Python怎么快速生成本项目的requeirments.txt
短信预约 -IT技能 免费直播动态提醒
在Python项目中，我们通常需要使用许多第三方库来提供额外的功能和工具。但是，直接将这些库上传到Git仓库并不是一种好的做法，因为这会使得代码库变得过于臃肿，并且很难管理。此外，有时候在部署应用程序时也需要安装特定版本的依赖项。
这时候，就可以使用requirements.txt文件来管理项目所需的依赖项。该文件列出了项目所需的所有依赖项及其版本号，使得其他人可以轻松地安装和运行该项目所需的所有依赖项。使用pip命令读取该文件，可以自动下载并安装所有列出的依赖项，这大大简化了项目启动/部署的流程。
因此，生成requirements.txt文件对于管理Python项目的依赖项非常重要，它能够确保项目的可重复性、可移植性和可维护性。
1.使用pipreqs生成requeirments.txt
在项目根目录下打开终端，运行以下命令安装pipreqs：
pip install pipreqs运行以下命令生成requirements.txt文件：
pipreqs . --encoding=utf8 --force其中，.表示当前目录，–encoding=utf8指定编码为UTF-8，–force选项强制覆盖已存在的requirements.txt文件。
等待执行完毕，即可在项目根目录下看到生成的requirements.txt文件。
2.使用pip
要使用pip生成当前Python项目的requirements.txt文件，请按照以下步骤操作：
1.确保你已经安装了pip和虚拟环境。
2.在虚拟环境中打开终端，并进入到项目的根目录下。
3.运行以下命令，生成包含所有依赖项的requirements.txt文件：
pip freeze > requirements.txt执行完毕后，你可以在项目的根目录下看到一个名为requirements.txt的文本文件，其中包含了所有依赖项及其版本号。
需要注意的是，pip freeze命令会将所有安装的包及其版本信息输出到控制台。通过重定向符号>将输出结果写入到文件中，就能够生成requirements.txt文件。但是，该文件中可能包含一些不必要的依赖项，如系统自带的库、测试工具等。因此，在使用生成的requirements.txt文件时，建议手动检查并删除不必要的依赖项，以减小项目体积。
以下是生成的requirements.txt文件，可以看到，有好多不必要的依赖项被生成
absl-py==1.0.0
addict==2.4.0
aiohttp==3.7.4.post0
alembic==1.8.1
argon2-cffi @ file:///opt/conda/conda-bld/argon2-cffi_1645000214183/work
argon2-cffi-bindings @ file:///C:/ci/argon2-cffi-bindings_1644569848815/work
astunparse==1.6.3
async-timeout==3.0.1
attrs @ file:///opt/conda/conda-bld/attrs_1642510447205/work
backcall @ file:///home/ktietz/class="lazy" data-src/ci/backcall_1611930011877/work
beautifulsoup4 @ file:///tmp/build/80754af9/beautifulsoup4_1631874778482/work
bilibili-api==5.1.2
bleach @ file:///opt/conda/conda-bld/bleach_1641577558959/work
blinker==1.5
cachetools==5.0.0
certifi @ file:///C:/b/abs_85o_6fm0se/croot/certifi_1671487778835/work/certifi
cffi @ file:///C:/ci_310/cffi_1642682485096/work
chardet==4.0.0
charset-normalizer==2.0.12
click @ file:///C:/ci/click_1646038601470/work
cloudpickle @ file:///tmp/build/80754af9/cloudpickle_1632508026186/work
colorama @ file:///tmp/build/80754af9/colorama_1607707115595/work
cryptography @ file:///C:/ci/cryptography_1652101770956/work
cycler==0.11.0
cytoolz==0.11.0
dask==1.1.4
debugpy @ file:///C:/ci/debugpy_1637091911212/work
decorator @ file:///opt/conda/conda-bld/decorator_1643638310831/work
defusedxml @ file:///tmp/build/80754af9/defusedxml_1615228127516/work
dnspython==2.3.0
docopt==0.6.2
einops==0.4.1
email-validator==1.3.1
entrypoints==0.3
fastjsonschema @ file:///tmp/build/80754af9/python-fastjsonschema_1620414857593/work/dist
Flask==2.2.3
Flask-Email==1.4.4
Flask-Mail==0.9.1
Flask-Migrate==3.1.0
Flask-Script==2.0.6
Flask-SQLAlchemy @ file:///tmp/build/80754af9/flask-sqlalchemy_1616180561581/work
Flask-WTF==1.1.1
flatbuffers==23.1.21
fonttools==4.30.0
fvcore==0.1.5.post20220305
gast==0.4.0
google-auth==2.6.5
google-auth-oauthlib==0.4.6
google-pasta==0.2.0
greenlet @ file:///C:/ci/greenlet_1628888257991/work
grpcio==1.45.0
grpcio-tools==1.45.0
h6py @ file:///C:/ci/h6py_1659089886851/work
idna==3.3
imagecodecs @ file:///C:/ci/imagecodecs_1635529223557/work
imageio @ file:///tmp/build/80754af9/imageio_1617700267927/work
importlib-metadata @ file:///C:/ci/importlib-metadata_1648562631189/work
importlib-resources==5.9.0
iopath==0.1.9
ipykernel @ file:///C:/ci/ipykernel_1647000985174/work/dist/ipykernel-6.9.1-py3-none-any.whl
ipython @ file:///C:/ci/ipython_1643800131373/work
ipython-genutils @ file:///tmp/build/80754af9/ipython_genutils_1606773439826/work
ipywidgets @ file:///tmp/build/80754af9/ipywidgets_1634143127070/work
itsdangerous @ file:///tmp/build/80754af9/itsdangerous_1621432558163/work
jedi @ file:///C:/ci/jedi_1644297241925/work
Jinja2 @ file:///C:/b/abs_7cdis66kl9/croot/jinja2_1666908141852/work
joblib @ file:///C:/b/abs_e60_bwl1v6/croot/joblib_1666298845728/work
jsonschema @ file:///Users/ktietz/demo/mc3/conda-bld/jsonschema_1630511932244/work
jupyter==1.0.0
jupyter-client @ file:///opt/conda/conda-bld/jupyter_client_1643638337975/work
jupyter-console @ file:///opt/conda/conda-bld/jupyter_console_1647002188872/work
jupyter-core @ file:///C:/ci/jupyter_core_1646976467633/work
jupyterlab-pygments @ file:///tmp/build/80754af9/jupyterlab_pygments_1601490720602/work
jupyterlab-widgets @ file:///tmp/build/80754af9/jupyterlab_widgets_1609884341231/work
keras==2.11.0
kiwisolver @ file:///C:/ci/kiwisolver_1653274189334/work
labelme==3.16.7
libclang==15.0.6.1
loguru @ file:///C:/ci/loguru_1643616607274/work
lxml==4.6.5
Mako==1.2.2
Markdown==3.3.6
MarkupSafe @ file:///C:/ci/markupsafe_1654508076077/work
matplotlib==3.5.1
matplotlib-inline @ file:///tmp/build/80754af9/matplotlib-inline_1628242447089/work
mistune @ file:///C:/ci/mistune_1594373272338/work
mkl-fft==1.3.1
mkl-random @ file:///C:/ci/mkl_random_1626186163140/work
mkl-service==2.4.0
mmcv==1.6.2
multidict==6.0.2
nbclient @ file:///tmp/build/80754af9/nbclient_1645431659072/work
nbconvert @ file:///C:/ci/nbconvert_1649759177374/work
nbformat @ file:///C:/ci/nbformat_1649845122517/work
nest-asyncio @ file:///C:/ci/nest-asyncio_1649848126026/work
networkx==2.2
notebook @ file:///C:/ci/notebook_1645002740769/work
numpy @ file:///C:/ci/numpy_and_numpy_base_1649782933444/work
oauthlib==3.2.0
opencv-python==4.5.5.64
openslide-python==1.2.0
opt-einsum==3.3.0
packaging @ file:///tmp/build/80754af9/packaging_1637314298585/work
pandas==1.3.5
pandocfilters @ file:///opt/conda/conda-bld/pandocfilters_1643405455980/work
parso @ file:///opt/conda/conda-bld/parso_1641458642106/work
pickleshare @ file:///tmp/build/80754af9/pickleshare_1606932040724/work
Pillow==9.0.1
pipreqs==0.4.11
portalocker==2.4.0
prettytable==3.3.0
prometheus-client @ file:///opt/conda/conda-bld/prometheus_client_1643788673601/work
prompt-toolkit @ file:///tmp/build/80754af9/prompt-toolkit_1633440160888/work
protobuf==3.19.6
pyasn1==0.4.8
pyasn1-modules==0.2.8
pycparser @ file:///tmp/build/80754af9/pycparser_1636541352034/work
pyecharts==1.9.1
pygame==2.2.0
Pygments @ file:///opt/conda/conda-bld/pygments_1644249106324/work
PyMySQL @ file:///C:/ci/pymysql_1610464946597/work
pyparsing==3.0.7
PyQt5-Qt5==5.15.2
PyQt5-sip==12.9.1
pyrsistent @ file:///C:/ci/pyrsistent_1636093257833/work
pytesseract==0.3.10
python-dateutil @ file:///tmp/build/80754af9/python-dateutil_1626374649649/work
pytz @ file:///C:/Windows/TEMP/abs_90eacd4e-8eff-491e-b26e-f707eba2cbe1ujvbhqz1/croots/recipe/pytz_1654762631027/work
PyWavelets @ file:///C:/ci/pywavelets_1648728036674/work
pywin32==302
pywinpty @ file:///C:/ci_310/pywinpty_1644230983541/work/target/wheels/pywinpty-2.0.2-cp37-none-win_amd64.whl
PyYAML==6.0
pyzmq @ file:///C:/ci/pyzmq_1638435182681/work
qtconsole @ file:///opt/conda/conda-bld/qtconsole_1649078897110/work
QtPy @ file:///opt/conda/conda-bld/qtpy_1649073884068/work
regex==2022.10.31
requests==2.27.1
requests-oauthlib==1.3.1
rsa==4.8
scikit-image @ file:///C:/ci/scikit-image_1648196140109/work
scikit-learn @ file:///C:/ci/scikit-learn_1642599122269/work
scipy @ file:///C:/ci/scipy_1641555141383/work
seaborn==0.11.2
Send2Trash @ file:///tmp/build/80754af9/send2trash_1632406701022/work
sip==4.19.13
six @ file:///tmp/build/80754af9/six_1644875935023/work
soupsieve @ file:///tmp/build/80754af9/soupsieve_1636706018808/work
SQLAlchemy @ file:///C:/Windows/Temp/abs_f8661157-660b-49bb-a790-69ab9f3b8f7c8a8s2psb/croots/recipe/sqlalchemy_1657867864564/work
tabulate==0.8.9
tensorboard==2.11.2
tensorboard-data-server==0.6.1
tensorboard-plugin-wit==1.8.1
tensorflow==2.11.0
tensorflow-estimator==2.11.0
tensorflow-intel==2.11.0
tensorflow-io-gcs-filesystem==0.31.0
termcolor==1.1.0
terminado @ file:///C:/ci/terminado_1644322782754/work
testpath @ file:///tmp/build/80754af9/testpath_1624638946665/work
thop==0.0.31.post2005241907
threadpoolctl @ file:///Users/ktietz/demo/mc3/conda-bld/threadpoolctl_1629802263681/work
tifffile @ file:///tmp/build/80754af9/tifffile_1627275862826/work
timm==0.6.7
toolz @ file:///tmp/build/80754af9/toolz_1636545406491/work
torch==1.9.1+cu102
torchaudio==0.9.1
torchmetrics==0.9.3
torchstat==0.0.7
torchvision==0.10.1+cu102
tornado @ file:///C:/ci/tornado_1606935947090/work
tqdm==4.63.0
traitlets @ file:///tmp/build/80754af9/traitlets_1636710298902/work
typing_extensions @ file:///opt/conda/conda-bld/typing_extensions_1647553014482/work
urllib3==1.26.9
wcwidth @ file:///Users/ktietz/demo/mc3/conda-bld/wcwidth_1629357192024/work
webencodings==0.5.1
Werkzeug==2.2.3
widgetsnbextension @ file:///C:/ci/widgetsnbextension_1645009553925/work
win32-setctime @ file:///home/tkoch/Workspace/win32_setctime/win32_setctime_1643630045199/work
wincertstore==0.2
wrapt==1.15.0
WTForms==3.0.1
xlwt==1.3.0
yacs==0.1.8
yapf==0.32.0
yarg==0.1.9
yarl==1.7.2
zipp @ file:///C:/ci/zipp_1652274072582/work以上就是Python怎么快速生成本项目的requeirments.txt的详细内容，更多请关注编程网其它相关文章！
免责声明：
① 本站未注明“稿件来源”的信息均来自网络整理。其文字、图片和音视频稿件的所属权归原作者所有。本站收集整理出于非商业性的教育和科研之目的，并不意味着本站赞同其观点或证实其内容的真实性。仅作为临时的测试数据，供内部测试之用。本站并未授权任何人以任何方式主动获取本站任何信息。
② 本站未注明“稿件来源”的临时测试数据将在测试完成后最终做删除处理。有问题或投稿请发送至: 邮箱/279061341@qq.com QQ/279061341
