automatic import of python-timebudgetopeneuler20.03

3 files changed, 446 insertions, 0 deletions

diff --git a/.gitignore b/.gitignore
index e69de29..2b2a383 100644
--- a/.gitignore
+++ b/.gitignore
@@ -0,0 +1 @@
+/timebudget-0.7.1.tar.gz
diff --git a/python-timebudget.spec b/python-timebudget.spec
new file mode 100644
index 0000000..f0f2505
--- /dev/null
+++ b/python-timebudget.spec
@@ -0,0 +1,444 @@
+%global _empty_manifest_terminate_build 0
+Name:		python-timebudget
+Version:	0.7.1
+Release:	1
+Summary:	Stupidly-simple speed profiling tool for python
+License:	Apache-2.0
+URL:		https://github.com/leopd/timebudget
+Source0:	https://mirrors.nju.edu.cn/pypi/web/packages/12/b5/359073c986ba4a23f5c554915bda5f012f382eb6f004b3e81fdc0f21203f/timebudget-0.7.1.tar.gz
+BuildArch:	noarch
+
+
+%description
+# timebudget
+### A stupidly-simple tool to see where your time is going in Python programs
+
+Trying to figure out where the time's going in your python code?  Tired of writing `elapsed = time.time() - start_time`?  You can find out with just a few lines of code after you
+
+```
+pip install timebudget
+```
+
+## The simplest way
+
+With just two lines of code (one is the import), you can see how long something takes...
+
+```python
+from timebudget import timebudget
+
+with timebudget("Loading and processing the file"):
+    raw = open(filename,'rt').readlines()
+    lines = [line.rstrip() for line in raw]
+```
+
+will print
+
+```
+Loading and processing the file took 1.453sec
+```
+
+
+## Record times and print a report
+
+To get a report on the total time from functions you care about, just annotate those functions:
+
+```python
+from timebudget import timebudget
+timebudget.set_quiet()  # don't show measurements as they happen
+timebudget.report_at_exit()  # Generate report when the program exits
+
+@timebudget  # Record how long this function takes
+def possibly_slow():
+    ...
+
+@timebudget  # ... and this function too
+def should_be_fast():
+    ...
+```
+
+And now when you run your program, you'll see how much time was spent in each annotated function:
+
+```
+timebudget report...
+            possibly_slow:  901.12ms for      3 calls
+           should_be_fast:   61.35ms for      2 calls
+```
+
+Or instead of calling `report_at_exit()` you can manually call 
+
+```python
+timebudget.report(reset=True)  # print out the report now, and reset the statistics
+```
+
+If you don't set `reset=True` then the statistics will accumulate into the next report.
+
+You can also wrap specific blocks of code to be recorded in the report, and optionally override
+the default `set_quiet` choice for any block:
+
+```python
+with timebudget("load-file", quiet=False):
+    text = open(filename,'rt').readlines()
+```
+
+
+## Percent of time in a loop
+
+If you are doing something repeatedly, and want to know the percent of time doing different things, time the loop itself, and pass the name to report.  That is, add a timebudget annotation or wrapper onto the thing which is happening repeatedly.  Each time this method or code-block is entered will now be considered one "cycle" and your report will tell you what fraction of time things take within this cycle.
+
+
+```python
+@timebudget
+def outer_loop():
+    if sometimes():
+        possibly_slow()
+    should_be_fast()
+    should_be_fast()
+
+for _ in range(NUM_CYCLES):
+    outer_loop()
+
+timebudget.report('outer_loop')
+```
+
+Then the report looks like:
+
+```
+timebudget report per outer_loop cycle...
+               outer_loop: 100.0%   440.79ms/cyc @     1.0 calls/cyc
+            possibly_slow:  40.9%   180.31ms/cyc @     0.6 calls/cyc
+           should_be_fast:  13.7%    60.19ms/cyc @     2.0 calls/cyc
+```
+
+Here, the times in milliseconds are the totals (averages per cycle), not the average time per call.  So in the above example, `should_be_fast` is taking about 30ms per call, but being called twice per loop.  Similarly, `possibly_slow` is still about 300ms each time it's called, but it's only getting called on 60% of the cycles on average, so on average it's using 41% of the time in `outer_loop` or 180ms.
+
+
+## Requirements
+
+Needs Python 3.6 or higher.  Other libraries are in `requirements.txt` and can be installed like
+
+```
+pip install -r requirements.txt  # only needed for developing timebudget.
+```
+
+## Testing
+
+To run tests:
+
+```
+pytest
+```
+
+## Inspiration
+
+This tool is inspired by [TQDM](https://github.com/tqdm/tqdm), the awesome progress bar.  TQDM is stupidly simple to add to your code, and just makes it better.  I aspire to imitate that.
+
+
+
+
+
+%package -n python3-timebudget
+Summary:	Stupidly-simple speed profiling tool for python
+Provides:	python-timebudget
+BuildRequires:	python3-devel
+BuildRequires:	python3-setuptools
+BuildRequires:	python3-pip
+%description -n python3-timebudget
+# timebudget
+### A stupidly-simple tool to see where your time is going in Python programs
+
+Trying to figure out where the time's going in your python code?  Tired of writing `elapsed = time.time() - start_time`?  You can find out with just a few lines of code after you
+
+```
+pip install timebudget
+```
+
+## The simplest way
+
+With just two lines of code (one is the import), you can see how long something takes...
+
+```python
+from timebudget import timebudget
+
+with timebudget("Loading and processing the file"):
+    raw = open(filename,'rt').readlines()
+    lines = [line.rstrip() for line in raw]
+```
+
+will print
+
+```
+Loading and processing the file took 1.453sec
+```
+
+
+## Record times and print a report
+
+To get a report on the total time from functions you care about, just annotate those functions:
+
+```python
+from timebudget import timebudget
+timebudget.set_quiet()  # don't show measurements as they happen
+timebudget.report_at_exit()  # Generate report when the program exits
+
+@timebudget  # Record how long this function takes
+def possibly_slow():
+    ...
+
+@timebudget  # ... and this function too
+def should_be_fast():
+    ...
+```
+
+And now when you run your program, you'll see how much time was spent in each annotated function:
+
+```
+timebudget report...
+            possibly_slow:  901.12ms for      3 calls
+           should_be_fast:   61.35ms for      2 calls
+```
+
+Or instead of calling `report_at_exit()` you can manually call 
+
+```python
+timebudget.report(reset=True)  # print out the report now, and reset the statistics
+```
+
+If you don't set `reset=True` then the statistics will accumulate into the next report.
+
+You can also wrap specific blocks of code to be recorded in the report, and optionally override
+the default `set_quiet` choice for any block:
+
+```python
+with timebudget("load-file", quiet=False):
+    text = open(filename,'rt').readlines()
+```
+
+
+## Percent of time in a loop
+
+If you are doing something repeatedly, and want to know the percent of time doing different things, time the loop itself, and pass the name to report.  That is, add a timebudget annotation or wrapper onto the thing which is happening repeatedly.  Each time this method or code-block is entered will now be considered one "cycle" and your report will tell you what fraction of time things take within this cycle.
+
+
+```python
+@timebudget
+def outer_loop():
+    if sometimes():
+        possibly_slow()
+    should_be_fast()
+    should_be_fast()
+
+for _ in range(NUM_CYCLES):
+    outer_loop()
+
+timebudget.report('outer_loop')
+```
+
+Then the report looks like:
+
+```
+timebudget report per outer_loop cycle...
+               outer_loop: 100.0%   440.79ms/cyc @     1.0 calls/cyc
+            possibly_slow:  40.9%   180.31ms/cyc @     0.6 calls/cyc
+           should_be_fast:  13.7%    60.19ms/cyc @     2.0 calls/cyc
+```
+
+Here, the times in milliseconds are the totals (averages per cycle), not the average time per call.  So in the above example, `should_be_fast` is taking about 30ms per call, but being called twice per loop.  Similarly, `possibly_slow` is still about 300ms each time it's called, but it's only getting called on 60% of the cycles on average, so on average it's using 41% of the time in `outer_loop` or 180ms.
+
+
+## Requirements
+
+Needs Python 3.6 or higher.  Other libraries are in `requirements.txt` and can be installed like
+
+```
+pip install -r requirements.txt  # only needed for developing timebudget.
+```
+
+## Testing
+
+To run tests:
+
+```
+pytest
+```
+
+## Inspiration
+
+This tool is inspired by [TQDM](https://github.com/tqdm/tqdm), the awesome progress bar.  TQDM is stupidly simple to add to your code, and just makes it better.  I aspire to imitate that.
+
+
+
+
+
+%package help
+Summary:	Development documents and examples for timebudget
+Provides:	python3-timebudget-doc
+%description help
+# timebudget
+### A stupidly-simple tool to see where your time is going in Python programs
+
+Trying to figure out where the time's going in your python code?  Tired of writing `elapsed = time.time() - start_time`?  You can find out with just a few lines of code after you
+
+```
+pip install timebudget
+```
+
+## The simplest way
+
+With just two lines of code (one is the import), you can see how long something takes...
+
+```python
+from timebudget import timebudget
+
+with timebudget("Loading and processing the file"):
+    raw = open(filename,'rt').readlines()
+    lines = [line.rstrip() for line in raw]
+```
+
+will print
+
+```
+Loading and processing the file took 1.453sec
+```
+
+
+## Record times and print a report
+
+To get a report on the total time from functions you care about, just annotate those functions:
+
+```python
+from timebudget import timebudget
+timebudget.set_quiet()  # don't show measurements as they happen
+timebudget.report_at_exit()  # Generate report when the program exits
+
+@timebudget  # Record how long this function takes
+def possibly_slow():
+    ...
+
+@timebudget  # ... and this function too
+def should_be_fast():
+    ...
+```
+
+And now when you run your program, you'll see how much time was spent in each annotated function:
+
+```
+timebudget report...
+            possibly_slow:  901.12ms for      3 calls
+           should_be_fast:   61.35ms for      2 calls
+```
+
+Or instead of calling `report_at_exit()` you can manually call 
+
+```python
+timebudget.report(reset=True)  # print out the report now, and reset the statistics
+```
+
+If you don't set `reset=True` then the statistics will accumulate into the next report.
+
+You can also wrap specific blocks of code to be recorded in the report, and optionally override
+the default `set_quiet` choice for any block:
+
+```python
+with timebudget("load-file", quiet=False):
+    text = open(filename,'rt').readlines()
+```
+
+
+## Percent of time in a loop
+
+If you are doing something repeatedly, and want to know the percent of time doing different things, time the loop itself, and pass the name to report.  That is, add a timebudget annotation or wrapper onto the thing which is happening repeatedly.  Each time this method or code-block is entered will now be considered one "cycle" and your report will tell you what fraction of time things take within this cycle.
+
+
+```python
+@timebudget
+def outer_loop():
+    if sometimes():
+        possibly_slow()
+    should_be_fast()
+    should_be_fast()
+
+for _ in range(NUM_CYCLES):
+    outer_loop()
+
+timebudget.report('outer_loop')
+```
+
+Then the report looks like:
+
+```
+timebudget report per outer_loop cycle...
+               outer_loop: 100.0%   440.79ms/cyc @     1.0 calls/cyc
+            possibly_slow:  40.9%   180.31ms/cyc @     0.6 calls/cyc
+           should_be_fast:  13.7%    60.19ms/cyc @     2.0 calls/cyc
+```
+
+Here, the times in milliseconds are the totals (averages per cycle), not the average time per call.  So in the above example, `should_be_fast` is taking about 30ms per call, but being called twice per loop.  Similarly, `possibly_slow` is still about 300ms each time it's called, but it's only getting called on 60% of the cycles on average, so on average it's using 41% of the time in `outer_loop` or 180ms.
+
+
+## Requirements
+
+Needs Python 3.6 or higher.  Other libraries are in `requirements.txt` and can be installed like
+
+```
+pip install -r requirements.txt  # only needed for developing timebudget.
+```
+
+## Testing
+
+To run tests:
+
+```
+pytest
+```
+
+## Inspiration
+
+This tool is inspired by [TQDM](https://github.com/tqdm/tqdm), the awesome progress bar.  TQDM is stupidly simple to add to your code, and just makes it better.  I aspire to imitate that.
+
+
+
+
+
+%prep
+%autosetup -n timebudget-0.7.1
+
+%build
+%py3_build
+
+%install
+%py3_install
+install -d -m755 %{buildroot}/%{_pkgdocdir}
+if [ -d doc ]; then cp -arf doc %{buildroot}/%{_pkgdocdir}; fi
+if [ -d docs ]; then cp -arf docs %{buildroot}/%{_pkgdocdir}; fi
+if [ -d example ]; then cp -arf example %{buildroot}/%{_pkgdocdir}; fi
+if [ -d examples ]; then cp -arf examples %{buildroot}/%{_pkgdocdir}; fi
+pushd %{buildroot}
+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 %{buildroot}/filelist.lst .
+mv %{buildroot}/doclist.lst .
+
+%files -n python3-timebudget -f filelist.lst
+%dir %{python3_sitelib}/*
+
+%files help -f doclist.lst
+%{_docdir}/*
+
+%changelog
+* Fri May 05 2023 Python_Bot <Python_Bot@openeuler.org> - 0.7.1-1
+- Package Spec generated
diff --git a/sources b/sources
new file mode 100644
index 0000000..eb32406
--- /dev/null
+++ b/sources
@@ -0,0 +1 @@
+f220b973de4c92b8b32b977ddd46c08a  timebudget-0.7.1.tar.gz