python-workshop
A series of Jupyter Notebooks on exploring Unidata technology with Python. See website for more information.
파일 탐색기
최종 버전 다운로드 (.zip)- NARR_19930313_0000.nc
- GOES_False_Color_RGB.ipynb
- GOES_RGB_Image.ipynb
- casestudy.ipynb
- CompositeRadar.ipynb
- Siphon Radar Server.ipynb
- skewt.py
- synopticplot.py
- wms_sample.ipynb
- AWIPS_Grids_and_Cartopy.ipynb
- Grid_Levels_and_Parameters.ipynb
- Map_Resources_and_Topography.ipynb
- Model_Sounding_Data.ipynb
- NEXRAD_Level_3_Plot_with_Matplotlib.ipynb
- Satellite_Imagery.ipynb
- Upper_Air_BUFR_Soundings.ipynb
- Watch_and_Warning_Polygons.ipynb
- Downloading GFS with Siphon.ipynb
- netCDF-Writing.ipynb
- Siphon_XARRAY_Cartopy_HRRR.ipynb
- What to do when things go wrong.ipynb
- map.py
- CartoPy.ipynb
- NetCDF and CF - The Basics.ipynb
- buoy_plotter.py
- Command_Line_Primer.ipynb
- example_output.png
- greetme.py
- sat_map.py
- Satellite_Declarative.ipynb
- Jupyter Notebooks Introduction.ipynb
- Plotting and Interactivity.ipynb
- color_scatter.py
- imshow_contour.py
- subplots.py
- anatomy-of-a-figure.png
- Matplotlib Basics.ipynb
- lift.py
- mixing.py
- QG_data.py
- qg_omega_total_fig.py
- term_B_calc.py
- Isentropic Analysis.ipynb
- QG Analysis.ipynb
- MetPy_Case_Study.ipynb
- distance.py
- temperature_change.py
- wind_speed.py
- Introduction to MetPy.ipynb
- MetPy_breakdown.png
- map.py
- Downloading model fields with NCSS.ipynb
- advection.py
- broadcasting.py
- heat_index.py
- slice.py
- slice_bonus.py
- sum_row.py
- vectorized_diff.py
- array_index.png
- Intermediate NumPy.ipynb
- Numpy Basics.ipynb
- NumPy Broadcasting and Vectorization.ipynb
- calc_stats.py
- drop_obs.py
- make_series.py
- rain_obs.py
- temperature_count.py
- Jan17_CO_ASOS.txt
- Pandas Introduction.ipynb
- Numpy and Matplotlib Basics.ipynb
- Primer Exercises.ipynb
- Primer.ipynb
- Scientific_Python_Ecosystem_Overview.ipynb
- dict_args.py
- enumerate.py
- final.py
- function_application.py
- functions.py
- looping1.py
- zip.py
- Advanced Pythonic Data Analysis.ipynb
- Pythonic Data Analysis.ipynb
- data_url.py
- sat_map.py
- GOES_Interactive_Plot.ipynb
- PlottingSatelliteData.ipynb
- datasets.py
- Siphon Overview.ipynb
- hodograph_preprocessing.py
- hodograph_segmented.py
- skewt_cape_cin.py
- skewt_get_data.py
- skewt_make_figure.py
- skewt_thermo.py
- skewt_wind_fiducials.py
- SkewT_and_Hodograph.ipynb
- data_conversion.py
- merge_texas.py
- mesonet_timeseries.py
- read_ok.py
- reduce_and_plot.py
- reduce_density.py
- time_series.py
- FIVEMIN_82.txt
- FIVEMIN_83.txt
- ONEMIN_82.txt
- ONEMIN_83.txt
- 201903222300.mdf
- Advanced StationPlots with Mesonet Data.ipynb
- Oklahoma_stations.csv
- Surface Data with Siphon and MetPy.ipynb
- WestTexas_stations.csv
- adv_plot.py
- basic_plot.py
- get_obs.py
- Basic Time Series Plotting.ipynb
- interp_solution.py
- mean_profile.py
- XArray and CF.ipynb
- XArray Introduction.ipynb
- stats.py
- temperature.py
- test_stats.py
- test_temperature.py
- Testing.md
- 10_Minutes_to_Conda.pdf
- conda.md
- git.md
- github-setup.md
- .dockerignore
- .gitattributes
- .gitignore
- .travis.yml
- appveyor.yml
- Dockerfile
- environment.yml
- gitconfig-template
- Instructor_Checklist.md
- LICENSE
- notebooks_preprocess.py
- README.md
- run_notebooks.py
# 설치 가이드
1. 코드 내려받기
git clone https://github.com/Unidata/python-workshop
깃허브에서 프로젝트 코드 전체를 내 컴퓨터로 내려받습니다.
cd python-workshop
방금 내려받은 프로젝트 폴더 안으로 이동합니다.
2. Docker
쉬움 추천사전 준비물
- Git GitHub에서 프로젝트 코드를 내려받으려면 필요합니다.
- Docker Desktop 컨테이너를 빌드하고 실행하려면 필요합니다. 설치 후 실행해서 백그라운드에 켜두세요.
docker build -t python-workshop .
Dockerfile을 기반으로 실행 가능한 이미지를 빌드합니다.
docker run -p 8080:80 python-workshop
빌드된 이미지를 실제 컨테이너로 실행합니다.
터미널에 docker compose ps 를 입력해 컨테이너들이 Up 상태인지 확인하세요. README에 포트 번호가 적혀있다면 브라우저에서 http://localhost:포트번호 로 접속해보세요.
// repository documentation
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