í«îÛpython-pure-eval-0.2.2-1.oe2403Žè¤>”Ð Ðùè<ì@ïPðT@‰Í7!.Ü¶›uj¤Œï·Gû7¼of=‡4openeuler@compass-ci.com ·Gû7¼oZNÿz¼í8k:~Žàt<ìµ ¬”µ’½¢ûmú"â¶[†'^õïÇ†^¸ìkyé"Ú;µB¹ªuo/ÞÖ¤éÊüqóâpçk–U’î²•åDZ."ß¹U#µv71d¢Bø6=!LÜ±hÁWþ}}ªÛMÅ{1k‡¶øšã-GïèŠŒÔ¡Œ¼ I¾XªŸ6EKÈF«Æ(!9s$Eê3õ¤Y¡DSŒŒR%PžY"n,¿ñßëT´à3šežãçK9ÛëÁwî˜Cô=÷ü¤Çðæî¸NE“‡£’’iï¦þo2` 6~KÓÓ–&¶ê~õ£AÒSÊ[1…*‚*GÂ«¬/x9¢*/À è?2ýXìÑdyGçÑBÒ"@›âò_£¹ —Œ¿ðAäAõâjiÍ‡™W#`Ì÷$½mj4yi÷óì,"o(1ao3Yçù±4ãéÀG”´ðÖŽü†p„H1ž6x¾ÐÙ?µ7¾72b7c0c0e9980bb366d34773407198430e2ad3961cb1389d03f4eaf2526a07c07804e7d2848726e4eeeb7feb878677e80f5c7116bÀl <›j#FJ9iC,'Bv”À>ÿÿÿ€Žè7dÃ?d³dèéêì "í Qîxï|ñö”÷˜ø ú¹üÐý÷þý ž ¨²¼Äì‰(ž8¨9¬:ÜAõFüGH$I,R0X4Y<\\]d^‘d’e—fœ“ Æ¤äªåìéðë1Cpython-pure-eval0.2.21.oe2403Safely evaluate AST nodes without side effects [![Build Status](https://travis-ci.org/alexmojaki/pure_eval.svg?branch=master)](https://travis-ci.org/alexmojaki/pure_eval) [![Coverage Status](https://coveralls.io/repos/github/alexmojaki/pure_eval/badge.svg?branch=master)](https://coveralls.io/github/alexmojaki/pure_eval?branch=master) [![Supports Python versions 3.5+](https://img.shields.io/pypi/pyversions/pure_eval.svg)](https://pypi.python.org/pypi/pure_eval) This is a Python package that lets you safely evaluate certain AST nodes without triggering arbitrary code that may have unwanted side effects. It can be installed from PyPI: pip install pure_eval To demonstrate usage, suppose we have an object defined as follows: ```python class Rectangle: def __init__(self, width, height): self.width = width self.height = height @property def area(self): print("Calculating area...") return self.width * self.height rect = Rectangle(3, 5) ``` Given the `rect` object, we want to evaluate whatever expressions we can in this source code: ```python source = "(rect.width, rect.height, rect.area)" ``` This library works with the AST, so let's parse the source code and peek inside: ```python import ast tree = ast.parse(source) the_tuple = tree.body[0].value for node in the_tuple.elts: print(ast.dump(node)) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='area', ctx=Load()) ``` Now to actually use the library. First construct an Evaluator: ```python from pure_eval import Evaluator evaluator = Evaluator({"rect": rect}) ``` The argument to `Evaluator` should be a mapping from variable names to their values. Or if you have access to the stack frame where `rect` is defined, you can instead use: ```python evaluator = Evaluator.from_frame(frame) ``` Now to evaluate some nodes, using `evaluator[node]`: ```python print("rect.width:", evaluator[the_tuple.elts[0]]) print("rect:", evaluator[the_tuple.elts[0].value]) ``` Output: ``` rect.width: 3 rect: <__main__.Rectangle object at 0x105b0dd30> ``` OK, but you could have done the same thing with `eval`. The useful part is that it will refuse to evaluate the property `rect.area` because that would trigger unknown code. If we try, it'll raise a `CannotEval` exception. ```python from pure_eval import CannotEval try: print("rect.area:", evaluator[the_tuple.elts[2]]) # fails except CannotEval as e: print(e) # prints CannotEval ``` To find all the expressions that can be evaluated in a tree: ```python for node, value in evaluator.find_expressions(tree): print(ast.dump(node), value) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) 3 Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) 5 Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> ``` Note that this includes `rect` three times, once for each appearance in the source code. Since all these nodes are equivalent, we can group them together: ```python from pure_eval import group_expressions for nodes, values in group_expressions(evaluator.find_expressions(tree)): print(len(nodes), "nodes with value:", values) ``` Output: ``` 1 nodes with value: 3 1 nodes with value: 5 3 nodes with value: <__main__.Rectangle object at 0x10d374d30> ``` If we want to list all the expressions in a tree, we may want to filter out certain expressions whose values are obvious. For example, suppose we have a function `foo`: ```python def foo(): pass ``` If we refer to `foo` by its name as usual, then that's not interesting: ```python from pure_eval import is_expression_interesting node = ast.parse('foo').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='foo', ctx=Load()) False ``` But if we refer to it by a different name, then it's interesting: ```python node = ast.parse('bar').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='bar', ctx=Load()) True ``` In general `is_expression_interesting` returns False for the following values: - Literals (e.g. `123`, `'abc'`, `[1, 2, 3]`, `{'a': (), 'b': ([1, 2], [3])}`) - Variables or attributes whose name is equal to the value's `__name__`, such as `foo` above or `self.foo` if it was a method. - Builtins (e.g. `len`) referred to by their usual name. To make things easier, you can combine finding expressions, grouping them, and filtering out the obvious ones with: ```python evaluator.interesting_expressions_grouped(root) ``` To get the source code of an AST node, I recommend [asttokens](https://github.com/gristlabs/asttokens). Here's a complete example that brings it all together: ```python from asttokens import ASTTokens from pure_eval import Evaluator source = """ x = 1 d = {x: 2} y = d[x] """ names = {} exec(source, names) atok = ASTTokens(source, parse=True) for nodes, value in Evaluator(names).interesting_expressions_grouped(atok.tree): print(atok.get_text(nodes[0]), "=", value) ``` Output: ```python x = 1 d = {1: 2} y = 2 d[x] = 2 ```f=‡dc-64g.compass-ci“5MIThttp://openeuler.orgUnspecifiedpure_eval-0.2.2.tar.gzhttp://github.com/alexmojaki/pure_evallinuxnoarchKÃGr´´f=†Íf=†Í2b45320af6dfaa1750f543d714b6d1c520a1688dec6fd24d339063ce0aaa9ac3f35c974c26cd4731516297cdc7ea3f1586ffab84b81988c84f0ae377482d7ee0 rootrootrootrootÿÿÿÿÿÿÿÿpython3-pure-evalpython-pure-eval-help python3-develpython3-pippython3-setuptoolspython3-setuptools_scmpython3-tomlrpmlib(CompressedFileNames)rpmlib(FileDigests)3.0.4-14.6.0-14.18.2dgdÀPython_Bot - 0.2.2-1- Package Spec generatednoarchdc-64g.compass-ci 17153083190.2.2-1.oe24030.2.2-1.oe2403pure_eval-0.2.2.tar.gzpython-pure-eval.speccpiogzip9utf-8266902da25b7b25c1da2a921cbfabb4e78be9496eaf38924efdbbe443ba511ef2e2ff7a8f56e03ff02b9017c376a8c604b8891212111ba43cc8262c5e9ed328b Name: python-pure-eval Version: 0.2.2 Release: 1 Summary: Safely evaluate AST nodes without side effects License: MIT URL: http://github.com/alexmojaki/pure_eval Source0: https://files.pythonhosted.org/packages/97/5a/0bc937c25d3ce4e0a74335222aee05455d6afa2888032185f8ab50cdf6fd/pure_eval-0.2.2.tar.gz BuildArch: noarch Requires: python3-pytest %description [![Build Status](https://travis-ci.org/alexmojaki/pure_eval.svg?branch=master)](https://travis-ci.org/alexmojaki/pure_eval) [![Coverage Status](https://coveralls.io/repos/github/alexmojaki/pure_eval/badge.svg?branch=master)](https://coveralls.io/github/alexmojaki/pure_eval?branch=master) [![Supports Python versions 3.5+](https://img.shields.io/pypi/pyversions/pure_eval.svg)](https://pypi.python.org/pypi/pure_eval) This is a Python package that lets you safely evaluate certain AST nodes without triggering arbitrary code that may have unwanted side effects. It can be installed from PyPI: pip install pure_eval To demonstrate usage, suppose we have an object defined as follows: ```python class Rectangle: def __init__(self, width, height): self.width = width self.height = height @property def area(self): print("Calculating area...") return self.width * self.height rect = Rectangle(3, 5) ``` Given the `rect` object, we want to evaluate whatever expressions we can in this source code: ```python source = "(rect.width, rect.height, rect.area)" ``` This library works with the AST, so let's parse the source code and peek inside: ```python import ast tree = ast.parse(source) the_tuple = tree.body[0].value for node in the_tuple.elts: print(ast.dump(node)) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='area', ctx=Load()) ``` Now to actually use the library. First construct an Evaluator: ```python from pure_eval import Evaluator evaluator = Evaluator({"rect": rect}) ``` The argument to `Evaluator` should be a mapping from variable names to their values. Or if you have access to the stack frame where `rect` is defined, you can instead use: ```python evaluator = Evaluator.from_frame(frame) ``` Now to evaluate some nodes, using `evaluator[node]`: ```python print("rect.width:", evaluator[the_tuple.elts[0]]) print("rect:", evaluator[the_tuple.elts[0].value]) ``` Output: ``` rect.width: 3 rect: <__main__.Rectangle object at 0x105b0dd30> ``` OK, but you could have done the same thing with `eval`. The useful part is that it will refuse to evaluate the property `rect.area` because that would trigger unknown code. If we try, it'll raise a `CannotEval` exception. ```python from pure_eval import CannotEval try: print("rect.area:", evaluator[the_tuple.elts[2]]) # fails except CannotEval as e: print(e) # prints CannotEval ``` To find all the expressions that can be evaluated in a tree: ```python for node, value in evaluator.find_expressions(tree): print(ast.dump(node), value) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) 3 Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) 5 Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> ``` Note that this includes `rect` three times, once for each appearance in the source code. Since all these nodes are equivalent, we can group them together: ```python from pure_eval import group_expressions for nodes, values in group_expressions(evaluator.find_expressions(tree)): print(len(nodes), "nodes with value:", values) ``` Output: ``` 1 nodes with value: 3 1 nodes with value: 5 3 nodes with value: <__main__.Rectangle object at 0x10d374d30> ``` If we want to list all the expressions in a tree, we may want to filter out certain expressions whose values are obvious. For example, suppose we have a function `foo`: ```python def foo(): pass ``` If we refer to `foo` by its name as usual, then that's not interesting: ```python from pure_eval import is_expression_interesting node = ast.parse('foo').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='foo', ctx=Load()) False ``` But if we refer to it by a different name, then it's interesting: ```python node = ast.parse('bar').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='bar', ctx=Load()) True ``` In general `is_expression_interesting` returns False for the following values: - Literals (e.g. `123`, `'abc'`, `[1, 2, 3]`, `{'a': (), 'b': ([1, 2], [3])}`) - Variables or attributes whose name is equal to the value's `__name__`, such as `foo` above or `self.foo` if it was a method. - Builtins (e.g. `len`) referred to by their usual name. To make things easier, you can combine finding expressions, grouping them, and filtering out the obvious ones with: ```python evaluator.interesting_expressions_grouped(root) ``` To get the source code of an AST node, I recommend [asttokens](https://github.com/gristlabs/asttokens). Here's a complete example that brings it all together: ```python from asttokens import ASTTokens from pure_eval import Evaluator source = """ x = 1 d = {x: 2} y = d[x] """ names = {} exec(source, names) atok = ASTTokens(source, parse=True) for nodes, value in Evaluator(names).interesting_expressions_grouped(atok.tree): print(atok.get_text(nodes[0]), "=", value) ``` Output: ```python x = 1 d = {1: 2} y = 2 d[x] = 2 ``` %package -n python3-pure-eval Summary: Safely evaluate AST nodes without side effects Provides: python-pure-eval BuildRequires: python3-devel BuildRequires: python3-setuptools BuildRequires: python3-pip BuildRequires: python3-setuptools_scm BuildRequires: python3-toml %description -n python3-pure-eval [![Build Status](https://travis-ci.org/alexmojaki/pure_eval.svg?branch=master)](https://travis-ci.org/alexmojaki/pure_eval) [![Coverage Status](https://coveralls.io/repos/github/alexmojaki/pure_eval/badge.svg?branch=master)](https://coveralls.io/github/alexmojaki/pure_eval?branch=master) [![Supports Python versions 3.5+](https://img.shields.io/pypi/pyversions/pure_eval.svg)](https://pypi.python.org/pypi/pure_eval) This is a Python package that lets you safely evaluate certain AST nodes without triggering arbitrary code that may have unwanted side effects. It can be installed from PyPI: pip install pure_eval To demonstrate usage, suppose we have an object defined as follows: ```python class Rectangle: def __init__(self, width, height): self.width = width self.height = height @property def area(self): print("Calculating area...") return self.width * self.height rect = Rectangle(3, 5) ``` Given the `rect` object, we want to evaluate whatever expressions we can in this source code: ```python source = "(rect.width, rect.height, rect.area)" ``` This library works with the AST, so let's parse the source code and peek inside: ```python import ast tree = ast.parse(source) the_tuple = tree.body[0].value for node in the_tuple.elts: print(ast.dump(node)) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='area', ctx=Load()) ``` Now to actually use the library. First construct an Evaluator: ```python from pure_eval import Evaluator evaluator = Evaluator({"rect": rect}) ``` The argument to `Evaluator` should be a mapping from variable names to their values. Or if you have access to the stack frame where `rect` is defined, you can instead use: ```python evaluator = Evaluator.from_frame(frame) ``` Now to evaluate some nodes, using `evaluator[node]`: ```python print("rect.width:", evaluator[the_tuple.elts[0]]) print("rect:", evaluator[the_tuple.elts[0].value]) ``` Output: ``` rect.width: 3 rect: <__main__.Rectangle object at 0x105b0dd30> ``` OK, but you could have done the same thing with `eval`. The useful part is that it will refuse to evaluate the property `rect.area` because that would trigger unknown code. If we try, it'll raise a `CannotEval` exception. ```python from pure_eval import CannotEval try: print("rect.area:", evaluator[the_tuple.elts[2]]) # fails except CannotEval as e: print(e) # prints CannotEval ``` To find all the expressions that can be evaluated in a tree: ```python for node, value in evaluator.find_expressions(tree): print(ast.dump(node), value) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) 3 Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) 5 Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> ``` Note that this includes `rect` three times, once for each appearance in the source code. Since all these nodes are equivalent, we can group them together: ```python from pure_eval import group_expressions for nodes, values in group_expressions(evaluator.find_expressions(tree)): print(len(nodes), "nodes with value:", values) ``` Output: ``` 1 nodes with value: 3 1 nodes with value: 5 3 nodes with value: <__main__.Rectangle object at 0x10d374d30> ``` If we want to list all the expressions in a tree, we may want to filter out certain expressions whose values are obvious. For example, suppose we have a function `foo`: ```python def foo(): pass ``` If we refer to `foo` by its name as usual, then that's not interesting: ```python from pure_eval import is_expression_interesting node = ast.parse('foo').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='foo', ctx=Load()) False ``` But if we refer to it by a different name, then it's interesting: ```python node = ast.parse('bar').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='bar', ctx=Load()) True ``` In general `is_expression_interesting` returns False for the following values: - Literals (e.g. `123`, `'abc'`, `[1, 2, 3]`, `{'a': (), 'b': ([1, 2], [3])}`) - Variables or attributes whose name is equal to the value's `__name__`, such as `foo` above or `self.foo` if it was a method. - Builtins (e.g. `len`) referred to by their usual name. To make things easier, you can combine finding expressions, grouping them, and filtering out the obvious ones with: ```python evaluator.interesting_expressions_grouped(root) ``` To get the source code of an AST node, I recommend [asttokens](https://github.com/gristlabs/asttokens). Here's a complete example that brings it all together: ```python from asttokens import ASTTokens from pure_eval import Evaluator source = """ x = 1 d = {x: 2} y = d[x] """ names = {} exec(source, names) atok = ASTTokens(source, parse=True) for nodes, value in Evaluator(names).interesting_expressions_grouped(atok.tree): print(atok.get_text(nodes[0]), "=", value) ``` Output: ```python x = 1 d = {1: 2} y = 2 d[x] = 2 ``` %package help Summary: Development documents and examples for pure-eval Provides: python3-pure-eval-doc %description help [![Build Status](https://travis-ci.org/alexmojaki/pure_eval.svg?branch=master)](https://travis-ci.org/alexmojaki/pure_eval) [![Coverage Status](https://coveralls.io/repos/github/alexmojaki/pure_eval/badge.svg?branch=master)](https://coveralls.io/github/alexmojaki/pure_eval?branch=master) [![Supports Python versions 3.5+](https://img.shields.io/pypi/pyversions/pure_eval.svg)](https://pypi.python.org/pypi/pure_eval) This is a Python package that lets you safely evaluate certain AST nodes without triggering arbitrary code that may have unwanted side effects. It can be installed from PyPI: pip install pure_eval To demonstrate usage, suppose we have an object defined as follows: ```python class Rectangle: def __init__(self, width, height): self.width = width self.height = height @property def area(self): print("Calculating area...") return self.width * self.height rect = Rectangle(3, 5) ``` Given the `rect` object, we want to evaluate whatever expressions we can in this source code: ```python source = "(rect.width, rect.height, rect.area)" ``` This library works with the AST, so let's parse the source code and peek inside: ```python import ast tree = ast.parse(source) the_tuple = tree.body[0].value for node in the_tuple.elts: print(ast.dump(node)) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) Attribute(value=Name(id='rect', ctx=Load()), attr='area', ctx=Load()) ``` Now to actually use the library. First construct an Evaluator: ```python from pure_eval import Evaluator evaluator = Evaluator({"rect": rect}) ``` The argument to `Evaluator` should be a mapping from variable names to their values. Or if you have access to the stack frame where `rect` is defined, you can instead use: ```python evaluator = Evaluator.from_frame(frame) ``` Now to evaluate some nodes, using `evaluator[node]`: ```python print("rect.width:", evaluator[the_tuple.elts[0]]) print("rect:", evaluator[the_tuple.elts[0].value]) ``` Output: ``` rect.width: 3 rect: <__main__.Rectangle object at 0x105b0dd30> ``` OK, but you could have done the same thing with `eval`. The useful part is that it will refuse to evaluate the property `rect.area` because that would trigger unknown code. If we try, it'll raise a `CannotEval` exception. ```python from pure_eval import CannotEval try: print("rect.area:", evaluator[the_tuple.elts[2]]) # fails except CannotEval as e: print(e) # prints CannotEval ``` To find all the expressions that can be evaluated in a tree: ```python for node, value in evaluator.find_expressions(tree): print(ast.dump(node), value) ``` Output: ```python Attribute(value=Name(id='rect', ctx=Load()), attr='width', ctx=Load()) 3 Attribute(value=Name(id='rect', ctx=Load()), attr='height', ctx=Load()) 5 Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> Name(id='rect', ctx=Load()) <__main__.Rectangle object at 0x105568d30> ``` Note that this includes `rect` three times, once for each appearance in the source code. Since all these nodes are equivalent, we can group them together: ```python from pure_eval import group_expressions for nodes, values in group_expressions(evaluator.find_expressions(tree)): print(len(nodes), "nodes with value:", values) ``` Output: ``` 1 nodes with value: 3 1 nodes with value: 5 3 nodes with value: <__main__.Rectangle object at 0x10d374d30> ``` If we want to list all the expressions in a tree, we may want to filter out certain expressions whose values are obvious. For example, suppose we have a function `foo`: ```python def foo(): pass ``` If we refer to `foo` by its name as usual, then that's not interesting: ```python from pure_eval import is_expression_interesting node = ast.parse('foo').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='foo', ctx=Load()) False ``` But if we refer to it by a different name, then it's interesting: ```python node = ast.parse('bar').body[0].value print(ast.dump(node)) print(is_expression_interesting(node, foo)) ``` Output: ```python Name(id='bar', ctx=Load()) True ``` In general `is_expression_interesting` returns False for the following values: - Literals (e.g. `123`, `'abc'`, `[1, 2, 3]`, `{'a': (), 'b': ([1, 2], [3])}`) - Variables or attributes whose name is equal to the value's `__name__`, such as `foo` above or `self.foo` if it was a method. - Builtins (e.g. `len`) referred to by their usual name. To make things easier, you can combine finding expressions, grouping them, and filtering out the obvious ones with: ```python evaluator.interesting_expressions_grouped(root) ``` To get the source code of an AST node, I recommend [asttokens](https://github.com/gristlabs/asttokens). Here's a complete example that brings it all together: ```python from asttokens import ASTTokens from pure_eval import Evaluator source = """ x = 1 d = {x: 2} y = d[x] """ names = {} exec(source, names) atok = ASTTokens(source, parse=True) for nodes, value in Evaluator(names).interesting_expressions_grouped(atok.tree): print(atok.get_text(nodes[0]), "=", value) ``` Output: ```python x = 1 d = {1: 2} y = 2 d[x] = 2 ``` %prep cd '/home/lkp/rpmbuild/BUILD' rm -rf 'pure_eval-0.2.2' /usr/lib/rpm/rpmuncompress -x '/home/lkp/rpmbuild/SOURCES/pure_eval-0.2.2.tar.gz' STATUS=$? if [ $STATUS -ne 0 ]; then exit $STATUS fi cd 'pure_eval-0.2.2' /usr/bin/chmod -Rf a+rX,u+w,g-w,o-w . \ CFLAGS="${CFLAGS:-${RPM_OPT_FLAGS}}" LDFLAGS="${LDFLAGS:-${RPM_LD_FLAGS}}"\ /usr/bin/python3 setup.py build --executable="/usr/bin/python3 -s" sleep 1 %install \ CFLAGS="${CFLAGS:-${RPM_OPT_FLAGS}}" LDFLAGS="${LDFLAGS:-${RPM_LD_FLAGS}}"\ /usr/bin/python3 setup.py install -O1 --skip-build --root /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64 install -d -m755 /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64//usr/share/doc/python-pure-eval if [ -d doc ]; then cp -arf doc /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64//usr/share/doc/python-pure-eval; fi if [ -d docs ]; then cp -arf docs /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64//usr/share/doc/python-pure-eval; fi if [ -d example ]; then cp -arf example /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64//usr/share/doc/python-pure-eval; fi if [ -d examples ]; then cp -arf examples /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64//usr/share/doc/python-pure-eval; fi pushd /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64 if [ -d usr/lib ]; then find usr/lib -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/lib64 ]; then find usr/lib64 -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/bin ]; then find usr/bin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi if [ -d usr/sbin ]; then find usr/sbin -type f -printf "\"/%h/%f\"\n" >> filelist.lst fi touch doclist.lst if [ -d usr/share/man ]; then find usr/share/man -type f -printf "\"/%h/%f.gz\"\n" >> doclist.lst fi popd mv /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64/filelist.lst . mv /home/lkp/rpmbuild/BUILDROOT/python-pure-eval-0.2.2-1.oe2403.x86_64/doclist.lst . %files -n python3-pure-eval -f filelist.lst %dir /usr/lib/python3.11/site-packages/* %files help -f doclist.lst /usr/share/doc/* %changelog * Fri May 19 2023 Python_Bot - 0.2.2-1 - Package Spec generated ?ÿÿü‹”ÛŒ&]÷ ð¶m›ÓzÚ¶mMOsº§mÛ¶»§mÛ¶mÛ¶ñìû~ÿÝÍn²ÉîžJnÊÍ½•T¥RçV~àp˜ÿÿÙs1±þÏÁÌÁÁjÌÅñÛøß6£ß¬€ÿ§`æü™³ƒ‰¾‰‹¡€‘åŸÍÉÐÑÔäŸ Ž„É¢¼42™ÙZ›0Z™¸1¹Ú:X2ýÏ1LÆæŽNLNÖv&n.¿ ¹,Í™þÓ\y[{npÔŸú0øBjpŸü”1ÿy/»y¾¼Õ¾ðjƒvžõœ=")Y,&e$ÿCzmþ·ïG.Å+ÕXøKËâÂ0*°¡’Ðò$Ôõy³…èû(Òk}_õ©ek{C±ç·GIƒoívóë¹×±²U¨Ò—(ç½þaÃbÆðu±söÕÏÃ¥öÇíìú†5±“ËKTÏbŽïÇŒÑ½@O]×Us“åÕµWÙ¯››Ÿ/o(´õ—mG.¼ÙçÍUË°‰ÈñsƒH¿Ìvùã[±lú®yò}·Ûð¥#»y|î(oˆ¯WÞ{þ{ï×›î#ÐE/¶s—cÝ=íÎWðË¥é¸p Ü2ÿêÑ¼JÎ;¸¿zVš×›Žÿ’4H“¬kÊôÈaeËæß¨™v\=»|Þ¸ô‚¼Á[ ¿Ï}w²ï;üˆb¢zoê'Öøþ¦Yq¼túŒúfˆJÌ¼²ãˆéÖõm>|ökq½XÓˆ'¿Üº¯Öh(“0‡H?q˜ I~«ò"m¿áÀ,RÜ¶Øºá´©e;›Õó_àžè|–,l»¼Ê+4Halÿy“Ôýƒü›ç ÚËpò€ØÆÅ¤ÛlŠ;vÍkx[™ÿRPÀ'‰BkíïÚVV!m$ÇþW3ƒ¦Å°á/µCkÊŽ]üÈð 0Ô[•ÊNÁ³œO¯Ïvßï÷ËÔï¡±·!÷TgcŒ«zßbŠVÖãw’®ì‘fÁÝ™ûÊ«7+‚þÃéÐYiÔ¬aá¸·õØUŽƒ†ÀiCZ²‹„ÓkÊt°4ÕŒæ–"$nY¸l–<^™[m”aø½©‡ ¡9çômîç¬¸{QüwÝ¾1…u,~hoÈöÂ…µ¯æÎ +ú.ÆÈnÅÉlþm¬'òª K–²AoÎ„WïiÂÜøá‘÷½x'í}´Ÿ×>RÚµü ÉRz‹»9ÏªÀ¦/¦+àtCàÖ—íÆGÓº¸UGôi8„ûðµõüF~Þðü§§ô«‡|Š ÖáÖ“È MÀ¡Å"; 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