Spaces:
Running
Running
Uploading Model
Browse files- .gitattributes +2 -35
- .gitignore +210 -0
- .vscode/settings.json +4 -0
- app.py +22 -17
- app/__init__.py +0 -7
- app/model.py +0 -11
- app/routes.py +0 -12
- model/dji.csv +31 -0
- model/nasdaq100.csv +102 -0
- model/nasdaq_all.csv +0 -0
- model/sp500.csv +504 -0
- preprocess.py +544 -0
- requirements.txt +9 -2
- us_stock.py +361 -0
.gitattributes
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saved_model/**/* filter=lfs diff=lfs merge=lfs -text
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model/word2vec-google-news-300.model filter=lfs diff=lfs merge=lfs -text
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Target_Model/* filter=lfs diff=lfs merge=lfs -text
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.gitignore
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@@ -0,0 +1,210 @@
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# Model
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logs/
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#Target_Model/
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#model/word*.npy
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# Byte-compiled / optimized / DLL files
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__pycache__/
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*.py[cod]
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*$py.class
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# C extensions
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*.so
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# Distribution / packaging
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.Python
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build/
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develop-eggs/
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dist/
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downloads/
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eggs/
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.eggs/
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lib/
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lib64/
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parts/
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sdist/
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var/
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wheels/
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share/python-wheels/
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*.egg-info/
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.installed.cfg
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*.egg
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MANIFEST
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# PyInstaller
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# Usually these files are written by a python script from a template
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# before PyInstaller builds the exe, so as to inject date/other infos into it.
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*.manifest
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*.spec
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+
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# Installer logs
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pip-log.txt
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44 |
+
pip-delete-this-directory.txt
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+
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# Unit test / coverage reports
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htmlcov/
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.tox/
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.nox/
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.coverage
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.coverage.*
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.cache
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nosetests.xml
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coverage.xml
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*.cover
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*.py,cover
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.hypothesis/
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.pytest_cache/
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cover/
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# Translations
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+
*.mo
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*.pot
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+
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# Django stuff:
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66 |
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*.log
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+
local_settings.py
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68 |
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db.sqlite3
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db.sqlite3-journal
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# Flask stuff:
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72 |
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instance/
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.webassets-cache
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# Scrapy stuff:
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.scrapy
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+
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# Sphinx documentation
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79 |
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docs/_build/
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+
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# PyBuilder
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82 |
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.pybuilder/
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target/
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+
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# Jupyter Notebook
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86 |
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.ipynb_checkpoints
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87 |
+
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# IPython
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89 |
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profile_default/
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ipython_config.py
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+
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92 |
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# pyenv
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93 |
+
# For a library or package, you might want to ignore these files since the code is
|
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# intended to run in multiple environments; otherwise, check them in:
|
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# .python-version
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+
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# pipenv
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+
# According to pypa/pipenv#598, it is recommended to include Pipfile.lock in version control.
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# However, in case of collaboration, if having platform-specific dependencies or dependencies
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# having no cross-platform support, pipenv may install dependencies that don't work, or not
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# install all needed dependencies.
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#Pipfile.lock
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+
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# poetry
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# Similar to Pipfile.lock, it is generally recommended to include poetry.lock in version control.
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# This is especially recommended for binary packages to ensure reproducibility, and is more
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# commonly ignored for libraries.
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# https://python-poetry.org/docs/basic-usage/#commit-your-poetrylock-file-to-version-control
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#poetry.lock
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+
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# pdm
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# Similar to Pipfile.lock, it is generally recommended to include pdm.lock in version control.
|
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#pdm.lock
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# pdm stores project-wide configurations in .pdm.toml, but it is recommended to not include it
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# in version control.
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# https://pdm.fming.dev/latest/usage/project/#working-with-version-control
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.pdm.toml
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.pdm-python
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.pdm-build/
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# PEP 582; used by e.g. github.com/David-OConnor/pyflow and github.com/pdm-project/pdm
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__pypackages__/
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# Celery stuff
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celerybeat-schedule
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celerybeat.pid
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+
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# SageMath parsed files
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*.sage.py
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+
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# Environments
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.env
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.venv
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env/
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venv/
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ENV/
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env.bak/
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venv.bak/
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# Spyder project settings
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141 |
+
.spyderproject
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.spyproject
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+
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# Rope project settings
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.ropeproject
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+
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# mkdocs documentation
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/site
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# mypy
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.mypy_cache/
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.dmypy.json
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153 |
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dmypy.json
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154 |
+
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# Pyre type checker
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156 |
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.pyre/
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+
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# pytype static type analyzer
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.pytype/
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+
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# Cython debug symbols
|
162 |
+
cython_debug/
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+
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164 |
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# PyCharm
|
165 |
+
# JetBrains specific template is maintained in a separate JetBrains.gitignore that can
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166 |
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# be found at https://github.com/github/gitignore/blob/main/Global/JetBrains.gitignore
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# and can be added to the global gitignore or merged into this file. For a more nuclear
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# option (not recommended) you can uncomment the following to ignore the entire idea folder.
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#.idea/
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+
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# General
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+
.DS_Store
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173 |
+
.AppleDouble
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.LSOverride
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+
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# Icon must end with two \r
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+
Icon
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178 |
+
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+
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+
# Thumbnails
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181 |
+
._*
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182 |
+
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183 |
+
# Files that might appear in the root of a volume
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184 |
+
.DocumentRevisions-V100
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185 |
+
.fseventsd
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186 |
+
.Spotlight-V100
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.TemporaryItems
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.Trashes
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+
.VolumeIcon.icns
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190 |
+
.com.apple.timemachine.donotpresent
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+
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+
# Directories potentially created on remote AFP share
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193 |
+
.AppleDB
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194 |
+
.AppleDesktop
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195 |
+
Network Trash Folder
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196 |
+
Temporary Items
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197 |
+
.apdisk
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+
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199 |
+
.vscode/*
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+
!.vscode/settings.json
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!.vscode/tasks.json
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+
!.vscode/launch.json
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+
!.vscode/extensions.json
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+
!.vscode/*.code-snippets
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+
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206 |
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# Local History for Visual Studio Code
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207 |
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.history/
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+
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# Built Visual Studio Code Extensions
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*.vsix
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.vscode/settings.json
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{
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"git.ignoreLimitWarning": true,
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"python.analysis.autoImportCompletions": true
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}
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app.py
CHANGED
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import
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import
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#
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st.write('输入文本,获取模型预测结果。')
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#
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from fastapi import FastAPI, HTTPException
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from pydantic import BaseModel
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#from preprocess import preprocess_text
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# 初始化 FastAPI 应用
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app = FastAPI()
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# 定义请求体模型
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class TextRequest(BaseModel):
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text: str
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@app.post("/api/preprocess")
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async def api_preprocess(request: TextRequest):
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"""
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API: 接收新闻文本,返回预处理结果。
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"""
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if not request.text.strip():
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raise HTTPException(status_code=400, detail="Text cannot be empty.")
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result = request.text + 'ABC'
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return result
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# 启动服务
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if __name__ == "__main__":
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import uvicorn
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uvicorn.run(app, host="0.0.0.0", port=8000)
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app/__init__.py
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from flask import Flask
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def create_app():
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app = Flask(__name__)
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from .routes import api
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app.register_blueprint(api)
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return app
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app/model.py
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from transformers import pipeline
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# 加载模型
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#model = pipeline('text-classification')
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def predict(text):
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try:
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result = text + ' is a good movie'
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return result
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except Exception as e:
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return {'error': str(e)}
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app/routes.py
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from flask import Blueprint, request, jsonify
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from .model import predict
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api = Blueprint('api', __name__)
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@api.route('/predict', methods=['POST'])
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def predict_route():
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data = request.get_json()
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if not data or 'input' not in data:
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return jsonify({'error': 'Invalid input'}), 400
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prediction = predict(data['input'])
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return jsonify({'prediction': prediction})
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model/dji.csv
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1 |
+
Company,Exchange,Symbol,Industry
|
2 |
+
3M,NYSE,MMM,Conglomerate
|
3 |
+
American Express,NYSE,AXP,Financial services
|
4 |
+
Amgen,NASDAQ,AMGN,Biopharmaceutical
|
5 |
+
Amazon,NASDAQ,AMZN,Retailing
|
6 |
+
Apple,NASDAQ,AAPL,Information technology
|
7 |
+
Boeing,NYSE,BA,Aerospace�and�defense
|
8 |
+
Caterpillar,NYSE,CAT,Construction�and�mining
|
9 |
+
Chevron,NYSE,CVX,Petroleum industry
|
10 |
+
Cisco,NASDAQ,CSCO,Information technology
|
11 |
+
Coca-Cola,NYSE,KO,Drink industry
|
12 |
+
Disney,NYSE,DIS,Broadcasting�and�entertainment
|
13 |
+
Dow,NYSE,DOW,Chemical industry
|
14 |
+
Goldman Sachs,NYSE,GS,Financial services
|
15 |
+
Home Depot,NYSE,HD,Home Improvement
|
16 |
+
Honeywell,NASDAQ,HON,Conglomerate
|
17 |
+
IBM,NYSE,IBM,Information technology
|
18 |
+
Intel,NASDAQ,INTC,Semiconductor industry
|
19 |
+
Johnson & Johnson,NYSE,JNJ,Pharmaceutical industry
|
20 |
+
JPMorgan Chase,NYSE,JPM,Financial services
|
21 |
+
McDonald's,NYSE,MCD,Food industry
|
22 |
+
Merck,NYSE,MRK,Pharmaceutical industry
|
23 |
+
Microsoft,NASDAQ,MSFT,Information technology
|
24 |
+
Nike,NYSE,NKE,Clothing industry
|
25 |
+
Procter & Gamble,NYSE,PG,Fast-moving consumer goods
|
26 |
+
Salesforce,NYSE,CRM,Information technology
|
27 |
+
Travelers,NYSE,TRV,Insurance
|
28 |
+
UnitedHealth Group,NYSE,UNH,Managed health care
|
29 |
+
Verizon,NYSE,VZ,Telecommunications industry
|
30 |
+
Visa,NYSE,V,Financial services
|
31 |
+
Walmart,NYSE,WMT,Retailing
|
model/nasdaq100.csv
ADDED
@@ -0,0 +1,102 @@
|
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|
1 |
+
Symbol,Name
|
2 |
+
AAPL,Apple Inc. Common Stock
|
3 |
+
ABNB,"Airbnb, Inc. Class A Common Stock"
|
4 |
+
ADBE,Adobe Inc. Common Stock
|
5 |
+
ADI,"Analog Devices, Inc. Common Stock"
|
6 |
+
ADP,"Automatic Data Processing, Inc. Common Stock"
|
7 |
+
ADSK,"Autodesk, Inc. Common Stock"
|
8 |
+
AEP,"American Electric Power Company, Inc. Common Stock"
|
9 |
+
AMAT,"Applied Materials, Inc. Common Stock"
|
10 |
+
AMD,"Advanced Micro Devices, Inc. Common Stock"
|
11 |
+
AMGN,Amgen Inc. Common Stock
|
12 |
+
AMZN,"Amazon.com, Inc. Common Stock"
|
13 |
+
ANSS,"ANSYS, Inc. Common Stock"
|
14 |
+
ARM,Arm Holdings plc American Depositary Shares
|
15 |
+
ASML,ASML Holding N.V. New York Registry Shares
|
16 |
+
AVGO,Broadcom Inc. Common Stock
|
17 |
+
AZN,AstraZeneca PLC American Depositary Shares
|
18 |
+
BIIB,Biogen Inc. Common Stock
|
19 |
+
BKNG,Booking Holdings Inc. Common Stock
|
20 |
+
BKR,Baker Hughes Company Class A Common Stock
|
21 |
+
CCEP,Coca-Cola Europacific Partners plc Ordinary Shares
|
22 |
+
CDNS,"Cadence Design Systems, Inc. Common Stock"
|
23 |
+
CDW,CDW Corporation Common Stock
|
24 |
+
CEG,Constellation Energy Corporation Common Stock
|
25 |
+
CHTR,"Charter Communications, Inc. Class A Common Stock New"
|
26 |
+
CMCSA,Comcast Corporation Class A Common Stock
|
27 |
+
COST,Costco Wholesale Corporation Common Stock
|
28 |
+
CPRT,"Copart, Inc. (DE) Common Stock"
|
29 |
+
CRWD,"CrowdStrike Holdings, Inc. Class A Common Stock"
|
30 |
+
CSCO,"Cisco Systems, Inc. Common Stock (DE)"
|
31 |
+
CSGP,"CoStar Group, Inc. Common Stock"
|
32 |
+
CSX,CSX Corporation Common Stock
|
33 |
+
CTAS,Cintas Corporation Common Stock
|
34 |
+
CTSH,Cognizant Technology Solutions Corporation Class A Common Stock
|
35 |
+
DASH,"DoorDash, Inc. Class A Common Stock"
|
36 |
+
DDOG,"Datadog, Inc. Class A Common Stock"
|
37 |
+
DLTR,Dollar Tree Inc. Common Stock
|
38 |
+
DXCM,"DexCom, Inc. Common Stock"
|
39 |
+
EA,Electronic Arts Inc. Common Stock
|
40 |
+
EXC,Exelon Corporation Common Stock
|
41 |
+
FANG,"Diamondback Energy, Inc. Common Stock"
|
42 |
+
FAST,Fastenal Company Common Stock
|
43 |
+
FTNT,"Fortinet, Inc. Common Stock"
|
44 |
+
GEHC,GE HealthCare Technologies Inc. Common Stock
|
45 |
+
GFS,GlobalFoundries Inc. Ordinary Shares
|
46 |
+
GILD,"Gilead Sciences, Inc. Common Stock"
|
47 |
+
GOOG,Alphabet Inc. Class C Capital Stock
|
48 |
+
GOOGL,Alphabet Inc. Class A Common Stock
|
49 |
+
HON,Honeywell International Inc. Common Stock
|
50 |
+
IDXX,"IDEXX Laboratories, Inc. Common Stock"
|
51 |
+
ILMN,"Illumina, Inc. Common Stock"
|
52 |
+
INTC,Intel Corporation Common Stock
|
53 |
+
INTU,Intuit Inc. Common Stock
|
54 |
+
ISRG,"Intuitive Surgical, Inc. Common Stock"
|
55 |
+
KDP,Keurig Dr Pepper Inc. Common Stock
|
56 |
+
KHC,The Kraft Heinz Company Common Stock
|
57 |
+
KLAC,KLA Corporation Common Stock
|
58 |
+
LIN,Linde plc Ordinary Shares
|
59 |
+
LRCX,Lam Research Corporation Common Stock
|
60 |
+
LULU,lululemon athletica inc. Common Stock
|
61 |
+
MAR,Marriott International Class A Common Stock
|
62 |
+
MCHP,Microchip Technology Incorporated Common Stock
|
63 |
+
MDB,"MongoDB, Inc. Class A Common Stock"
|
64 |
+
MDLZ,"Mondelez International, Inc. Class A Common Stock"
|
65 |
+
MELI,"MercadoLibre, Inc. Common Stock"
|
66 |
+
META,"Meta Platforms, Inc. Class A Common Stock"
|
67 |
+
MNST,Monster Beverage Corporation
|
68 |
+
MRNA,"Moderna, Inc. Common Stock"
|
69 |
+
MRVL,"Marvell Technology, Inc. Common Stock"
|
70 |
+
MSFT,Microsoft Corporation Common Stock
|
71 |
+
MU,"Micron Technology, Inc. Common Stock"
|
72 |
+
NFLX,"Netflix, Inc. Common Stock"
|
73 |
+
NVDA,NVIDIA Corporation Common Stock
|
74 |
+
NXPI,NXP Semiconductors N.V. Common Stock
|
75 |
+
ODFL,"Old Dominion Freight Line, Inc. Common Stock"
|
76 |
+
ON,ON Semiconductor Corporation Common Stock
|
77 |
+
ORLY,"O'Reilly Automotive, Inc. Common Stock"
|
78 |
+
PANW,"Palo Alto Networks, Inc. Common Stock"
|
79 |
+
PAYX,"Paychex, Inc. Common Stock"
|
80 |
+
PCAR,PACCAR Inc. Common Stock
|
81 |
+
PDD,PDD Holdings Inc. American Depositary Shares
|
82 |
+
PEP,"PepsiCo, Inc. Common Stock"
|
83 |
+
PYPL,"PayPal Holdings, Inc. Common Stock"
|
84 |
+
QCOM,QUALCOMM Incorporated Common Stock
|
85 |
+
REGN,"Regeneron Pharmaceuticals, Inc. Common Stock"
|
86 |
+
ROP,"Roper Technologies, Inc. Common Stock"
|
87 |
+
ROST,"Ross Stores, Inc. Common Stock"
|
88 |
+
SBUX,Starbucks Corporation Common Stock
|
89 |
+
SMCI,"Super Micro Computer, Inc. Common Stock"
|
90 |
+
SNPS,"Synopsys, Inc. Common Stock"
|
91 |
+
TEAM,Atlassian Corporation Class A Common Stock
|
92 |
+
TMUS,"T-Mobile US, Inc. Common Stock"
|
93 |
+
TSLA,"Tesla, Inc. Common Stock"
|
94 |
+
TTD,"The Trade Desk, Inc. Class A Common Stock"
|
95 |
+
TTWO,"Take-Two Interactive Software, Inc. Common Stock"
|
96 |
+
TXN,Texas Instruments Incorporated Common Stock
|
97 |
+
VRSK,"Verisk Analytics, Inc. Common Stock"
|
98 |
+
VRTX,Vertex Pharmaceuticals Incorporated Common Stock
|
99 |
+
WBD,"Warner Bros. Discovery, Inc. Series A Common Stock"
|
100 |
+
WDAY,"Workday, Inc. Class A Common Stock"
|
101 |
+
XEL,Xcel Energy Inc. Common Stock
|
102 |
+
ZS,"Zscaler, Inc. Common Stock"
|
model/nasdaq_all.csv
ADDED
The diff for this file is too large to render.
See raw diff
|
|
model/sp500.csv
ADDED
@@ -0,0 +1,504 @@
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|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
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1 |
+
Symbol,Security,GICS Sector,GICS Sub-Industry,Headquarters Location,Date added,CIK,Founded
|
2 |
+
A,Agilent Technologies,Health Care,Life Sciences Tools & Services,"Santa Clara, California",2000-06-05,1090872,1999
|
3 |
+
AAL,American Airlines Group,Industrials,Passenger Airlines,"Fort Worth, Texas",2015-03-23,6201,1934
|
4 |
+
AAPL,Apple Inc.,Information Technology,"Technology Hardware, Storage & Peripherals","Cupertino, California",1982-11-30,320193,1977
|
5 |
+
ABBV,AbbVie,Health Care,Biotechnology,"North Chicago, Illinois",2012-12-31,1551152,2013 (1888)
|
6 |
+
ABNB,Airbnb,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","San Francisco, California",2023-09-18,1559720,2008
|
7 |
+
ABT,Abbott,Health Care,Health Care Equipment,"North Chicago, Illinois",1957-03-04,1800,1888
|
8 |
+
ACGL,Arch Capital Group,Financials,Property & Casualty Insurance,"Hamilton, Bermuda",2022-11-01,947484,1995
|
9 |
+
ACN,Accenture,Information Technology,IT Consulting & Other Services,"Dublin, Ireland",2011-07-06,1467373,1989
|
10 |
+
ADBE,Adobe Inc.,Information Technology,Application Software,"San Jose, California",1997-05-05,796343,1982
|
11 |
+
ADI,Analog Devices,Information Technology,Semiconductors,"Wilmington, Massachusetts",1999-10-12,6281,1965
|
12 |
+
ADM,Archer-Daniels-Midland,Consumer Staples,Agricultural Products & Services,"Chicago, Illinois",1957-03-04,7084,1902
|
13 |
+
ADP,Automated Data Processing,Industrials,Human Resource & Employment Services,"Roseland, New Jersey",1981-03-31,8670,1949
|
14 |
+
ADSK,Autodesk,Information Technology,Application Software,"San Francisco, California",1989-12-01,769397,1982
|
15 |
+
AEE,Ameren,Utilities,Multi-Utilities,"St. Louis, Missouri",1991-09-19,1002910,1902
|
16 |
+
AEP,American Electric Power,Utilities,Electric Utilities,"Columbus, Ohio",1957-03-04,4904,1906
|
17 |
+
AES,AES Corporation,Utilities,Independent Power Producers & Energy Traders,"Arlington, Virginia",1998-10-02,874761,1981
|
18 |
+
AFL,Aflac,Financials,Life & Health Insurance,"Columbus, Georgia",1999-05-28,4977,1955
|
19 |
+
AIG,American International Group,Financials,Multi-line Insurance,"New York City, New York",1980-03-31,5272,1919
|
20 |
+
AIZ,Assurant,Financials,Multi-line Insurance,"Atlanta, Georgia",2007-04-10,1267238,1892
|
21 |
+
AJG,Arthur J. Gallagher & Co.,Financials,Insurance Brokers,"Rolling Meadows, Illinois",2016-05-31,354190,1927
|
22 |
+
AKAM,Akamai,Information Technology,Internet Services & Infrastructure,"Cambridge, Massachusetts",2007-07-12,1086222,1998
|
23 |
+
ALB,Albemarle Corporation,Materials,Specialty Chemicals,"Charlotte, North Carolina",2016-07-01,915913,1994
|
24 |
+
ALGN,Align Technology,Health Care,Health Care Supplies,"Tempe, Arizona",2017-06-19,1097149,1997
|
25 |
+
ALL,Allstate,Financials,Property & Casualty Insurance,"Northbrook, Illinois",1995-07-13,899051,1931
|
26 |
+
ALLE,Allegion,Industrials,Building Products,"Dublin, Ireland",2013-12-02,1579241,1908
|
27 |
+
AMAT,Applied Materials,Information Technology,Semiconductor Materials & Equipment,"Santa Clara, California",1995-03-16,6951,1967
|
28 |
+
AMCR,Amcor,Materials,Paper & Plastic Packaging Products & Materials,"Warmley, Bristol, United Kingdom",2019-06-07,1748790,2019 (1860)
|
29 |
+
AMD,Advanced Micro Devices,Information Technology,Semiconductors,"Santa Clara, California",2017-03-20,2488,1969
|
30 |
+
AME,Ametek,Industrials,Electrical Components & Equipment,"Berwyn, Pennsylvania",2013-09-23,1037868,1930
|
31 |
+
AMGN,Amgen,Health Care,Biotechnology,"Thousand Oaks, California",1992-01-02,318154,1980
|
32 |
+
AMP,Ameriprise Financial,Financials,Asset Management & Custody Banks,"Minneapolis, Minnesota",2005-10-03,820027,1894
|
33 |
+
AMT,American Tower,Real Estate,Telecom Tower REITs,"Boston, Massachusetts",2007-11-19,1053507,1995
|
34 |
+
AMZN,Amazon,Consumer Discretionary,Broadline Retail,"Seattle, Washington",2005-11-18,1018724,1994
|
35 |
+
ANET,Arista Networks,Information Technology,Communications Equipment,"Santa Clara, California",2018-08-28,1596532,2004
|
36 |
+
ANSS,Ansys,Information Technology,Application Software,"Canonsburg, Pennsylvania",2017-06-19,1013462,1969
|
37 |
+
AON,Aon,Financials,Insurance Brokers,"London, UK",1996-04-23,315293,1982 (1919)
|
38 |
+
AOS,A. O. Smith,Industrials,Building Products,"Milwaukee, Wisconsin",2017-07-26,91142,1916
|
39 |
+
APA,APA Corporation,Energy,Oil & Gas Exploration & Production,"Houston, Texas",1997-07-28,1841666,1954
|
40 |
+
APD,Air Products and Chemicals,Materials,Industrial Gases,"Allentown, Pennsylvania",1985-04-30,2969,1940
|
41 |
+
APH,Amphenol,Information Technology,Electronic Components,"Wallingford, Connecticut",2008-09-30,820313,1932
|
42 |
+
APTV,Aptiv,Consumer Discretionary,Automotive Parts & Equipment,"Dublin, Ireland",2012-12-24,1521332,1994
|
43 |
+
ARE,Alexandria Real Estate Equities,Real Estate,Office REITs,"Pasadena, California",2017-03-20,1035443,1994
|
44 |
+
ATO,Atmos Energy,Utilities,Gas Utilities,"Dallas, Texas",2019-02-15,731802,1906
|
45 |
+
AVB,AvalonBay Communities,Real Estate,Multi-Family Residential REITs,"Arlington, Virginia",2007-01-10,915912,1978
|
46 |
+
AVGO,Broadcom Inc.,Information Technology,Semiconductors,"Palo Alto, California",2014-05-08,1730168,1961
|
47 |
+
AVY,Avery Dennison,Materials,Paper & Plastic Packaging Products & Materials,"Mentor, Ohio",1987-12-31,8818,1990
|
48 |
+
AWK,American Water Works,Utilities,Water Utilities,"Camden, New Jersey",2016-03-04,1410636,1886
|
49 |
+
AXON,Axon Enterprise,Industrials,Aerospace & Defense,"Scottsdale, Arizona",2023-05-04,1069183,1993
|
50 |
+
AXP,American Express,Financials,Consumer Finance,"New York City, New York",1976-06-30,4962,1850
|
51 |
+
AZO,AutoZone,Consumer Discretionary,Automotive Retail,"Memphis, Tennessee",1997-01-02,866787,1979
|
52 |
+
BA,Boeing,Industrials,Aerospace & Defense,"Arlington, Virginia",1957-03-04,12927,1916
|
53 |
+
BAC,Bank of America,Financials,Diversified Banks,"Charlotte, North Carolina",1976-06-30,70858,1998 (1923 / 1874)
|
54 |
+
BALL,Ball Corporation,Materials,"Metal, Glass & Plastic Containers","Broomfield, Colorado",1984-10-31,9389,1880
|
55 |
+
BAX,Baxter International,Health Care,Health Care Equipment,"Deerfield, Illinois",1972-09-30,10456,1931
|
56 |
+
BBWI,"Bath & Body Works, Inc.",Consumer Discretionary,Other Specialty Retail,"Columbus, Ohio",1983-09-30,701985,1963
|
57 |
+
BBY,Best Buy,Consumer Discretionary,Computer & Electronics Retail,"Richfield, Minnesota",1999-06-29,764478,1966
|
58 |
+
BDX,Becton Dickinson,Health Care,Health Care Equipment,"Franklin Lakes, New Jersey",1972-09-30,10795,1897
|
59 |
+
BEN,Franklin Templeton,Financials,Asset Management & Custody Banks,"San Mateo, California",1998-04-30,38777,1947
|
60 |
+
BF.B,Brown–Forman,Consumer Staples,Distillers & Vintners,"Louisville, Kentucky",1982-10-31,14693,1870
|
61 |
+
BG,Bunge Global SA,Consumer Staples,Agricultural Products & Services,"Chesterfield, Missouri",2023-03-15,1996862,1818
|
62 |
+
BIIB,Biogen,Health Care,Biotechnology,"Cambridge, Massachusetts",2003-11-13,875045,1978
|
63 |
+
BIO,Bio-Rad,Health Care,Life Sciences Tools & Services,"Hercules, California",2020-06-22,12208,1952
|
64 |
+
BK,Bank of New York Mellon,Financials,Asset Management & Custody Banks,"New York City, New York",1995-03-31,1390777,1784
|
65 |
+
BKNG,Booking Holdings,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Norwalk, Connecticut",2009-11-06,1075531,1996
|
66 |
+
BKR,Baker Hughes,Energy,Oil & Gas Equipment & Services,"Houston, Texas",2017-07-07,1701605,2017
|
67 |
+
BLDR,Builders FirstSource,Industrials,Building Products,"Irving, Texas",2023-12-18,1316835,1998
|
68 |
+
BLK,BlackRock,Financials,Asset Management & Custody Banks,"New York City, New York",2011-04-04,1364742,1988
|
69 |
+
BMY,Bristol Myers Squibb,Health Care,Pharmaceuticals,"New York City, New York",1957-03-04,14272,1989 (1887)
|
70 |
+
BR,Broadridge Financial Solutions,Industrials,Data Processing & Outsourced Services,"Lake Success, New York",2018-06-18,1383312,1962
|
71 |
+
BRK.B,Berkshire Hathaway,Financials,Multi-Sector Holdings,"Omaha, Nebraska",2010-02-16,1067983,1839
|
72 |
+
BRO,Brown & Brown,Financials,Insurance Brokers,"Daytona Beach, Florida",2021-09-20,79282,1939
|
73 |
+
BSX,Boston Scientific,Health Care,Health Care Equipment,"Marlborough, Massachusetts",1995-02-24,885725,1979
|
74 |
+
BWA,BorgWarner,Consumer Discretionary,Automotive Parts & Equipment,"Auburn Hills, Michigan",2011-12-19,908255,1880
|
75 |
+
BX,Blackstone,Financials,Asset Management & Custody Banks,"New York City, New York",2023-09-18,1393818,1985
|
76 |
+
BXP,Boston Properties,Real Estate,Office REITs,"Boston, Massachusetts",2006-04-03,1037540,1970
|
77 |
+
C,Citigroup,Financials,Diversified Banks,"New York City, New York",1988-05-31,831001,1998
|
78 |
+
CAG,Conagra Brands,Consumer Staples,Packaged Foods & Meats,"Chicago, Illinois",1983-08-31,23217,1919
|
79 |
+
CAH,Cardinal Health,Health Care,Health Care Distributors,"Dublin, Ohio",1997-05-27,721371,1971
|
80 |
+
CARR,Carrier Global,Industrials,Building Products,"Palm Beach Gardens, Florida",2020-04-03,1783180,"2020 (1915, United Technologies spinoff)"
|
81 |
+
CAT,Caterpillar Inc.,Industrials,Construction Machinery & Heavy Transportation Equipment,"Irving, Texas",1957-03-04,18230,1925
|
82 |
+
CB,Chubb Limited,Financials,Property & Casualty Insurance,"Zurich, Switzerland",2010-07-15,896159,1985
|
83 |
+
CBOE,Cboe Global Markets,Financials,Financial Exchanges & Data,"Chicago, Illinois",2017-03-01,1374310,1973
|
84 |
+
CBRE,CBRE Group,Real Estate,Real Estate Services,"Dallas, Texas",2006-11-10,1138118,1906
|
85 |
+
CCI,Crown Castle,Real Estate,Telecom Tower REITs,"Houston, Texas",2012-03-14,1051470,1994
|
86 |
+
CCL,Carnival,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Miami, Florida",1998-12-22,815097,1972
|
87 |
+
CDNS,Cadence Design Systems,Information Technology,Application Software,"San Jose, California",2017-09-18,813672,1988
|
88 |
+
CDW,CDW,Information Technology,Technology Distributors,"Lincolnshire, Illinois",2019-09-23,1402057,1984
|
89 |
+
CE,Celanese,Materials,Specialty Chemicals,"Irving, Texas",2018-12-24,1306830,1918
|
90 |
+
CEG,Constellation Energy,Utilities,Electric Utilities,"Baltimore, Maryland",2022-02-02,1868275,1999
|
91 |
+
CF,CF Industries,Materials,Fertilizers & Agricultural Chemicals,"Deerfield, Illinois",2008-08-27,1324404,1946
|
92 |
+
CFG,Citizens Financial Group,Financials,Regional Banks,"Providence, Rhode Island",2016-01-29,759944,1828
|
93 |
+
CHD,Church & Dwight,Consumer Staples,Household Products,"Ewing, New Jersey",2015-12-29,313927,1847
|
94 |
+
CHRW,CH Robinson,Industrials,Air Freight & Logistics,"Eden Prairie, Minnesota",2007-03-02,1043277,1905
|
95 |
+
CHTR,Charter Communications,Communication Services,Cable & Satellite,"Stamford, Connecticut",2016-09-08,1091667,1993
|
96 |
+
CI,Cigna,Health Care,Health Care Services,"Bloomfield, Connecticut",1976-06-30,1739940,1982
|
97 |
+
CINF,Cincinnati Financial,Financials,Property & Casualty Insurance,"Fairfield, Ohio",1997-12-18,20286,1950
|
98 |
+
CL,Colgate-Palmolive,Consumer Staples,Household Products,"New York City, New York",1957-03-04,21665,1806
|
99 |
+
CLX,Clorox,Consumer Staples,Household Products,"Oakland, California",1969-03-31,21076,1913
|
100 |
+
CMA,Comerica,Financials,Diversified Banks,"Dallas, Texas",1995-12-01,28412,1849
|
101 |
+
CMCSA,Comcast,Communication Services,Cable & Satellite,"Philadelphia, Pennsylvania",2002-11-19,1166691,1963
|
102 |
+
CME,CME Group,Financials,Financial Exchanges & Data,"Chicago, Illinois",2006-08-11,1156375,1848
|
103 |
+
CMG,Chipotle Mexican Grill,Consumer Discretionary,Restaurants,"Newport Beach, California",2011-04-28,1058090,1993
|
104 |
+
CMI,Cummins,Industrials,Construction Machinery & Heavy Transportation Equipment,"Columbus, Indiana",1965-03-31,26172,1919
|
105 |
+
CMS,CMS Energy,Utilities,Multi-Utilities,"Jackson, Michigan",1957-03-04,811156,1886
|
106 |
+
CNC,Centene Corporation,Health Care,Managed Health Care,"St. Louis, Missouri",2016-03-30,1071739,1984
|
107 |
+
CNP,CenterPoint Energy,Utilities,Multi-Utilities,"Houston, Texas",1985-07-31,1130310,1882
|
108 |
+
COF,Capital One,Financials,Consumer Finance,"Tysons Corner, Virginia",1998-07-01,927628,1994
|
109 |
+
COO,CooperCompanies,Health Care,Health Care Supplies,"San Ramon, California",2016-09-23,711404,1958
|
110 |
+
COP,ConocoPhillips,Energy,Oil & Gas Exploration & Production,"Houston, Texas",1957-03-04,1163165,2002
|
111 |
+
COR,Cencora,Health Care,Health Care Distributors,"Conshohocken, Pennsylvania",2001-08-30,1140859,1985
|
112 |
+
COST,Costco,Consumer Staples,Consumer Staples Merchandise Retail,"Issaquah, Washington",1993-10-01,909832,1976
|
113 |
+
CPB,Campbell Soup Company,Consumer Staples,Packaged Foods & Meats,"Camden, New Jersey",1957-03-04,16732,1869
|
114 |
+
CPRT,Copart,Industrials,Diversified Support Services,"Dallas, Texas",2018-07-02,900075,1982
|
115 |
+
CPT,Camden Property Trust,Real Estate,Multi-Family Residential REITs,"Houston, Texas",2022-04-04,906345,1981
|
116 |
+
CRL,Charles River Laboratories,Health Care,Life Sciences Tools & Services,"Wilmington, Massachusetts",2021-05-14,1100682,1947
|
117 |
+
CRM,Salesforce,Information Technology,Application Software,"San Francisco, California",2008-09-15,1108524,1999
|
118 |
+
CSCO,Cisco,Information Technology,Communications Equipment,"San Jose, California",1993-12-01,858877,1984
|
119 |
+
CSGP,CoStar Group,Real Estate,Real Estate Services,"Washington, D.C.",2022-09-19,1057352,1987
|
120 |
+
CSX,CSX,Industrials,Rail Transportation,"Jacksonville, Florida",1957-03-04,277948,1980
|
121 |
+
CTAS,Cintas,Industrials,Diversified Support Services,"Mason, Ohio",2001-03-01,723254,1929
|
122 |
+
CTLT,Catalent,Health Care,Pharmaceuticals,"Somerset, New Jersey",2020-09-21,1596783,2007
|
123 |
+
CTRA,Coterra,Energy,Oil & Gas Exploration & Production,"Houston, Texas",2008-06-23,858470,2021 (1989)
|
124 |
+
CTSH,Cognizant,Information Technology,IT Consulting & Other Services,"Teaneck, New Jersey",2006-11-17,1058290,1994
|
125 |
+
CTVA,Corteva,Materials,Fertilizers & Agricultural Chemicals,"Indianapolis, Indiana",2019-06-03,1755672,2019
|
126 |
+
CVS,CVS Health,Health Care,Health Care Services,"Woonsocket, Rhode Island",1957-03-04,64803,1996
|
127 |
+
CVX,Chevron Corporation,Energy,Integrated Oil & Gas,"San Ramon, California",1957-03-04,93410,1879
|
128 |
+
CZR,Caesars Entertainment,Consumer Discretionary,Casinos & Gaming,"Reno, Nevada",2021-03-22,1590895,1973
|
129 |
+
D,Dominion Energy,Utilities,Multi-Utilities,"Richmond, Virginia",2016-11-30,715957,1983
|
130 |
+
DAL,Delta Air Lines,Industrials,Passenger Airlines,"Atlanta, Georgia",2013-09-11,27904,1929
|
131 |
+
DAY,Dayforce,Industrials,Human Resource & Employment Services,"Minneapolis, Minnesota",2021-09-20,1725057,1992
|
132 |
+
DD,DuPont,Materials,Specialty Chemicals,"Wilmington, Delaware",2019-04-02,1666700,2017 (1802)
|
133 |
+
DE,John Deere,Industrials,Agricultural & Farm Machinery,"Moline, Illinois",1957-03-04,315189,1837
|
134 |
+
DECK,Deckers Brands,Consumer Discretionary,Footwear,"Goleta, California",2024-03-01,910521,1973
|
135 |
+
DFS,Discover Financial,Financials,Consumer Finance,"Riverwoods, Illinois",2007-07-02,1393612,1985
|
136 |
+
DG,Dollar General,Consumer Staples,Consumer Staples Merchandise Retail,"Goodlettsville, Tennessee",2012-12-03,29534,1939
|
137 |
+
DGX,Quest Diagnostics,Health Care,Health Care Services,"Secaucus, New Jersey",2002-12-12,1022079,1967
|
138 |
+
DHI,DR Horton,Consumer Discretionary,Homebuilding,"Arlington, Texas",2005-06-22,882184,1978
|
139 |
+
DHR,Danaher Corporation,Health Care,Life Sciences Tools & Services,"Washington, D.C.",1998-11-18,313616,1969
|
140 |
+
DIS,Walt Disney,Communication Services,Movies & Entertainment,"Burbank, California",1976-06-30,1744489,1923
|
141 |
+
DLR,Digital Realty,Real Estate,Data Center REITs,"Austin, Texas",2016-05-18,1297996,2004
|
142 |
+
DLTR,Dollar Tree,Consumer Staples,Consumer Staples Merchandise Retail,"Chesapeake, Virginia",2011-12-19,935703,1986
|
143 |
+
DOC,Healthpeak,Real Estate,Health Care REITs,"Denver, Colorado",2008-03-31,765880,1985
|
144 |
+
DOV,Dover Corporation,Industrials,Industrial Machinery & Supplies & Components,"Downers Grove, Illinois",1985-10-31,29905,1955
|
145 |
+
DOW,Dow Inc.,Materials,Commodity Chemicals,"Midland, Michigan",2019-04-01,1751788,2019 (1897)
|
146 |
+
DPZ,Domino's,Consumer Discretionary,Restaurants,"Ann Arbor, Michigan",2020-05-12,1286681,1960
|
147 |
+
DRI,Darden Restaurants,Consumer Discretionary,Restaurants,"Orlando, Florida",1995-05-31,940944,1938
|
148 |
+
DTE,DTE Energy,Utilities,Multi-Utilities,"Detroit, Michigan",1957-03-04,936340,1995
|
149 |
+
DUK,Duke Energy,Utilities,Electric Utilities,"Charlotte, North Carolina",1976-06-30,1326160,1904
|
150 |
+
DVA,DaVita Inc.,Health Care,Health Care Services,"Denver, Colorado",2008-07-31,927066,1979
|
151 |
+
DVN,Devon Energy,Energy,Oil & Gas Exploration & Production,"Oklahoma City, Oklahoma",2000-08-30,1090012,1971
|
152 |
+
DXCM,Dexcom,Health Care,Health Care Equipment,"San Diego, California",2020-05-12,1093557,1999
|
153 |
+
EA,Electronic Arts,Communication Services,Interactive Home Entertainment,"Redwood City, California",2002-07-22,712515,1982
|
154 |
+
EBAY,eBay,Consumer Discretionary,Broadline Retail,"San Jose, California",2002-07-22,1065088,1995
|
155 |
+
ECL,Ecolab,Materials,Specialty Chemicals,"Saint Paul, Minnesota",1989-01-31,31462,1923
|
156 |
+
ED,Consolidated Edison,Utilities,Multi-Utilities,"New York City, New York",1957-03-04,1047862,1823
|
157 |
+
EFX,Equifax,Industrials,Research & Consulting Services,"Atlanta, Georgia",1997-06-19,33185,1899
|
158 |
+
EG,Everest Re,Financials,Reinsurance,"Hamilton, Bermuda",2017-06-19,1095073,1973
|
159 |
+
EIX,Edison International,Utilities,Electric Utilities,"Rosemead, California",1957-03-04,827052,1886
|
160 |
+
EL,Estée Lauder Companies (The),Consumer Staples,Personal Care Products,"New York City, New York",2006-01-05,1001250,1946
|
161 |
+
ELV,Elevance Health,Health Care,Managed Health Care,"Indianapolis, Indiana",2002-07-25,1156039,2014 (1946)
|
162 |
+
EMN,Eastman Chemical Company,Materials,Specialty Chemicals,"Kingsport, Tennessee",1994-01-01,915389,1920
|
163 |
+
EMR,Emerson Electric,Industrials,Electrical Components & Equipment,"Ferguson, Missouri",1965-03-31,32604,1890
|
164 |
+
ENPH,Enphase,Information Technology,Semiconductor Materials & Equipment,"Fremont, California",2021-01-07,1463101,2006
|
165 |
+
EOG,EOG Resources,Energy,Oil & Gas Exploration & Production,"Houston, Texas",2000-11-02,821189,1999
|
166 |
+
EPAM,EPAM Systems,Information Technology,IT Consulting & Other Services,"Newtown, Pennsylvania",2021-12-14,1352010,1993
|
167 |
+
EQIX,Equinix,Real Estate,Data Center REITs,"Redwood City, California",2015-03-20,1101239,1998
|
168 |
+
EQR,Equity Residential,Real Estate,Multi-Family Residential REITs,"Chicago, Illinois",2001-12-03,906107,1969
|
169 |
+
EQT,EQT,Energy,Oil & Gas Exploration & Production,"Pittsburgh, Pennsylvania",2022-10-03,33213,1888
|
170 |
+
ES,Eversource,Utilities,Electric Utilities,"Hartford, Connecticut",2009-07-24,72741,1966
|
171 |
+
ESS,Essex Property Trust,Real Estate,Multi-Family Residential REITs,"San Mateo, California",2014-04-02,920522,1971
|
172 |
+
ETN,Eaton Corporation,Industrials,Electrical Components & Equipment,"Dublin, Ireland",1957-03-04,1551182,1911
|
173 |
+
ETR,Entergy,Utilities,Electric Utilities,"New Orleans, Louisiana",1957-03-04,65984,1913
|
174 |
+
ETSY,Etsy,Consumer Discretionary,Broadline Retail,"New York City, New York",2020-09-21,1370637,2005
|
175 |
+
EVRG,Evergy,Utilities,Electric Utilities,"Kansas City, Missouri",2018-06-05,1711269,1909
|
176 |
+
EW,Edwards Lifesciences,Health Care,Health Care Equipment,"Irvine, California",2011-04-01,1099800,1958
|
177 |
+
EXC,Exelon,Utilities,Electric Utilities,"Chicago, Illinois",1957-03-04,1109357,2000
|
178 |
+
EXPD,Expeditors International,Industrials,Air Freight & Logistics,"Seattle, Washington",2007-10-10,746515,1979
|
179 |
+
EXPE,Expedia Group,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Seattle, Washington",2007-10-02,1324424,1996
|
180 |
+
EXR,Extra Space Storage,Real Estate,Self-Storage REITs,"Salt Lake City, Utah",2016-01-19,1289490,1977
|
181 |
+
F,Ford Motor Company,Consumer Discretionary,Automobile Manufacturers,"Dearborn, Michigan",1957-03-04,37996,1903
|
182 |
+
FANG,Diamondback Energy,Energy,Oil & Gas Exploration & Production,"Midland, Texas",2018-12-03,1539838,2007
|
183 |
+
FAST,Fastenal,Industrials,Trading Companies & Distributors,"Winona, Minnesota",2008-09-15,815556,1967
|
184 |
+
FCX,Freeport-McMoRan,Materials,Copper,"Phoenix, Arizona",2011-07-01,831259,1912
|
185 |
+
FDS,FactSet,Financials,Financial Exchanges & Data,"Norwalk, Connecticut",2021-12-20,1013237,1978
|
186 |
+
FDX,FedEx,Industrials,Air Freight & Logistics,"Memphis, Tennessee",1980-12-31,1048911,1971
|
187 |
+
FE,FirstEnergy,Utilities,Electric Utilities,"Akron, Ohio",1997-11-28,1031296,1997
|
188 |
+
FFIV,"F5, Inc.",Information Technology,Communications Equipment,"Seattle, Washington",2010-12-20,1048695,1996
|
189 |
+
FI,Fiserv,Financials,Transaction & Payment Processing Services,"Brookfield, Wisconsin",2001-04-02,798354,1984
|
190 |
+
FICO,Fair Isaac,Information Technology,Application Software,"Bozeman, Montana",2023-03-20,814547,1956
|
191 |
+
FIS,Fidelity National Information Services,Financials,Transaction & Payment Processing Services,"Jacksonville, Florida",2006-11-10,1136893,1968
|
192 |
+
FITB,Fifth Third Bank,Financials,Diversified Banks,"Cincinnati, Ohio",1996-03-29,35527,1858
|
193 |
+
FLT,Fleetcor,Financials,Transaction & Payment Processing Services,"Atlanta, Georgia",2018-06-20,1175454,2000
|
194 |
+
FMC,FMC Corporation,Materials,Fertilizers & Agricultural Chemicals,"Philadelphia, Pennsylvania",2009-08-19,37785,1883
|
195 |
+
FOX,Fox Corporation (Class B),Communication Services,Broadcasting,"New York City, New York",2019-03-04,1754301,2019
|
196 |
+
FOXA,Fox Corporation (Class A),Communication Services,Broadcasting,"New York City, New York",2019-03-04,1754301,2019
|
197 |
+
FRT,Federal Realty,Real Estate,Retail REITs,"Rockville, Maryland",2016-02-01,34903,1962
|
198 |
+
FSLR,First Solar,Information Technology,Semiconductors,"Tempe, Arizona",2022-12-19,1274494,1999
|
199 |
+
FTNT,Fortinet,Information Technology,Systems Software,"Sunnyvale, California",2018-10-11,1262039,2000
|
200 |
+
FTV,Fortive,Industrials,Industrial Machinery & Supplies & Components,"Everett, Washington",2016-07-01,1659166,2016
|
201 |
+
GD,General Dynamics,Industrials,Aerospace & Defense,"Falls Church, Virginia",1957-03-04,40533,1899
|
202 |
+
GE,General Electric,Industrials,Industrial Conglomerates,"Boston, Massachusetts",1957-03-04,40545,1892
|
203 |
+
GEHC,GE HealthCare,Health Care,Health Care Equipment,"Chicago, Illinois",2023-01-04,1932393,1994
|
204 |
+
GEN,Gen Digital,Information Technology,Systems Software,"Tempe, Arizona",2003-03-25,849399,1982
|
205 |
+
GILD,Gilead Sciences,Health Care,Biotechnology,"Foster City, California",2004-07-01,882095,1987
|
206 |
+
GIS,General Mills,Consumer Staples,Packaged Foods & Meats,"Golden Valley, Minnesota",1957-03-04,40704,1856
|
207 |
+
GL,Globe Life,Financials,Life & Health Insurance,"McKinney, Texas",1989-04-30,320335,1900
|
208 |
+
GLW,Corning Inc.,Information Technology,Electronic Components,"Corning, New York",1995-02-27,24741,1851
|
209 |
+
GM,General Motors,Consumer Discretionary,Automobile Manufacturers,"Detroit, Michigan",2013-06-06,1467858,1908
|
210 |
+
GNRC,Generac,Industrials,Electrical Components & Equipment,"Waukesha, Wisconsin",2021-03-22,1474735,1959
|
211 |
+
GOOG,Alphabet Inc. (Class C),Communication Services,Interactive Media & Services,"Mountain View, California",2006-04-03,1652044,1998
|
212 |
+
GOOGL,Alphabet Inc. (Class A),Communication Services,Interactive Media & Services,"Mountain View, California",2014-04-03,1652044,1998
|
213 |
+
GPC,Genuine Parts Company,Consumer Discretionary,Distributors,"Atlanta, Georgia",1973-12-31,40987,1925
|
214 |
+
GPN,Global Payments,Financials,Transaction & Payment Processing Services,"Atlanta, Georgia",2016-04-25,1123360,2000
|
215 |
+
GRMN,Garmin,Consumer Discretionary,Consumer Electronics,"Schaffhausen, Switzerland",2012-12-12,1121788,1989
|
216 |
+
GS,Goldman Sachs,Financials,Investment Banking & Brokerage,"New York City, New York",2002-07-22,886982,1869
|
217 |
+
GWW,W. W. Grainger,Industrials,Industrial Machinery & Supplies & Components,"Lake Forest, Illinois",1981-06-30,277135,1927
|
218 |
+
HAL,Halliburton,Energy,Oil & Gas Equipment & Services,"Houston, Texas",1957-03-04,45012,1919
|
219 |
+
HAS,Hasbro,Consumer Discretionary,Leisure Products,"Pawtucket, Rhode Island",1984-09-30,46080,1923
|
220 |
+
HBAN,Huntington Bancshares,Financials,Regional Banks,"Columbus, Ohio; Detroit, Michigan",1997-08-28,49196,1866
|
221 |
+
HCA,HCA Healthcare,Health Care,Health Care Facilities,"Nashville, Tennessee",2015-01-27,860730,1968
|
222 |
+
HD,Home Depot (The),Consumer Discretionary,Home Improvement Retail,"Atlanta, Georgia",1988-03-31,354950,1978
|
223 |
+
HES,Hess Corporation,Energy,Integrated Oil & Gas,"New York City, New York",1984-05-31,4447,1919
|
224 |
+
HIG,Hartford (The),Financials,Property & Casualty Insurance,"Hartford, Connecticut",1957-03-04,874766,1810
|
225 |
+
HII,Huntington Ingalls Industries,Industrials,Aerospace & Defense,"Newport News, Virginia",2018-01-03,1501585,2011
|
226 |
+
HLT,Hilton Worldwide,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Tysons Corner, Virginia",2017-06-19,1585689,1919
|
227 |
+
HOLX,Hologic,Health Care,Health Care Equipment,"Marlborough, Massachusetts",2016-03-30,859737,1985
|
228 |
+
HON,Honeywell,Industrials,Industrial Conglomerates,"Charlotte, North Carolina",1957-03-04,773840,1906
|
229 |
+
HPE,Hewlett Packard Enterprise,Information Technology,"Technology Hardware, Storage & Peripherals","Houston, Texas",2015-11-02,1645590,2015
|
230 |
+
HPQ,HP Inc.,Information Technology,"Technology Hardware, Storage & Peripherals","Palo Alto, California",1974-12-31,47217,1939 (2015)
|
231 |
+
HRL,Hormel Foods,Consumer Staples,Packaged Foods & Meats,"Austin, Minnesota",2009-03-04,48465,1891
|
232 |
+
HSIC,Henry Schein,Health Care,Health Care Distributors,"Melville, New York",2015-03-17,1000228,1932
|
233 |
+
HST,Host Hotels & Resorts,Real Estate,Hotel & Resort REITs,"Bethesda, Maryland",2007-03-20,1070750,1993
|
234 |
+
HSY,Hershey's,Consumer Staples,Packaged Foods & Meats,"Hershey, Pennsylvania",1957-03-04,47111,1894
|
235 |
+
HUBB,Hubbell Incorporated,Industrials,Industrial Machinery & Supplies & Components,"Shelton, Connecticut",2023-10-18,48898,1888
|
236 |
+
HUM,Humana,Health Care,Managed Health Care,"Louisville, Kentucky",2012-12-10,49071,1961
|
237 |
+
HWM,Howmet Aerospace,Industrials,Aerospace & Defense,"Pittsburgh, Pennsylvania",2016-10-21,4281,1888
|
238 |
+
IBM,IBM,Information Technology,IT Consulting & Other Services,"Armonk, New York",1957-03-04,51143,1911
|
239 |
+
ICE,Intercontinental Exchange,Financials,Financial Exchanges & Data,"Atlanta, Georgia",2007-09-26,1571949,2000
|
240 |
+
IDXX,Idexx Laboratories,Health Care,Health Care Equipment,"Westbrook, Maine",2017-01-05,874716,1983
|
241 |
+
IEX,IDEX Corporation,Industrials,Industrial Machinery & Supplies & Components,"Lake Forest, Illinois",2019-08-09,832101,1988
|
242 |
+
IFF,International Flavors & Fragrances,Materials,Specialty Chemicals,"New York City, New York",1976-03-31,51253,1958 (1889)
|
243 |
+
ILMN,Illumina,Health Care,Life Sciences Tools & Services,"San Diego, California",2015-11-19,1110803,1998
|
244 |
+
INCY,Incyte,Health Care,Biotechnology,"Wilmington, Delaware",2017-02-28,879169,1991
|
245 |
+
INTC,Intel,Information Technology,Semiconductors,"Santa Clara, California",1976-12-31,50863,1968
|
246 |
+
INTU,Intuit,Information Technology,Application Software,"Mountain View, California",2000-12-05,896878,1983
|
247 |
+
INVH,Invitation Homes,Real Estate,Single-Family Residential REITs,"Dallas, Texas",2022-09-19,1687229,2012
|
248 |
+
IP,International Paper,Materials,Paper & Plastic Packaging Products & Materials,"Memphis, Tennessee",1957-03-04,51434,1898
|
249 |
+
IPG,Interpublic Group of Companies (The),Communication Services,Advertising,"New York City, New York",1992-10-01,51644,1961 (1930)
|
250 |
+
IQV,IQVIA,Health Care,Life Sciences Tools & Services,"Durham, North Carolina",2017-08-29,1478242,1982
|
251 |
+
IR,Ingersoll Rand,Industrials,Industrial Machinery & Supplies & Components,"Davidson, North Carolina",2020-03-03,1699150,1859
|
252 |
+
IRM,Iron Mountain,Real Estate,Other Specialized REITs,"Boston, Massachusetts",2009-01-06,1020569,1951
|
253 |
+
ISRG,Intuitive Surgical,Health Care,Health Care Equipment,"Sunnyvale, California",2008-06-02,1035267,1995
|
254 |
+
IT,Gartner,Information Technology,IT Consulting & Other Services,"Stamford, Connecticut",2017-04-05,749251,1979
|
255 |
+
ITW,Illinois Tool Works,Industrials,Industrial Machinery & Supplies & Components,"Glenview, Illinois",1986-02-28,49826,1912
|
256 |
+
IVZ,Invesco,Financials,Asset Management & Custody Banks,"Atlanta, Georgia",2008-08-21,914208,1935
|
257 |
+
J,Jacobs Solutions,Industrials,Construction & Engineering,"Dallas, Texas",2007-10-26,52988,1947
|
258 |
+
JBHT,J.B. Hunt,Industrials,Cargo Ground Transportation,"Lowell, Arkansas",2015-07-01,728535,1961
|
259 |
+
JBL,Jabil,Information Technology,Electronic Manufacturing Services,"St. Petersburg, Florida",2023-12-18,898293,1966
|
260 |
+
JCI,Johnson Controls,Industrials,Building Products,"Cork, Ireland",2010-08-27,833444,1885
|
261 |
+
JKHY,Jack Henry & Associates,Financials,Transaction & Payment Processing Services,"Monett, Missouri",2018-11-13,779152,1976
|
262 |
+
JNJ,Johnson & Johnson,Health Care,Pharmaceuticals,"New Brunswick, New Jersey",1973-06-30,200406,1886
|
263 |
+
JNPR,Juniper Networks,Information Technology,Communications Equipment,"Sunnyvale, California",2006-06-02,1043604,1996
|
264 |
+
JPM,JPMorgan Chase,Financials,Diversified Banks,"New York City, New York",1975-06-30,19617,2000 (1799 / 1871)
|
265 |
+
K,Kellanova,Consumer Staples,Packaged Foods & Meats,"Chicago, Illinois",1989-09-11,55067,1906
|
266 |
+
KDP,Keurig Dr Pepper,Consumer Staples,Soft Drinks & Non-alcoholic Beverages,"Burlington, Massachusetts",2022-06-21,1418135,1981
|
267 |
+
KEY,KeyCorp,Financials,Regional Banks,"Cleveland, Ohio",1994-03-01,91576,1825
|
268 |
+
KEYS,Keysight,Information Technology,Electronic Equipment & Instruments,"Santa Rosa, California",2018-11-06,1601046,2014 (1939)
|
269 |
+
KHC,Kraft Heinz,Consumer Staples,Packaged Foods & Meats,"Chicago, Illinois; Pittsburgh, Pennsylvania",2015-07-06,1637459,2015 (1869)
|
270 |
+
KIM,Kimco Realty,Real Estate,Retail REITs,"New Hyde Park, New York",2006-04-04,879101,1958
|
271 |
+
KLAC,KLA Corporation,Information Technology,Semiconductor Materials & Equipment,"Milpitas, California",1997-09-30,319201,1975/1977 (1997)
|
272 |
+
KMB,Kimberly-Clark,Consumer Staples,Household Products,"Irving, Texas",1957-03-04,55785,1872
|
273 |
+
KMI,Kinder Morgan,Energy,Oil & Gas Storage & Transportation,"Houston, Texas",2012-05-25,1506307,1997
|
274 |
+
KMX,CarMax,Consumer Discretionary,Automotive Retail,"Richmond, Virginia",2010-06-28,1170010,1993
|
275 |
+
KO,Coca-Cola Company (The),Consumer Staples,Soft Drinks & Non-alcoholic Beverages,"Atlanta, Georgia",1957-03-04,21344,1886
|
276 |
+
KR,Kroger,Consumer Staples,Food Retail,"Cincinnati, Ohio",1957-03-04,56873,1883
|
277 |
+
KVUE,Kenvue,Consumer Staples,Personal Care Products,"Skillman, New Jersey",2023-08-25,1944048,2022 (Johnson & Johnson spinoff)
|
278 |
+
L,Loews Corporation,Financials,Multi-line Insurance,"New York City, New York",1995-05-31,60086,1959
|
279 |
+
LDOS,Leidos,Industrials,Diversified Support Services,"Reston, Virginia",2019-08-09,1336920,1969
|
280 |
+
LEN,Lennar,Consumer Discretionary,Homebuilding,"Miami, Florida",2005-10-04,920760,1954
|
281 |
+
LH,LabCorp,Health Care,Health Care Services,"Burlington, North Carolina",2004-11-01,920148,1978
|
282 |
+
LHX,L3Harris,Industrials,Aerospace & Defense,"Melbourne, Florida",2008-09-22,202058,"2019 (L3 1997, Harris 1895)"
|
283 |
+
LIN,Linde plc,Materials,Industrial Gases,"Guildford, United Kingdom",1992-07-01,1707925,1879
|
284 |
+
LKQ,LKQ Corporation,Consumer Discretionary,Distributors,"Chicago, Illinois",2016-05-23,1065696,1998
|
285 |
+
LLY,Eli Lilly and Company,Health Care,Pharmaceuticals,"Indianapolis, Indiana",1970-12-31,59478,1876
|
286 |
+
LMT,Lockheed Martin,Industrials,Aerospace & Defense,"Bethesda, Maryland",1957-03-04,936468,1995
|
287 |
+
LNT,Alliant Energy,Utilities,Electric Utilities,"Madison, Wisconsin",2016-07-01,352541,1917
|
288 |
+
LOW,Lowe's,Consumer Discretionary,Home Improvement Retail,"Mooresville, North Carolina",1984-02-29,60667,1904/1946/1959
|
289 |
+
LRCX,Lam Research,Information Technology,Semiconductor Materials & Equipment,"Fremont, California",2012-06-29,707549,1980
|
290 |
+
LULU,Lululemon Athletica,Consumer Discretionary,"Apparel, Accessories & Luxury Goods","Vancouver, Canada",2023-10-18,1397187,1998
|
291 |
+
LUV,Southwest Airlines,Industrials,Passenger Airlines,"Dallas, Texas",1994-07-01,92380,1967
|
292 |
+
LVS,Las Vegas Sands,Consumer Discretionary,Casinos & Gaming,"Las Vegas, Nevada",2019-10-03,1300514,1988
|
293 |
+
LW,Lamb Weston,Consumer Staples,Packaged Foods & Meats,"Eagle, Idaho",2018-12-03,1679273,2016 (1950)
|
294 |
+
LYB,LyondellBasell,Materials,Specialty Chemicals,"Rotterdam, Netherlands",2012-09-05,1489393,2007
|
295 |
+
LYV,Live Nation Entertainment,Communication Services,Movies & Entertainment,"Beverly Hills, California",2019-12-23,1335258,2010
|
296 |
+
MA,Mastercard,Financials,Transaction & Payment Processing Services,"Harrison, New York",2008-07-18,1141391,1966
|
297 |
+
MAA,Mid-America Apartment Communities,Real Estate,Multi-Family Residential REITs,"Memphis, Tennessee",2016-12-02,912595,1977
|
298 |
+
MAR,Marriott International,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Bethesda, Maryland",1998-05-29,1048286,1927
|
299 |
+
MAS,Masco,Industrials,Building Products,"Livonia, Michigan",1981-06-30,62996,1929
|
300 |
+
MCD,McDonald's,Consumer Discretionary,Restaurants,"Chicago, Illinois",1970-06-30,63908,1940
|
301 |
+
MCHP,Microchip Technology,Information Technology,Semiconductors,"Chandler, Arizona",2007-09-07,827054,1989
|
302 |
+
MCK,McKesson,Health Care,Health Care Distributors,"Irving, Texas",1999-01-13,927653,1833
|
303 |
+
MCO,Moody's Corporation,Financials,Financial Exchanges & Data,"New York City, New York",1998-07-01,1059556,1909
|
304 |
+
MDLZ,Mondelez International,Consumer Staples,Packaged Foods & Meats,"Chicago, Illinois",2012-10-02,1103982,2012
|
305 |
+
MDT,Medtronic,Health Care,Health Care Equipment,"Dublin, Ireland",1986-10-31,1613103,1949
|
306 |
+
MET,MetLife,Financials,Life & Health Insurance,"New York City, New York",2000-12-11,1099219,1868
|
307 |
+
META,Meta Platforms,Communication Services,Interactive Media & Services,"Menlo Park, California",2013-12-23,1326801,2004
|
308 |
+
MGM,MGM Resorts,Consumer Discretionary,Casinos & Gaming,"Paradise, Nevada",2017-07-26,789570,1986
|
309 |
+
MHK,Mohawk Industries,Consumer Discretionary,Home Furnishings,"Calhoun, Georgia",2013-12-23,851968,1878
|
310 |
+
MKC,McCormick & Company,Consumer Staples,Packaged Foods & Meats,"Hunt Valley, Maryland",2003-03-20,63754,1889
|
311 |
+
MKTX,MarketAxess,Financials,Financial Exchanges & Data,"New York City, New York",2019-07-01,1278021,2000
|
312 |
+
MLM,Martin Marietta Materials,Materials,Construction Materials,"Raleigh, North Carolina",2014-07-02,916076,1993
|
313 |
+
MMC,Marsh McLennan,Financials,Insurance Brokers,"New York City, New York",1987-08-31,62709,1905
|
314 |
+
MMM,3M,Industrials,Industrial Conglomerates,"Saint Paul, Minnesota",1957-03-04,66740,1902
|
315 |
+
MNST,Monster Beverage,Consumer Staples,Soft Drinks & Non-alcoholic Beverages,"Corona, California",2012-06-28,865752,2012 (1935)
|
316 |
+
MO,Altria,Consumer Staples,Tobacco,"Richmond, Virginia",1957-03-04,764180,1985
|
317 |
+
MOH,Molina Healthcare,Health Care,Managed Health Care,"Long Beach, California",2022-03-02,1179929,1980
|
318 |
+
MOS,Mosaic Company (The),Materials,Fertilizers & Agricultural Chemicals,"Tampa, Florida",2011-09-26,1285785,2004 (1865 / 1909)
|
319 |
+
MPC,Marathon Petroleum,Energy,Oil & Gas Refining & Marketing,"Findlay, Ohio",2011-07-01,1510295,2009 (1887)
|
320 |
+
MPWR,Monolithic Power Systems,Information Technology,Semiconductors,"Kirkland, Washington",2021-02-12,1280452,1997
|
321 |
+
MRK,Merck & Co.,Health Care,Pharmaceuticals,"Kenilworth, New Jersey",1957-03-04,310158,1891
|
322 |
+
MRNA,Moderna,Health Care,Biotechnology,"Cambridge, Massachusetts",2021-07-21,1682852,2010
|
323 |
+
MRO,Marathon Oil,Energy,Oil & Gas Exploration & Production,"Houston, Texas",1957-03-04,101778,1887
|
324 |
+
MS,Morgan Stanley,Financials,Investment Banking & Brokerage,"New York City, New York",1993-07-29,895421,1935
|
325 |
+
MSCI,MSCI,Financials,Financial Exchanges & Data,"New York City, New York",2018-04-04,1408198,1969
|
326 |
+
MSFT,Microsoft,Information Technology,Systems Software,"Redmond, Washington",1994-06-01,789019,1975
|
327 |
+
MSI,Motorola Solutions,Information Technology,Communications Equipment,"Chicago, Illinois",1957-03-04,68505,1928 (2011)
|
328 |
+
MTB,M&T Bank,Financials,Regional Banks,"Buffalo, New York",2004-02-23,36270,1856
|
329 |
+
MTCH,Match Group,Communication Services,Interactive Media & Services,"Dallas, Texas",2021-09-20,891103,1986
|
330 |
+
MTD,Mettler Toledo,Health Care,Life Sciences Tools & Services,"Columbus, Ohio",2016-09-06,1037646,1945
|
331 |
+
MU,Micron Technology,Information Technology,Semiconductors,"Boise, Idaho",1994-09-27,723125,1978
|
332 |
+
NCLH,Norwegian Cruise Line Holdings,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Miami, Florida",2017-10-13,1513761,2011 (1966)
|
333 |
+
NDAQ,"Nasdaq, Inc.",Financials,Financial Exchanges & Data,"New York City, New York",2008-10-22,1120193,1971
|
334 |
+
NDSN,Nordson Corporation,Industrials,Industrial Machinery & Supplies & Components,"Westlake, Ohio",2022-02-15,72331,1935
|
335 |
+
NEE,NextEra Energy,Utilities,Multi-Utilities,"Juno Beach, Florida",1976-06-30,753308,1984 (1925)
|
336 |
+
NEM,Newmont,Materials,Gold,"Denver, Colorado",1969-06-30,1164727,1921
|
337 |
+
NFLX,Netflix,Communication Services,Movies & Entertainment,"Los Gatos, California",2010-12-20,1065280,1997
|
338 |
+
NI,NiSource,Utilities,Multi-Utilities,"Merrillville, Indiana",2000-11-02,1111711,1912
|
339 |
+
NKE,"Nike, Inc.",Consumer Discretionary,"Apparel, Accessories & Luxury Goods","Washington County, Oregon",1988-11-30,320187,1964
|
340 |
+
NOC,Northrop Grumman,Industrials,Aerospace & Defense,"West Falls Church, Virginia",1957-03-04,1133421,"1994 (Northrop 1939, Grumman 1930)"
|
341 |
+
NOW,ServiceNow,Information Technology,Systems Software,"Santa Clara, California",2019-11-21,1373715,2003
|
342 |
+
NRG,NRG Energy,Utilities,Independent Power Producers & Energy Traders,"Houston, Texas",2010-01-29,1013871,1992
|
343 |
+
NSC,Norfolk Southern Railway,Industrials,Rail Transportation,"Atlanta, Georgia",1957-03-04,702165,1881/1894 (1980)
|
344 |
+
NTAP,NetApp,Information Technology,"Technology Hardware, Storage & Peripherals","San Jose, California",1999-06-25,1002047,1992
|
345 |
+
NTRS,Northern Trust,Financials,Asset Management & Custody Banks,"Chicago, Illinois",1998-01-30,73124,1889
|
346 |
+
NUE,Nucor,Materials,Steel,"Charlotte, North Carolina",1985-04-30,73309,1940
|
347 |
+
NVDA,Nvidia,Information Technology,Semiconductors,"Santa Clara, California",2001-11-30,1045810,1993
|
348 |
+
NVR,"NVR, Inc.",Consumer Discretionary,Homebuilding,"Reston, Virginia",2019-09-26,906163,1980
|
349 |
+
NWS,News Corp (Class B),Communication Services,Publishing,"New York City, New York",2015-09-18,1564708,2013 (News Corporation 1980)
|
350 |
+
NWSA,News Corp (Class A),Communication Services,Publishing,"New York City, New York",2013-08-01,1564708,2013 (News Corporation 1980)
|
351 |
+
NXPI,NXP Semiconductors,Information Technology,Semiconductors,"Eindhoven, Netherlands",2021-03-22,1413447,1953
|
352 |
+
O,Realty Income,Real Estate,Retail REITs,"San Diego, California",2015-04-07,726728,1969
|
353 |
+
ODFL,Old Dominion,Industrials,Cargo Ground Transportation,"Thomasville, North Carolina",2019-12-09,878927,1934
|
354 |
+
OKE,ONEOK,Energy,Oil & Gas Storage & Transportation,"Tulsa, Oklahoma",2010-03-15,1039684,1906
|
355 |
+
OMC,Omnicom Group,Communication Services,Advertising,"New York City, New York",1997-12-31,29989,1986
|
356 |
+
ON,ON Semiconductor,Information Technology,Semiconductors,"Phoenix, Arizona",2022-06-21,1097864,1999
|
357 |
+
ORCL,Oracle Corporation,Information Technology,Application Software,"Austin, Texas",1989-08-31,1341439,1977
|
358 |
+
ORLY,O'Reilly Auto Parts,Consumer Discretionary,Automotive Retail,"Springfield, Missouri",2009-03-27,898173,1957
|
359 |
+
OTIS,Otis Worldwide,Industrials,Industrial Machinery & Supplies & Components,"Farmington, Connecticut",2020-04-03,1781335,"2020 (1853, United Technologies spinoff)"
|
360 |
+
OXY,Occidental Petroleum,Energy,Oil & Gas Exploration & Production,"Houston, Texas",1957-03-04,797468,1920
|
361 |
+
PANW,Palo Alto Networks,Information Technology,Systems Software,"Santa Clara, California",2023-06-20,1327567,2005
|
362 |
+
PARA,Paramount Global,Communication Services,Movies & Entertainment,"New York City, New York",1994-09-30,813828,2019 (Paramount Pictures 1912)
|
363 |
+
PAYC,Paycom,Industrials,Human Resource & Employment Services,"Oklahoma City, Oklahoma",2020-01-28,1590955,1998
|
364 |
+
PAYX,Paychex,Industrials,Human Resource & Employment Services,"Penfield, New York",1998-10-01,723531,1971
|
365 |
+
PCAR,Paccar,Industrials,Construction Machinery & Heavy Transportation Equipment,"Bellevue, Washington",1980-12-31,75362,1905
|
366 |
+
PCG,PG&E Corporation,Utilities,Multi-Utilities,"San Francisco, California",2022-10-03,1004980,1905
|
367 |
+
PEG,Public Service Enterprise Group,Utilities,Electric Utilities,"Newark, New Jersey",1957-03-04,788784,1903
|
368 |
+
PEP,PepsiCo,Consumer Staples,Soft Drinks & Non-alcoholic Beverages,"Purchase, New York",1957-03-04,77476,1898
|
369 |
+
PFE,Pfizer,Health Care,Pharmaceuticals,"New York City, New York",1957-03-04,78003,1849
|
370 |
+
PFG,Principal Financial Group,Financials,Life & Health Insurance,"Des Moines, Iowa",2002-07-22,1126328,1879
|
371 |
+
PG,Procter & Gamble,Consumer Staples,Personal Care Products,"Cincinnati, Ohio",1957-03-04,80424,1837
|
372 |
+
PGR,Progressive Corporation,Financials,Property & Casualty Insurance,"Mayfield Village, Ohio",1997-08-04,80661,1937
|
373 |
+
PH,Parker Hannifin,Industrials,Industrial Machinery & Supplies & Components,"Cleveland, Ohio",1985-11-30,76334,1917
|
374 |
+
PHM,PulteGroup,Consumer Discretionary,Homebuilding,"Atlanta, Georgia",1984-04-30,822416,1956
|
375 |
+
PKG,Packaging Corporation of America,Materials,Paper & Plastic Packaging Products & Materials,"Lake Forest, Illinois",2017-07-26,75677,1959
|
376 |
+
PLD,Prologis,Real Estate,Industrial REITs,"San Francisco, California",2003-07-17,1045609,1983
|
377 |
+
PM,Philip Morris International,Consumer Staples,Tobacco,"New York City, New York",2008-03-31,1413329,2008 (1847)
|
378 |
+
PNC,PNC Financial Services,Financials,Regional Banks,"Pittsburgh, Pennsylvania",1988-04-30,713676,1845
|
379 |
+
PNR,Pentair,Industrials,Industrial Machinery & Supplies & Components,"Worsley, United Kingdom",2012-10-01,77360,1966
|
380 |
+
PNW,Pinnacle West,Utilities,Multi-Utilities,"Phoenix, Arizona",1999-10-04,764622,1985
|
381 |
+
PODD,Insulet,Health Care,Health Care Equipment,"Acton, Massachusetts",2023-03-15,1145197,2000
|
382 |
+
POOL,Pool Corporation,Consumer Discretionary,Distributors,"Covington, Louisiana",2020-10-07,945841,1993
|
383 |
+
PPG,PPG Industries,Materials,Specialty Chemicals,"Pittsburgh, Pennsylvania",1957-03-04,79879,1883
|
384 |
+
PPL,PPL Corporation,Utilities,Electric Utilities,"Allentown, Pennsylvania",2001-10-01,922224,1920
|
385 |
+
PRU,Prudential Financial,Financials,Life & Health Insurance,"Newark, New Jersey",2002-07-22,1137774,1875
|
386 |
+
PSA,Public Storage,Real Estate,Self-Storage REITs,"Glendale, California",2005-08-19,1393311,1972
|
387 |
+
PSX,Phillips 66,Energy,Oil & Gas Refining & Marketing,"Houston, Texas",2012-05-01,1534701,2012 (1917)
|
388 |
+
PTC,PTC,Information Technology,Application Software,"Boston, Massachusetts",2021-04-20,857005,1985
|
389 |
+
PWR,Quanta Services,Industrials,Construction & Engineering,"Houston, Texas",2009-07-01,1050915,1997
|
390 |
+
PXD,Pioneer Natural Resources,Energy,Oil & Gas Exploration & Production,"Irving, Texas",2008-09-24,1038357,1997
|
391 |
+
PYPL,PayPal,Financials,Transaction & Payment Processing Services,"San Jose, California",2015-07-20,1633917,1998
|
392 |
+
QCOM,Qualcomm,Information Technology,Semiconductors,"San Diego, California",1999-07-22,804328,1985
|
393 |
+
QRVO,Qorvo,Information Technology,Semiconductors,"Greensboro, North Carolina",2015-06-11,1604778,2015
|
394 |
+
RCL,Royal Caribbean Group,Consumer Discretionary,"Hotels, Resorts & Cruise Lines","Miami, Florida",2014-12-05,884887,1997
|
395 |
+
REG,Regency Centers,Real Estate,Retail REITs,"Jacksonville, Florida",2017-03-02,910606,1963
|
396 |
+
REGN,Regeneron,Health Care,Biotechnology,"Tarrytown, New York",2013-05-01,872589,1988
|
397 |
+
RF,Regions Financial Corporation,Financials,Regional Banks,"Birmingham, Alabama",1998-08-28,1281761,1971
|
398 |
+
RHI,Robert Half,Industrials,Human Resource & Employment Services,"Menlo Park, California",2000-12-05,315213,1948
|
399 |
+
RJF,Raymond James,Financials,Investment Banking & Brokerage,"St. Petersburg, Florida",2017-03-20,720005,1962
|
400 |
+
RL,Ralph Lauren Corporation,Consumer Discretionary,"Apparel, Accessories & Luxury Goods","New York City, New York",2007-02-02,1037038,1967
|
401 |
+
RMD,ResMed,Health Care,Health Care Equipment,"San Diego, California",2017-07-26,943819,1989
|
402 |
+
ROK,Rockwell Automation,Industrials,Electrical Components & Equipment,"Milwaukee, Wisconsin",2000-03-12,1024478,1903
|
403 |
+
ROL,"Rollins, Inc.",Industrials,Environmental & Facilities Services,"Atlanta, Georgia",2018-10-01,84839,1948
|
404 |
+
ROP,Roper Technologies,Information Technology,Electronic Equipment & Instruments,"Sarasota, Florida",2009-12-23,882835,1981
|
405 |
+
ROST,Ross Stores,Consumer Discretionary,Apparel Retail,"Dublin, California",2009-12-21,745732,1982
|
406 |
+
RSG,Republic Services,Industrials,Environmental & Facilities Services,"Phoenix, Arizona",2008-12-05,1060391,1998 (1981)
|
407 |
+
RTX,RTX Corporation,Industrials,Aerospace & Defense,"Waltham, Massachusetts",1957-03-04,101829,1922
|
408 |
+
RVTY,Revvity,Health Care,Health Care Equipment,"Waltham, Massachusetts",1985-05-31,31791,1937
|
409 |
+
SBAC,SBA Communications,Real Estate,Telecom Tower REITs,"Boca Raton, Florida",2017-09-01,1034054,1989
|
410 |
+
SBUX,Starbucks,Consumer Discretionary,Restaurants,"Seattle, Washington",2000-06-07,829224,1971
|
411 |
+
SCHW,Charles Schwab Corporation,Financials,Investment Banking & Brokerage,"Westlake, Texas",1997-06-02,316709,1971
|
412 |
+
SHW,Sherwin-Williams,Materials,Specialty Chemicals,"Cleveland, Ohio",1964-06-30,89800,1866
|
413 |
+
SJM,J.M. Smucker Company (The),Consumer Staples,Packaged Foods & Meats,"Orrville, Ohio",2008-11-06,91419,1897
|
414 |
+
SLB,Schlumberger,Energy,Oil & Gas Equipment & Services,"Houston, Texas",1957-03-04,87347,1926
|
415 |
+
SMCI,Supermicro,Information Technology,"Technology Hardware, Storage & Peripherals","San Jose, California",2024-03-18,1375365,1993
|
416 |
+
SNA,Snap-on,Industrials,Industrial Machinery & Supplies & Components,"Kenosha, Wisconsin",1982-09-30,91440,1920
|
417 |
+
SNPS,Synopsys,Information Technology,Application Software,"Sunnyvale, California",2017-03-16,883241,1986
|
418 |
+
SO,Southern Company,Utilities,Electric Utilities,"Atlanta, Georgia",1957-03-04,92122,1945
|
419 |
+
SPG,Simon Property Group,Real Estate,Retail REITs,"Indianapolis, Indiana",2002-06-26,1063761,2003
|
420 |
+
SPGI,S&P Global,Financials,Financial Exchanges & Data,"New York City, New York",1957-03-04,64040,1917
|
421 |
+
SRE,Sempra Energy,Utilities,Multi-Utilities,"San Diego, California",2017-03-17,1032208,1998
|
422 |
+
STE,Steris,Health Care,Health Care Equipment,"Dublin, Ireland",2019-12-23,1757898,1985
|
423 |
+
STLD,Steel Dynamics,Materials,Steel,"Fort Wayne, Indiana",2022-12-22,1022671,1993
|
424 |
+
STT,State Street Corporation,Financials,Asset Management & Custody Banks,"Boston, Massachusetts",2003-03-14,93751,1792
|
425 |
+
STX,Seagate Technology,Information Technology,"Technology Hardware, Storage & Peripherals","Dublin, Ireland",2012-07-02,1137789,1979
|
426 |
+
STZ,Constellation Brands,Consumer Staples,Distillers & Vintners,"Victor, New York",2005-07-01,16918,1945
|
427 |
+
SWK,Stanley Black & Decker,Industrials,Industrial Machinery & Supplies & Components,"New Britain, Connecticut",1982-09-30,93556,1843
|
428 |
+
SWKS,Skyworks Solutions,Information Technology,Semiconductors,"Irvine, California",2015-03-12,4127,2002
|
429 |
+
SYF,Synchrony Financial,Financials,Consumer Finance,"Stamford, Connecticut",2015-11-18,1601712,2003
|
430 |
+
SYK,Stryker Corporation,Health Care,Health Care Equipment,"Kalamazoo, Michigan",2000-12-12,310764,1941
|
431 |
+
SYY,Sysco,Consumer Staples,Food Distributors,"Houston, Texas",1986-12-31,96021,1969
|
432 |
+
T,AT&T,Communication Services,Integrated Telecommunication Services,"Dallas, Texas",1983-11-30,732717,1983 (1885)
|
433 |
+
TAP,Molson Coors Beverage Company,Consumer Staples,Brewers,"Chicago, Illinois",1976-06-30,24545,"2005 (Molson 1786, Coors 1873)"
|
434 |
+
TDG,TransDigm Group,Industrials,Aerospace & Defense,"Cleveland, Ohio",2016-06-03,1260221,1993
|
435 |
+
TDY,Teledyne Technologies,Information Technology,Electronic Equipment & Instruments,"Thousand Oaks, California",2020-06-22,1094285,1960
|
436 |
+
TECH,Bio-Techne,Health Care,Life Sciences Tools & Services,"Minneapolis, Minnesota",2021-08-30,842023,1976
|
437 |
+
TEL,TE Connectivity,Information Technology,Electronic Manufacturing Services,"Schaffhausen, Switzerland",2011-10-17,1385157,2007
|
438 |
+
TER,Teradyne,Information Technology,Semiconductor Materials & Equipment,"North Reading, Massachusetts",2020-09-21,97210,1960
|
439 |
+
TFC,Truist,Financials,Regional Banks,"Charlotte, North Carolina",1997-12-04,92230,1872
|
440 |
+
TFX,Teleflex,Health Care,Health Care Equipment,"Wayne, Pennsylvania",2019-01-18,96943,1943
|
441 |
+
TGT,Target Corporation,Consumer Staples,Consumer Staples Merchandise Retail,"Minneapolis, Minnesota",1976-12-31,27419,1902
|
442 |
+
TJX,TJX Companies,Consumer Discretionary,Apparel Retail,"Framingham, Massachusetts",1985-09-30,109198,1987
|
443 |
+
TMO,Thermo Fisher Scientific,Health Care,Life Sciences Tools & Services,"Waltham, Massachusetts",2004-08-03,97745,2006 (1902)
|
444 |
+
TMUS,T-Mobile US,Communication Services,Wireless Telecommunication Services,"Bellevue, Washington",2019-07-15,1283699,1994
|
445 |
+
TPR,"Tapestry, Inc.",Consumer Discretionary,"Apparel, Accessories & Luxury Goods","New York City, New York",2004-09-01,1116132,2017
|
446 |
+
TRGP,Targa Resources,Energy,Oil & Gas Storage & Transportation,"Houston, Texas",2022-10-12,1389170,2005
|
447 |
+
TRMB,Trimble Inc.,Information Technology,Electronic Equipment & Instruments,"Westminster, Colorado",2021-01-21,864749,1978
|
448 |
+
TROW,T. Rowe Price,Financials,Asset Management & Custody Banks,"Baltimore, Maryland",2019-07-29,1113169,1937
|
449 |
+
TRV,Travelers Companies (The),Financials,Property & Casualty Insurance,"New York City, New York",2002-08-21,86312,1853
|
450 |
+
TSCO,Tractor Supply,Consumer Discretionary,Other Specialty Retail,"Brentwood, Tennessee",2014-01-24,916365,1938
|
451 |
+
TSLA,"Tesla, Inc.",Consumer Discretionary,Automobile Manufacturers,"Austin, Texas",2020-12-21,1318605,2003
|
452 |
+
TSN,Tyson Foods,Consumer Staples,Packaged Foods & Meats,"Springdale, Arkansas",2005-08-10,100493,1935
|
453 |
+
TT,Trane Technologies,Industrials,Building Products,"Dublin, Ireland",2010-11-17,1466258,1871
|
454 |
+
TTWO,Take-Two Interactive,Communication Services,Interactive Home Entertainment,"New York City, New York",2018-03-19,946581,1993
|
455 |
+
TXN,Texas Instruments,Information Technology,Semiconductors,"Dallas, Texas",2001-03-12,97476,1930
|
456 |
+
TXT,Textron,Industrials,Aerospace & Defense,"Providence, Rhode Island",1978-12-31,217346,1923
|
457 |
+
TYL,Tyler Technologies,Information Technology,Application Software,"Plano, Texas",2020-06-22,860731,1966
|
458 |
+
UAL,United Airlines Holdings,Industrials,Passenger Airlines,"Chicago, Illinois",2015-09-03,100517,1967
|
459 |
+
UBER,Uber,Industrials,Passenger Ground Transportation,"San Francisco, California",2023-12-18,1543151,2009
|
460 |
+
UDR,"UDR, Inc.",Real Estate,Multi-Family Residential REITs,"Highlands Ranch, Colorado",2016-03-07,74208,1972
|
461 |
+
UHS,Universal Health Services,Health Care,Health Care Facilities,"King of Prussia, Pennsylvania",2014-09-20,352915,1979
|
462 |
+
ULTA,Ulta Beauty,Consumer Discretionary,Other Specialty Retail,"Bolingbrook, Illinois",2016-04-18,1403568,1990
|
463 |
+
UNH,UnitedHealth Group,Health Care,Managed Health Care,"Minnetonka, Minnesota",1994-07-01,731766,1977
|
464 |
+
UNP,Union Pacific Corporation,Industrials,Rail Transportation,"Omaha, Nebraska",1957-03-04,100885,1862
|
465 |
+
UPS,United Parcel Service,Industrials,Air Freight & Logistics,"Sandy Springs, Georgia",2002-07-22,1090727,1907
|
466 |
+
URI,United Rentals,Industrials,Trading Companies & Distributors,"Stamford, Connecticut",2014-09-20,1067701,1997
|
467 |
+
USB,U.S. Bank,Financials,Diversified Banks,"Minneapolis, Minnesota",1999-11-01,36104,1968
|
468 |
+
V,Visa Inc.,Financials,Transaction & Payment Processing Services,"San Francisco, California",2009-12-21,1403161,1958
|
469 |
+
VFC,VF Corporation,Consumer Discretionary,"Apparel, Accessories & Luxury Goods","Denver, Colorado",1979-06-30,103379,1899
|
470 |
+
VICI,Vici Properties,Real Estate,Hotel & Resort REITs,"New York City, New York",2022-06-08,1705696,2017
|
471 |
+
VLO,Valero Energy,Energy,Oil & Gas Refining & Marketing,"San Antonio, Texas",2002-12-20,1035002,1980
|
472 |
+
VLTO,Veralto,Industrials,Environmental & Facilities Services,"Waltham, Massachusetts",2023-10-02,1967680,2023
|
473 |
+
VMC,Vulcan Materials Company,Materials,Construction Materials,"Birmingham, Alabama",1999-06-30,1396009,1909
|
474 |
+
VRSK,Verisk,Industrials,Research & Consulting Services,"Jersey City, New Jersey",2015-10-08,1442145,1971
|
475 |
+
VRSN,Verisign,Information Technology,Internet Services & Infrastructure,"Dulles, Virginia",2006-02-01,1014473,1995
|
476 |
+
VRTX,Vertex Pharmaceuticals,Health Care,Biotechnology,"Cambridge, Massachusetts",2013-09-23,875320,1989
|
477 |
+
VTR,Ventas,Real Estate,Health Care REITs,"Chicago, Illinois",2009-03-04,740260,1998
|
478 |
+
VTRS,Viatris,Health Care,Pharmaceuticals,"Pittsburgh, Pennsylvania",2004-04-23,1792044,1961
|
479 |
+
VZ,Verizon,Communication Services,Integrated Telecommunication Services,"New York City, New York",1983-11-30,732712,1983 (1877)
|
480 |
+
WAB,Wabtec,Industrials,Construction Machinery & Heavy Transportation Equipment,"Pittsburgh, Pennsylvania",2019-02-27,943452,1999 (1869)
|
481 |
+
WAT,Waters Corporation,Health Care,Life Sciences Tools & Services,"Milford, Massachusetts",2002-01-02,1000697,1958
|
482 |
+
WBA,Walgreens Boots Alliance,Consumer Staples,Drug Retail,"Deerfield, Illinois",1979-12-31,1618921,2014
|
483 |
+
WBD,Warner Bros. Discovery,Communication Services,Broadcasting,"New York City, New York",2022-04-11,1437107,2022 (Warner Bros. 1923)
|
484 |
+
WDC,Western Digital,Information Technology,"Technology Hardware, Storage & Peripherals","San Jose, California",2009-07-01,106040,1970
|
485 |
+
WEC,WEC Energy Group,Utilities,Electric Utilities,"Milwaukee, Wisconsin",2008-10-31,783325,1896
|
486 |
+
WELL,Welltower,Real Estate,Health Care REITs,"Toledo, Ohio",2009-01-30,766704,1970
|
487 |
+
WFC,Wells Fargo,Financials,Diversified Banks,"San Francisco, California",1976-06-30,72971,1852
|
488 |
+
WM,Waste Management,Industrials,Environmental & Facilities Services,"Houston, Texas",1998-08-31,823768,1968
|
489 |
+
WMB,Williams Companies,Energy,Oil & Gas Storage & Transportation,"Tulsa, Oklahoma",1975-03-31,107263,1908
|
490 |
+
WMT,Walmart,Consumer Staples,Consumer Staples Merchandise Retail,"Bentonville, Arkansas",1982-08-31,104169,1962
|
491 |
+
WRB,Berkley,Financials,Property & Casualty Insurance,"Greenwich, Connecticut",2019-12-05,11544,1967
|
492 |
+
WRK,WestRock,Materials,Paper & Plastic Packaging Products & Materials,"Atlanta, Georgia",2015-06-25,1732845,2015
|
493 |
+
WST,West Pharmaceutical Services,Health Care,Health Care Supplies,"Exton, Pennsylvania",2020-05-22,105770,1923
|
494 |
+
WTW,Willis Towers Watson,Financials,Insurance Brokers,"London, United Kingdom",2016-01-05,1140536,2016
|
495 |
+
WY,Weyerhaeuser,Real Estate,Timber REITs,"Seattle, Washington",1979-10-01,106535,1900
|
496 |
+
WYNN,Wynn Resorts,Consumer Discretionary,Casinos & Gaming,"Paradise, Nevada",2008-11-14,1174922,2002
|
497 |
+
XEL,Xcel Energy,Utilities,Multi-Utilities,"Minneapolis, Minnesota",1957-03-04,72903,1909
|
498 |
+
XOM,ExxonMobil,Energy,Integrated Oil & Gas,"Irving, Texas",1957-03-04,34088,1999
|
499 |
+
XRAY,Dentsply Sirona,Health Care,Health Care Supplies,"Charlotte, North Carolina",2008-11-14,818479,2016 (1969)
|
500 |
+
XYL,Xylem Inc.,Industrials,Industrial Machinery & Supplies & Components,"White Plains, New York",2011-11-01,1524472,2011
|
501 |
+
YUM,Yum! Brands,Consumer Discretionary,Restaurants,"Louisville, Kentucky",1997-10-06,1041061,1997
|
502 |
+
ZBH,Zimmer Biomet,Health Care,Health Care Equipment,"Warsaw, Indiana",2001-08-07,1136869,1927
|
503 |
+
ZBRA,Zebra Technologies,Information Technology,Electronic Equipment & Instruments,"Lincolnshire, Illinois",2019-12-23,877212,1969
|
504 |
+
ZTS,Zoetis,Health Care,Pharmaceuticals,"Parsippany, New Jersey",2013-06-21,1555280,1952
|
preprocess.py
ADDED
@@ -0,0 +1,544 @@
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|
1 |
+
import re
|
2 |
+
import sys
|
3 |
+
import os
|
4 |
+
import numpy as np
|
5 |
+
from collections import defaultdict
|
6 |
+
import pandas as pd
|
7 |
+
import time
|
8 |
+
|
9 |
+
# 如果使用 spaCy 进行 NLP 处理
|
10 |
+
import spacy
|
11 |
+
|
12 |
+
# 如果使用某种情感分析工具,比如 Hugging Face 的模型
|
13 |
+
from transformers import pipeline
|
14 |
+
|
15 |
+
# 还需要导入 pickle 模块(如果你在代码的其他部分使用了它来处理序列化/反序列化)
|
16 |
+
import pickle
|
17 |
+
from gensim.models import KeyedVectors
|
18 |
+
import akshare as ak
|
19 |
+
|
20 |
+
from gensim.models import Word2Vec
|
21 |
+
from transformers import pipeline, AutoTokenizer, AutoModelForSequenceClassification
|
22 |
+
|
23 |
+
|
24 |
+
|
25 |
+
|
26 |
+
|
27 |
+
sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
|
28 |
+
from us_stock import *
|
29 |
+
|
30 |
+
|
31 |
+
|
32 |
+
|
33 |
+
# 强制使用 GPU
|
34 |
+
#spacy.require_gpu()
|
35 |
+
|
36 |
+
# 加载模型
|
37 |
+
nlp = spacy.load("en_core_web_md")
|
38 |
+
|
39 |
+
# 检查是否使用 GPU
|
40 |
+
print("Is NPL GPU used Preprocessing.py:", spacy.prefer_gpu())
|
41 |
+
|
42 |
+
|
43 |
+
# 使用合适的模型和tokenizer
|
44 |
+
model_name = "ProsusAI/finbert" # 选择合适的预训练模型
|
45 |
+
tokenizer = AutoTokenizer.from_pretrained(model_name)
|
46 |
+
sa_model = AutoModelForSequenceClassification.from_pretrained(model_name)
|
47 |
+
|
48 |
+
# 初始化情感分析器
|
49 |
+
sentiment_analyzer = pipeline('sentiment-analysis', model=sa_model, tokenizer=tokenizer)
|
50 |
+
|
51 |
+
|
52 |
+
|
53 |
+
|
54 |
+
index_us_stock_index_INX = ak.index_us_stock_sina(symbol=".INX")
|
55 |
+
index_us_stock_index_DJI = ak.index_us_stock_sina(symbol=".DJI")
|
56 |
+
index_us_stock_index_IXIC = ak.index_us_stock_sina(symbol=".IXIC")
|
57 |
+
index_us_stock_index_NDX = ak.index_us_stock_sina(symbol=".NDX")
|
58 |
+
|
59 |
+
|
60 |
+
class LazyWord2Vec:
|
61 |
+
def __init__(self, model_path):
|
62 |
+
self.model_path = model_path
|
63 |
+
self._model = None
|
64 |
+
|
65 |
+
@property
|
66 |
+
def model(self):
|
67 |
+
if self._model is None:
|
68 |
+
print("Loading Word2Vec model...")
|
69 |
+
self._model = KeyedVectors.load(self.model_path, mmap='r')
|
70 |
+
return self._model
|
71 |
+
|
72 |
+
@property
|
73 |
+
def vector_size(self):
|
74 |
+
self.load_model()
|
75 |
+
return self.model.vector_size # 现在你可以正确访问 vector_size 属性
|
76 |
+
|
77 |
+
|
78 |
+
def __getitem__(self, key):
|
79 |
+
return self.model[key]
|
80 |
+
|
81 |
+
def __contains__(self, key):
|
82 |
+
return key in self.model
|
83 |
+
|
84 |
+
# 加载预训练的 Google News Word2Vec 模型
|
85 |
+
# 定义路径列表
|
86 |
+
search_paths = ["/BuckLake/Model/",
|
87 |
+
"/Users/parker/Development/Server/BuckLake/Model/",
|
88 |
+
"/Users/liuyue/Work/BuckLake/Model/"]
|
89 |
+
|
90 |
+
# 获取当前文件所在目录的路径
|
91 |
+
current_directory = os.getcwd()
|
92 |
+
print(f"Current directory: {current_directory}")
|
93 |
+
current_directory = os.path.dirname(os.path.abspath(__file__))
|
94 |
+
|
95 |
+
# 添加相对于当前项目的路径
|
96 |
+
# search_paths.insert(0, os.path.join(current_directory, 'model'))
|
97 |
+
search_paths.insert(1, os.path.join(current_directory, '..', 'Model'))
|
98 |
+
|
99 |
+
|
100 |
+
# 定义相对路径
|
101 |
+
filename = 'word2vec-google-news-300.model'
|
102 |
+
|
103 |
+
# 初始化word2vec_path为None
|
104 |
+
word2vec_path = None
|
105 |
+
|
106 |
+
# 遍历路径列表
|
107 |
+
for path in search_paths:
|
108 |
+
potential_path = os.path.join(path, filename)
|
109 |
+
if os.path.exists(potential_path):
|
110 |
+
word2vec_path = potential_path
|
111 |
+
break
|
112 |
+
else:
|
113 |
+
print(f"{potential_path} not found.")
|
114 |
+
|
115 |
+
# 如果找到路径,加载模型
|
116 |
+
if word2vec_path:
|
117 |
+
print(f"Loading Word2Vec model from {word2vec_path}...")
|
118 |
+
word2vec_model = LazyWord2Vec(word2vec_path)
|
119 |
+
else:
|
120 |
+
raise FileNotFoundError(f"{filename} not found in any of the search paths: {search_paths}")
|
121 |
+
|
122 |
+
|
123 |
+
|
124 |
+
def pos_tagging(text):
|
125 |
+
try:
|
126 |
+
doc = nlp(text)
|
127 |
+
tokens, pos_tags, tags = [], [], []
|
128 |
+
for token in doc:
|
129 |
+
if token.is_punct or token.is_stop:
|
130 |
+
continue
|
131 |
+
tokens.append(token.text)
|
132 |
+
pos_tags.append(token.pos_)
|
133 |
+
tags.append(token.tag_)
|
134 |
+
except Exception as e:
|
135 |
+
print(f"Error in pos_tagging for text: {text[:50]}... Error: {str(e)}")
|
136 |
+
return "", "", ""
|
137 |
+
|
138 |
+
return tokens, pos_tags, tags
|
139 |
+
|
140 |
+
|
141 |
+
# 命名实体识别函数
|
142 |
+
def named_entity_recognition(text):
|
143 |
+
try:
|
144 |
+
doc = nlp(text)
|
145 |
+
entities = [(ent.text, ent.label_) for ent in doc.ents]
|
146 |
+
except Exception as e:
|
147 |
+
print(f"Error in named_entity_recognition for text: {text[:50]}... Error: {str(e)}")
|
148 |
+
entities = []
|
149 |
+
|
150 |
+
return entities or [("", "")]
|
151 |
+
|
152 |
+
|
153 |
+
|
154 |
+
# 处理命名实体识别结果
|
155 |
+
def process_entities(entities):
|
156 |
+
entity_counts = defaultdict(int)
|
157 |
+
try:
|
158 |
+
for entity in entities:
|
159 |
+
etype = entity[1] # 取出实体类型
|
160 |
+
entity_counts[etype] += 1 # 直接对实体类型进行计数
|
161 |
+
|
162 |
+
# 将字典转化为有序的数组
|
163 |
+
entity_types = sorted(entity_counts.keys())
|
164 |
+
counts = np.array([entity_counts[etype] for etype in entity_types])
|
165 |
+
except Exception as e:
|
166 |
+
print(f"Error in process_entities: {str(e)}")
|
167 |
+
counts = np.zeros(len(entities))
|
168 |
+
entity_types = []
|
169 |
+
|
170 |
+
return counts, entity_types
|
171 |
+
|
172 |
+
|
173 |
+
|
174 |
+
# 处理词性标注结果
|
175 |
+
def process_pos_tags(pos_tags):
|
176 |
+
pos_counts = defaultdict(int)
|
177 |
+
try:
|
178 |
+
for pos in pos_tags:
|
179 |
+
pos_counts[pos[1]] += 1 # 使用POS标签(如NN, VB等)
|
180 |
+
|
181 |
+
# 将字典转化为有序的数组
|
182 |
+
pos_types = sorted(pos_counts.keys())
|
183 |
+
counts = np.array([pos_counts[pos] for pos in pos_types])
|
184 |
+
except Exception as e:
|
185 |
+
print(f"Error in process_pos_tags: {str(e)}")
|
186 |
+
counts = np.zeros(len(pos_tags))
|
187 |
+
pos_types = []
|
188 |
+
|
189 |
+
return counts, pos_types
|
190 |
+
|
191 |
+
|
192 |
+
|
193 |
+
|
194 |
+
# 函数:获取文档向量
|
195 |
+
def get_document_vector(words, model = word2vec_model):
|
196 |
+
try:
|
197 |
+
# 获取每个词的词向量,如果词不在模型中则跳过
|
198 |
+
word_vectors = [model[word] for word in words if word in model]
|
199 |
+
# 对词向量进行平均,得到文档向量;如果没有词在模型中则返回零向量
|
200 |
+
document_vector = np.mean(word_vectors, axis=0) if word_vectors else np.zeros(model.vector_size)
|
201 |
+
except Exception as e:
|
202 |
+
print(f"Error in get_document_vector for words: {words[:5]}... Error: {str(e)}")
|
203 |
+
document_vector = np.zeros(model.vector_size)
|
204 |
+
|
205 |
+
return document_vector
|
206 |
+
|
207 |
+
|
208 |
+
|
209 |
+
# 函数:获取情感得分
|
210 |
+
def get_sentiment_score(text):
|
211 |
+
try:
|
212 |
+
# 直接将原始文本传递给 sentiment_analyzer,它会自动处理 tokenization
|
213 |
+
result = sentiment_analyzer(text, truncation=True, max_length=512)[0]
|
214 |
+
score = result['score'] if result['label'] == 'positive' else -result['score']
|
215 |
+
except Exception as e:
|
216 |
+
print(f"Error in get_sentiment_score for text: {text[:50]}... Error: {str(e)}")
|
217 |
+
score = 0.0
|
218 |
+
|
219 |
+
return score
|
220 |
+
|
221 |
+
|
222 |
+
|
223 |
+
def get_stock_info(stock_codes, news_date):
|
224 |
+
# 获取股票代码和新闻日期
|
225 |
+
stock_codes = stock_codes.split(',')
|
226 |
+
|
227 |
+
news_date = news_date.strftime('%Y%m%d')
|
228 |
+
print(f"Getting stock info for {stock_codes} on {news_date}")
|
229 |
+
|
230 |
+
previous_stock_history = []
|
231 |
+
following_stock_history = []
|
232 |
+
previous_stock_index_history = []
|
233 |
+
following_stock_index_history = []
|
234 |
+
|
235 |
+
def process_history(stock_history, target_date):
|
236 |
+
# 如果数据为空,创建一个空的 DataFrame 并填充为 0
|
237 |
+
if stock_history.empty:
|
238 |
+
empty_data = pd.DataFrame({
|
239 |
+
'开盘': [0] * 4,
|
240 |
+
'收盘': [0] * 4,
|
241 |
+
'最高': [0] * 4,
|
242 |
+
'最低': [0] * 4,
|
243 |
+
'成交量': [0] * 4,
|
244 |
+
'成交额': [0] * 4
|
245 |
+
})
|
246 |
+
return empty_data, empty_data
|
247 |
+
|
248 |
+
# 确保 'date' 列存在
|
249 |
+
if 'date' not in stock_history.columns:
|
250 |
+
print(f"'date' column not found in stock history. Returning empty data.")
|
251 |
+
return pd.DataFrame([[0] * 6] * 4), pd.DataFrame([[0] * 6] * 4)
|
252 |
+
|
253 |
+
# 将日期转换为 datetime 格式,便于比较
|
254 |
+
stock_history['date'] = pd.to_datetime(stock_history['date'])
|
255 |
+
target_date = pd.to_datetime(target_date)
|
256 |
+
|
257 |
+
# 找到目标日期的索引
|
258 |
+
target_row = stock_history[stock_history['date'] == target_date]
|
259 |
+
|
260 |
+
if target_row.empty:
|
261 |
+
# 如果目标日期找不到,找到离目标日期最近的日期
|
262 |
+
closest_date_index = (stock_history['date'] - target_date).abs().idxmin()
|
263 |
+
target_date = stock_history.loc[closest_date_index, 'date']
|
264 |
+
target_row = stock_history[stock_history['date'] == target_date]
|
265 |
+
|
266 |
+
# 确保找到的目标日期有数据
|
267 |
+
if target_row.empty:
|
268 |
+
return pd.DataFrame([[0] * 6] * 4), pd.DataFrame([[0] * 6] * 4)
|
269 |
+
|
270 |
+
target_index = target_row.index[0]
|
271 |
+
target_pos = stock_history.index.get_loc(target_index)
|
272 |
+
|
273 |
+
# 取出目标日期及其前3条记录
|
274 |
+
previous_rows = stock_history.iloc[max(0, target_pos - 3):target_pos + 1]
|
275 |
+
|
276 |
+
# 取出目标日期及其后4条记录
|
277 |
+
following_rows = stock_history.iloc[target_pos:target_pos + 4]
|
278 |
+
|
279 |
+
# 删除日期列
|
280 |
+
previous_rows = previous_rows.drop(columns=['date'])
|
281 |
+
following_rows = following_rows.drop(columns=['date'])
|
282 |
+
|
283 |
+
# 如果 previous_rows 或 following_rows 的行数不足 4,则填充至 4 行
|
284 |
+
if len(previous_rows) < 4:
|
285 |
+
previous_rows = previous_rows.reindex(range(4), fill_value=0)
|
286 |
+
|
287 |
+
if len(following_rows) < 4:
|
288 |
+
following_rows = following_rows.reindex(range(4), fill_value=0)
|
289 |
+
|
290 |
+
# 只返回前4行,并只返回前6列(开盘、收盘、最高、最低、成交量、成交额)
|
291 |
+
previous_rows = previous_rows.iloc[:4, :6]
|
292 |
+
following_rows = following_rows.iloc[:4, :6]
|
293 |
+
|
294 |
+
return previous_rows, following_rows
|
295 |
+
|
296 |
+
if not stock_codes or stock_codes == ['']:
|
297 |
+
# 如果 stock_codes 为空,直接获取并返回大盘数据
|
298 |
+
stock_index_history = get_stock_index_history("", news_date)
|
299 |
+
previous_rows, following_rows = process_history(stock_index_history, news_date)
|
300 |
+
previous_stock_index_history.append(previous_rows.values.tolist())
|
301 |
+
following_stock_index_history.append(following_rows.values.tolist())
|
302 |
+
|
303 |
+
# 个股补零逻辑
|
304 |
+
previous_stock_history.append([[0] * len(previous_rows.columns)] * len(previous_rows))
|
305 |
+
following_stock_history.append([[0] * len(following_rows.columns)] * len(following_rows))
|
306 |
+
|
307 |
+
|
308 |
+
|
309 |
+
else:
|
310 |
+
for stock_code in stock_codes:
|
311 |
+
stock_code = stock_code.strip()
|
312 |
+
stock_history = get_stock_history(stock_code, news_date)
|
313 |
+
stock_index_history = get_stock_index_history(stock_code, news_date)
|
314 |
+
|
315 |
+
# 处理个股数据
|
316 |
+
previous_rows, following_rows = process_history(stock_history, news_date)
|
317 |
+
previous_stock_history.append(previous_rows.values.tolist())
|
318 |
+
following_stock_history.append(following_rows.values.tolist())
|
319 |
+
|
320 |
+
# 处理大盘数据
|
321 |
+
previous_rows, following_rows = process_history(stock_index_history, news_date)
|
322 |
+
previous_stock_index_history.append(previous_rows.values.tolist())
|
323 |
+
following_stock_index_history.append(following_rows.values.tolist())
|
324 |
+
|
325 |
+
return previous_stock_history, following_stock_history, previous_stock_index_history, following_stock_index_history
|
326 |
+
|
327 |
+
|
328 |
+
|
329 |
+
def lemmatized_entry(entry):
|
330 |
+
entry_start_time = time.time()
|
331 |
+
# Step 1 - 条目聚合
|
332 |
+
lemmatized_text = preprocessing_entry(entry)
|
333 |
+
|
334 |
+
|
335 |
+
return lemmatized_text
|
336 |
+
|
337 |
+
|
338 |
+
|
339 |
+
|
340 |
+
|
341 |
+
|
342 |
+
# 1. 数据清理
|
343 |
+
# 1.1 合并数据
|
344 |
+
# 1.2 去除噪声
|
345 |
+
# 1.3 大小写转换
|
346 |
+
# 1.4 去除停用词
|
347 |
+
# 1.5 词汇矫正与拼写检查
|
348 |
+
# 1.6 词干提取与词形还原
|
349 |
+
|
350 |
+
|
351 |
+
|
352 |
+
# 强制使用 GPU
|
353 |
+
# spacy.require_gpu()
|
354 |
+
|
355 |
+
# 加载模型
|
356 |
+
nlp = spacy.load("en_core_web_md")
|
357 |
+
|
358 |
+
# 检查是否使用 GPU
|
359 |
+
print("Is NPL GPU used Lemmatized:", spacy.prefer_gpu())
|
360 |
+
|
361 |
+
|
362 |
+
|
363 |
+
|
364 |
+
def preprocessing_entry(news_entry):
|
365 |
+
"""数据清理启动函数
|
366 |
+
|
367 |
+
Args:
|
368 |
+
text (str): preprocessing后的文本
|
369 |
+
|
370 |
+
Returns:
|
371 |
+
[str]]: 词干提取后的String列表
|
372 |
+
"""
|
373 |
+
|
374 |
+
# 1.1 合并数据
|
375 |
+
text = merge_text(news_entry)
|
376 |
+
|
377 |
+
# 1.2 去除噪声
|
378 |
+
text = disposal_noise(text)
|
379 |
+
|
380 |
+
# 1.3 大小写转换
|
381 |
+
text = text.lower()
|
382 |
+
|
383 |
+
# 1.4 去除停用词
|
384 |
+
text = remove_stopwords(text)
|
385 |
+
|
386 |
+
# 1.5 拼写检查
|
387 |
+
#text = correct_spelling(text)
|
388 |
+
#print(f"1.5 拼写检查后的文本:{text}")
|
389 |
+
|
390 |
+
# 1.6 词干提取与词形还原
|
391 |
+
lemmatized_text_list = lemmatize_text(text)
|
392 |
+
#print(f"1.6 词干提取与词形还原后的文本:{lemmatized_text_list}")
|
393 |
+
|
394 |
+
return lemmatized_text_list
|
395 |
+
|
396 |
+
|
397 |
+
|
398 |
+
# 1.1 合并数据
|
399 |
+
def merge_text(news_entry):
|
400 |
+
return news_entry
|
401 |
+
|
402 |
+
|
403 |
+
# 1.2 去除噪声
|
404 |
+
def disposal_noise(text):
|
405 |
+
# 移除HTML标签
|
406 |
+
text = re.sub(r'<.*?>', '', text)
|
407 |
+
# 移除URLs
|
408 |
+
text = re.sub(r'http\S+|www\S+|https\S+', '', text, flags=re.MULTILINE)
|
409 |
+
# 移除方括号内的内容
|
410 |
+
# text = re.sub(r'\[.*?\]', '', text)
|
411 |
+
# 移除标点符号
|
412 |
+
# text = re.sub(r'[^\w\s]', '', text)
|
413 |
+
# 移除多余的空格
|
414 |
+
text = re.sub(r'\s+', ' ', text).strip()
|
415 |
+
# 或者选择性地过滤,例如移除表情符号
|
416 |
+
# text = re.sub(r'[^\w\s.,!?]', '', text)
|
417 |
+
# 移除换行符和制表符
|
418 |
+
text = re.sub(r'[\n\t\r]', ' ', text)
|
419 |
+
|
420 |
+
|
421 |
+
return text
|
422 |
+
|
423 |
+
# 1.4 去除停用词
|
424 |
+
|
425 |
+
|
426 |
+
def remove_stopwords(text):
|
427 |
+
# 使用 spaCy 处理文本
|
428 |
+
doc = nlp(text)
|
429 |
+
# 去除停用词,并且仅保留标识为“词”(Token.is_alpha)类型的标记
|
430 |
+
filtered_sentence = [token.text for token in doc if not token.is_stop and (token.is_alpha or token.like_num)]
|
431 |
+
return ' '.join(filtered_sentence)
|
432 |
+
|
433 |
+
|
434 |
+
|
435 |
+
|
436 |
+
|
437 |
+
# 1.5 拼写检查
|
438 |
+
# 该函数用于检查输入文本的拼写错误,并修正
|
439 |
+
# def correct_spelling(text):
|
440 |
+
# corrected_text = []
|
441 |
+
# doc = nlp(text)
|
442 |
+
# for token in doc:
|
443 |
+
# if token.is_alpha: # 仅检查字母构成的单词
|
444 |
+
# corrected_word = spell.correction(token.text)
|
445 |
+
# if corrected_word is None:
|
446 |
+
# # 如果拼写检查没有建议,保留原始单词
|
447 |
+
# corrected_word = token.text
|
448 |
+
# corrected_text.append(corrected_word)
|
449 |
+
# else:
|
450 |
+
# corrected_text.append(token.text)
|
451 |
+
# return " ".join(corrected_text)
|
452 |
+
|
453 |
+
|
454 |
+
# 1.6 词干提取与词形还原
|
455 |
+
# 该函数用于对输入文本进行词形还原,返回一个包含词形还原后单词
|
456 |
+
def lemmatize_text(text):
|
457 |
+
# 提取词干化后的词
|
458 |
+
lemmatized_words = []
|
459 |
+
doc = nlp(text) # 需要在这里处理输入文本
|
460 |
+
for token in doc:
|
461 |
+
# 忽略标点符号和空格
|
462 |
+
if not token.is_punct and not token.is_space and (token.is_alpha or token.like_num):
|
463 |
+
lemmatized_words.append(token.lemma_)
|
464 |
+
return lemmatized_words
|
465 |
+
|
466 |
+
|
467 |
+
|
468 |
+
|
469 |
+
|
470 |
+
|
471 |
+
# 2. 数据增强和特征提取
|
472 |
+
# 2.1 词性标注(Part-of-Speech Tagging)
|
473 |
+
# 为每个词标注其词性(如名词、动词、形容词等),这有助于后续的句法分析和信息提取。
|
474 |
+
# 工具:spaCy 或 NLTK
|
475 |
+
# 2.2 命名实体识别(NER)
|
476 |
+
# 识别文本中的命名实体,如人名、地名、组织机构等,提取出这些实体信息。
|
477 |
+
# 工具:spaCy 或 Stanford NER
|
478 |
+
# 2.3 句法分析与依存分析
|
479 |
+
# 分析句子结构,理解单词之间的关系(如主谓宾结构)。
|
480 |
+
# 工具:spaCy 或 NLTK
|
481 |
+
|
482 |
+
|
483 |
+
|
484 |
+
# 2 特征提取
|
485 |
+
|
486 |
+
|
487 |
+
# 强制使用 GPU
|
488 |
+
#spacy.require_gpu()
|
489 |
+
|
490 |
+
# 加载模型
|
491 |
+
nlp = spacy.load("en_core_web_md")
|
492 |
+
|
493 |
+
# 检查是否使用 GPU
|
494 |
+
print("Is NPL GPU used Enchance_text.py:", spacy.prefer_gpu())
|
495 |
+
|
496 |
+
|
497 |
+
|
498 |
+
# 2.3 句法分析与依存分析
|
499 |
+
def dependency_parsing(text):
|
500 |
+
doc = nlp(text)
|
501 |
+
dependencies = []
|
502 |
+
|
503 |
+
for token in doc:
|
504 |
+
# 过滤标点符号和停用词,或其他不需要的词性
|
505 |
+
if token.is_punct or token.is_stop:
|
506 |
+
continue
|
507 |
+
|
508 |
+
# 可以进一步根据特定的依存关系类型过滤结果
|
509 |
+
# 常见的依存关系类型: 'nsubj' (名词主语), 'dobj' (直接宾语), 等等
|
510 |
+
# if token.dep_ not in {'nsubj', 'dobj', ...}:
|
511 |
+
# continue
|
512 |
+
|
513 |
+
dependencies.append((token.text, token.dep_, token.head.text))
|
514 |
+
|
515 |
+
return dependencies
|
516 |
+
|
517 |
+
|
518 |
+
|
519 |
+
def processing_entry(entry):
|
520 |
+
# print(f"processing_entry: {entry}")
|
521 |
+
|
522 |
+
|
523 |
+
lemmatized_entry = preprocessing_entry(entry)
|
524 |
+
# print(f"lemmatized_entry: {lemmatized_entry}")
|
525 |
+
|
526 |
+
cleaned_text = disposal_noise(entry)
|
527 |
+
# print(f"disposal_noise: {cleaned_text}")
|
528 |
+
|
529 |
+
pos_tag = pos_tagging(cleaned_text)
|
530 |
+
# print(f"pos_tagging: {db_pos_tag}")
|
531 |
+
|
532 |
+
ner = named_entity_recognition(cleaned_text)
|
533 |
+
# print(f"named_entity_recognition: {db_ner}")
|
534 |
+
|
535 |
+
dependency_parsed = dependency_parsing(cleaned_text)
|
536 |
+
# print(f"dependency_parsing: {db_dependency_parsing}")
|
537 |
+
|
538 |
+
sentiment_score = get_sentiment_score(cleaned_text)
|
539 |
+
# print(f"sentiment_score: {sentiment_score}")
|
540 |
+
|
541 |
+
|
542 |
+
|
543 |
+
|
544 |
+
return (lemmatized_entry, pos_tag, ner, dependency_parsed, sentiment_score)
|
requirements.txt
CHANGED
@@ -1,3 +1,10 @@
|
|
1 |
-
flask
|
2 |
streamlit
|
3 |
-
transformers
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
streamlit
|
2 |
+
transformers
|
3 |
+
akshare
|
4 |
+
blis==0.7.11
|
5 |
+
spacy==3.7.5
|
6 |
+
gensim
|
7 |
+
numpy
|
8 |
+
fastapi
|
9 |
+
uvicorn
|
10 |
+
gensim
|
us_stock.py
ADDED
@@ -0,0 +1,361 @@
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
|
1 |
+
import logging
|
2 |
+
import re
|
3 |
+
import akshare as ak
|
4 |
+
import pandas as pd
|
5 |
+
from datetime import datetime, timedelta
|
6 |
+
import time # 导入标准库的 time 模块
|
7 |
+
|
8 |
+
import os
|
9 |
+
|
10 |
+
import requests
|
11 |
+
import threading
|
12 |
+
import asyncio
|
13 |
+
|
14 |
+
|
15 |
+
logging.basicConfig(level=logging.INFO)
|
16 |
+
|
17 |
+
|
18 |
+
# 获取当前文件的目录
|
19 |
+
base_dir = os.path.dirname(os.path.abspath(__file__))
|
20 |
+
|
21 |
+
# 构建CSV文件的绝对路径
|
22 |
+
nasdaq_100_path = os.path.join(base_dir, '../model/nasdaq100.csv')
|
23 |
+
dow_jones_path = os.path.join(base_dir, '../model/dji.csv')
|
24 |
+
sp500_path = os.path.join(base_dir, '../model/sp500.csv')
|
25 |
+
nasdaq_composite_path = os.path.join(base_dir, '../model/nasdaq_all.csv')
|
26 |
+
# 从CSV文件加载成分股数据
|
27 |
+
nasdaq_100_stocks = pd.read_csv(nasdaq_100_path)
|
28 |
+
dow_jones_stocks = pd.read_csv(dow_jones_path)
|
29 |
+
sp500_stocks = pd.read_csv(sp500_path)
|
30 |
+
nasdaq_composite_stocks = pd.read_csv(nasdaq_composite_path)
|
31 |
+
|
32 |
+
|
33 |
+
def fetch_stock_us_spot_data_with_retries():
|
34 |
+
# 定义重试间隔时间序列(秒)
|
35 |
+
retry_intervals = [10, 20, 60, 300, 600]
|
36 |
+
retry_index = 0 # 初始重试序号
|
37 |
+
|
38 |
+
while True:
|
39 |
+
try:
|
40 |
+
# 尝试获取API数据
|
41 |
+
symbols = ak.stock_us_spot_em()
|
42 |
+
return symbols # 成功获取数据后返回
|
43 |
+
|
44 |
+
except Exception as e:
|
45 |
+
print(f"Error fetching data: {e}")
|
46 |
+
|
47 |
+
# 获取当前重试等待时间
|
48 |
+
wait_time = retry_intervals[retry_index]
|
49 |
+
print(f"Retrying in {wait_time} seconds...")
|
50 |
+
time.sleep(wait_time) # 等待指定的秒数
|
51 |
+
|
52 |
+
# 更新重试索引,但不要超出重试时间列表的范围
|
53 |
+
retry_index = min(retry_index + 1, len(retry_intervals) - 1)
|
54 |
+
|
55 |
+
|
56 |
+
|
57 |
+
async def fetch_stock_us_spot_data_with_retries_async():
|
58 |
+
retry_intervals = [10, 20, 60, 300, 600]
|
59 |
+
retry_index = 0
|
60 |
+
|
61 |
+
while True:
|
62 |
+
try:
|
63 |
+
symbols = await asyncio.to_thread(ak.stock_us_spot_em)
|
64 |
+
return symbols
|
65 |
+
except Exception as e:
|
66 |
+
print(f"Error fetching data: {e}")
|
67 |
+
wait_time = retry_intervals[retry_index]
|
68 |
+
print(f"Retrying in {wait_time} seconds...")
|
69 |
+
await asyncio.sleep(wait_time)
|
70 |
+
retry_index = min(retry_index + 1, len(retry_intervals) - 1)
|
71 |
+
|
72 |
+
symbols = asyncio.run(fetch_stock_us_spot_data_with_retries_async())
|
73 |
+
|
74 |
+
|
75 |
+
# 全局变量
|
76 |
+
index_us_stock_index_INX = None
|
77 |
+
index_us_stock_index_DJI = None
|
78 |
+
index_us_stock_index_IXIC = None
|
79 |
+
index_us_stock_index_NDX = None
|
80 |
+
|
81 |
+
def update_stock_indices():
|
82 |
+
global index_us_stock_index_INX, index_us_stock_index_DJI, index_us_stock_index_IXIC, index_us_stock_index_NDX
|
83 |
+
try:
|
84 |
+
index_us_stock_index_INX = ak.index_us_stock_sina(symbol=".INX")
|
85 |
+
index_us_stock_index_DJI = ak.index_us_stock_sina(symbol=".DJI")
|
86 |
+
index_us_stock_index_IXIC = ak.index_us_stock_sina(symbol=".IXIC")
|
87 |
+
index_us_stock_index_NDX = ak.index_us_stock_sina(symbol=".NDX")
|
88 |
+
print("Stock indices updated")
|
89 |
+
except Exception as e:
|
90 |
+
print(f"Error updating stock indices: {e}")
|
91 |
+
|
92 |
+
# 设置定时器,每隔12小时更新一次
|
93 |
+
threading.Timer(12 * 60 * 60, update_stock_indices).start()
|
94 |
+
|
95 |
+
# 程序开始时立即更新一次
|
96 |
+
update_stock_indices()
|
97 |
+
|
98 |
+
|
99 |
+
# 创建列名转换的字典
|
100 |
+
column_mapping = {
|
101 |
+
'日期': 'date',
|
102 |
+
'开盘': 'open',
|
103 |
+
'收盘': 'close',
|
104 |
+
'最高': 'high',
|
105 |
+
'最低': 'low',
|
106 |
+
'成交量': 'volume',
|
107 |
+
'成交额': 'amount',
|
108 |
+
'振幅': 'amplitude',
|
109 |
+
'涨跌幅': 'price_change_percentage',
|
110 |
+
'涨跌额': 'price_change_amount',
|
111 |
+
'换手率': 'turnover_rate'
|
112 |
+
}
|
113 |
+
|
114 |
+
# 定义一个标准的列顺序
|
115 |
+
standard_columns = ['date', 'open', 'close', 'high', 'low', 'volume', 'amount']
|
116 |
+
|
117 |
+
|
118 |
+
# 定义查找函数
|
119 |
+
def find_stock_entry(stock_code):
|
120 |
+
# 使用 str.endswith 来匹配股票代码
|
121 |
+
matching_row = symbols[symbols['代码'].str.endswith(stock_code)]
|
122 |
+
# print(symbols)
|
123 |
+
if not matching_row.empty:
|
124 |
+
# print(f"股票代码 {stock_code} 找到, 代码为 {matching_row['代码'].values[0]}")
|
125 |
+
return matching_row['代码'].values[0]
|
126 |
+
else:
|
127 |
+
return ""
|
128 |
+
|
129 |
+
'''
|
130 |
+
# 示例调用
|
131 |
+
# 测试函数
|
132 |
+
result = find_stock_entry('AAPL')
|
133 |
+
|
134 |
+
if isinstance(result, pd.DataFrame) and not result.empty:
|
135 |
+
# 如果找到的结果不为空,获取代码列的值
|
136 |
+
code_value = result['代码'].values[0]
|
137 |
+
print(code_value)
|
138 |
+
else:
|
139 |
+
print(result)
|
140 |
+
'''
|
141 |
+
|
142 |
+
|
143 |
+
def reduce_columns(df, columns_to_keep):
|
144 |
+
return df[columns_to_keep]
|
145 |
+
|
146 |
+
|
147 |
+
# 返回个股历史数据
|
148 |
+
def get_stock_history(symbol, news_date, retries=10):
|
149 |
+
# 定义重试间隔时间序列(秒)
|
150 |
+
retry_intervals = [10, 20, 60, 300, 600]
|
151 |
+
retry_count = 0
|
152 |
+
|
153 |
+
# 如果传入的symbol不包含数字前缀,则通过 find_stock_entry 获取完整的symbol
|
154 |
+
if not any(char.isdigit() for char in symbol):
|
155 |
+
full_symbol = find_stock_entry(symbol)
|
156 |
+
if len(symbol) != 0 and full_symbol:
|
157 |
+
symbol = full_symbol
|
158 |
+
else:
|
159 |
+
symbol = ""
|
160 |
+
|
161 |
+
|
162 |
+
# 将news_date转换为datetime对象
|
163 |
+
news_date_dt = datetime.strptime(news_date, "%Y%m%d")
|
164 |
+
|
165 |
+
# 计算start_date和end_date
|
166 |
+
start_date = (news_date_dt - timedelta(weeks=2)).strftime("%Y%m%d")
|
167 |
+
end_date = (news_date_dt + timedelta(weeks=2)).strftime("%Y%m%d")
|
168 |
+
|
169 |
+
stock_hist_df = None
|
170 |
+
retry_index = 0 # 初始化重试索引
|
171 |
+
|
172 |
+
while retry_count <= retries and len(symbol) != 0: # 无限循环重试
|
173 |
+
try:
|
174 |
+
# 尝试获取API数据
|
175 |
+
stock_hist_df = ak.stock_us_hist(symbol=symbol, period="daily", start_date=start_date, end_date=end_date, adjust="")
|
176 |
+
|
177 |
+
if stock_hist_df.empty: # 检查是否为空数据
|
178 |
+
# print(f"No data for {symbol} on {news_date}.")
|
179 |
+
stock_hist_df = None # 将 DataFrame 设置为 None
|
180 |
+
break
|
181 |
+
|
182 |
+
|
183 |
+
except (requests.exceptions.Timeout, ConnectionError) as e:
|
184 |
+
print(f"Request timed out: {e}. Retrying...")
|
185 |
+
retry_count += 1 # 增加重试次数
|
186 |
+
continue
|
187 |
+
|
188 |
+
|
189 |
+
except (TypeError, ValueError, BaseException) as e:
|
190 |
+
print(f"Error {e} scraping data for {symbol} on {news_date}. Break...")
|
191 |
+
# 可能是没数据,直接Break
|
192 |
+
break
|
193 |
+
|
194 |
+
# 如果发生异常,等待一段时间再重试
|
195 |
+
wait_time = retry_intervals[retry_index]
|
196 |
+
print(f"Waiting for {wait_time} seconds before retrying...")
|
197 |
+
time.sleep(wait_time)
|
198 |
+
retry_index = (retry_index + 1) if retry_index < len(retry_intervals) - 1 else retry_index # 更新重试索引,不超过列表长度
|
199 |
+
|
200 |
+
# 如果获取失败或数据为空,返回填充为0的 DataFrame
|
201 |
+
if stock_hist_df is None or stock_hist_df.empty:
|
202 |
+
# 构建一个空的 DataFrame,包含指定日期范围的空数据
|
203 |
+
date_range = pd.date_range(start=start_date, end=end_date)
|
204 |
+
stock_hist_df = pd.DataFrame({
|
205 |
+
'date': date_range,
|
206 |
+
'开盘': 0,
|
207 |
+
'收盘': 0,
|
208 |
+
'最高': 0,
|
209 |
+
'最低': 0,
|
210 |
+
'成交量': 0,
|
211 |
+
'成交额': 0,
|
212 |
+
'振幅': 0,
|
213 |
+
'涨跌幅': 0,
|
214 |
+
'涨跌额': 0,
|
215 |
+
'换手率': 0
|
216 |
+
})
|
217 |
+
|
218 |
+
# 使用rename方法转换列名
|
219 |
+
stock_hist_df = stock_hist_df.rename(columns=column_mapping)
|
220 |
+
stock_hist_df = stock_hist_df.reindex(columns=standard_columns)
|
221 |
+
# 处理个股数据,保留所需列
|
222 |
+
stock_hist_df = reduce_columns(stock_hist_df, standard_columns)
|
223 |
+
return stock_hist_df
|
224 |
+
|
225 |
+
# 统一列名
|
226 |
+
stock_hist_df = stock_hist_df.rename(columns=column_mapping)
|
227 |
+
stock_hist_df = stock_hist_df.reindex(columns=standard_columns)
|
228 |
+
# 处理个股数据,保留所需列
|
229 |
+
stock_hist_df = reduce_columns(stock_hist_df, standard_columns)
|
230 |
+
return stock_hist_df
|
231 |
+
|
232 |
+
|
233 |
+
'''
|
234 |
+
# 示例调用
|
235 |
+
result = get_stock_history('AAPL', '20240214')
|
236 |
+
print(result)
|
237 |
+
'''
|
238 |
+
# result = get_stock_history('ATMU', '20231218')
|
239 |
+
# print(result)
|
240 |
+
|
241 |
+
|
242 |
+
# 返回个股所属指数历史数据
|
243 |
+
def get_stock_index_history(symbol, news_date):
|
244 |
+
# 检查股票所属的指数
|
245 |
+
if symbol in nasdaq_100_stocks['Symbol'].values:
|
246 |
+
index_code = ".NDX"
|
247 |
+
index_data = index_us_stock_index_NDX
|
248 |
+
elif symbol in dow_jones_stocks['Symbol'].values:
|
249 |
+
index_code = ".DJI"
|
250 |
+
index_data = index_us_stock_index_DJI
|
251 |
+
elif symbol in sp500_stocks['Symbol'].values:
|
252 |
+
index_code = ".INX"
|
253 |
+
index_data = index_us_stock_index_INX
|
254 |
+
elif symbol in nasdaq_composite_stocks["Symbol"].values or symbol is None or symbol == "":
|
255 |
+
index_code = ".IXIC"
|
256 |
+
index_data = index_us_stock_index_IXIC
|
257 |
+
else:
|
258 |
+
|
259 |
+
index_code = ".IXIC"
|
260 |
+
index_data = index_us_stock_index_IXIC
|
261 |
+
|
262 |
+
# print(f"股票代码 {symbol} 不属于纳斯达克100、道琼斯工业、标准普尔500或纳斯达克综合指数。")
|
263 |
+
# 将 news_date 转换为 datetime 对象
|
264 |
+
news_date_dt = datetime.strptime(news_date, "%Y%m%d")
|
265 |
+
|
266 |
+
# 计算 start_date 和 end_date
|
267 |
+
start_date = (news_date_dt - timedelta(weeks=2)).strftime("%Y-%m-%d")
|
268 |
+
end_date = (news_date_dt + timedelta(weeks=2)).strftime("%Y-%m-%d")
|
269 |
+
|
270 |
+
# 构建一个空的 DataFrame,包含指定日期范围的空数据
|
271 |
+
date_range = pd.date_range(start=start_date, end=end_date)
|
272 |
+
stock_hist_df = pd.DataFrame({
|
273 |
+
'date': date_range,
|
274 |
+
'open': 0,
|
275 |
+
'high': 0,
|
276 |
+
'low': 0,
|
277 |
+
'close': 0,
|
278 |
+
'volume': 0,
|
279 |
+
'amount': 0
|
280 |
+
})
|
281 |
+
# 统一列名
|
282 |
+
stock_hist_df = stock_hist_df.rename(columns=column_mapping)
|
283 |
+
stock_hist_df = stock_hist_df.reindex(columns=standard_columns)
|
284 |
+
# 处理个股数据,保留所需列
|
285 |
+
stock_hist_df = reduce_columns(stock_hist_df, standard_columns)
|
286 |
+
return stock_hist_df
|
287 |
+
|
288 |
+
# 将 news_date 转换为 datetime 对象
|
289 |
+
news_date_dt = datetime.strptime(news_date, "%Y%m%d")
|
290 |
+
|
291 |
+
# 计算 start_date 和 end_date
|
292 |
+
start_date = (news_date_dt - timedelta(weeks=2)).strftime("%Y-%m-%d")
|
293 |
+
end_date = (news_date_dt + timedelta(weeks=2)).strftime("%Y-%m-%d")
|
294 |
+
|
295 |
+
# 确保 index_data['date'] 是 datetime 类型
|
296 |
+
index_data['date'] = pd.to_datetime(index_data['date'])
|
297 |
+
|
298 |
+
# 从指数历史数据中提取指定日期范围的数据
|
299 |
+
index_hist_df = index_data[(index_data['date'] >= start_date) & (index_data['date'] <= end_date)]
|
300 |
+
|
301 |
+
# 统一列名
|
302 |
+
index_hist_df = index_hist_df.rename(columns=column_mapping)
|
303 |
+
index_hist_df = index_hist_df.reindex(columns=standard_columns)
|
304 |
+
# 处理个股数据,保留所需列
|
305 |
+
index_hist_df = reduce_columns(index_hist_df, standard_columns)
|
306 |
+
return index_hist_df
|
307 |
+
'''
|
308 |
+
# 示例调用
|
309 |
+
result = get_stock_index_history('AAPL', '20240214')
|
310 |
+
print(result)
|
311 |
+
'''
|
312 |
+
|
313 |
+
|
314 |
+
|
315 |
+
def find_stock_codes_or_names(entities):
|
316 |
+
"""
|
317 |
+
从给定的实体列表中检索股票代码或公司名称。
|
318 |
+
|
319 |
+
:param entities: 命名实体识别结果列表,格式为 [('实体名称', '实体类型'), ...]
|
320 |
+
:return: 相关的股票代码列表
|
321 |
+
"""
|
322 |
+
stock_codes = set()
|
323 |
+
|
324 |
+
# 合并所有股票字典并清理数据,确保都是字符串
|
325 |
+
all_symbols = pd.concat([nasdaq_100_stocks['Symbol'],
|
326 |
+
dow_jones_stocks['Symbol'],
|
327 |
+
sp500_stocks['Symbol'],
|
328 |
+
nasdaq_composite_stocks['Symbol']]).dropna().astype(str).unique().tolist()
|
329 |
+
|
330 |
+
all_names = pd.concat([nasdaq_100_stocks['Name'],
|
331 |
+
nasdaq_composite_stocks['Name'],
|
332 |
+
sp500_stocks['Security'],
|
333 |
+
dow_jones_stocks['Company']]).dropna().astype(str).unique().tolist()
|
334 |
+
|
335 |
+
# 创建一个 Name 到 Symbol 的映射
|
336 |
+
name_to_symbol = {}
|
337 |
+
for idx, name in enumerate(all_names):
|
338 |
+
if idx < len(all_symbols):
|
339 |
+
symbol = all_symbols[idx]
|
340 |
+
name_to_symbol[name.lower()] = symbol
|
341 |
+
|
342 |
+
# 查找实体映射到的股票代码
|
343 |
+
for entity, entity_type in entities:
|
344 |
+
entity_lower = entity.lower()
|
345 |
+
entity_upper = entity.upper()
|
346 |
+
|
347 |
+
# 检查 Symbol 列
|
348 |
+
if entity_upper in all_symbols:
|
349 |
+
stock_codes.add(entity_upper)
|
350 |
+
print(f"Matched symbol: {entity_upper}")
|
351 |
+
|
352 |
+
# 检查 Name 列,确保完整匹配而不是部分匹配
|
353 |
+
for name, symbol in name_to_symbol.items():
|
354 |
+
# 使用正则表达式进行严格匹配
|
355 |
+
pattern = rf'\b{re.escape(entity_lower)}\b'
|
356 |
+
if re.search(pattern, name):
|
357 |
+
stock_codes.add(symbol.upper())
|
358 |
+
print(f"Matched name/company: '{entity_lower}' in '{name}' -> {symbol.upper()}")
|
359 |
+
|
360 |
+
print(f"Stock codes found: {stock_codes}")
|
361 |
+
return list(stock_codes)
|