Skip to main content

Load a ProcDump memory dump into a Pandas DataFrame

Project description

ProcDump memory dump to Pandas DataFrame

# Download ProcDump: https://learn.microsoft.com/pt-br/sysinternals/downloads/procdump

$pip install a-pandas-ex-memorydump-to-df



import pandas as pd

from a_pandas_ex_memorydump_to_df import pd_add_memorydf

pd_add_memorydf()



df = pd.Q_df_from_memory(

    pid=9132, procdumppath=r"C:\Program Files\procdump.exe", with_utf8_bytes=False

)  # with_utf8_bytes=True takes much more time!





The method will convert all bytes to every possible format which means, the DataFrame 

might get huge. 







# Notepad.exe

#       aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66

# 0            00000000        00010000  ...               46               46

# 1            00000000        00010010  ...               46               46

# 2            00000000        00010020  ...               46               46

# 3            00000000        00010030  ...               46               46

# 4            00000000        00010040  ...               46               46

#                ...             ...  ...              ...              ...

# 64014        00007ff5        fffb0fc0  ...               46               46

# 64015        00007ff5        fffb0fd0  ...               46               46

# 64016        00007ff5        fffb0fe0  ...               46               46

# 64017        00007ff5        fffb0ff0  ...               46               46

# 64018        00007ff5        fffb1000  ...                0                0

# [64019 rows x 304 columns]



# df.size

# Out[16]: 19461776



# explorer.exe

# df

# Out[10]:

#         aa_address1_hex aa_address2_hex  ...  aa_ascii_int_63  aa_ascii_int_66

# 0              00000000        00010000  ...               46               46

# 1              00000000        00010010  ...               46               46

# 2              00000000        00010020  ...               46               46

# 3              00000000        00010030  ...               46               46

# 4              00000000        00010040  ...               46               46

#                  ...             ...  ...              ...              ...

# 3234712        00007ff5        fffb0fc0  ...               46               46

# 3234713        00007ff5        fffb0fd0  ...               46               46

# 3234714        00007ff5        fffb0fe0  ...               46               46

# 3234715        00007ff5        fffb0ff0  ...               46               46

# 3234716        00007ff5        fffb1000  ...                0                0

#

# [3234717 rows x 304 columns]

#

# df.size

# Out[11]: 983353968



# Location of the temp file (procdump)

# df.tmp_file_path

# Out[14]: 'C:\\Users\\Gamer\\AppData\\Local\\Temp\\tmpsypcc1g5.dmp'

# df.tmp_delete_file()  $ file must be closed before

Let's compare the converted values with the ones from CheatEngine

Project details


Download files

Download the file for your platform. If you're not sure which to choose, learn more about installing packages.

Source Distribution

a_pandas_ex_memorydump_to_df-0.10.tar.gz (8.9 kB view details)

Uploaded Source

Built Distribution

a_pandas_ex_memorydump_to_df-0.10-py3-none-any.whl (9.8 kB view details)

Uploaded Python 3

File details

Details for the file a_pandas_ex_memorydump_to_df-0.10.tar.gz.

File metadata

File hashes

Hashes for a_pandas_ex_memorydump_to_df-0.10.tar.gz
Algorithm Hash digest
SHA256 63dd4b68b3dd9cafe05510b4eee8627fa65c7a46919329bb72a1973c02d2b6e4
MD5 5bab2b8c44f87af7f010c9535a82a52b
BLAKE2b-256 3676bd1b59a05b2f7818476055e59ccb215465e19237022e1814ba1e6d073487

See more details on using hashes here.

File details

Details for the file a_pandas_ex_memorydump_to_df-0.10-py3-none-any.whl.

File metadata

File hashes

Hashes for a_pandas_ex_memorydump_to_df-0.10-py3-none-any.whl
Algorithm Hash digest
SHA256 5aa8ed9d7b412483b87afb4fd9e2e4407369d4c8977e833e64da9891173c7b09
MD5 e75020d73d3c3c6a232a52c2c76a130f
BLAKE2b-256 e70b5b58c1bdac7b39ed277296aea217d667e4e89a5aaedf3126fa1ed45b7a31

See more details on using hashes here.

Supported by

AWS Cloud computing and Security Sponsor Datadog Monitoring Fastly CDN Google Download Analytics Pingdom Monitoring Sentry Error logging StatusPage Status page