Result for 37C828032B911A01059F18CAE1FD31CF16495426

Query result

Key	Value
FileSize	91436
MD5	8FC02DC0CAE8F0E5564BD38E9B6155A2
PackageDescription	Sparse linear algebra extension for Python This provides a set of sparse matrix types for Python, with modules which implement: - Iterative methods for solving linear systems of equations - A set of standard preconditioners - An interface to a direct solver for sparse linear systems of equations - The JDSYM eigensolver . All of these modules are implemented as C extension modules based on standard sparse and dense matrix libraries (UMFPACK/AMD, SuperLU, BLAS/LAPACK) for maximum performance and robustness.
PackageMaintainer	Debian Science Maintainers <debian-science-maintainers@lists.alioth.debian.org>
PackageName	python-sparse
PackageSection	python
PackageVersion	1.1.1-2
SHA-1	37C828032B911A01059F18CAE1FD31CF16495426
SHA-256	1F60CDA4E79899E85B4FB41D0B720FA3F91CC26A48C9CFF2D7D46A8C641B2041
hashlookup:children-total	39
hashlookup:trust	50

Network graph view

Children (Total: 39)

The searched file hash includes 39 children files known and seen by metalookup. A sample is included below:

Key	Value
FileName	./usr/lib/python2.7/dist-packages/pysparse/superlu.aarch64-linux-gnu.so
FileSize	16688
MD5	44221A9166603CDA41C9996D83A81909
SHA-1	0E209786C131E307FB4B3DF745C1F85975C58FB8
SHA-256	5637E9BA575436834E98DC26400386F32CAA1D3C4A24E356A56495110B742CC1
SSDEEP	192:X/MeE8FuuojS+mscA6VB2OY3IOWLRfmuT+R3WqBeaL9nC:bIBjS+/c7hY3IbfmqRkeaQ
TLSH	T16572929EF944D93FCA8943B984C74AB0F7248249935693A7350D466A2FC339B9E3D4CC

Key	Value
FileName	./usr/include/python2.7/pysparse/qmrs.h
FileSize	292
MD5	E4298D4F555C2EC1ABC32E1A1E7D5004
SHA-1	18816B97DCF83D67CDBE5D374F4D2550B0B8A3C8
SHA-256	3CA79D79AB368EF8F24745A31E51085CD3DBD9149B95BCDAF2AC0BDD24B13D9B
SSDEEP	6:N0OqfRAgEh5AMULjcWIRF9VHjdLXIPSLrly09EJGmlG4sj61XA4O:NkfRAgEXAMUncNRFxK3eEJGB466C4O
TLSH	T162E0C20F8B4CBAA72825D0D091CE0894E6AF8233894AB4ADE354F6C5830305530728B6

Key	Value
FileName	./usr/include/python2.7/pysparse/blas.h
FileSize	24588
MD5	49F1C08BA5F0F6DD48893FCB6116CB78
SHA-1	1FD1179A6A42C0395EB116DAF6526DF7BA66E87B
SHA-256	911D331E788E9C039BC4EBDD040565871015D31BBFCF272F50693FD4C61D1FF5
SSDEEP	768:3l0ljBl7ltBrBlvBCBvlBYBlZBlQBvlBalBdBlBNdBlhlNk2BBvBW0BlXp/B87lb:3l0ljBl7ltBrBlvBCBvlBYBlZBlQBvlP
TLSH	T114B2B55C0AA15446EB5E3EE846CAC186D001525348DE6ACA7C3DCA71AF8FFC812BDD97

Key	Value
FileName	./usr/include/python2.7/pysparse/sss_mat.h
FileSize	534
MD5	31AB02D781928B2C7D27EA48F3839217
SHA-1	2157E4B64360F6D418BE2186F5E61269FC6CE535
SHA-256	55F8F26AA1D088106857F3BD70DECE346EC6247F237812DEFCC988EC233CEBE5
SSDEEP	12:9qntAMUsJoxQvjUqT2c32RD6PvOFeJKFc+y5LAUzN70aU3vL:9qnt7bGxhAZ32RDkzJOy5LAUiaU3z
TLSH	T127F02B39BE659D7E15858F95F001E215C46B463CA1E4FCD0974E68A43F6343123BA10F

Key	Value
FileName	./usr/include/python2.7/pysparse/mmio.h
FileSize	4190
MD5	99B0D3E560F0F7683EAA61AD1AE50D12
SHA-1	2679E15FC5FB1DB86A2F5D6C4BEA224EFF2CD134
SHA-256	231F7B39611DC5822CDDF7DCFB6349B64C11DAE123ADBA67B52899C97218F9B1
SSDEEP	48:bFf7DYI9gxvDlegdFINhKU0hrleUcqEqKK0DHSnGMm8QeTULXQXhEqGUOkeEerp:pfwD9f1Eqp2SGMLboeerp
TLSH	T1DC810FA148956D222AB36B25529D14C0153DF833D99610EC387A7BFC5F2E0790CF3B9C

Key	Value
FileName	./usr/include/python2.7/pysparse/spmatrix.h
FileSize	2297
MD5	34BF67EF9C5E87626950E4085A1EF734
SHA-1	2E1BBE148CB5C1ACD2683BF473CC58A5C01E4576
SHA-256	4C238DF752843A8B4AFF78C9C074CDF34F67FFA9C47953037B299EFEC364C47F
SSDEEP	48:QRePWL2ILWsRtMZKxcZNrQc0MNMQcXRt8ZKxcPBQc0PNYQchWyR3NQKQcew:vsVcZN0c0MNBctcPqc0PN9cvNQ/cew
TLSH	T1C541EC0E3DB9373602D440248E95CA0DAB35A65723BD0EA0705CF8E2BF74A516A35F7D

Key	Value
FileName	./usr/lib/python3.11/site-packages/django_json_widget/__init__.py
FileSize	22
MD5	C30F35B39F0592CEE5F49F42C48E715B
SHA-1	345E1F1488BB17032A4FB465548C4D6E0B1A855A
SHA-256	13EEB00198E22D15489C0045C6B5A8A9D6253BFB7ECD584AF1735F367683CB32
SSDEEP	3:cvZLs:81s
TLSH

Key	Value
FileName	./usr/lib/python2.7/dist-packages/pysparse/precon.aarch64-linux-gnu.so
FileSize	15872
MD5	09F4ED5FF1B38A71F92708EBD3076C6E
SHA-1	351C53116183A6D8CC5790294451761E86399625
SHA-256	140627BF487260E0FC226988D71D0C57048BC10A4F54166F65B615524BA58BFE
SSDEEP	192:FnA+28k0vmyrDBkjlrE+KFr9oB/O2FuCR3WZ2m:iBKLrdkJo+T22FUZ
TLSH	T10962C7ADF94D993BC6D99774C886837177728148E36AB3D3610A85902F837CF8F19A4C

Key	Value
FileName	./usr/lib/python2.7/dist-packages/pysparse/poisson_vec.py
FileSize	2613
MD5	0D269E8CC5FDD19D5F07B8BFF4D16762
SHA-1	48720D118E7665775F3BB3C39781D559F5FB5556
SHA-256	F6EFD68B87B0453F3184DC798C0DDD5C8E6A720E0912BAB55895B3BF05F859DB
SSDEEP	48:pc2M/hqEz2M/hZTb2M/AmeEeRTNiZa6Ez27RTj2M/Am0Sba2M///eMs:pc2khzz2khZTb2kITN8a3STj2kBba2kU
TLSH	T1E65123278D3724B94B838895F8818BE33BA4157789447CE4FD6DA8D85F4D83A8770793

Key	Value
FileName	./usr/share/doc/python-sparse/copyright
FileSize	7221
MD5	085B7563090928F54A9AA31E8D4DD7E1
SHA-1	4B8BFE8B80B92F35B8E85F109FD7E28813A972C1
SHA-256	E9B386BFD19B28F28D8B4840511EB8E46911C94F7775290B018E59A8CCD37C46
SSDEEP	192:9CYrsqrsAN3r3LaGev0pmvXH3ibadiKxxbxhlSOdjrpp0:97rsqrsA1DLPevmmvXH3vdHXhl10
TLSH	T110E1929E6F8857720193CA92379E9588F28D973F76232C053C4C835823A791C97FE1D9