blocks|key|4049248|text|如果您担心耗尽磁盘空间，您可以运行此命令来清理conda用于设置您的环境的所有临时包、压缩文件等。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|4049249|conda+clean+--all|code-block|syntax|javascript|4049250|随着时间的推移，这些文件会使磁盘变得杂乱无章。|4049251|使用|4049252|du+-h+-s+$(conda+info+--base)/envs/test-1|4049253|用于包的文件大小。|4049254|entityMap^0|0|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|D|7|R|8|@]|9|@]|A|$E|F]]|$1|G|3|H|5|6|7|S|8|@]|9|@]|A|$]]|$1|I|3|J|5|6|7|T|8|@]|9|@]|A|$]]|$1|K|3|L|5|D|7|U|8|@]|9|@]|A|$E|F]]|$1|M|3|N|5|6|7|V|8|@]|9|@]|A|$]]|$1|O|3|-4|5|6|7|W|8|@]|9|@]|A|$]]]|P|$]]

If you are concerned about using up disk space, you can run this command to clean up all the temporary packages, zip files, etc that conda used to setup your environment.
<pre><code>conda clean --all
</code></pre>
These files remain and can clutter up your disk over time.
use
<pre><code>du -h -s $(conda info --base)/envs/test-1
</code></pre>
for the file size of the package

blocks|key|4049273|text|du+tool可以告诉您特定目录占用了多少磁盘空间。例如，创建一个相同的conda环境(Miniconda)并检查其磁盘使用情况，如下所示：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4049274|$+conda+create+-n+testenv+-y+python+numpy+pandas

$+du+-h+-s+$(conda+info+--base)/envs/testenv
1.2G++++/opt/miniconda/envs/testenv+|code-block|syntax|javascript|4049275|entityMap^0|0|7|0|0^^$0|@$1|2|3|4|5|6|7|M|8|@$9|N|A|O|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|P|8|@]|D|@]|E|$I|J]]|$1|K|3|-4|5|6|7|Q|8|@]|D|@]|E|$]]]|L|$]]

The <code>du tool</code> can tell you how much disk space is occupied by a particular directory.
For example, create an identical conda environment (Miniconda) and check its disk usage like this:
<pre><code>$ conda create -n testenv -y python numpy pandas

$ du -h -s $(conda info --base)/envs/testenv
1.2G /opt/miniconda/envs/testenv 
</code></pre>

blocks|key|3266718|text|挖掘conda-meta|type|unstyled|depth|inlineStyleRanges|entityRanges|data|3266719|实现这一点的一种方法是为环境的conda-meta/目录中的每个包挖掘JSON元数据文件。所列的大小有两种：|offset|length|style|CODE|3266720|3266721|size+-+package|unordered-list-item|BOLD|3266722|size_in_bytes的总压缩tarball大小-包|3266723|中的单个解压缩文件大小|3266724|既然您似乎对包的总大小感兴趣，那么让我们来做一个更简单的+size+。这将使我们得到一个快速排名的软件包，根据他们的下载大小。|3266725|命令|3266726|##+activate+the+environment+of+interest
conda+activate+foo

##+search+all+the+JSONs+for+'"size":'
grep+'"size":'+${CONDA_PREFIX}/conda-meta/*.json+%7C\+

++##+sort+result
++sort+-k3rn+%7C\

++##+show+only+filename
++sed+'s/.*conda-meta\///g'+%7C\

++##+print+with+columns
++column+-t|code-block|syntax|javascript|3266727|示例输出|3266728|jaxlib-0.1.67-py39h6e9494a_0.json:++++++++++"size":++38576847,
scipy-1.6.3-py39h056f1c0_0.json:++++++++++++"size":++19495906,
python-3.9.4-h9133fd0_0_cpython.json:+++++++"size":++13160553,
libopenblas-0.3.15-openmp_h5e1b9a4_1.json:++"size":++9163719,
numpy-1.20.3-py39h7eed0ac_1.json:+++++++++++"size":++5732039,
tk-8.6.10-hb0a8c7a_1.json:++++++++++++++++++"size":++3420669,
openssl-1.1.1k-h0d85af4_0.json:+++++++++++++"size":++1985060,
sqlite-3.35.5-h44b9ce1_0.json:++++++++++++++"size":++1810221,
libgfortran5-9.3.0-h6c81a4c_22.json:++++++++"size":++1766473,
pip-21.1.2-pyhd8ed1ab_0.json:+++++++++++++++"size":++1147500,
libcxx-11.1.0-habf9029_0.json:++++++++++++++"size":++1055976,
setuptools-49.6.0-py39h6e9494a_3.json:++++++"size":++972968,
ncurses-6.2-h2e338ed_4.json:++++++++++++++++"size":++901840,
jax-0.2.14-pyhd8ed1ab_0.json:+++++++++++++++"size":++571585,
llvm-openmp-11.1.0-hda6cdc1_1.json:+++++++++"size":++274368,
readline-8.1-h05e3726_0.json:+++++++++++++++"size":++272444,
xz-5.2.5-haf1e3a3_1.json:+++++++++++++++++++"size":++233058,
certifi-2021.5.30-py39h6e9494a_0.json:++++++"size":++144599,
ca-certificates-2021.5.30-h033912b_0.json:++"size":++139088,
tzdata-2021a-he74cb21_0.json:+++++++++++++++"size":++123802,
zlib-1.2.11-h7795811_1010.json:+++++++++++++"size":++104180,
absl-py-0.12.0-pyhd8ed1ab_0.json:+++++++++++"size":++98565,
tqdm-4.61.0-pyhd8ed1ab_0.json:++++++++++++++"size":++81513,
opt_einsum-3.3.0-pyhd8ed1ab_1.json:+++++++++"size":++54494,
libffi-3.3-h046ec9c_2.json:+++++++++++++++++"size":++46425,
wheel-0.36.2-pyhd3deb0d_0.json:+++++++++++++"size":++31381,
python-flatbuffers-2.0-pyhd8ed1ab_0.json:+++"size":++28606,
libgfortran-5.0.0-9_3_0_h6c81a4c_22.json:+++"size":++19280,
six-1.16.0-pyh6c4a22f_0.json:+++++++++++++++"size":++14259,
libblas-3.9.0-9_openblas.json:++++++++++++++"size":++11762,
libcblas-3.9.0-9_openblas.json:+++++++++++++"size":++11671,
liblapack-3.9.0-9_openblas.json:++++++++++++"size":++11671,
python_abi-3.9-1_cp39.json:+++++++++++++++++"size":++3921,|3266729|上面的输出显示jaxlib是最大的包，其次是scipy，然后是python解释器本身。在这种情况下，如果我想要删除jaxlib，也需要删除jax。|3266730|备注|3266731|我认为以上是按大小排列软件包的第一次近似。size_in_bytes可能更准确，但要彻底，还需要考虑哪些单独的文件是硬链接的，因为在每个环境级别上，这些文件实际上不应该被计算在包中。对于他们来说，每个系统只有一个副本，并且它在不同的环境中被重用。|3266732|entityMap^0|0|F|B|0|0|0|4|0|0|D|0|0|S|6|0|0|2|0|0|0|4|0|0|7|6|M|5|V|6|1L|6|1X|3|0|0|L|D|0^^$0|@$1|2|3|4|5|6|7|1B|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|1C|8|@$D|1D|E|1E|F|G]]|9|@]|A|$]]|$1|H|3|-4|5|6|7|1F|8|@]|9|@]|A|$]]|$1|I|3|J|5|K|7|1G|8|@$D|1H|E|1I|F|L]]|9|@]|A|$]]|$1|M|3|N|5|K|7|1J|8|@$D|1K|E|1L|F|L]]|9|@]|A|$]]|$1|O|3|P|5|6|7|1M|8|@]|9|@]|A|$]]|$1|Q|3|R|5|6|7|1N|8|@$D|1O|E|1P|F|L]]|9|@]|A|$]]|$1|S|3|T|5|6|7|1Q|8|@$D|1R|E|1S|F|L]]|9|@]|A|$]]|$1|U|3|V|5|W|7|1T|8|@]|9|@]|A|$X|Y]]|$1|Z|3|10|5|6|7|1U|8|@$D|1V|E|1W|F|L]]|9|@]|A|$]]|$1|11|3|12|5|W|7|1X|8|@]|9|@]|A|$X|Y]]|$1|13|3|14|5|6|7|1Y|8|@$D|1Z|E|20|F|G]|$D|21|E|22|F|G]|$D|23|E|24|F|G]|$D|25|E|26|F|G]|$D|27|E|28|F|G]]|9|@]|A|$]]|$1|15|3|16|5|6|7|29|8|@]|9|@]|A|$]]|$1|17|3|18|5|6|7|2A|8|@$D|2B|E|2C|F|G]]|9|@]|A|$]]|$1|19|3|-4|5|6|7|2D|8|@]|9|@]|A|$]]]|1A|$]]

<h1>Mine the conda-meta</h1>
One way to get at this is by mining the JSON metadata files for each package inside an environment's <code>conda-meta/</code> directory. There are two types of sizes listed:
<ul>
<li>size - total zipped tarball size for the package</li>
<li>size_in_bytes - individual unzipped file sizes within a package</li>
</ul>
Since you seem interested in total size of a package, let's do the simpler size. This will let us get a quick ranking of packages by their download size.
Commands
<pre class="lang-bash prettyprint-override"><code>## activate the environment of interest
conda activate foo

## search all the JSONs for '&quot;size&quot;:'
grep '&quot;size&quot;:' ${CONDA_PREFIX}/conda-meta/*.json |\ 

 ## sort result
 sort -k3rn |\

 ## show only filename
 sed 's/.*conda-meta\///g' |\

 ## print with columns
 column -t
</code></pre>
Example Output
<pre class="lang-bash prettyprint-override"><code>jaxlib-0.1.67-py39h6e9494a_0.json: &quot;size&quot;: 38576847,
scipy-1.6.3-py39h056f1c0_0.json: &quot;size&quot;: 19495906,
python-3.9.4-h9133fd0_0_cpython.json: &quot;size&quot;: 13160553,
libopenblas-0.3.15-openmp_h5e1b9a4_1.json: &quot;size&quot;: 9163719,
numpy-1.20.3-py39h7eed0ac_1.json: &quot;size&quot;: 5732039,
tk-8.6.10-hb0a8c7a_1.json: &quot;size&quot;: 3420669,
openssl-1.1.1k-h0d85af4_0.json: &quot;size&quot;: 1985060,
sqlite-3.35.5-h44b9ce1_0.json: &quot;size&quot;: 1810221,
libgfortran5-9.3.0-h6c81a4c_22.json: &quot;size&quot;: 1766473,
pip-21.1.2-pyhd8ed1ab_0.json: &quot;size&quot;: 1147500,
libcxx-11.1.0-habf9029_0.json: &quot;size&quot;: 1055976,
setuptools-49.6.0-py39h6e9494a_3.json: &quot;size&quot;: 972968,
ncurses-6.2-h2e338ed_4.json: &quot;size&quot;: 901840,
jax-0.2.14-pyhd8ed1ab_0.json: &quot;size&quot;: 571585,
llvm-openmp-11.1.0-hda6cdc1_1.json: &quot;size&quot;: 274368,
readline-8.1-h05e3726_0.json: &quot;size&quot;: 272444,
xz-5.2.5-haf1e3a3_1.json: &quot;size&quot;: 233058,
certifi-2021.5.30-py39h6e9494a_0.json: &quot;size&quot;: 144599,
ca-certificates-2021.5.30-h033912b_0.json: &quot;size&quot;: 139088,
tzdata-2021a-he74cb21_0.json: &quot;size&quot;: 123802,
zlib-1.2.11-h7795811_1010.json: &quot;size&quot;: 104180,
absl-py-0.12.0-pyhd8ed1ab_0.json: &quot;size&quot;: 98565,
tqdm-4.61.0-pyhd8ed1ab_0.json: &quot;size&quot;: 81513,
opt_einsum-3.3.0-pyhd8ed1ab_1.json: &quot;size&quot;: 54494,
libffi-3.3-h046ec9c_2.json: &quot;size&quot;: 46425,
wheel-0.36.2-pyhd3deb0d_0.json: &quot;size&quot;: 31381,
python-flatbuffers-2.0-pyhd8ed1ab_0.json: &quot;size&quot;: 28606,
libgfortran-5.0.0-9_3_0_h6c81a4c_22.json: &quot;size&quot;: 19280,
six-1.16.0-pyh6c4a22f_0.json: &quot;size&quot;: 14259,
libblas-3.9.0-9_openblas.json: &quot;size&quot;: 11762,
libcblas-3.9.0-9_openblas.json: &quot;size&quot;: 11671,
liblapack-3.9.0-9_openblas.json: &quot;size&quot;: 11671,
python_abi-3.9-1_cp39.json: &quot;size&quot;: 3921,
</code></pre>
The above output shows <code>jaxlib</code> is the largest package, followed by <code>scipy</code>, then the <code>python</code> interpreter itself. In this case, if I wanted to remove <code>jaxlib</code> it would also entail removing <code>jax</code>.
<h3>Notes</h3>
I think the above serves as a first approximation for ranking the packages by size. The <code>size_in_bytes</code> could possibly be more exact, but to be thorough one would need to also consider which individual files are hardlinked, since those actually shouldn't be counted against the package on a per environment level. For them, there is only one copy per system and it gets reused across environments.

blocks|key|4049335|text|您可以通过pip通信使用subprocess模块(Python3.7)：|type|unstyled|depth|inlineStyleRanges|offset|length|style|CODE|entityRanges|data|4049336|from+pip._internal.commands.show+import+search_packages_info
import+subprocess
import+sys
import+json
import+pathlib
import+math
import+operator

TMPL+=+'{:<30}+{:<30}+{:<10}+{:>9}'


def+humanize(size):
++++"""Convert+size+in+bytes+to+human+readable+output."""
++++try:
++++++++units+=+['B',+'KB',+'MB',+'GB']
++++++++i+=+math.floor(math.log(size)+/+math.log(1024))
++++++++hsize+=+f"{round(size+/+1024**i)}{units[i]}"
++++except+ValueError:
++++++++hsize+=+'0B'
++++return+hsize


def+pip_list_ext():
++++"""List+installed+packages+with+additional+information."""
++++#+python+-m+pip+list+--format+--json+--verbose
++++pip_list+=+subprocess.run([sys.executable,+'-m',+'pip',+'list',
+++++++++++++++++++++++++++++++'--format',+'json',+'--verbose'],
++++++++++++++++++++++++++++++capture_output=True)

++++if+pip_list.returncode+!=+0:
++++++++raise+RuntimeError('...')

++++query+=+[pkg['name']+for+pkg+in+json.loads(pip_list.stdout)]
++++packages+=+[]
++++for+pkg+in+search_packages_info(query):
++++++++location+=+pathlib.Path(pkg['location'])
++++++++pkg['installer']+=+pkg.get('installer',+'')
++++++++pkg['files']+=+pkg.get('files',+[])
++++++++size+=+sum((location+/+f).stat().st_size
+++++++++++++++++++++++for+f+in+pkg['files']+if+(location+/+f).is_file())
++++++++pkg['size']+=+size
++++++++packages.append(pkg)

++++return+packages

if+__name__+==+'__main__':
++++packages+=+pip_list_ext()

++++print(TMPL.format('Package',+'Version',+'Installer',+'Size'))
++++print(TMPL.format('-'*30,+'-'*30,+'-'*10,+'-'*9))
++++for+pkg+in+packages:
++++++++print(TMPL.format(pkg['name'],+pkg['version'],
++++++++++++++++++++++++++pkg['installer'],+humanize(pkg['size'])))

++++#+TOP+10
++++N+=+10
++++pkgs+=+sorted(packages,+key=operator.itemgetter('size'),+reverse=True)
++++print(f"\nTOP+{N}:")
++++for+i,+pkg+in+enumerate(pkgs[:N],+1):
++++++++print(f"{i:>2}.+{pkg['name']}+({humanize(pkg['size'])})")|code-block|syntax|javascript|4049337|样本输出|4049338|Package++++++++++++++++++++++++Version++++++++++++++++++++++++Installer+++++++Size
------------------------------+------------------------------+----------+---------
appnope++++++++++++++++++++++++0.1.2++++++++++++++++++++++++++conda+++++++++++13KB
backcall+++++++++++++++++++++++0.2.0++++++++++++++++++++++++++conda+++++++++++58KB
certifi++++++++++++++++++++++++2021.5.30+++++++++++++++++++++++++++++++++++++261KB
cffi+++++++++++++++++++++++++++1.14.5+++++++++++++++++++++++++conda++++++++++780KB
cryptography+++++++++++++++++++3.4.7++++++++++++++++++++++++++conda++++++++++++2MB
decorator++++++++++++++++++++++5.0.9++++++++++++++++++++++++++conda+++++++++++35KB
ipython++++++++++++++++++++++++7.22.0+++++++++++++++++++++++++conda++++++++++++4MB
ipython-genutils+++++++++++++++0.2.0++++++++++++++++++++++++++conda+++++++++++66KB
jedi+++++++++++++++++++++++++++0.17.2+++++++++++++++++++++++++conda++++++++++++5MB
mkl-fft++++++++++++++++++++++++1.3.0++++++++++++++++++++++++++++++++++++++++++++0B
mkl-random+++++++++++++++++++++1.2.1++++++++++++++++++++++++++conda++++++++++++1MB
mkl-service++++++++++++++++++++2.3.0++++++++++++++++++++++++++++++++++++++++++++0B
numpy++++++++++++++++++++++++++1.20.2+++++++++++++++++++++++++conda+++++++++++23MB
pandas+++++++++++++++++++++++++1.2.4++++++++++++++++++++++++++++++++++++++++++27MB
parso++++++++++++++++++++++++++0.7.0++++++++++++++++++++++++++conda++++++++++320KB
pexpect++++++++++++++++++++++++4.8.0++++++++++++++++++++++++++conda++++++++++177KB
pickleshare++++++++++++++++++++0.7.5++++++++++++++++++++++++++conda+++++++++++23KB
pip++++++++++++++++++++++++++++21.1.2+++++++++++++++++++++++++++++++++++++++++++0B
prompt-toolkit+++++++++++++++++3.0.17+++++++++++++++++++++++++conda++++++++++++2MB
ptyprocess+++++++++++++++++++++0.7.0++++++++++++++++++++++++++conda+++++++++++40KB
pycparser++++++++++++++++++++++2.20+++++++++++++++++++++++++++conda++++++++++547KB
Pygments+++++++++++++++++++++++2.9.0++++++++++++++++++++++++++conda++++++++++++6MB
pyOpenSSL++++++++++++++++++++++20.0.1+++++++++++++++++++++++++conda++++++++++212KB
python-dateutil++++++++++++++++2.8.1++++++++++++++++++++++++++conda++++++++++619KB
pytz+++++++++++++++++++++++++++2021.1+++++++++++++++++++++++++conda++++++++++971KB
setuptools+++++++++++++++++++++52.0.0.post20210125++++++++++++++++++++++++++++++0B
six++++++++++++++++++++++++++++1.15.0+++++++++++++++++++++++++conda+++++++++++63KB
traitlets++++++++++++++++++++++5.0.5++++++++++++++++++++++++++conda++++++++++798KB
wcwidth++++++++++++++++++++++++0.2.5++++++++++++++++++++++++++conda++++++++++411KB
wheel++++++++++++++++++++++++++0.36.2+++++++++++++++++++++++++++++++++++++++++++0B|4049339|TOP+10:
+1.+pandas+(27MB)
+2.+numpy+(23MB)
+3.+Pygments+(6MB)
+4.+jedi+(5MB)
+5.+ipython+(4MB)
+6.+cryptography+(2MB)
+7.+prompt-toolkit+(2MB)
+8.+mkl-random+(1MB)
+9.+pytz+(971KB)
10.+traitlets+(798KB)|4049340|entityMap^0|5|3|C|A|0|0|0|0|0^^$0|@$1|2|3|4|5|6|7|S|8|@$9|T|A|U|B|C]|$9|V|A|W|B|C]]|D|@]|E|$]]|$1|F|3|G|5|H|7|X|8|@]|D|@]|E|$I|J]]|$1|K|3|L|5|6|7|Y|8|@]|D|@]|E|$]]|$1|M|3|N|5|H|7|Z|8|@]|D|@]|E|$I|J]]|$1|O|3|P|5|H|7|10|8|@]|D|@]|E|$I|J]]|$1|Q|3|-4|5|6|7|11|8|@]|D|@]|E|$]]]|R|$]]

You can use <code>pip</code> module through <code>subprocess</code> communication (Python &gt;= 3.7):
<pre class="lang-py prettyprint-override"><code>from pip._internal.commands.show import search_packages_info
import subprocess
import sys
import json
import pathlib
import math
import operator

TMPL = '{:&lt;30} {:&lt;30} {:&lt;10} {:&gt;9}'


def humanize(size):
 &quot;&quot;&quot;Convert size in bytes to human readable output.&quot;&quot;&quot;
 try:
 units = ['B', 'KB', 'MB', 'GB']
 i = math.floor(math.log(size) / math.log(1024))
 hsize = f&quot;{round(size / 1024**i)}{units[i]}&quot;
 except ValueError:
 hsize = '0B'
 return hsize


def pip_list_ext():
 &quot;&quot;&quot;List installed packages with additional information.&quot;&quot;&quot;
 # python -m pip list --format --json --verbose
 pip_list = subprocess.run([sys.executable, '-m', 'pip', 'list',
 '--format', 'json', '--verbose'],
 capture_output=True)

 if pip_list.returncode != 0:
 raise RuntimeError('...')

 query = [pkg['name'] for pkg in json.loads(pip_list.stdout)]
 packages = []
 for pkg in search_packages_info(query):
 location = pathlib.Path(pkg['location'])
 pkg['installer'] = pkg.get('installer', '')
 pkg['files'] = pkg.get('files', [])
 size = sum((location / f).stat().st_size
 for f in pkg['files'] if (location / f).is_file())
 pkg['size'] = size
 packages.append(pkg)

 return packages

if __name__ == '__main__':
 packages = pip_list_ext()

 print(TMPL.format('Package', 'Version', 'Installer', 'Size'))
 print(TMPL.format('-'*30, '-'*30, '-'*10, '-'*9))
 for pkg in packages:
 print(TMPL.format(pkg['name'], pkg['version'],
 pkg['installer'], humanize(pkg['size'])))

 # TOP 10
 N = 10
 pkgs = sorted(packages, key=operator.itemgetter('size'), reverse=True)
 print(f&quot;\nTOP {N}:&quot;)
 for i, pkg in enumerate(pkgs[:N], 1):
 print(f&quot;{i:&gt;2}. {pkg['name']} ({humanize(pkg['size'])})&quot;)
</code></pre>
Sample output
<pre><code>Package Version Installer Size
------------------------------ ------------------------------ ---------- ---------
appnope 0.1.2 conda 13KB
backcall 0.2.0 conda 58KB
certifi 2021.5.30 261KB
cffi 1.14.5 conda 780KB
cryptography 3.4.7 conda 2MB
decorator 5.0.9 conda 35KB
ipython 7.22.0 conda 4MB
ipython-genutils 0.2.0 conda 66KB
jedi 0.17.2 conda 5MB
mkl-fft 1.3.0 0B
mkl-random 1.2.1 conda 1MB
mkl-service 2.3.0 0B
numpy 1.20.2 conda 23MB
pandas 1.2.4 27MB
parso 0.7.0 conda 320KB
pexpect 4.8.0 conda 177KB
pickleshare 0.7.5 conda 23KB
pip 21.1.2 0B
prompt-toolkit 3.0.17 conda 2MB
ptyprocess 0.7.0 conda 40KB
pycparser 2.20 conda 547KB
Pygments 2.9.0 conda 6MB
pyOpenSSL 20.0.1 conda 212KB
python-dateutil 2.8.1 conda 619KB
pytz 2021.1 conda 971KB
setuptools 52.0.0.post20210125 0B
six 1.15.0 conda 63KB
traitlets 5.0.5 conda 798KB
wcwidth 0.2.5 conda 411KB
wheel 0.36.2 0B
</code></pre>
<pre><code>TOP 10:
 1. pandas (27MB)
 2. numpy (23MB)
 3. Pygments (6MB)
 4. jedi (5MB)
 5. ipython (4MB)
 6. cryptography (2MB)
 7. prompt-toolkit (2MB)
 8. mkl-random (1MB)
 9. pytz (971KB)
10. traitlets (798KB)
</code></pre>

blocks|key|859938|text|此解决方案适用于Windows+10。|type|unstyled|depth|inlineStyleRanges|entityRanges|data|859939|安装Windows，以便您有命令实用程序du。运行du命令，在Anaconda中查找site-packages下的包大小，并将结果存储在csv文件中。|offset|length|style|CODE|859940|$+du+-c+-v+Lib/site-packages/+>+packages.csv|code-block|syntax|javascript|859941|使用Excel打开packages.csv。按降序排序包大小的列。现在，您已经了解了具有最大包大小的包的信息。|859942|entityMap^0|0|K|2|P|2|16|D|0|0|9|C|0^^$0|@$1|2|3|4|5|6|7|Q|8|@]|9|@]|A|$]]|$1|B|3|C|5|6|7|R|8|@$D|S|E|T|F|G]|$D|U|E|V|F|G]|$D|W|E|X|F|G]]|9|@]|A|$]]|$1|H|3|I|5|J|7|Y|8|@]|9|@]|A|$K|L]]|$1|M|3|N|5|6|7|Z|8|@$D|10|E|11|F|G]]|9|@]|A|$]]|$1|O|3|-4|5|6|7|12|8|@]|9|@]|A|$]]]|P|$]]

This solution works for Windows 10.
Install Windows SysInternals so that you have the command utility <code>du</code>.
Run the <code>du</code> command to find out the packages size under <code>site-packages</code> in Anaconda and store result in csv file.
<pre><code>$ du -c -v Lib/site-packages/ &gt; packages.csv
</code></pre>
Open <code>packages.csv</code> using Excel. Sort the column for the package size in descending order. Now, you have the information on the packages with the largest package size.

I would like to find out the size of conda packages to delete the huge and seldom used ones. Which conda command should I use to find out the package size?
<code>conda list</code> will list the packages but does not show the package size.
I welcome other methods to find out package size.
I'm using Windows 10.

Conda command to list size of packages

翻译质量差，导致语言生硬或混乱。

没有提供实际的解决方法或示例。

解答不清晰，无法理解或解决问题。

页面排版不美观，阅读体验差。

文章

问答

视频

教程

学习中心

腾讯云实验室

直播

竞赛

腾讯云代码分析专区

腾讯iOA零信任安全管理系统专区

腾讯云架构师技术同盟交流圈

腾讯云数据库专区

腾讯云智能顾问专区

腾讯云原生专区

腾讯混元专区

腾讯云TCE专区

腾讯云Lighthouse专区

腾讯云HAI专区

腾讯云Edgeone专区

腾讯云存储专区

腾讯云智能专区

腾讯轻联专区 

腾讯云开发专区

TAPD专区

腾讯轻量云游戏服专区

EdgeOne AI 安全实战专区

腾讯云最具价值专家

腾讯云架构师技术同盟

腾讯云创作之星

腾讯云开发者先锋

腾讯云代码助手

云原生构建

TAPD 敏捷项目管理

Cloud Studio

SDK中心

API中心

命令行工具

涵盖代码开发、场景应用、自动测试全流程，助你从零构建专属AI助手

一站式MCP教程库，解锁AI应用新玩法

聚焦“写作效率、视觉美观与运行性能”三方面进行全面升级，为您提供更高效、稳定的创作环境

社区富文本&Markdown编辑器全新改版上线，欢迎大家体验!

诚挚邀请您参与本次调研，分享您的真实使用感受与建议。您的反馈至关重要，感谢您的支持与参与！

社区新版编辑器体验调研

我想找出conda软件包的大小，以删除那些很少使用的大型软件包。我应该使用哪个conda命令来找出包的大小？conda list将列出包，但不显示包大小。我欢迎其他方法来找出包装尺寸。我在用Windows 10。

问用于列出包大小的Conda命令
EN

Stack Overflow用户

社区

活动

圈层

关于

腾讯云开发者

热门产品

热门推荐

更多推荐

问用于列出包大小的Conda命令EN