Linux		27.785	Core-i7-9700K	8.81
AWS workspace	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	x86_64	Linux	3.10.12	29.355
google cloudshell	Intel(R) Xeon(R) CPU @ 2.20GHz	x86_64	Linux		29.818
WUYING: 8 vCPU / 16 GiB Linux	Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz	x86_64	Linux		33.572	Xeon-Platinum-8163
TC03 TC11	Intel(R) Xeon(R) Gold 6248R CPU @ 3.00GHz	AMD64	Window		34.612	Xeon-Gold-6248R	23.26
2018 Macbook pro	Intel(R) Core(TM) i7-8559U CPU @ 2.70GHz	x86_64	Darwin 22.1.0		37.105	Core-i7-8559U	5.38
JVM	Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz	x86_64	Linux		38.685	Xeon-Gold-6126	12.21
TC01	Intel(R) Xeon(R) CPU E5-2643 v4 @ 3.40GHz	AMD64	Windows		39.258	Xeon-E5-2643-v4	7.62
Jquant	Intel(R) Xeon(R) Platinum 8163 CPU @ 2.50GHz	x86_64	Linux		40.128	Xeon-Platinum-8163
google colab free tier	Intel(R) Xeon(R) CPU @ 2.20GHz	x86_64	Linux		43.078
aws cloudshell	Intel(R) Xeon(R) Platinum 8259CL CPU @ 2.50GHz	x86_64	Linux		49.396
JVM	Intel(R) Xeon(R) Gold 6126 CPU @ 2.60GHz	AMD64	Windows		62.969
binder-examples/conda[^4]	Intel(R) Xeon(R) Gold 6140 CPU @ 2.30GHz	x86_64	Linux		74.349	Xeon-Gold-6140	15.8
serv00-FreeBSD	Intel(R) Xeon(R) Silver 4214R CPU @ 2.40GHz	AMD64	Linux		75.571
Oracle 1G-1G-0.5Gbps	AMD EPYC 7551 32-Core Processor	x86_64	Linux		98.732	EPYC-7551	14.67
mini PC	Intel(R) Atom(TM) x5-Z8350 CPU @ 1.44GHz	x86_64	Linux		135.107	Atom-x5-Z8350	0.57

• Note
  • Kinds of Arch explanation[^1]

GPU collection

id	name	total memory	Synthetic benchmark	CUDA API
17	NVIDIA GeForce RTX 4060	8188.0MB	50.69	NA
colab 10cent CloudStudio	Tesla T4	15360.0MB	28.16	70627
5690	NVIDIA RTX 3500 Ada Generation Laptop GPU	12282 MB
dell	NVIDIA T600 Laptop GPU	4096.0MB	16.69	26600
01	Quadro M4000	8192.0MB	17.27	16648

Feature in develop

1. work through ws, transfer file using websocket
2. py-ios-device python based Apple instruments protocol，you can get CPU, Memory and

• Streaming upload server in Python extended from uploadserver.other metrics from real iOS devices

Performance source

• https://browser.geekbench.com/ *
• https://technical.city/en/video/GeForce-RTX-4060-vs-Tesla-T4
• https://technical.city/en/video/Tesla-T4-vs-T600

[^1]: mainstream CPU architecture [^2]: Apple A16 [^3]: apple ios devices name

[^4]: binder: Get your own copy of this repository